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songyang0716/Topic_Modeling | ['information retrieval'] | ['Probabilistic Latent Semantic Analysis'] | btm.py lda.py plsa.py BTM LDA plsa argmax defaultdict len range multinomial bincount randint sum zeros enumerate argmax defaultdict print randint multinomial append zeros sum range enumerate len multiply rand len matmul dot zeros sum range enumerate | songyang0716/Topic_Modeling | 3,700 |
sonsus/albert_paraphrase | ['word embeddings'] | ['How Contextual are Contextualized Word Representations? Comparing the Geometry of BERT, ELMo, and GPT-2 Embeddings'] | retrain.py data/prepdata_test.py data/merge_traindev4sub.py data/prepdata.py config.py train_albert.py utils.py dataload.py PPDataset get_loader write_sub MLP accuracy retrieve_conf get_arguments_from_cmd evaldev main savemodel loadmodel_info accuracy get_arguments_from_cmd evaldev main savemodel get_lr_from_optim get_time get_date open_vocab log_time merge split_kfold tokenize open_vocab tokenize preptest print PPDataset DataLoader albertmodel clsmodel pooler_output len tqdm eval log enumerate str print modelsaveroot debug infer_now model_date_name get_date mkdir Path toDict print modelsaveroot dict get_date mkdir Path save load vocab model modelsaveroot model_date_name Path expconf Munch from_pretrained itos num_attention_heads smaller num_hidden_layers hidden_size len pooler_output zero_grad cls_warmups xavier_uniform_ albert device savemodel log seed cls AlbertForPreTraining write_sub retrieve_conf evaldev load_state_dict to getsch cls_numsteps manual_seed_all cross_entropy detach copy eval manual_seed item enumerate AdamW accuracy tqdm parameters get_loader train step loadmodel_info len items list model from_pretrained itos model sop_logits list num_attention_heads view num_hidden_layers warmups range smaller backward alpha_warmup contiguous numep min print empty_cache hidden_size load Munch open param_groups now now print time Path list defaultdict defaultdict open_vocab | # Semantic Textual Similarity Classification ## I. ๋ฌธ์ ํํ (Quora Question Pair์ ๊ฐ์ ํ์) 1. ๋ ๋ฌธ์ฅ์ด ์ฃผ์ด์ง๋ค 2. ๊ฐ์ ๋ป์ธ๊ฐ? Binary Classification ### ์ ์ฝ์ฌํญ 1: ์ค์ ๋ฌธ์ฅ์ด ๋ฌด์์ธ์ง๋ ๋ชจ๋ฅธ๋ค - ์ฅ์ : cleaned-up, tokenized ๋์์ผ๋ฏ๋ก tokenizer ์ ํ ๋ฑ๋ฑ์์ ํ ์ผ์ด ์ค์๋ค๊ณ ๋ณผ ์ ์๋ค - ๋จ์ : vocab์ด ์๋ค -> pretrained word vector๋ค์ ์ฌ์ฉํ ์ ์๋ค. ๋ง์ฐฌ๊ฐ์ง๋ก pretrained weight๋ค๋ ์ฌ์ฉํ๊ธฐ ์ด๋ ค์ ๋ณด์ธ๋ค - ๋ฌผ๋ก multilingual NMT ์์คํ
์ ๋ดค์ ๋ ๋ค๋ฅธ vocabulary์์ ํ์ต๋ ๊ฑธ ๊ฐ์ ธ์์ ์ฌ์ฉํด๋ณผ ์๋ ์์์ง๋ง... ์ ๋๋ค๊ณ ํด๋ ๋ฉ๋๋๋ ๋ฐฉ๋ฒ์ ์๋๋ผ์ pass ๊ทธ๋ฆฌ๊ณ vocab์ด๋ model์ด ๋๋ฌด ์ปค์ง๋ค. ### ์ ์ฝ์ฌํญ 2: ๋ฐ์ดํฐ์
์ฌ์ด์ฆ๊ฐ ์๋ค (40k instances) - ์ ์ฌ k-fold CV๋ฅผ ํ๋ค: 1:9 ์ฌ์ด์ฆ์ split์ ์ธ ๊ฐ ๋ง๋ ๋ค | 3,701 |
sorenbouma/keras-oneshot | ['one shot learning'] | ['Siamese neural networks for one-shot image recognition'] | load_data.py util.py vis_utils.py loadimgs Siamese_Loader plot_oneshot_task format_axis concat_images save_alphabets plot_alphabet Siamese_Loader join format print chdir system stack vstack append imread listdir reshape astype shape zeros range show subplots set_title matshow concat_images arange reshape set_xticklabels grid set_yticklabels set_visible set_facecolor xticks yticks xticks grid arange yticks join subplots set_title matshow set_xticklabels ones print set_yticklabels arange astype yticks grid xticks imread listdir len join print savefig plot_alphabet listdir len | sorenbouma/keras-oneshot | 3,702 |
sorooshafiee/Regularization-via-Transportation | ['generalization bounds'] | ['Regularization via Mass Transportation'] | dro_model.py PASCAL VOC/imdb.py PASCAL VOC/utils.py fio.py PASCAL VOC/finetune.py PASCAL VOC/train_classifiers.py PASCAL VOC/config.py parallel_process.py dist_rob_svm_without_support hinge_loss_minimization ksvm dist_rob_ksvm lower_bound_risk worst_case_distribution regularized_svm_without_support worst_case_distribution_inf upper_bound_for_risk_estimation dist_rob_svm_with_support regularized_ksvm svm upper_bound_risk lower_bound_for_risk_estimation regularized_svm_with_support cache print_count decache validation_process test_performance parallel_classification_table1 parallel_classification_figure parallel_classification_table2 euclidean_proj_simplex save_obj projection validate train_model proj_op train prox_op func main golden_section euclidean_proj_l1ball load_obj train_classifier ksvm dist_rob_ksvm hinge_ksvm regularized_ksvm VOC_to_IMAGENET compute_precrec _load_mat _voc_ap _n_classes _get_id get_labels compute_kernel _index_of_class _set_sizes update dist_rob_svm_without_support regularized_svm_without_support dist_rob_svm_with_support regularized_svm_with_support addVar quicksum flatten setParam list shape Model range update addQConstr float MINIMIZE chgCoeff enumerate remove optimize sort addConstr setObjective array len addVar quicksum flatten setParam list shape Model range update addQConstr float MINIMIZE chgCoeff enumerate remove optimize sort addConstr setObjective array update addQConstr list optimize addVar sort quicksum addConstr setObjective flatten shape Model array setParam MINIMIZE range len update addQConstr list optimize addVar sort quicksum addConstr setObjective flatten shape Model array setParam MINIMIZE range update optimize addVar quicksum addConstr setObjective flatten shape Model array setParam MINIMIZE range update regularized_ksvm dist_rob_ksvm eye addVar quicksum flatten setParam list Model range update addQConstr float MINIMIZE chgCoeff enumerate remove optimize sort addConstr setObjective array update addQConstr list remove optimize addVar sort quicksum addConstr setObjective flatten Model array setParam MINIMIZE range update list remove optimize addVar sort quicksum addConstr setObjective flatten MINIMIZE Model setParam float chgCoeff range enumerate update list remove optimize addVar sort quicksum addConstr setObjective flatten MINIMIZE Model setParam float chgCoeff range enumerate update list optimize addVar quicksum addConstr setObjective flatten Model ObjVal setParam zeros MINIMIZE range enumerate len update list optimize addVar quicksum addConstr setObjective flatten Model ObjVal setParam zeros MINIMIZE range enumerate len update T optimize MAXIMIZE addVar quicksum addConstr setObjective flatten shape Model setParam zeros range x len update optimize MAXIMIZE addVar quicksum addConstr setObjective flatten shape Model setParam zeros array range x len print strip rjust print_count len ljust print_count len polynomial_kernel permutation DataFrame max idxmax test_performance append train_test_split fit_transform range laplacian_kernel mean nan Imputer validation_process rbf_kernel index transform MinMaxScaler StratifiedKFold DataFrame idxmax roc_auc_score list exp defaultdict len append train_test_split fit_transform shuffle mean svm items hinge_loss_minimization transform StandardScaler array split items list defaultdict ksvm StratifiedKFold sign dot append accuracy_score array split dot ksvm sign items list exp maximum sign dot mean roc_auc_score array transform svm MinMaxScaler train_test_split fit_transform accuracy_score cumsum shape clip euclidean_proj_simplex abs norm shape zeros euclidean_proj_l1ball range norm T inf min sqrt sum range T shape zeros euclidean_proj_l1ball range zero_grad to step enumerate compute_AP batch_size eval zeros numpy len deepcopy time format validate print mean load_state_dict train range state_dict validate in_features SGD BCEWithLogitsLoss StepLR coefficient to save_obj format mean lower load_obj Linear train_model join print parameters isfile alexnet time ksvm print zeros enumerate isinf hinge_ksvm update optimize addVar quicksum addConstr setObjective Model array setParam MINIMIZE range max arange upper getattr sets sum _n_classes _index_of_class append _set_sizes range enumerate sum _n_classes _index_of_class append _set_sizes range enumerate items list _load_mat astype dot zeros array range enumerate cumsum _voc_ap argsort shape zeros sum range join _get_id lower copy2 range makedirs | # Regularization-via-Transportation | 3,703 |
soumyardash/SemEval2020-Task4 | ['common sense reasoning'] | ['CS-NET at SemEval-2020 Task 4: Siamese BERT for ComVE'] | Subtask_B/dataset.py Subtask_A/train.py Subtask_A/dataset.py Subtask_A/model.py Subtask_B/model.py Subtask_B/train.py CVEdatasetA prepare_features CVEclassifier format_time train flat_accuracy CVEdatasetB prepare_features CVEclassifier format_time train flat_accuracy sep_token convert_tokens_to_ids append tokenize cls_token len flatten int round model tuple clip_grad_norm_ zero_grad numpy save format_time argmax str flat_accuracy append to range format eval enumerate time criterion backward print parameters step len | # C*ommon* S*ense* Net at SemEval2020-Task4 by Soumya Ranjan Dash*, Sandeep Routray*, Prateek Varshney*, Ashutosh Modi ## Siamese BERT for ComVE This repository gives a Pytorch implementation of the method in the system description paper. ## Prerequisites - Python3.5 (or higher) - Pytorch 1.5.1 - numpy - transformers - csv | 3,704 |
sounakdey/doodle2search | ['sketch based image retrieval', 'image retrieval'] | ['Doodle to Search: Practical Zero-Shot Sketch-based Image Retrieval'] | src/loss/loss.py src/options.py src/loss/decoder.py src/data/class_word2vec.py src/data/sketchy_extended.py src/test.py src/loss/layers.py src/data/generator_train.py src/models/encoder.py src/train.py src/download_gdrive.py src/data/data_utils.py src/data/quickdraw_extended.py src/utils.py src/models/triplet_alexnet.py src/data/tuberlin_extended.py src/Logger/LogMetric.py download_file_from_google_drive Options main test main train adjust_learning_rate prec load_checkpoint precak save_checkpoint rec create_class_embeddings get_file_list default_image_loader_tuberlin create_dict_texts get_file_list_quickdraw_fixed default_image_loader get_file_list_quickdraw get_random_file_from_path default_sketch_loader_quickdraw load_data QuickDraw_Extended_train QuickDraw_Extended QuickDraw_Extended_valid_test Sketchy_Extended_valid_test Sketchy_Extended Sketchy_Extended_train TUBerlin_Extended TUBerlin_Extended_valid_test TUBerlin_Extended_train AverageMeter Logger LinearNN MetricNN GraphNN Wcompute gmul grad_reverse GradReverse Gconv DetangledJoinDomainLoss DomainLoss cosine_loss SemanticLoss l1_loss cosine_similarity mse_loss normalize EncoderCNN AttentionModel TripletAlexNet get get_confirm_token save_response_content Session set_grad_enabled cpu_count cuda str list cdist im_net append range sk_net format plot concatenate set mean eval enumerate time print min numpy load EncoderCNN format print load_checkpoint Compose test DataLoader DataParallel load_data load_state_dict cuda param_groups learning_rate update time sk_net format criterion backward print set_grad_enabled AverageMeter zero_grad size im_net item step enumerate len nopretrain SGD unsqueeze adjust_learning_rate save_checkpoint save log list epochs append range cat eval avg join DetangledJoinDomainLoss learning_rate log_interval add_scalar parameters randint train step len join save makedirs print format load isfile len set min len set argsort min cpu_count len load dump print open Word2Vec save append array enumerate list sorted set fromarray convert array resize fromarray convert merge resize array split load join fromarray invert reshape resize merge NameError join glob glob join load join concatenate NameError randint enumerate seed join load concatenate randint enumerate exit seed join load create_dict_texts QuickDraw_Extended_valid_test shuffle data_path exp_idf QuickDraw_Extended_train splitlines isfile create_class_embeddings dataset seed join load Sketchy_Extended_valid_test create_dict_texts shuffle data_path exp_idf splitlines isfile create_class_embeddings dataset Sketchy_Extended_train seed join load create_dict_texts TUBerlin_Extended_valid_test shuffle TUBerlin_Extended_train data_path exp_idf isfile create_class_embeddings dataset listdir len bmm size squeeze contiguous cat split squeeze norm cosine_similarity | sounakdey/doodle2search | 3,705 |
sourabhmadur/Neural-Style-Transfer | ['style transfer'] | ['A Neural Algorithm of Artistic Style'] | utils.py vgg19_style.py style.py optimize gram_matrix load_image Vgg19 as_list reshape transpose matmul int imread min resize | sourabhmadur/Neural-Style-Transfer | 3,706 |
sourabhsh55/Neural-Style-Transferring | ['style transfer'] | ['A Neural Algorithm of Artistic Style'] | Neural_Styling.py features load_img cal_slope gram_matrix content_loss get_model compute_losses convert_to_tensor expand_dims asarray VGG19 get_model sudo_model gram_matrix reduce_mean content_loss range len int reshape matmul | sourabhsh55/Neural-Style-Transferring | 3,707 |
souryadey/deep-n-cheap | ['automl'] | ['Deep-n-Cheap: An Automated Search Framework for Low Complexity Deep Learning'] | data/data.py model/model.py model/tf_model.py model/torch_model.py data/tf_data.py model_search.py main.py data/torch_data.py ei downsample bayesopt gp_predict activation dropout_mlp form_shortcuts_start_every form_shortcuts kernelfunc_se run_model_search_cnn batch_norm dropout convert_keys default_weight_decay distancefunc_ramp covmat shortcut_conns lossfunc get_states run_model_search_mlp get_data get_data_npz get_data get_data_npz Net run_network get_numparams get_numparams train_batch run_network Hook Net eval_data save_net append get_numparams range minimum list asarray rand i4_sobol_generate astype item append randint range form_shortcuts get_numparams min run_network log10 max default_weight_decay minimum distancefunc distancefunc_ramp kernelfunc zeros sum range enumerate len ones covmat T len cdf pdf update ei format asarray print ones covmat len inv lossfunc gp_predict get_states argsort eye append zeros range enumerate asarray format product print lossfunc append range len int asarray arange format print astype lossfunc ceil zeros append list format asarray print lossfunc append keys int asarray arange format print astype lossfunc ceil zeros append enumerate format asarray print lossfunc append format asarray print lossfunc append minimum update time format asarray get_numparams dropout batch_norm print shortcut_conns activation bayesopt downsample append range enumerate len update time format asarray print activation bayesopt dropout_mlp append range enumerate len reshape load_data int len load join int len MNIST list FashionMNIST Compose Subset CIFAR10 dataset CIFAR100 range as_tensor Net sum tuple build tuple argmax max round SparseCategoricalCrossentropy argmin Adam build TimeHistory sum format inf MeanSquaredError Net item LearningRateScheduler compile evaluate print EarlyStopping min array fit backward zero_grad lossfunc item step max net eval save state_dict data train_batch MultiStepLR DataParallel DataLoader mlp MSELoss device_count randperm eval_data to CrossEntropyLoss range bias_init time tqdm parameters wt_init train step len | # deep-n-cheap  ## Extended version Code for the extended version of Deep-n-Cheap can be found [here](https://github.com/usc-hal/deep-n-cheap/tree/nlp). ## Welcome This repository implements _Deep-n-Cheap_ โ an AutoML framework to search for deep learning models. Features include: - **Complexity oriented**: Get models with good performance and low training time or parameter count - Cuttomizable search space for both architecture and training hyperparameters - Supports models on CNNs, MLPs, Regression - available for tensorflow.keras and pytorch frameworks **Highlight**: State-of-the-art performance on benchmark and custom datasets with training time orders of magnitude lower than competing frameworks and NAS efforts. | 3,708 |
sparshgarg23/object-detection-and-tracking- | ['multiple object tracking'] | ['Simple Online and Realtime Tracking'] | detect.py scan.py calibrate_camera.py video.py heatmap.py train.py data.py track.py desc.py utils.py lanefit1.py match.py lanefit.py gen_example_images.py line_fit_video.py video_to_imgs.py line_fit.py img_detection.py Line.py combined_thresh.py calibrate_camera dir_threshold hls_thresh combined_thresh abs_sobel_thresh mag_thresh files_to_images FileHDF5 list_files create_xy _Descriptor HogDesc HogMap VideoDetector ImgDetector separate HeatMap calc_curve viz2 tunedfit final_viz viz1 linefit calc_vehicle_offset calc_curve viz2 tunedfit final_viz viz1 linefit calc_vehicle_offset Line calc_curve viz2 line_fit final_viz viz1 tune_fit calc_vehicle_offset annotate_video annotate_image BoxMatcher ImgPyramid ImgScanner MultipleScanner Box BoxTracker save_model evaluate_params test load_model plot_images process_image str COLOR_BGR2GRAY print reshape float32 findChessboardCorners append zeros imread calibrateCamera cvtColor CV_64F uint8 COLOR_RGB2GRAY zeros_like absolute Sobel max cvtColor CV_64F uint8 COLOR_RGB2GRAY zeros_like astype sqrt Sobel max cvtColor CV_64F COLOR_RGB2GRAY zeros_like arctan2 absolute Sobel cvtColor COLOR_RGB2HLS cvtColor zeros_like zeros_like dir_threshold hls_thresh abs_sobel_thresh mag_thresh append join sample glob COLOR_BGR2GRAY append imread array cvtColor concatenate ones shuffle zeros train_test_split len remove _separate_box print tolist append int sum concatenate astype polyfit mean rectangle nonzero append argmax array range linspace array nonzero polyfit show clear plot imshow ylim savefig linspace xlim show addWeighted clear zeros_like int_ plot fillPoly hstack astype imshow ylim savefig linspace xlim array absolute polyfit addWeighted LINE_AA int_ fillPoly putText hstack linspace zeros warpPerspective array int sum concatenate astype polyfit mean rectangle nonzero append argmax array range linspace array nonzero polyfit add_fit calc_curve tunedfit final_viz combinedthresh get_fit linefit calc_vehicle_offset undistort perspective_transform write_videofile VideoFileClip fl_image print classification_report zip SVC GridSearchCV fit show subplot subplots len imshow enumerate | sparshgarg23/object-detection-and-tracking- | 3,709 |
spatial-privacy/3d-spatial-privacy | ['mixed reality'] | ['Conservative Plane Releasing for Spatial Privacy Protection in Mixed Reality'] | loupe.py query_sets.py info3d.py pointnetvlad_eval.py transform_nets.py tf_util.py pointnetvlad_cls.py loading_pointclouds.py infoArCore.py loading_pointclouds_4096.py generalizations.py nn_matchers.py GetRansacPlanes GetLocalizedPlanes getQuantizedPointCloudOnly downSampleDescriptors getPartialPointCloudEbE getTriangleAreas getQuantizedCenteredPointCollection rotatePointCloud getLocalizedPlanes getGeneralizedPointCloudOld getSelfSimilarityDescriptors OLDgetQuantizedPointCloudOnly getPartialPointCloud getSpinImageDescriptors getRansacPlanesOld getSpinImageDescriptorsZ getQueryBiasedMatches getGeneralizedPointCloud getRankedErrorMaps getRansacPlanes getPrincipalCurvaturesHY getMatches getErrorRate getEuclideanNearestNeighbours getPrincipalCurvatures rotatePointCollection getLOCALIZEDRansacPlanes getDynamicLocalSelfSimilarity OLDgetPartialPointCloud getLocalSelfSimilarity getLocalBiasedMatches mean_confidence_interval getDelaunayTriangles getPointCloudArea OLDgetQuantizedPointCloud updatePlanesWithSubsumption getQuantizedPointCloud getCurvatures fillArCorePlanes subsumeCoplanar get_query_tuple rotate_point_cloud get_sets_dict get_rotated_tuple get_jittered_tuple jitter_point_cloud get_queries_dict load_pc_files load_pc_file get_query_tuple rotate_point_cloud get_sets_dict get_rotated_tuple get_jittered_tuple jitter_point_cloud get_queries_dict load_pc_files load_pc_file NetVLAD PoolingBaseModel nn_vote_count_0 nn_vote_count_with_ratio_scores_1 skip_diag_masking get_score_kdtree getRankedErrors_withKeypointMatches nn_vote_count_with_distance_scores_2 unique_nn_vote_count_with_distance_scores_4 get_score_kdtree_lean unique_nn_vote_count_with_ratio_scores_3_ForPartials get_best_kp_matches NN_matcher unique_nn_vote_count_with_ratio_scores_3 softmargin_loss quadruplet_loss_sm lazy_quadruplet_loss_sm lazy_triplet_loss lazy_softmargin_loss triplet_loss lazy_quadruplet_loss best_pos_distance placeholder_inputs forward quadruplet_loss get_similarity evaluate get_bn_decay get_recall get_latent_vectors check_in_test_set get_sets_dict output_to_file construct_successive_query_sets construct_query_sets construct_query_and_database_sets batch_norm_template batch_norm_for_conv1d conv2d_transpose dropout fully_connected conv3d batch_norm_for_conv2d batch_norm_for_fc avg_pool2d conv2d conv1d avg_pool3d max_pool3d max_pool2d _variable_with_weight_decay batch_norm_for_conv3d _variable_on_cpu feature_transform_net input_transform_net simplices time norm arange fabs T asarray Delaunay delete copy getPointCloudArea append randint enumerate len simplices norm asarray T fabs concatenate Delaunay delete choice len ppf array len norm reshape transpose sort argsort repeat clip cross norm abs int asarray print min copy shape append zeros clip len int asarray print min copy shape floor ceil zeros max clip append len int place asarray print min delete copy where floor ceil zeros max enumerate append len int place asarray transpose delete copy where nonzero append zeros enumerate len time asarray copy getQuantizedPointCloud append time print cos delete copy sin append simplices norm asarray T fabs concatenate Delaunay delete time place arange asarray concatenate len delete copy choice flatten index where unique append kneighbors fit time asarray arange place concatenate len delete copy choice flatten unique append kneighbors fit time asarray arange place concatenate print len delete copy choice flatten unique append kneighbors fit simplices norm T format fabs print Delaunay isnan cross nanmean nanstd abs simplices time norm arange fabs T asarray Delaunay delete copy getPointCloudArea append randint enumerate len time norm arange fabs print delete copy append randint enumerate len time norm fabs getRansacPlanes print delete copy shape append enumerate time norm arange fabs getRansacPlanes concatenate print delete copy choice around unique append round enumerate norm format concatenate print getDelaunayTriangles cross nansum append abs len append concatenate enumerate len getQuantizedPointCloudOnly cos delete flatten clip OLDgetQuantizedPointCloudOnly sin ceil append sum asarray arccos copy enumerate time norm print zeros amax len getQuantizedPointCloudOnly asarray time arccos norm amax cos delete copy ceil flatten sin append zeros sum clip enumerate len int clip asarray norm arccos concatenate len delete copy pi cross flatten floor append getDynamicLocalSelfSimilarity zeros enumerate getLocalSelfSimilarity int format arccos concatenate print reshape multiply abs pi mean shape repeat getEuclideanNearestNeighbours sum max clip len int sum arccos concatenate abs reshape multiply pi mean shape repeat getEuclideanNearestNeighbours median argmax clip len norm reshape transpose sort argsort repeat clip len norm reshape transpose multiply sort argsort repeat clip len norm reshape transpose sort argsort repeat clip amax len format asarray concatenate print eig getEuclideanNearestNeighbours append zeros sum len format asarray concatenate print eig getEuclideanNearestNeighbours append zeros sum len format asarray concatenate print reshape multiply eig shape repeat getEuclideanNearestNeighbours append zeros sum len append getRankedErrorMaps mean_confidence_interval asarray append zeros sum enumerate reshape concatenate asarray matmul copy int norm asarray concatenate insert multiply reshape rand cross append abs ConvexHull simplices arange Delaunay delete where abs append asarray concatenate copy choice unique enumerate norm T cross dot getPointCloudArea zeros len fromfile join print reshape append array load_pc_file reshape cos pi dot shape uniform sin zeros array range shape clip randn list shuffle set load_pc_files append keys range load_pc_file list rotate_point_cloud squeeze shuffle set load_pc_files append expand_dims keys range load_pc_file list squeeze shuffle set jitter_point_cloud load_pc_files append expand_dims keys range load_pc_file getGeneralizedPointCloudOld asarray arange getRansacPlanes ones KDTree random pi choice query getSpinImageDescriptors getRansacPlanesOld append rotatePointCloud getGeneralizedPointCloud amax enumerate asarray arange ones KDTree random pi choice query getSpinImageDescriptors append rotatePointCloud amax enumerate append get_best_kp_matches asarray isnan time T asarray multiply len get_best_kp_matches unique append enumerate T asarray multiply len unique append enumerate sum len append zeros argmax enumerate amax concatenate multiply size flatten nan_to_num mean bincount zeros sum append enumerate amax concatenate print multiply size flatten nan_to_num mean bincount zeros sum append enumerate T asarray multiply len unique append zeros sum enumerate T asarray print multiply len unique append zeros sum enumerate argmax sum norm exp count_nonzero skip_diag_masking ones multiply insert greater where shape repeat unique abs float32 placeholder value l2_normalize print reshape squeeze matmul conv2d NetVLAD expand_dims reshape subtract maximum reduce_sum add reduce_mean best_pos_distance tile fill zeros squared_difference reshape subtract reduce_max maximum reduce_sum add reduce_mean best_pos_distance tile fill zeros squared_difference exp reshape subtract reduce_sum reduce_mean best_pos_distance tile fill log squared_difference exp reshape subtract reduce_max reduce_sum reduce_mean best_pos_distance tile fill log squared_difference softmargin_loss reshape subtract maximum reduce_sum add reduce_mean best_pos_distance tile fill zeros squared_difference lazy_softmargin_loss reshape subtract reduce_max maximum reduce_sum add reduce_mean best_pos_distance tile fill zeros squared_difference reshape triplet_loss subtract maximum reduce_sum add reduce_mean best_pos_distance tile fill zeros squared_difference lazy_triplet_loss reshape subtract reduce_max maximum reduce_sum add reduce_mean best_pos_distance tile fill zeros squared_difference minimum exponential_decay zeros list arange print reshape squeeze shape vstack array run load_pc_files append zeros expand_dims keys range len int asarray print cumsum KDTree query dot array append float round max range len print KDTree query dot mean append array range len print join iterrows print KDTree output_to_file astype rename append DataFrame read_csv join iterrows query_radius list format print KDTree tolist astype output_to_file range keys rename append DataFrame array read_csv len join iterrows query_radius list format print KDTree tolist astype output_to_file range keys rename append DataFrame array read_csv len multiply add_to_collection xavier_initializer _variable_on_cpu l2_loss truncated_normal_initializer value reshape fully_connected conv2d max_pool2d expand_dims value fully_connected reshape conv2d max_pool2d | spatial-privacy/3d-spatial-privacy | 3,710 |
spbu-math-cs/Riemannian-Gaussian-Processes | ['gaussian processes'] | ['Matรฉrn Gaussian processes on Riemannian manifolds'] | manifold_matern/__init__.py manifold_matern/utils.py manifold_matern/plotting.py manifold_matern/manifold_matern_gp.py manifold_matern/laplace_eigenvalues.py setup.py manifold_matern/cli.py demo_dragon.py construct_ground_truth argument_parser get_eigenpairs ManifoldMaternGP plot_function_3d plot_example plot_function_3d_with_data set_camera mesh_triangulation construct_mesh_graph export_fun convert_to_firedrake_function jitchol check_mesh_connected rescale_eigenfunctions num_vertices get construct_mesh_graph pi sin zeros range shortest_path_length add_argument ArgumentParser inner Options getEigenpair create handle solve getConverged real append setValue sum range setST grad copy sqrt setType SINVERT T setFromOptions SMALLEST_MAGNITUDE getArray getVecs setWhichEigenpairs setOperators zeros setDimensions mesh_triangulation triangular_mesh plot_function_3d data_ro points3d compute_view_plane_normal render z_minus_view Function plot_function_3d_with_data set_camera savefig figure cholesky File write Function data_ro values sum zeros_like Graph sqrt coo_matrix zeros data_ro enumerate values len construct_mesh_graph | spbu-math-cs/Riemannian-Gaussian-Processes | 3,711 |
spcl/deep-weather | ['weather forecasting'] | ['Deep Learning for Post-Processing Ensemble Weather Forecasts'] | Bias_Correction/args.py Bias_Correction/models/memory_saving_gradients.py Bias_Correction/cross_validate.py Bias_Correction/data/GRIBemos.py Uncertainty_Quantification/Deep500_recipe/events.py Uncertainty_Quantification/Deep500_recipe/recipe_UQ.py Uncertainty_Quantification/Pytorch/utils.py Uncertainty_Quantification/Deep500_recipe/losses.py Uncertainty_Quantification/Pytorch/models.py Uncertainty_Quantification/Deep500_recipe/scheduler.py Uncertainty_Quantification/Deep500_recipe/loader.py Bias_Correction/models/tile_CNN.py Bias_Correction/models/emos.py Bias_Correction/plot.py Bias_Correction/models/layers.py Bias_Correction/data/dataset.py Uncertainty_Quantification/Pytorch/infer.py Bias_Correction/config.py Uncertainty_Quantification/RESNET2D.py Bias_Correction/models/Unet2.py Bias_Correction/combine_pred.py Bias_Correction/models/Unet2_l2.py Uncertainty_Quantification/Deep500_recipe/utils.py Bias_Correction/models/LCN_unet.py Uncertainty_Quantification/train.py Uncertainty_Quantification/Preprocessing/GRIB2npy.py Uncertainty_Quantification/Preprocessing/preprocessing_parameters.py Uncertainty_Quantification/Deep500_recipe/models.py Bias_Correction/main.py Bias_Correction/models/refmse.py Bias_Correction/data/data_macro.py Bias_Correction/models/LCN.py Uncertainty_Quantification/Pytorch/train.py Bias_Correction/models/refcrps.py Bias_Correction/models/utils.py Bias_Correction/models/Unet3_local.py Uncertainty_Quantification/parameters.py Uncertainty_Quantification/Pytorch/loader.py Bias_Correction/data/GRIBglobal.py Uncertainty_Quantification/Preprocessing/npy2tfr.py Bias_Correction/models/Unet3.py Bias_Correction/models/one2one.py Bias_Correction/models/Unet2_main.py Bias_Correction/models/models.py Uncertainty_Quantification/Pytorch/ssim.py Bias_Correction/run.py Bias_Correction/models/Unet3_tile.py Bias_Correction/global_macros.py Uncertainty_Quantification/predict.py print_flag getFlag getModel combine_pred convert_mean_std parse_pos getTypes getHeights parse_normal main getFlags GetModelAndOptNames cross_validate main plotHeatmap GetModelAndOptNames reorg getmap_overlay generate_row_col_labels GetModelAndOptNames plotLoss rmse plotheatmap boxplot stepquantize heatmap run TF2FLRD _parse_ makeTFRecordyearly makeTFRecord getfilelist getNextDateFile GRIBsfc GRIBplslice getSample getxyfilenames getMeanStd GRIBpl GRIBextract GRIBprocess meanparse getSelectedSuffix makeTFRecordyearly makeTFRecord getfilelist getNextDateFile GRIBsfc GRIBplslice getSample getxyfilenames getSelectedSuffix getMeanStd GRIBpl GRIBextract GRIBprocess meanparse get_split_string reduce_std py_func emos CRPS reduce_var LCN2D_layer upconv_op R2p1D_layer centre_crop_and_concat_layer affine_layer conv3Dpad conv_batch_relu3d_layer tile_conv_layer conv_tile_batch_relu3d_layer upsample_conv2d_layer upconv3d_layer LCN3D_layer LCN LCN_unet gradients_memory capture_ops format_ops gradients _to_op _to_ops _is_iterable debug_print my_add_control_inputs tf_gradients tf_toposort gradients_speed gradients_collection fast_backward_ops simple_conv_tile unet3_l2 unet3_l1 unet3_l1_tile unet3_l3 simple_conv one2one reduce_std py_func refcrps CRPS reduce_var refmse TileCNN Unet2 Unet2_l2 main parse Unet3 Unet3_local Unet3_tile getLoss getEvaluate getLossSlice getSSIM variable_summaries get_n_trainable_parameters base_model getCrop general_model TFRecord2FLRD TFRparser CRPS Model py_func TFRecord2FLRD TFRparser RMSETerminalBarEvent WeatherDataset CallableD500WeatherDataset D500WeatherDataset WeatherShuffleSampler MSSSIMLoss MixLoss pool batch_norm upsample concat activation ConvBatchRelu Conv resnet2d_simple unet3d Incep fixed_components_gen executor mutable_components_gen model CyclicLRScheduler reduce_sample_x random_crop horizontal_flip UQDataClass transpose vertical_flip args_parser standardize reduce_sample_y calc Npy2TFRecord main WeatherDataset WDatamodule pool batch_norm upsample concat activation ConvBatchRelu Conv resnet2d_simple MSSSIMLoss unet3d Incep MixLoss MS_SSIM _ssim ms_ssim SSIM ssim _fspecial_gauss_1d gaussian_filter main reduce_sample_x random_crop horizontal_flip transpose vertical_flip standardize reduce_sample_y unstandardize DEFINE_list DEFINE_integer strftime LOGGER_ROOT DEFINE_float CKPT_ROOT DEFINE_bool FLAGS DEFINE_string list format print getattr keys load str arange glob sort print shape stack save append len load mean save zeros range parse_single_example parse_single_example print exit seed format arange file_comment parsefcn print set_random_seed mean append reset_default_graph range len getFlags GetModelAndOptNames print_flag cross_validate seed arange TF_DATA_DIRECTORY file_comment parsefcn getFlag set_random_seed reset_default_graph load seed arange GetModelAndOptNames TF_DATA_DIRECTORY file_comment parsefcn getFlag set_random_seed reset_default_graph load seed show getTypes arange GetModelAndOptNames TF_DATA_DIRECTORY file_comment parsefcn subplots set_title getFlag set_random_seed sqrt save reset_default_graph load show subplots plot xlabel ylabel title legend open items list arange set_xticklabels set_yticklabels set_yticks get_xticklabels colorbar imshow set_visible set_ylabel set_xticks setp gca tick_params codes_count_in_file reshape codes_grib_new_from_file copy codes_get_values nan full range open clip copy where range len load reorg getmap_overlay generate_row_col_labels subplots show TF_DATA_DIRECTORY print min exit colorbar imshow title set_ylabel rmse max open print_flag getFlag open parse_single_example TFRecordDataset shuffle map prefetch batch save open str codes_count_in_file codes_get parse codes_release codes_grib_new_from_file copy Nm Ni nan trange int reshape codes_get_values Nj full len print GRIBextract GRIBprocess list keys GRIBprocess list keys print GRIBprocess load remove glob square mean shape sqrt save isfile zeros len join str int month day date year split join split str getNextDateFile getSelectedSuffix glob append getSample load str TFRecordWriter print write SerializeToString close Example trange len getxyfilenames print arange makeTFRecordyearly join split get_split_string get_split_string concatenate sqrt pi str get_default_graph randint reduce_mean square pad constant conv3d range get_shape int constant conv3Dpad concat min pad max range batch_normalization tile_conv_layer relu get_shape print reshape transpose shape zip upsample_conv2d_layer upconv3d_layer conv3d_transpose resize_images reshape transpose shape conv2d batch_normalization conv3d relu get_shape slice concat int32 array Variable get_shape zeros ones constant affine_layer Variable concat reduce_sum pad zeros range constant affine_layer absolute_difference Variable reduce_sum roll pad stack zeros range my_add_control_inputs device stop_gradient fast_backward_ops values sgv list get_collection _unsparsify tf_gradients tf_toposort intersection ceil append range filter_ts_from_regex _set_device format_ops get_backward_walk_ops _to_ops debug_print op set sqrt zip get_forward_walk_ops copy_with_input_replacements reroute_ts filter_ts keys int items len toposort list inputs set outputs intersection get_forward_walk_ops append difference get_backward_walk_ops set int time str select_ops extend get_default_graph hasattr iter print tuple add_control_inputs append conv3d conv_batch_relu3d_layer conv3d conv_tile_batch_relu3d_layer upconv_op centre_crop_and_concat_layer conv3d conv_batch_relu3d_layer append max_pooling3d upconv_op centre_crop_and_concat_layer conv3d conv_batch_relu3d_layer conv_tile_batch_relu3d_layer max_pooling3d upconv_op centre_crop_and_concat_layer conv3d conv_batch_relu3d_layer append max_pooling3d upconv_op centre_crop_and_concat_layer conv3d conv_batch_relu3d_layer append max_pooling3d parse_single_example reshape getTypes getHeights mean_squared_error getTypes getHeights absolute_difference transpose getTypes getHeights getTypes getHeights getTypes TF_DATA_DIRECTORY reshape square sqrt reduce_mean getHeights get_shape trainable_variables DO_CRPS parse_single_example TFRecordDataset map batch shuffle prefetch BatchNorm2d BatchNorm3d resnet2d_simple L1Loss MSSSIMLoss MixLoss model parse_known_args parse_args add_argument ArgumentParser reshape concatenate crop_lat randint crop_lon flip flip str print len empty enumerate Example write SerializeToString checkpoint_start resnet2d_simple unet3d ArgumentParser save WeatherDataset parse_known_args load_state_dict append parse_args add_argparse_args eval enumerate load add_argument output numpy array makedirs to exp conv3d warn conv2d conv enumerate mean pow device to gaussian_filter relu squeeze _ssim shape repeat _fspecial_gauss_1d range len view relu squeeze min _ssim avg_pool avg_pool2d shape stack repeat prod device append avg_pool3d to _fspecial_gauss_1d range len val setup print train shuffle test fix_split WDatamodule from_argparse_args fit | # Deep Learning for Post-Processing Ensemble Weather Forecasts We make available the data as well as the code that is necessary to run the models in our [paper](https://arxiv.org/abs/2005.08748) through this repository. It is our hope that our findings and the data can be used to further advance weather forecasting research. ## Research description Our research focuses on applying recent architectures from Deep Learning to Ensemble Weather Forecasts. To achieve this we use global reforecast data from the ECMWF that we call **ENS10**, as well as reanalysis data **ERA5**. More specifically, ENS10 is aimed at providing researchers with a basic dataset of forecasted values that would be used in modern numerical weather prediction pipelines. Using ERA5 data as ground truth, we then use a subset of the ensemble forecasts to post-process and improve. Our aim is to help weather forecasting centers predict extreme weather events cheaper and more accurately. <p align="center"> <img width="40%" src="/report/G_Winston_E10_step1.png"> <img width="40%" src="/report/G_Winston_B5U5C-E10_step1.png"> </p> In the case of tropical cyclone [Winston](https://en.wikipedia.org/wiki/Cyclone_Winston) we achieve a relative improvement of over 26% in forecast skill, measured in Continuous Ranked Probability Score (CRPS) over the full 10 member ensemble, using a subset of five trajectories. Additionally, the models specifically predict the future path of the cyclone more accurately. | 3,712 |
speakstone/TextSnake | ['scene text detection'] | ['TextSnake: A Flexible Representation for Detecting Text of Arbitrary Shapes'] | util/detection.py util/visualize.py train_textsnake.py dataset/total_text/Evaluation_Protocol/Python_scripts/Pascal_VOC.py bai_pachong/index.py util/augmentation.py dataset/synth-text/make_list.py util/shedule.py dataset/synth_text.py bai_pachong/main.py dataset/dataload.py eval_textsnake.py util/summary.py util/misc.py util/config.py network/resnet.py network/loss.py dataset/total_text.py demo.py bai_pachong/Img_Deduplication.py dataset/data_coco.py dataset/deploy.py dataset/data_util.py dataset/total_text/Evaluation_Protocol/Python_scripts/polygon_wrapper.py util/option.py bai_pachong/test.py network/vgg.py network/textnet.py dataset/total_text/Evaluation_Protocol/Python_scripts/Deteval.py main write_to_file inference main write_to_file inference validation save_model load_model main train filecount md5sum delfile Crawler dowmloadPic TextDataset pil_load_img TextInstance get convert txt_convert get_and_check get_filename_as_int pil_load_img DeployDataset SynthText TotalText gt_reading_mod many_to_many input_reading_mod detection_filtering sigma_calculation tau_calculation one_to_one one_to_many input_reading_mod detection_filtering gt_reading_mod approx_area_of_intersection iou shapely_area area_of_intersection area shapely_area_of_intersection iod TextLoss ResNet50 TextNet Upsample make_layers VGG16 VGG Rotate AugmentColor SquarePadding Compose RandomMirror RandomResizedLimitCrop RandomContrast Augmentation RandomResizedCrop Resize BaseTransform Normalize RandomBrightness Padding print_config update_config TextDetector norm2 merge_polygons disjoint_find split_edge_seqence AverageMeter cos split_long_edges fill_hole rescale_result mkdirs regularize_sin_cos vector_cos find_bottom to_device vector_sin find_long_edges disjoint_merge BaseOptions str2bool arg2str FixLR LogSummary visualize_network_output visualize_detection imwrite rescale_result to_device write_to_file exp_name vis_dir mkdirs format replace synchronize astype detect enumerate join time uint8 print numpy visualize_detection len join load_model DeployDataset TextNet print DataLoader TextDetector device output_dir inference to cuda exp_name append concatenate zip format TotalText call backbone_name checkepoch save_dir join format print mkdirs backbone_name save save_dir exp_name print format load load_state_dict save_model model zero_grad to_device write_scalars get_lr update format visualize_network_output avg item enumerate time criterion backward print AverageMeter step len FixLR DataParallel StepLR mgpu max_epoch Adam strftime range LogSummary start_epoch TextLoss resume lr SynthText validation log_dir parameters train int read update read md5 close open getcwd remove md5sum walk get str S print write close findall content open array open findall findall strip open list basename getroot append get parse format close get_filename_as_int join int items print text write dumps get_and_check dict len join list format items print strip write dumps close append get_filename_as_int open loadmat list squeeze map iod enumerate split range where range where range where polygon zeros sum max minimum min max maximum buffer stack Polygon zeros_like maximum where polygon zeros sum max zeros_like maximum where polygon zeros sum max sum zeros_like maximum where polygon zeros round max Conv2d items list print items list format makedirs astype resize uint8 astype copy floodFill shape zeros bool sqrt sqrt sqrt norm2 concatenate append range len append len append len cumsum sum range append disjoint_find Polygon merge_two_polygon astype xy unique append array range len vars sorted items strftime join uint8 format imwrite concatenate astype vis_dir mkdir resize numpy max range exp_name len uint8 concatenate polylines COLOR_GRAY2BGR astype ascontiguousarray copy cvtColor | speakstone/TextSnake | 3,713 |
src-d/lapjv | ['time series', 'dynamic time warping'] | ['Comparing Temporal Graphs Using Dynamic Time Warping'] | setup.py test.py doc/conf.py get_numpy_include LapjvTests | [](https://github.com/src-d/lapjv/actions) [](https://pypi.python.org/pypi/lapjv) Linear Assignment Problem solver using Jonker-Volgenant algorithm ================================================================== This project is the rewrite of [pyLAPJV](https://github.com/hrldcpr/pyLAPJV) which supports Python 3 and updates the core code. The performance is twice as high as the original thanks to the optimization of the augmenting row reduction phase using Intel AVX2 intrinsics. It is a native Python 3 module and does not work with Python 2.x, stick to pyLAPJV otherwise. [](http://web.archive.org/web/20180611012448/https://blog.sourced.tech/post/lapjv//) [Linear assignment problem](https://en.wikipedia.org/wiki/Assignment_problem) | 3,714 |
sremedios/multiple_instance_learning | ['multiple instance learning'] | ['Extracting 2D weak labels from volume labels using multiple instance learning in CT hemorrhage detection'] | utils/vis_training_curve.py utils/logger.py utils/utils.py utils/save_figures.py utils/preprocess.py utils/skullstrip.py utils/parse_history.py utils/class_mapping.py utils/calculate_threshold_dual.py utils/reorient.py train.py utils/tfrecord_utils.py utils/augmentations.py make_tfrecord.py utils/check_data.py utils/patch_ops.py utils/apply_model.py utils/pad.py models/resnet.py utils/calculate_threshold.py intensity_normalize clip_negatives prepare_data step_bag_val mil_prediction running_average step_bag_gradient show_progbar residual_block resnet apply_model_single_input apply_triplanar_models apply_model flip_dim2 flip_dim3 flip_dim1 rotate_2D get_dice calc_dice get_dice calc_dice read_mapping write_mapping write_log center_crop pad_image pad_crop_image_2D get_nonoverlapping_patches get_intersection PadImage CreatePatchesForTraining get_slices get_patches get_center_coords preprocess preprocess_dir reorient orient save_slice scale_ct_for_png skullstrip parse_seg_bag image_seg_example parse_bag image_example write_dice_scores threshold remove_ext now preprocess write_log get_root_filename get_dice dice_metric parse_args save_args_to_csv write_stats min max get_fdata clip_negatives astype float32 get_axial_slices zeros argsort int format min write flush trainable_variables gradient softmax_cross_entropy_with_logits mil_prediction model reduce_mean softmax range add residual_block Input Model list tqdm zeros array range predict list tqdm zeros array range predict list reshape transpose copy tqdm average shape zip append zeros array range predict logical_and bool sum astype load copy get_data get_zooms get_dice sum permutations set list pad append zeros float round range ceil int floor center_crop pad zeros float round shape asarray zeros print shape time set shuffle where set nonzero get_intersection minimum deepcopy list asarray ndarray concatenate multiply astype SystemRandom nonzero sample range append len reshape shape pad_crop_image_2D append array range rollaxis reshape shape append array range get_data get_patches max list transpose sum range asarray shuffle zip listdir load join int minimum print sort PadImage tqdm zeros len join remove isdir skullstrip copy orient exists makedirs join print apply_async close ThreadPool tqdm rmtree preprocess listdir exists makedirs print join system exists stdout join decode close system makedirs T max divide join remove_ext convert zfill save scale_ct_for_png enumerate print join system exists Feature get uint8 decode_raw reshape float32 float16 cast parse_single_example Feature get decode_raw float64 reshape float32 cast parse_single_example join makedirs print add_argument exit ArgumentParser decode join strip urlopen split print flatten dice_metric append range sum sort copy get_data get_zooms get_dice label remove_small_objects sum pad_image regionprops enumerate load join get_data Nifti1Image get_root_filename save label remove_small_objects | sremedios/multiple_instance_learning | 3,715 |
sremes/nssm-gp | ['gaussian processes'] | ['Neural Non-Stationary Spectral Kernel'] | nssm_gp/__init__.py setup.py experiments/datasets.py nssm_gp/neural.py experiments/run-experiment.py nssm_gp/spectral_kernels.py nssm_gp/spectral_svgp.py experiments/get_best_results.py nssm_gp/initializers.py Sunspots Concrete Boston Kin8mn Datasets Energy Naval SolarRadiance Mocap2 Skin WineRed Motorcycle WineWhite Protein Power Dataset Mocap get_scores simple_model random_Z init_spectral _gsm_rand_params init_gsm init_neural robust_kernel NeuralSpectralKernel _create_params SMKernelComponent square_dist SMKernel BSMKernelComponent BSMKernel ProductBSMKernel SpectralSVGP _check_eigvals square_dist stack read_csv RBF SVGP copy randint std len randint sort copy RBF collect print compute_log_likelihood shape range compile collect print compute_log_likelihood shape range compile collect print compute_log_likelihood shape range compile jitter_level reduce_min self_adjoint_eigvals square reduce_sum rand astype BSMKernelComponent append range append range BSMKernel self_adjoint_eigvals | sremes/nssm-gp | 3,716 |
sreycodes/YLR | ['link prediction'] | ['Link Prediction Based on Graph Neural Networks', 'Gravity-Inspired Graph Autoencoders for Directed Link Prediction'] | code/graph_vae_orig.py code/gae/initializations.py code/graph_vae_weighted.py code/graph_vae.py code/gae/preprocessing.py code/gae/input_data.py code/gae/model.py code/gae/train.py code/gae/optimizer.py code/gae/layers.py save_visualization save_network_statistics pause get_dataset get_graph_and_features get_roc_score get_network_statistics save_visualization save_network_statistics get_dataset get_graph_and_features get_roc_score get_network_statistics save_visualization save_network_statistics get_dataset get_graph_and_features get_roc_score get_network_statistics weight_variable_glorot parse_index_file load_data dropout_sparse get_layer_uid pairwise_distance GravityInspiredDecoder GraphConvolution InnerProductDecoder GraphConvolutionSparse Layer DirectedGCNModelVAE Model GCNModelVAE GCNModelAE OptimizerAE OptimizerVAE sparse_to_tuple preprocess_graph construct_feed_dict mask_test_edges get_bridge_edges dfs mask_test_edges_directed get_roc_score input eval update T hstack z_mean average_precision_score dot sigmoid append roc_auc_score run arange debug mean rename read_csv get_dummies fillna len iterrows normalize tocsr lil_matrix print debug unique to_list save_npz to_dict range len degree set_edgecolor dict clf savefig figure gca draw_spring number_connected_components diameter number_of_nodes float number_of_edges density average_clustering sum transitivity values print get_network_statistics reshape reconstructions sqrt random_uniform append int strip open load list format lil_matrix from_dict_of_lists tolil tuple sort len min adjacency_matrix parse_index_file append max range open sparse_retain floor cast transpose matmul reduce_sum data shape transpose tocoo tocoo flatten coo_matrix array eye sum diags dict update range dfs append min enumerate int remove print eliminate_zeros tolil sparse_to_tuple from_scipy_sparse_matrix shuffle set dia_matrix add floor randint triu array bridges eliminate_zeros subgraph where floor number_weakly_connected_components max bridges to_undirected sparse_to_tuple add dia_matrix add_edge fill_diagonal shuffle set adjacency_matrix stack enumerate int remove toarray print from_scipy_sparse_matrix weakly_connected_components randint array remove_edge len | sreycodes/YLR | 3,717 |
srihari-humbarwadi/FastFCN_TF2.0 | ['semantic segmentation'] | ['FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation'] | train.py JPU.py resnet.py conv_block JPU_DeepLab sepconv_block JPU ASPP preprocess_input decode_predictions ResNet50 ResNet101 ResNet152 get_image random_crop load_data conv_block sepconv_block range append as_list conv_block set_shape conv_block output ResNet101 Model JPU ASPP constant case read_file cast resize decode_png shape crop_to_bounding_box random_crop | srihari-humbarwadi/FastFCN_TF2.0 | 3,718 |
srihari-humbarwadi/adain-tensorflow2.x | ['style transfer'] | ['Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization'] | adain/dataset_utils/tfrecord_writer.py adain/distribute.py adain/cfg/__init__.py adain/export.py adain/model/layers/reflection_padding_2d.py adain/trainer.py adain/main.py adain/dataloader/tfrecord_parser.py adain/dataset_utils/create_tfrecords.py adain/dataloader/preprocessing_pipeline.py adain/cfg/config.py adain/model/network/style_transfer_network.py adain/model/__init__.py adain/model/layers/adaptive_instance_normalization.py adain/learning_rate_schedule.py adain/model/builder.py adain/dataloader/__init__.py adain/dataloader/input_pipeline.py adain/model/layers/__init__.py adain/image_utils.py get_strategy main prepare_visualization_image plot_to_image imshow read_image read_image_cv2 InverseDecay main set_precision Trainer Config InputPipeline parse_example main write_tfrecords TFrecordWriter model_builder get_optimizer ReflectionPadding2D get_vgg_model StyleTransferNetwork name connect info items list format export_dir model get_concrete_function debug print build Trainer params set_verbosity save info InferenceModule output_shapes convert_variables_to_constants_v2_as_graph PreprocessingPipeline grayscale_to_rgb set_shape read_file expand_dims decode_image COLOR_RGB2BGR IMREAD_UNCHANGED imread cvtColor uint8 axis title figure BytesIO seek close getvalue savefig decode_png subplot uint8 subplots axis tight_layout imshow title set_global_policy format compute_dtype Policy variable_dtype info set_jit strategy xla get_strategy precision gpu_memory_allow_growth InputPipeline list_physical_devices set_precision parse_single_example set_shape cast decode_image format flush_last warning TFrecordWriter push sorted num_shards glob shuffle num_images prefix mkdir output_dir write_tfrecords image_paths_pattern len constant offset isinstance reshape get_config new_layer Model scale Conv2D from_config VGG19 Input | # AdaIN ### This work is supported by Cloud TPUs from Google's TPU Research Cloud (TRC) ## Getting started - Download the coco2017 and wikiart datasets - Generate the tfrecords for training and validation. ``` python3 -m adain.dataset_utils.create_tfrecords --image_paths_pattern coco/train2017/* --prefix coco-train --output_dir tfrecords python3 -m adain.dataset_utils.create_tfrecords --image_paths_pattern coco/val2017/* --prefix coco-val --output_dir tfrecords python3 -m adain.dataset_utils.create_tfrecords --image_paths_pattern wikiart/train/* --prefix wikiart-train --output_dir tfrecords ``` | 3,719 |
sriloksagar/fashion-mnist | ['data augmentation'] | ['DENSER: Deep Evolutionary Network Structured Representation'] | utils/helper.py configs.py benchmark/convnet.py app.py benchmark/runner.py utils/argparser.py utils/mnist_reader.py visualization/project_zalando.py start_s3_sync get_json_logger touch touch_dir _get_logger main cnn_model_fn PredictJob JobWorker JobManager get_args_request parse_arg get_args_cli now_int upload_result_s3 get_sprite_image invert_grayscale create_sprite_image vector_to_matrix_mnist UploadS3Thread load_mnist UploadS3Thread start Event dirname makedirs makedirs setFormatter touch_dir DEBUG getLogger addHandler StreamHandler Formatter touch setLevel INFO FileHandler setFormatter getLogger addHandler Formatter touch setLevel INFO FileHandler dense max_pooling2d dropout one_hot minimize reshape GradientDescentOptimizer conv2d softmax_cross_entropy asarray evaluate print Estimator shuffle labels images numpy_input_fn train range read_data_sets int append items list defaultdict utcfromtimestamp info int isinstance ones sqrt ceil array range vector_to_matrix_mnist invert_grayscale join | sriloksagar/fashion-mnist | 3,720 |
srk97/targeted-adversarial-mnist | ['adversarial attack'] | ['Boosting Adversarial Attacks with Momentum'] | adversary.py adversary_momentum.py model.py max_pool_2x2 conv2d deepnn main bias_variable weight_variable truncated_normal constant print data_dir add_graph mkdtemp float32 placeholder FileWriter int64 reduce_mean get_default_graph deepnn read_data_sets | srk97/targeted-adversarial-mnist | 3,721 |
srv/Posidonia-semantic-segmentation | ['semantic segmentation'] | ['Deep Semantic Segmentation in an AUV for Online Posidonia Oceanica Meadows identification'] | vgg16fcn8/submodules/evaluation/kitti_test.py preprocess/change_ext.py preprocess/set_bw.py uncertainty/uncertainty_net.py vgg16fcn8/inference.py evaluation/set_thr.py vgg16fcn8/train.py vgg16fcn8/optimizer/generic_optimizer.py vgg16fcn8/decoder/kitti_multiloss.py vgg16fcn8/encoder/fcn8_vgg.py uncertainty/per_error.py uncertainty/uncertainty_hand.py preprocess/adapt_gt.py vgg16fcn8/inference_frozen.py vgg16fcn8/submodules/evaluation/kitti_devkit/helper.py vgg16fcn8/inputs/kitti_seg_input.py vgg16fcn8/evals/kitti_eval.py vgg16fcn8/change_npy.py vgg16fcn8/freeze.py preprocess/maketxt.py evaluation/view_error.py vgg16fcn8/encoder/resnet.py vgg16fcn8/submodules/evaluation/overlay_utils.py preprocess/crop_image.py vgg16fcn8/decoder/fcn.py uncertainty/per_inc.py evaluation/matrix.py vgg16fcn8/submodules/evaluation/kitti_devkit/seg_utils.py preprocess/reshape.py main fast_overlay main dict_merge decoder upsample_initilizer _compute_cross_entropy_mean _compute_f1 _compute_soft_ui _activation_summary _upscore_layer evaluation _add_softmax loss decoder _compute_cross_entropy_mean _compute_f1 _compute_soft_ui evaluation _add_softmax loss inference _initalize_variables _relu _max_pool _get_variable block _imagenet_preprocess _fc stack _conv _bn checkpoint_fn inference resize_label_image eval_image evaluate _dtypes random_crop resize_label_image start_enqueuing_threads random_resize crop_to_size create_queues _read_processed_image _make_data_gen _enqueue_join inputs random_crop_soft _load_gt_file jitter_input shuffle_join _processe_image main resize_label_image_with_pad get_learning_rate training main _create_input_placeholder create_test_output do_inference overlay_segmentation replace_colors setFigLinesBW overlayImageWithConfidence saveBEVImageWithAxes evalExp setAxLinesBW plotPrecisionRecall getGroundTruth modBev_plot calcEvalMeasures pxEval_maximizeFMeasure setFigLinesBW overlayImageWithConfidence saveBEVImageWithAxes evalExp setAxLinesBW plotPrecisionRecall modBev_plot calcEvalMeasures pxEval_maximizeFMeasure make_overlay join RUN do_inference data_file info toimage reshape dot shape paste items initialize_training_folder mod _add_paths_to_sys error hypes exit literal_eval do_training load_plugins set_gpus_to_use dict_merge set_dirs maybe_download_and_extract variance_scaling_initializer l2_regularizer _activation_summary _upscore_layer conv2d shape add set_shape _add_softmax Print name zero_fraction histogram scalar reduce_mean reduce_sum reduce_mean reduce_sum reshape to_int32 reduce_sum append argmax equal join upscore32 fc7 build pool5 conv4_3 pool3 pool4 FCN8VGG convert_to_tensor global_variables _imagenet_preprocess join restore format get_default_session error exit Saver checkpoint_fn info global_variables_initializer run concat split range get_shape list _get_variable assign_moving_average add_to_collection batch_normalization cond moments range len _get_variable xw_plus_b truncated_normal_initializer l2_regularizer _get_variable truncated_normal_initializer list all evalExp array range shape imresize join list time shape dirname append zeros array range pxEval_maximizeFMeasure run join count shuffle realpath dirname imread split join all concatenate reshape _load_gt_file shape array random_crop resize_label_image crop_to_size random_resize random_crop_soft randint max randint shape zeros randint concatenate zeros concatenate imresize shape normalvariate zeros randint max size float32 FIFOQueue cast scalar Thread _make_data_gen enqueue float32 placeholder start int32 next range per_image_whitening random_hue random_saturation dequeue random_brightness expand_dims info random_contrast add_queue_runner QueueRunner size _enqueue_join dequeue maximum float32 cast RandomShuffleQueue scalar _dtypes random_brightness random_contrast random_hue random_saturation to_float format name error dequeue dequeue_many _processe_image image set_shape expand_dims _make_data_gen inputs create_queues max enumerate join format mkdir dirname info float32 placeholder load_modules_from_logdir load_hypes_from_logdir gpus realpath logdir toimage convert putpixel shape range toimage convert putpixel shape paste range CV_LOAD_IMAGE_UNCHANGED imread astype copy cumsum flipud sum concatenate arange set_trace where zeros float argmax max calcEvalMeasures len dict astype setAxLinesBW get_axes set_markersize get_lines get_color set_marker set_dashes clear setFigLinesBW plot xlabel grid close ylabel title ylim savefig figure legend xlim xticks yticks clear set_cmap set_size_inches modBev_plot close imshow savefig figure gca float set_xticklabels set_yticklabels set_xlabel set_yticks set_ylabel set_xticks linspace mycm get_cmap | srv/Posidonia-semantic-segmentation | 3,722 |
ssahn0215/genetic_expert_guided_learning | ['imitation learning'] | ['Guiding Deep Molecular Optimization with Genetic Exploration'] | run_pretrain.py model/genetic_operator/mutate.py get_logp_stats.py run_gegl_constrained.py model/genetic_expert.py util/smiles/dataset.py get_low_scoring_dataset.py model/genetic_operator/crossover.py util/smiles/function.py util/storage/recorder.py util/chemistry/rd_filter.py runner/gegl_trainer.py model/neural_apprentice.py util/chemistry/standard_benchmarks.py util/smiles/char_dict.py runner/guacamol_generator.py run_gegl.py runner/pretrain_trainer.py util/chemistry/benchmarks.py util/storage/priority_queue.py reproduce GeneticOperatorHandler SmilesGenerator SmilesGeneratorHandler crossover mol_ok crossover_ring crossover_non_ring ring_OK cut_ring cut change_atom mutate delete_atom add_ring append_atom change_bond_order insert_atom delete_cyclic_bond GeneticExpertGuidedLearningTrainer GeneticExpertGuidedLearningGenerator PreTrainer ThresholdedImprovementScoringFunction penalized_logp_cyclebasis _penalized_logp_cyclebasis load_benchmark similarity_constrained_penalized_logp_atomrings _penalized_logp_atomrings penalized_logp_atomrings similarity_constrained_penalized_logp_cyclebasis RDFilter valsartan_smarts amlodipine_rings perindopril_rings decoration_hop zaleplon_with_other_formula logP_benchmark similarity_cns_mpo hard_fexofenadine hard_osimertinib hard_cobimetinib pioglitazone_mpo ranolazine_mpo start_pop_ranolazine isomers_c9h10n2o2pf2cl qed_benchmark similarity smarts_with_other_target cns_mpo weird_physchem sitagliptin_replacement median_tadalafil_sildenafil isomers_c7h8n2o2 tpsa_benchmark isomers_c11h24 scaffold_hop median_camphor_menthol SmilesCharDictionary load_forbidden_symbols load_char_idx load_encode_dict load_dataset filter_by_score process_smis smis_to_actions MaxRewardPriorityQueue unravel_elems StorageElement Recorder unravel_elems RecorderElement crossover mutate FragmentOnBonds GetSubstructMatches MolFromSmarts choice MolFromSmarts choice GetSubstructMatches FragmentOnBonds range GetMolFrags AtomRings max MolFromSmarts HasSubstructMatch SanitizeMol randn mol_ok MolFromSmarts ReactionFromSmarts cut_ring append range mol_ok ReactionFromSmarts append cut range crossover_ring crossover_non_ring MolToSmiles Kekulize range replace list range choice replace list range choice choice change_atom delete_atom add_ring append append_atom choice ReactionFromSmarts change_bond_order insert_atom Kekulize RunReactants range delete_cyclic_bond calculateScore AtomRings MolLogP max Graph GetAdjacencyMatrix MolLogP calculateScore max cycle_basis uniform_specification RdkitScoringFunction uniform_specification RdkitScoringFunction uniform_specification ThresholdedImprovementScoringFunction RdkitScoringFunction TanimotoScoringFunction uniform_specification ThresholdedImprovementScoringFunction RdkitScoringFunction TanimotoScoringFunction get uniform_specification uniform_specification uniform_specification ClippedScoreModifier TanimotoScoringFunction uniform_specification RdkitScoringFunction ArithmeticMeanScoringFunction ClippedScoreModifier mean_cls TanimotoScoringFunction uniform_specification RdkitScoringFunction ClippedScoreModifier mean_cls TanimotoScoringFunction uniform_specification RdkitScoringFunction ClippedScoreModifier TanimotoScoringFunction uniform_specification RdkitScoringFunction ArithmeticMeanScoringFunction uniform_specification ArithmeticMeanScoringFunction RdkitScoringFunction uniform_specification ArithmeticMeanScoringFunction TanimotoScoringFunction uniform_specification ClippedScoreModifier TanimotoScoringFunction uniform_specification RdkitScoringFunction uniform_specification RdkitScoringFunction uniform_specification uniform_specification uniform_specification mean_cls TanimotoScoringFunction uniform_specification RdkitScoringFunction TanimotoScoringFunction uniform_specification RdkitScoringFunction TanimotoScoringFunction MolFromSmiles IsomerScoringFunction TanimotoScoringFunction uniform_specification RdkitScoringFunction logP tpsa uniform_specification IsomerScoringFunction TanimotoScoringFunction MolFromSmiles SMARTSScoringFunction logP RdkitScoringFunction tpsa bertz uniform_specification uniform_specification GeometricMeanScoringFunction TanimotoScoringFunction MolFromSmiles TanimotoScoringFunction uniform_specification mol_weight RdkitScoringFunction uniform_specification ArithmeticMeanScoringFunction TanimotoScoringFunction SMARTSScoringFunction uniform_specification ArithmeticMeanScoringFunction TanimotoScoringFunction SMARTSScoringFunction ClippedScoreModifier TanimotoScoringFunction uniform_specification RdkitScoringFunction GeometricMeanScoringFunction set str list with_suffix filter allowed filter_by_score list pool set list max_smi_len zeros range enumerate len list map zip | # genetic_expert_guided_learning This is an official implementation of our paper Guiding Deep Molecular Optimization with Genetic Exploration (https://arxiv.org/pdf/2007.04897.pdf). Our code is largely inspired by GuacaMol baselines (https://github.com/BenevolentAI/guacamol_baselines). ## 1. Setting up the environment You can set up the environment by following commands. dmo is shortcut for deep-molecular-optimization ``` conda create -n dmo python=3.6 conda activate dmo conda install pytorch torchvision cudatoolkit=10.1 -c pytorch conda install -c dglteam dgl-cuda10.1 conda install -c rdkit rdkit | 3,723 |
ssahn3087/pedestrian_detection | ['person re identification'] | ['Triplet-based Deep Similarity Learning for Person Re-Identification'] | dataset_utils/coco_user_dataset_generator.py faster_rcnn/roi_pooling/modules/roi_pool.py faster_rcnn/network.py faster_rcnn/utils/__init__.py demo_tracking.py dataset_utils/extract_annotations.py faster_rcnn/setup.py faster_rcnn/roi_align/modules/roi_align.py faster_rcnn/nms/_ext/nms/__init__.py faster_rcnn/datasets/pascal_voc.py faster_rcnn/datasets/imdb2.py faster_rcnn/datasets/kitti_tracking.py faster_rcnn/rpn_msr/anchor_target_layer.py faster_rcnn/datasets/kittivoc.py faster_rcnn/pycocotools/coco.py faster_rcnn/roi_data_layer/minibatch2.py faster_rcnn/datasets/ds_utils.py faster_rcnn/roi_pooling/modules/roi_pool_py.py faster_rcnn/roi_pooling/_ext/roi_pooling/__init__.py train.py demo_image.py faster_rcnn/datasets/pascal3d.py val.py faster_rcnn/utils/nms.py demo_video.py faster_rcnn/roi_data_layer/roidb2.py faster_rcnn/roi_data_layer/roidb.py faster_rcnn/roi_align/build.py faster_rcnn/fast_rcnn/bbox_transform.py faster_rcnn/fast_rcnn/__init__.py faster_rcnn/roi_pooling/build.py faster_rcnn/datasets/pascal_voc2.py faster_rcnn/rpn_msr/proposal_layer.py faster_rcnn/datasets/imdb.py faster_rcnn/faster_rcnn_vgg.py faster_rcnn/fast_rcnn/config2.py faster_rcnn/nms/build.py faster_rcnn/resnet.py faster_rcnn/vgg16.py faster_rcnn/rpn_msr/proposal_target_layer.py faster_rcnn/pycocotools/__init__.py faster_rcnn/triplet.py faster_rcnn/roi_data_layer/layer.py faster_rcnn/utils/boxes_grid.py faster_rcnn/datasets/imagenet3d.py test.py faster_rcnn/roi_data_layer/sampler.py faster_rcnn/rpn_msr/generate.py faster_rcnn/datasets/factory.py faster_rcnn/roi_data_layer/roibatchLoader.py faster_rcnn/datasets/voc_eval.py faster_rcnn/roi_data_layer/minibatch.py faster_rcnn/nms/nms_cpu.py faster_rcnn/roi_pooling/functions/roi_pool.py faster_rcnn/rpn_msr/generate_anchors.py faster_rcnn/fast_rcnn/config.py faster_rcnn/nms/nms_gpu.py faster_rcnn/utils/timer.py faster_rcnn/utils/blob.py faster_rcnn/datasets/coco.py faster_rcnn/faster_rcnn_res.py faster_rcnn/pycocotools/cocoeval.py faster_rcnn/rpn_msr/__init__.py dataset_utils/dataset_info.py faster_rcnn/pycocotools/mask.py faster_rcnn/roi_align/_ext/roi_align/__init__.py visualize_tsne.py faster_rcnn/roi_data_layer/__init__.py faster_rcnn/datasets/__init__.py faster_rcnn/roi_align/functions/roi_align.py faster_rcnn/nms/nms_wrapper.py faster_rcnn/datasets/kitti.py dataset_utils/extract_images.py faster_rcnn/datasets/nthu.py faster_rcnn/datasets/nissan.py faster_rcnn/datasets/CaltechPedestrians.py test track test make_dir make_dir log_print score_analysis id_match_test test draw_graph extract_by_post_class extract_hist_info make_dir load_json_file save_img make_dir FasterRCNN RPN nms_detections FasterRCNN RPN nms_detections load_net _smooth_l1_loss set_trainable load_pretrained_npy vis_detections init_data get_triplet_rois print_weight_grad clip_gradient np_to_variable Conv2d data_to_variable load_net_pedestrians save_net FC weights_normal_init train_net_params ResNet resnet50 RESNET Bottleneck conv3x3 resnet101 BasicBlock find_in_path customize_compiler_for_nvcc custom_build_ext cross_entropy_l2_dist euclidean_distance_loss cross_entropy_cosine_sim VGG16 CaltechPedestrians coco unique_boxes xywh_to_xyxy validate_boxes xyxy_to_xywh filter_small_boxes _selective_search_IJCV_top_k get_imdb list_imdbs imagenet3d imdb imdb kitti kittivoc kitti_tracking nissan nthu pascal3d pascal_voc pascal_voc parse_rec voc_eval voc_ap _which clip_boxes bbox_transform bbox_transform_batch bbox_transform_inv clip_boxes_batch bbox_overlaps_batch bbox_overlaps cfg_from_list cfg_from_file _merge_a_into_b get_log_dir get_output_dir cfg_from_list _add_more_info cfg_from_file _merge_a_into_b get_output_dir nms_cpu nms_gpu nms _import_symbols COCO Params COCOeval RoIAlignFunction RoIAlign RoIAlignAvg RoIAlignMax _import_symbols RoIDataLayer get_minibatch process_img_by_lib _get_image_blob _project_im_rois _get_viewpoint_estimation_labels _sample_rois _get_image_blob_multiscale _project_im_rois_multiscale _vis_minibatch _get_image_blob get_minibatch _get_bbox_regression_labels roibatchLoader rank_roidb_ratio prepare_roidb filter_roidb extract_roidb add_bbox_regression_targets prepare_roidb _compute_targets sampler RoIPoolFunction RoIPool RoIPool _import_symbols _unmap anchor_target_layer _compute_targets_batch imdb_proposals_det _vis_proposals im_proposals imdb_proposals _get_image_blob generate_anchors _scale_enum _whctrs _ratio_enum _mkanchors proposal_layer proposal_target_layer im_list_to_blob prep_im_for_blob get_boxes_grid nms Timer init_data imwrite tuple Timer cuda cfg_from_file get_imdb waitKey imshow tic FasterRCNN_RES imread FasterRCNN_VGG format copy eval detect FONT_HERSHEY_PLAIN classes enumerate load_net toc join print putText rectangle VideoCapture init_data tuple Timer VideoWriter argmax VideoWriter_fourcc cuda release str multiply cfg_from_file get_imdb tic extract_feature_vector FasterRCNN_RES append FasterRCNN_VGG format ascontiguousarray copy eval detect FONT_HERSHEY_PLAIN enumerate load_net toc read int isOpened print id_track putText rectangle bbox_overlaps split VideoCapture VideoWriter VideoWriter_fourcc destroyAllWindows release read int isOpened makedirs print cprint max process_img_by_lib flush write ascontiguousarray bbox_overlaps argmax range len int format init_data print num_triplet_test_images val_func len astype float32 eval extract_feature_vector append imread cuda range split int format init_data print num_triplet_test_images len astype float32 extract_background_features eval extract_feature_vector append imread cuda range split title savefig load items list time format print sort len tolist extend choice set append open gcf str show format describe print xlabel name ylabel title hist savefig view cat MAX_SIZE SCALES PIXEL_MEANS minimum tuple putText FONT_HERSHEY_PLAIN rectangle range items list File create_dataset items list asarray replace File from_numpy copy_ startswith items list asarray state_dict reshape File delete from_numpy copy_ startswith len items list format from_numpy copy_ permute item state_dict sum sorted mean pow float abs copy_ Variable type cuda parameters print named_parameters isinstance Conv2d normal_ modules zero_ Linear norm parameters sqrt mul_ max list items requires_grad data view size nonzero cuda range ResNet ResNet pathsep pjoin exists split append _compile compiler_so view debug size clamp normalize float sum view relu Variable debug size numel sqrt BCELoss normalize float sum cuda view relu Variable debug size numel unsqueeze BCELoss cosine_similarity normalize float sum cuda dot array unique pascal_voc selective_search_IJCV_roidb int parse findall text append find arange concatenate size maximum sum max range parse_rec cumsum argmax max sum range eps format astype mkdir float enumerate minimum join print sort maximum voc_ap argsort zeros bool array len join strip is_exe pathsep split stack log stack log expand_as exp unsqueeze clone size clamp_ range view size min expand max view size min contiguous expand masked_fill_ max join EXP_DIR name abspath ROOT_DIR makedirs join name strftime localtime LOG_DIR abspath ROOT_DIR makedirs items list ndarray isinstance type array _merge_a_into_b literal_eval zip split print abs RPN_SCALES argmin SPATIAL_SCALE ASPECTS sqrt SCALES_BASE repeat KERNEL_SIZE append zeros range array NUM_PER_OCTAVE len _add_more_info append numpy maximum item int nms_cuda dir _wrap_function getattr append callable USE_ALL_GT _get_image_blob randint array zeros len process_img_by_lib MAX_SIZE prep_im_for_blob PIXEL_MEANS append im_list_to_blob range len print cfg_from_file imread concatenate vstack round _project_im_rois BATCH_SIZE ones _project_im_rois_multiscale shape IS_EXTRAPOLATING range IS_MULTISCALE FG_FRACTION hstack astype SCALES_BASE HAS_RPN empty _sample_rois _get_image_blob_multiscale float32 BBOX_REG SCALES minimum _get_viewpoint_estimation_labels size astype extend choice _get_bbox_regression_labels array range astype float32 resize imread astype float32 SCALES_BASE resize append im_list_to_blob imread range len astype zeros float abs array zeros shape zeros shape show uint8 print min astype copy add_patch imshow Rectangle range image_index toarray roidb image_id_at argmax max range image_path_at len argsort append float array range len print len get_imdb extend rank_roidb_ratio imdb classes EPS _compute_targets sqrt zeros range len EPS astype extend log zeros float argmax bbox_overlaps range type_as format subplots set_title text draw axis tight_layout add_patch imshow Rectangle reshape forward _get_image_blob copy toc show format print average_time hstack _vis_proposals num_images im_proposals tic Timer imread range image_path_at toc show format print average_time hstack _vis_proposals num_images im_proposals tic Timer imread range image_path_at vstack _ratio_enum array hstack sqrt _whctrs round _mkanchors _whctrs _mkanchors zeros max range len min astype float32 shape resize float max arange reshape transpose hstack SPATIAL_SCALE dstack ASPECTS sqrt SCALES_BASE floor KERNEL_SIZE repeat meshgrid zeros max range len append maximum minimum | ssahn3087/pedestrian_detection | 3,724 |
ssarfjoo/improvedsegan | ['speech enhancement'] | ['SEGAN: Speech Enhancement Generative Adversarial Network'] | discriminator.py make_tfrecords.py generator.py ops.py bnorm.py main.py data_loader.py model.py VBN read_and_decode discriminator AEGenerator Generator main _int64_feature encoder_proc read_and_slice _bytes_feature slice_signal main Model SEAE SEGAN leakyrelu minmax_normalize minmax_denormalize tensor_summary prelu average_gradients batch_to_time atrous_conv1d conv2d conv1d gaussian_noise_layer highway time_to_batch deconv downconv histogram_summary sample_random_walk audio_summary residual_block variables_on_gpu0 scalar_summary read TFRecordReader decode_raw float32 set_shape int32 cast parse_single_example as_list int expand_dims seed print save_path name __flags synthesis_path ConfigProto append makedirs int list zip append range read slice_signal join write SerializeToString tostring Example read_and_slice zip split join unlink out_file splitext random_normal zeros range reshape randn scalar histogram audio xavier_initializer expand_dims format _linear f sigmoid range as_list get_shape xavier_initializer as_list print get_shape xavier_initializer get_shape expand_dims get_variable concat reduce_mean zip append expand_dims | ssarfjoo/improvedsegan | 3,725 |
ssfootball04/class-balanced-experts | ['long tail learning'] | ['Long-Tailed Recognition Using Class-Balanced Experts'] | gen_logits.py dataloader.py models.py utils.py main.py jointCalibration.py generate_features.py Threshold_Dataset Calibration_Dataset main gen_features_and_probs main gen_logits main train test main train test create_model_resnet10 create_model_resnet152 ResNet DotProduct_Classifier Bottleneck CalibrateExperts conv3x3 BasicBlock print_write source_import init_weights weights_init seed_everything plot_curves set_weights format print dataset eval to len DataLoader ArgumentParser device save gen_features_and_probs seed exp load_model pprint load_state_dict parse_args to BoolTensor cat format seed_everything vars class_mask load join print add_argument model_name Threshold_Dataset makedirs format print dataset eval to len gen_logits data_split format criterion batch_size model backward print zero_grad dataset cuda item float step long enumerate flush len format criterion model print dataset eval cat cuda item to max enumerate flush len SGD dataset cuda log list Calibration_Dataset StepLR step_size append plot_curves detach state_dict test lower logits_exp item gamma flush items deepcopy parameters train numpy nll_loss feature_extractor classifier named_children set_weights num_classes shape chain max_epochs lr CosineAnnealingLR enumerate int ResNet print ResNet init_weights spec_from_file_location exec_module module_from_spec print normal_ __name__ fill_ print load load_state_dict join format arange plot set_dpi set_xlabel grid add_subplot close set_ylabel savefig figure legend annotate len seed str manual_seed_all manual_seed print parameters format | ssfootball04/class-balanced-experts | 3,726 |
sshan-zhao/DG_via_ER | ['domain generalization'] | ['Domain Generalization via Entropy Regularization'] | train.py models/model_factory.py models/aux_models.py data/dataset.py utils.py models/resnet.py get_args Trainer save_options set_requires_grad get_optim_and_scheduler set_mode set_lambda get_val_dataloader get_train_transformers ConcatDataset MyDataset get_train_dataloader get_val_transformer get_random_subset _dataset_info get_split_dataset_info DisNet grad_reverse ClsNet GradReverse aux_models get_network resnet18 ResNet freeze_bn resnet50 add_argument ArgumentParser zip MultiStepLR SGD zip parameters train eva print items sorted join int list sample range len append int split _dataset_info get_train_transformers join ConcatDataset MyDataset DataLoader append source dataset datalist_dir _dataset_info len join isinstance ConcatDataset MyDataset target DataLoader get_val_transformer append dataset datalist_dir _dataset_info append flip RandomHorizontalFlip ColorJitter ClsNet DisNet eval __name__ ResNet apply load_url feat_ch load_state_dict aux_models ResNet apply load_url feat_ch load_state_dict aux_models | sshan-zhao/DG_via_ER | 3,727 |
sshleifer/Graph-WaveNet | ['traffic prediction'] | ['Graph WaveNet for Deep Spatial-Temporal Graph Modeling', 'Incrementally Improving Graph WaveNet Performance on Traffic Prediction'] | train.py generate_training_data.py test_gwnet.py test.py util.py engine.py gen_adj_mx.py model.py exp_results.py Trainer plot_loss_curve loss_curve make_results_table summary generate_train_val_test generate_graph_seq2seq_io_data get_adjacency_matrix nconv GraphConvNet GWNet main plot_learned_adj_matrix modify_args TestTrain main eval_ make_graph_inputs load_pickle calculate_scaled_laplacian calc_metrics mask_and_fillna calculate_normalized_laplacian load_adj calc_tstep_metrics _to_ser make_pred_df asym_adj DataLoader sym_adj load_dataset StandardScaler get_shared_arg_parser idxmin min mean round read_csv read_csv idxmin plot print loss_curve min axhline concatenate abs transpose min astype range shape stack append expand_dims dayofweek max timedelta64 values join arange concatenate print sort generate_graph_seq2seq_io_data read_hdf traffic_df_filename output_dir y_start round savez_compressed exp inf len flatten zeros std values enumerate make_graph_inputs load data make_pred_df batch_size print calc_tstep_metrics plot_learned_adj_matrix to_csv load_dataset eval load_state_dict plotheatmap device to seq_length checkpoint from_args relu DataFrame nodevec2 nodevec1 softmax numpy heatmap savefig mm max items list setattr model save DataFrame list transpose progress_bar step append range state_dict eval_ get_iterator shuffle valid_loss enumerate join load_checkpoint Series dict summary train epochs time transpose get_iterator eval append diags flatten coo_matrix sum array flatten coo_matrix diags diags tocoo flatten coo_matrix eye sum array calculate_normalized_laplacian csr_matrix reduce identity shape eigsh load_pickle load join DataLoader transform StandardScaler zeros_like where isnan sqrt float abs isnan zeros_like where clamp squeeze transpose get_iterator rename_axis eval append inverse_transform range enumerate dict DataFrame adjdata adjtype aptonly load_adj add_argument ArgumentParser | # Graph WaveNet for Deep Spatial-Temporal Graph Modeling This is the original pytorch implementation of Graph WaveNet in the following paper: [Graph WaveNet for Deep Spatial-Temporal Graph Modeling, IJCAI 2019] (https://arxiv.org/abs/1906.00121), with modifications presented in [Incrementally Improving Graph WaveNet Performance on Traffic Prediction] (https://arxiv.org/abs/1912.07390): <p align="center"> <img width="350" height="400" src=./fig/model.png> </p> ## Requirements - python 3 - see `requirements.txt` | 3,728 |
ssydasheng/Neural-Kernel-Network | ['gaussian processes', 'time series'] | ['Differentiable Compositional Kernel Learning for Gaussian Processes'] | data/timeSeries/datasets/solar.py visualize_bo.py bayesianOpt.py exp/bayes-opt.py data/hparams.py data/__init__.py data/timeSeries/datasets/airline.py kernels.py data/timeSeries/base.py data/register.py data/data.py data/timeSeries/datasets/manua.py exp/time-series.py utils/functions.py data/timeSeries/datasets/__init__.py exp/regression.py utils/create_logger.py exp/texture.py bo_functions.py BayesianOptimization stybtang Function michalewicz Michalewicz Stybtang Stybtang_transform SpectralMixture KernelWrapper minimum save_final load_final load_uci load_uci_pca load_texture standardize load_uci_woval_pca_train_val_split pca_split HParams get_data register load_data load_X_y data_file load_data mauna get_X_y irradiance_data_file NKNInfo run NKNInfo NKNInfo organize_symbol create_logger makedirs median_distance_local mean_distance_global _test_median_local median_distance_global mean_distance_local _test_median_global FFT get_kemans_init int list constant expand_dims range append range list permutation squeeze len PCA argsort transform array range fit join loadtxt astype standardize HParams float_type pca_split join loadtxt astype standardize HParams float_type pca_split join loadtxt astype standardize HParams train_test_split float_type mean std append join arange zeros_like randn rgb2gray copy shape HParams imread read_data get_Xy get_X_y load_all_channels load_X_y load_one_channel loadmat open list map split data_file load_data expand_dims split append float array irradiance_data_file open NKNInfo minimize KernelWrapper astype SGPR placeholder GPR expand_dims shape AdamOptimizer NeuralKernelNetwork predict_y std_y_train reset_default_graph get_kemans_init NKNWrapper objective astype sort as_coefficients_dict expand dirname join basicConfig format getLogger addHandler strftime StreamHandler setLevel INFO makedirs permutation fit sqrt expand_dims permutation sum sqrt expand_dims permutation sum abs reshape expand_dims permutation abs reshape expand_dims permutation print normal median_distance_global print median_distance_local eye show rfft scatter func linspace rfftfreq abs | ssydasheng/Neural-Kernel-Network | 3,729 |
ssydasheng/predictive-correlation-benchmark | ['active learning'] | ['Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?'] | utils/logging.py utils/utils.py utils/kfac_ops/loss_functions.py core/gpflowSlim/misc.py utils/kfac_ops/controller/weight_container.py core/gpflowSlim/quadrature.py data/register.py global_settings/method_args.py tasks/al_prediction.py utils/kernels.py core/gpflowSlim/densities.py core/gpflowSlim/base.py core/gpflowSlim/features.py core/gpflowSlim/conjugate_gradient.py core/wvi.py core/noisy_kfac.py core/gpflowSlim/kernels.py core/gpflowSlim/__init__.py notebooks/TAL_oracle_criterions.py core/fvi.py core/gpflowSlim/transforms.py tasks/al_selection.py scripts/gen_scripts.py utils/kfac_ops/layer_collection.py data/__init__.py utils/distributions.py tasks/al_oracle_pretrain.py data/data.py core/gpflowSlim/models/sgpr.py core/gpflowSlim/LBFGS.py core/kernels.py utils/nets.py core/gpflowSlim/_settings.py tasks/al_oracle_prediction.py core/gpflowSlim/decors.py main.py global_settings/task_args.py utils/gpnet.py utils/al_utils.py core/gpflowSlim/models/gplvm.py core/dropout.py utils/xll_utils.py core/gpflowSlim/ekernels.py tasks/al_oracle_selection.py core/gpflowSlim/neural_kernel_network/__init__.py core/gpflowSlim/params.py tasks/toy/generate_toy_data.py core/abstract.py utils/kfac_ops/controller/weight_controller.py utils/kfac_ops/optimizer.py utils/kernel_utils.py utils/kfac_ops/fisher_blocks.py tasks/toy/compute_metrics.py core/ensemble.py core/gpflowSlim/models/__init__.py core/gpflowSlim/likelihoods.py core/gpflowSlim/natgrad.py core/gpr.py notebooks/scatter_metrics.py utils/kfac_ops/utils.py core/gpflowSlim/models/gpmc.py core/gpflowSlim/neural_kernel_network/neural_kernel_network_wrapper_v2.py core/gpflowSlim/neural_kernel_network/neural_kernel_network_wrapper.py utils/kfac_ops/fisher_factors.py core/gpflowSlim/neural_kernel_network/neural_kernel_network_v2.py core/gpflowSlim/kernel_kitchen_sink.py core/gpflowSlim/kullback_leiblers.py utils/model_utils.py tasks/regression.py core/gpflowSlim/conv_kernels.py core/gpflowSlim/priors.py core/gpflowSlim/models/model.py core/gpflowSlim/neural_kernel_network/neural_kernel_network.py core/emHMC.py data/hparams.py core/gpflowSlim/models/svgp.py notebooks/uci_xll.py utils/toy_utils.py core/homoscedasticEnsemble.py core/gpflowSlim/models/kgpr.py global_settings/constants.py core/abstractVI.py core/gpflowSlim/mean_functions.py core/gpflowSlim/conditionals.py notebooks/TAL_oracle_prediction.py core/gpflowSlim/models/gpr.py core/gpflowSlim/_version.py core/gpflowSlim/distributions.py core/gpflowSlim/models/sgpmc.py utils/common_utils.py core/gaussianFVI.py utils/kfac_ops/estimator.py Abstract AbstractVI Dropout EMHMCScale EMHMC EnsembleNN AbstractFVI AbstractImplicitFVI AbstractExplicitFVI MiniBatchGaussianFVI GaussianFVI VFEGPR FITCGPR AbstractGPR FullGPR SVGPGPR HomoEnsembleNN SpectralMixture ExpDecay KernelWrapper NoisyKFAC BBB IPrior ITransform conditional uncertain_conditional feature_conditional base_conditional dot cgsolver vec AdditivePatchKernel ConvKernel name_scope exponential Test_multivariate_normal_feature multivariate_normal bernoulli gaussian lognormal laplace multivariate_normal_feature beta student_t gamma poisson RowIndependentDiagGaussian_2 RowIndependentDiagGaussian_1 MatrixVariateGaussian SumGaussian MatrixVariateDiagGaussian compute_mvg_kl_divergence UnivariateGaussian compute_prec_summvg_mvg_kl_divergence RowIndependentMVG compute_summvg_mvg_kl_divergence MultivariateGaussian GaussianDistribution Sum RBF Product Linear default_feature_conditional conditional InducingPoints Multiscale inducingpoint_wrapper InducingFeature Product Constant RatQuad Stationary Matern52 Matern32 Combination Kernel Polynomial make_deprecated_class Bias Exponential TPS Sum Periodic make_kernel_names Matern12 RBFComplex White _kernel_function Cosine Linear RBF Coregion CosineComplex Static ArcCosine _kernel_diag OrthogonalApproxProdSampler TransformSampler CosineV2Sampler SubsetApproxProdSampler Sampler ConcatSamplerGroup _gen_one ConstantSampler RBFSampler ArcCosineSampler _gen_identity SketchApproxProdSampler OuterProductSampler ListSamplerGroup SamplerKernel CosineRBFSampler RFFApproxSumSampler SamplerGroupKernel SamplerGroup EqApproxSumSampler NEqApproxSumSampler CosineSampler _generate_sketch_matrix LinearSampler RFFSampler _gen_orthogonal ReduceProdSamplerGroup _gen_random OneApproxProdSampler ApproxProdSampler FullyConnectedSamplerGroup RFFApproxProdSampler RandomApproxProdSampler gauss_kl dummy verbose_func dot linearize LBFGS Struct Gamma SwitchedLikelihood Bernoulli Poisson Beta StudentT Gaussian Exponential BroadcastingLikelihood MultiClass Likelihood RobustMax Ordinal probit Zero Product MeanFunction SwitchedMeanFunction Constant Customized Additive Identity IdentityConv2dMean PatchwiseConv2d Conv2dMean Linear mvg_reparameterize reparameterize is_number is_ndarray pretty_pandas_table vec_to_tri is_list normalize_num_type is_valid_param_value is_tensor EfficientNaturalGradient XiTransform swap_dimensions expectation_to_natural XiNat NaturalGradient expectation_to_meanvarsqrt XiSqrtMeanVar natural_to_meanvarsqrt meanvarsqrt_to_natural meanvarsqrt_to_expectation natural_to_expectation _inverse_lower_triangular Parameter Gamma Beta Gaussian Prior LogNormal Uniform Laplace hermgauss mvhermgauss mvnquad Exp Transform DiagMatrix LowerTriangular positiveRescale Log1pe Identity Logistic Chain Rescale _MutableNamedTuple _SettingsManager _namedtuplify _SettingsContextManager _parse _read_config_file PCA_reduce GPLVM BayesianGPLVM GPMC GPR TestPredict KGPR GPModel Model SGPMC SGPR SGPRUpperMixin GPRFITC SVGP NeuralKernelNetwork NeuralKernelNetwork Product _KernelLayer NKNWrapper Activation Linear Product _KernelLayer NKNWrapper Activation Linear standardize uci_woval HParams get_data register _emhmc_args _ensemble_args _hmc_args load_args _dropout_args _bbb_args _nng_args _gp_args _svgp_args _mfbnn_args _fbnn_args load_args _toy_args _transductive_active_learning_args _regression_args load_method_marginal load_xll load_refer_dataset load_metrics load_reference load_method init_plotting scatter_TAL_meta_corr filter_methods scatter_xll plot_rmse_all plot get_y_bot_and_up fetch_results init_plotting plot_lld_all pot_subplot_rmse plot_curve pot_subplot_lld plot_comparisons_small get_y_bot_and_up pot_subplot_rmse plot_curve plot_comparisons_large pot_subplot_lld load_refer_dataset load_reference load_method load_dataset al_oracle_selection write_gpu_cmds toy_metrics write_cpu_cmds al_oracle_pretrain al_oracle_prediction xll al_selection _run load_cached_data run _run run _run run _run load_cached_data run _run run _run run gen_f_correlation _run compute_oracle_lld_rmse run mkdata_relu normalize_active_learning_data get_batch_mode_MMIG_idx get_selected_data_idxs get_batch_mode_TIG_idx_Fast fetch_active_learning_dataset update_dataset compute_corr_or_covar get_batch_mode_MMIG_idx_v2 get_argmax_var HParams get_batch_mode_MMIG_idx_Fast get_argmax_corr_square regression_train plot_scatter reuse_variables makedirs get_config_from_json init_config get_logger set_jitter init_logger normal_log_lld process_config compute_pearson_and_spearman_r reuse compute_pair_wise_lld regression_test compute_mvg_kl_divergence build_rf_expansion get_gpnet NNGPReLUKernel SpectralMixture ExpDecay KernelWrapper GP_additive_rbf_kernel NKNInfo get_logger manage_folder_tree makedirs gen_correlation get_model gen_kern rand_generator mlp_input_outer MLP _dense _append_homog get_posterior KFAC_MLP compute_cov_relu_kernel compute_gaussian_relu_expectation merge_dicts variational_expectations save_model median_distance_local median_distance_global restore_model default_plotting_new Unbuffered default_plotting get_kemans_init sort_corr get_submatrices build_graph get_indices FisherEstimator _DeviceContextGenerator EigenCorrectedConvKFCBasicFB KroneckerProductFB EigenCorrectedKroneckerProductFB NaiveDiagonalFB FullFB FisherBlock _num_conv_locations _compute_pi_tracenorm ConvDiagonalFB ConvKFCBasicFB _compute_pi_adjusted_damping FullyConnectedDiagonalFB FullyConnectedKFACBasicFB EigenCorrectedFullyConnectedKFACBasicFB _concat_along_batch_dim set_global_constants FullyConnectedScaleFactor ConvDiagonalFactor scope_string_from_params FullyConnectedDiagonalFactor FisherFactor _compute_cov diagonal_covariance_initializer FullFactor DiagonalFactor ConvOutputEigenBasisFactor NaiveDiagonalFactor InverseProvidingFactor _append_homog ConvOutputKroneckerFactor scalar_or_tensor_to_string ConvScaleFactor set_global_constants ConvInputKroneckerFactor scope_string_from_name ScaleFactor EigenBasisProvidingFactor covariance_initializer FullyConnectedKroneckerFactor _maybe_colocate_with FullyConnectedEigenBasisFactor ConvInputEigenBasisKroneckerFactor inverse_initializer LayerCollection DistributionNegativeLogProbLoss insert_slice_in_zeros LossFunction NormalMeanNegativeLogProbLoss NegativeLogProbLoss NormalMeanVarianceNegativeLogProbLoss CategoricalLogitsNegativeLogProbLoss NaturalParamsNegativeLogProbLoss NGOptimizer posdef_eig_svd generate_random_signs layer_params_to_mat2d mat2d_to_layer_params posdef_inv kronecker_product posdef_eig_self_adjoint column_to_tensors LayerParametersDict set_global_constants compute_eigmvg_stdnormal_kl_divergence ensure_sequence posdef_inv_cholesky eigen_basis_kron_product_3d fwd_gradients posdef_eig SequenceDict posdef_inv_matrix_inverse eigen_basis_kron_product_2d posdef_inv_eig tensors_to_column EMVGWeightContainer MVGWeightContainer _compute_pi_tracenorm WeightContainer FFGWeightContainer WeightController eye jitter_level K Kdiag Kuf Kuu K Kdiag matrix_triangular_solve transpose square reduce_sum matmul matrix_band_part stack cholesky tile expand_dims matrix_diag matrix_transpose matrix_triangular_solve transpose Kuu matrix_band_part matmul eKdiag eKfu cholesky tile eKufKfu einsum norm log lgamma square pi cast float_type log clip_by_value matrix_triangular_solve pi cast float_type log tf_float norm matrix_triangular_solve transpose reduce_sum matmul pi matrix_diag_part cast cholesky eye float_type jitter log transpose to_double reduce_sum matmul matrix_diag_part trace cholesky eye cholesky_solve abs log matrix_triangular_solve transpose to_double eigvalsh reduce_sum matmul matrix_diag_part trace cholesky eye cholesky_solve abs log matrix_triangular_solve transpose to_double square reduce_sum matmul matrix_diag_part cholesky eye cholesky_solve abs log InducingPoints ndarray isinstance append str lower isinstance isinstance format __name__ float_type astype int randn transpose ceil empty range ones concatenate choice sparse_reorder int_type SparseTensor astype float_type len matrix_triangular_solve transpose size square matrix_band_part reduce_sum reduce_prod matrix_diag_part cast cholesky tile eye expand_dims log float_type print append reshape list reindex_axis dict zip DataFrame isinstance int_type DType isinstance float_type type list constant zip transpose jitter cholesky cholesky jitter eye matmul matmul cholesky _inverse_lower_triangular transpose matmul _inverse_lower_triangular natural_to_meanvarsqrt expectation_to_meanvarsqrt matmul transpose matmul ones list product hermgauss array prod reshape transpose mvhermgauss matmul pi func tile cholesky expand_dims len pop items list isinstance Mapping join read list ConfigParser map abspath eigh T cov join int loadtxt standardize HParams train_test_split mean std append items list edict add_argument_group add_argument add_argument_group add_argument add_argument_group add_argument add_argument_group add_argument add_argument_group add_argument add_argument_group add_argument add_argument_group add_argument add_argument_group add_argument add_argument_group add_argument index add_argument_group add_argument add_argument_group add_argument add_argument_group add_argument load join format load join seed format concatenate transpose get_indices run get_submatrices len EasyDict load join format print load_reference load_method test_y dict mean append range log EasyDict load join format pdf test_y dict mean append range log ones_like load_method_marginal asarray extend where append array enumerate len load join format mean append range subplots print load_metrics set_xlabel tight_layout init_plotting scatter set_ylabel savefig filter_methods zip legend list build_graph print load_refer_dataset extend mean zip append range Session enumerate len load_xll subplots asarray savez align_ylabels print load_metrics set_xlabel FormatStrFormatter tight_layout init_plotting scatter set_ylabel set_major_formatter filter_methods legend savefig fill_between plot list range len list get_y_bot_and_up plot_curve range len list get_y_bot_and_up plot_curve range len load join open print plot_rmse_all plot_lld_all fetch_results subplots set_title set_xlabel set_xlim FormatStrFormatter tight_layout set_linewidth set_ylabel pot_subplot_rmse set_major_formatter set_xticks legend get_lines savefig set_ylim subplots set_title set_xlabel set_xlim FormatStrFormatter tight_layout set_linewidth set_ylabel set_xticks set_major_formatter legend get_lines savefig set_ylim pot_subplot_lld subplots pot_subplot_rmse set_major_formatter open set_title FormatStrFormatter set_linewidth savefig legend range pot_subplot_lld set_xlim tight_layout get_lines load join print init_plotting set_ylabel set_xticks len load join subplots set_title set_xlabel set_xlim len FormatStrFormatter tight_layout init_plotting pot_subplot_lld set_xticks pot_subplot_rmse set_major_formatter savefig range open pdf mean sqrt log normalize_active_learning_data fetch_active_learning_dataset std_y_train HParams list format build_graph print load_refer_dataset extend mean zip append range std Session len format len write parallel_runs enumerate format len write parallel_runs enumerate append format append format append format append append append load join criteria regression_train trainable_variables assign Saver reset_default_graph dataset Session run infer_only_Z std name shape append range variables_initializer global_step train_y restore_model mean no_op join Variable active_iterations load_cached_data global_variables_initializer get_model epochs edict regression_test init_seed join var _run print tolist mean set_jitter array info append dataset n_runs get_logger range save_model fetch_active_learning_dataset normalize_active_learning_data train_x save criteria get_selected_data_idxs update_dataset print makedirs OFF lr_ann_ratio close ConfigProto deepcopy learning_rate return_val lprint format format std sqrt func_x_pred_cov tensor_diag_part reshape obs_var T concatenate inv pdf mean compute_cov_relu_kernel eye log obs_var gen_f_correlation compute_pearson_and_spearman_r concatenate load posterior_Kff savez reshape dict compute_oracle_lld_rmse diag makedirs seed normal list randn shuffle compute_cov_relu_kernel cholesky range print run concatenate argsort argsort T multiply squeeze inv append sum diag enumerate T print squeeze inv append diag enumerate norm T reshape sqrt cholesky diagonal expand_dims solve_triangular array len seed int arange concatenate shuffle train_ratio standardize dataset train_test_split uci_woval standardize list range concatenate set int list get_batch_mode_MMIG_idx_Fast print active_ratio shuffle compute_corr_or_covar get_argmax_var append max range get_argmax_corr_square update join time permutation logger default_feed_dict format batch_size concatenate zip add_summary num_networks epochs max range run format logger add mean add_summary epochs Summary run exp multiply squeeze pi log mean multiply log normal_log_lld join T histogram2d interpn xlabel ylabel tight_layout title clf scatter savefig zip tolist pr spr warn edict join get_config_from_json FileHandler getLogger addHandler strftime StreamHandler info setLevel INFO makedirs dirname config add_argument ArgumentParser parse_args process_config checkpoint_dir summary_dir dict info get_logger makedirs dtype cast normal NeuralKernelNetwork NKNWrapper KernelWrapper RBF range join print rmtree makedirs obs_var EnsembleNN Gaussian assign SVGPGPR log NoisyKFAC dtype exp logger cast EMHMC expand_dims get_kemans_init n_hidden relu group dropout_tau constant HomoEnsembleNN gen_correlation infer_joint FullGPR BBB n_base vf_val MiniBatchGaussianFVI dropout_rate method Dropout to_float shuffle get_next shape repeat lengthscales sqrt random_normal logger reshape concat tensor_diag_part sqrt func_x_pred_cov cast diag RBF median_distance_local print ARD median_distance_global Matern52 as_list concat ones len reshape activation matmul batch_normalization _append_homog T compute_gaussian_relu_expectation range len T arctan reshape pi sqrt diag update permutation fit sqrt expand_dims permutation sum abs reshape expand_dims permutation int restore format latest_checkpoint print_func range join format print_func dirname save makedirs len argsort T T float64 MultivariateNormalFullCovariance placeholder reduce_mean log_prob trace _compute_pi_tracenorm isinstance isinstance dtype cast matmul str scope_string_from_name join all isinstance append isinstance shape int len isinstance as_list isinstance reshape tuple shape append prod as_list reshape reshape isinstance isinstance cast eye eye cholesky maximum self_adjoint_eig to_double svd abs self_adjoint_eig transpose einsum random_uniform isinstance gradients to_float log reduce_sum | ssydasheng/predictive-correlation-benchmark | 3,730 |
stancld/GeneratingHeadline_GANs | ['text summarization'] | ['WikiHow: A Large Scale Text Summarization Dataset'] | Code/_old/PersonalFiles/Michael/encap_timeSeries_seq2seq (1).py Code/language_class.py Code/_old/PersonalFiles/Danko/baseline_encoder-decoder (RNN-GRU).py Code/data2PaddedArray.py Code/_old/PersonalFiles/Danko/PaddedArray2sentences.py Code/Models/Attention_seq2seq.py Code/_old/PersonalFiles/Zakhar/ReduceEmbedding.py Code/_old/pointer-generator.py Code/Models/discriminator_training_class.py Code/Models/generator_training_class.py Code/contractions.py Code/_old/PersonalFiles/Zakhar/Tokenizer.py Code/_old/GRU-attention-generator.py Code/_old/PersonalFiles/Zakhar/TF.py Code/Models/Adversarial_Training.py Code/text_preprocessing.py Code/_old/gans_for_abstractive_text_summarization.py Code/_old/PersonalFiles/Michael/encap_timeSeries_seq2seq.py Code/Models/CNN_text_clf.py Code/_old/ready_gans.py data2PaddedArray LangDict text_preprocessing AdversarialTraining _Seq2Seq _Encoder _Attention _Decoder _CNN_text_clf Discriminator_utility generator Attention Encoder GenerationProbability Decoder Encoder seq2seq_training _Attention _Decoder show_parameter instan_things _Seq2Seq seq2seq_evaluate _Encoder seq2seq_running seq2seq_training _Attention _Decoder show_parameter instan_things _Seq2Seq seq2seq_evaluate _Encoder seq2seq_running update tokenize int reshape array append max len join list format remove words ToktokTokenizer PorterStemmer keys compile print lossfunction model backward clip_grad_norm_ zero_grad parameters unsqueeze train step eval seq2seq_training deepcopy print seq2seq_evaluate float range _Attention _Decoder Adam parameters _Encoder to join rstrip replace split | ## Project for Statistical Natural Language Processing (COMP0087), University College London # Headline Generation via Adversarial Training ----- ### Collaborators: - Daniel Stancl ([email protected]) - Guoliang HE ([email protected]) - Dorota Jagnesakova ([email protected]) - Zakhar Borok ([email protected]) ### Abstract Originally developed for computer vision, Generative Advarsarial Nets (GANs) have achieved great success in producing real-valued data. While these nets bypass a lot of the problems associated with more widely used models based on maximum-likelihood approaches, it remains a challenge to successfully train them for tasks involving discrete outputs, such as text summarization. In this paper, we propose an adversarial training approach for an abstractive text summarization task: generating headlines for WikiHow articles. We make use of two models participating in a contest to outperform each other โ an encoder-decoder generator a discriminator. We train these with respect to two different loss functions and evaluate the resulting model's performance using ROUGE metrics. In particular, we see an improvement by 25.9 \% in ROUGE-1 and 42.6 \% in ROUGE-2 of our proposed adversarially-trained model as compared to baseline seq2seq models. | 3,731 |
stancld/GeneratingHeadlines_GANs | ['text summarization'] | ['WikiHow: A Large Scale Text Summarization Dataset'] | Code/gans_for_abstractive_text_summarization.py Code/_old/pointer-generator.py PersonalFiles/Michael/encap_timeSeries_seq2seq.py PersonalFiles/Michael/encap_timeSeries_seq2seq (1).py Code/data2PaddedArray.py PersonalFiles/Zakhar/TF.py Code/text_preprocessing.py Code/Models/discriminator.py Code/_old/GRU-attention-generator.py PersonalFiles/Zakhar/ReduceEmbedding.py PersonalFiles/Danko/baseline_encoder-decoder (RNN-GRU).py PersonalFiles/Zakhar/Tokenizer.py Code/contractions.py Code/Models/generator_training_class.py Code/Models/Attention_seq2seq.py data2PaddedArray text_preprocessing _Seq2Seq _Encoder _Attention _Decoder Discriminator_utility _Discriminator generator Attention Encoder GenerationProbability Decoder Encoder seq2seq_training _Attention _Decoder show_parameter instan_things _Seq2Seq seq2seq_evaluate _Encoder seq2seq_running seq2seq_training _Attention _Decoder show_parameter instan_things _Seq2Seq seq2seq_evaluate _Encoder seq2seq_running update tokenize int reshape array append max len join list format remove words ToktokTokenizer PorterStemmer keys compile print lossfunction model backward clip_grad_norm_ zero_grad parameters unsqueeze train step eval seq2seq_training deepcopy print seq2seq_evaluate float range _Attention _Decoder Adam parameters _Encoder to join rstrip replace split | stancld/GeneratingHeadlines_GANs | 3,732 |
stanford-futuredata/selection-via-proxy | ['active learning'] | ['Selection via Proxy: Efficient Data Selection for Deep Learning'] | svp/imagenet/active.py svp/common/utils.py svp/amazon/datasets.py svp/cifar/datasets.py svp/amazon/fasttext.py svp/imagenet/train.py svp/amazon/transforms.py svp/cifar/models.py svp/cifar/train.py svp/common/cli.py svp/imagenet/coreset.py svp/amazon/__main__.py svp/common/coreset.py svp/cifar/coreset.py svp/common/datasets.py svp/imagenet/datasets.py svp/amazon/active.py svp/cifar/active.py svp/common/selection/__init__.py svp/amazon/models.py svp/common/train.py svp/common/active.py svp/imagenet/models.py svp/cifar/__main__.py svp/imagenet/__main__.py svp/amazon/train.py setup.py svp/amazon/coreset.py svp/common/selection/k_center_greedy.py active coreset GZIPAmazonProductReviews parse DBPedia YahooAnswers AmazonReviewFull AGNews XiangZhangDataset SogouNews YelpReviewPolarity YelpReviewFull AmazonReviewPolarity create_dataset AmazonProductReviews TextClassification calculate_test_accuracy train_fastText read_labels calculate_rank shuffle_and_index normalize_text runtime run_command calculate_train_accuracy fasttext read_fasttext_probs create_dataset VDCNN9MaxPoolLite KMaxPoolBlock VDCNN17KMaxPool MaxPoolBlock VDCNN17Conv VDCNN29Conv ConvBlock VDCNN29KMaxPool VDCNN9MaxPool VDCNN VDCNN17MaxPool VDCNN49MaxPool ModelBuilder VDCNN9Conv VDCNN49Conv VDCNN49KMaxPool VDCNN9KMaxPool VDCNN29MaxPool kmax_pooling KMaxPool1d create_model_and_optimizer train PadOrTruncate Vocab training_options coreset cli active fasttext dataset_options train proxy_training_overrides active coreset _create_train_dataset _create_test_dataset create_dataset PreActBlock PreActResNet14 Bottleneck ResNet32 ResNet44 ResNet56 StochasticResNet152SVHN ResNet152SVHN PreActResNet110 ResNet20 WRN_40_4 BasicBlock ResNet152 ResNeXtBottleneck ResNet18 PreActResNet164Basic StochasticResNet110 StochasticResNet1202 ResNet50 WRN_16_4 StochasticResNet WRN_16_8 ResNet PreActResNet1001 ResNet34 PreActResNet20 StochasticBlock PreActResNet56 PreActBottleneck StochasticResNet56 ResNet101 PreActResNet164 StochasticResNet56_08 WRN_28_10 ResNeXt29 ResNet110 WRN ResNet1202 PreActResNet8 create_model_and_optimizer train training_options coreset cli active dataset_options train proxy_training_overrides CreateGraph symlink_target_to_proxy symlink_to_precomputed_proxy validate_splits check_different_models generate_models miscellaneous_options computing_options ForgettingEventsMeter validate_splits DatasetWithIndex maybe_open create_loaders run_training run_epoch AccuracySplits TimeSplits save_summary override_option get_learning_rate split_indices save_config create_run_dir capture_config AverageMeter save_result save_index set_random_seed RecordInputs config_run_env correct _save_result_helper k_center_greedy_slow k_center_greedy _calc_preds_and_features select active coreset create_dataset create_model_and_optimizer train _LabelSmoothing training_options coreset cli active dataset_options train proxy_training_overrides save_index set_random_seed symlink_to_precomputed_proxy validate_splits send generate_models symlink_target_to_proxy sorted len save_result select config_run_env next format partial save_config glob create_run_dir capture_config create_loaders classes zip join split_indices print create_dataset check_different_models makedirs callback save_index set_random_seed DataParallel dev validate_splits nevents len save_result select config_run_env ForgettingEventsMeter to CrossEntropyLoss inf save_config create_run_dir capture_config create_loaders run_training test classes join split_indices loadtxt create_dataset create_model_and_optimizer train array makedirs print join Compose Vocab save_index set_random_seed sign train_fastText shuffle_and_index save_result read_labels calculate_rank format save_config concatenate create_run_dir capture_config set join print makedirs now create_dataset array len print now format run_command zeros permutation to_csv len calculate_test_accuracy join format print now run_command calculate_train_accuracy read_fasttext_probs argmax read_labels read_labels arange shuffle argsort sum max len keys len print call save_config create_run_dir capture_config create_loaders set_random_seed config_run_env DataParallel classes create_dataset create_model_and_optimizer to CrossEntropyLoss parameters Adam SGD makedirs reverse decorator reverse decorator train_function reverse decorator active_function coreset_function fasttext_function set targets set targets CIFAR100 CIFAR10 CIFAR100 CIFAR10 _create_test_dataset _create_train_dataset partial __name__ expansion set targets len len list keys save_index DataLoader DataParallel dev DatasetWithIndex str initialize SubsetRandomSampler len to CrossEntropyLoss format run_training create_graph test clear join train makedirs print join symlink relpath join symlink relpath reverse decorator reverse decorator format arange split_indices print SubsetRandomSampler DataLoader DatasetWithIndex len join get_learning_rate state_dict isinstance TimeSplits param_groups print timedelta DataParallel avg AccuracySplits save zip run_epoch range save_summary save_result avg now zip train AverageMeter tqdm seed manual_seed_all manual_seed timestamp format now str timestamp join format makedirs tuple device_count device range len arange print save_index shuffle len list topk expand_as sum max _save_result_helper isinstance join write join format join savetxt param_groups argmax minimum list setdiff1d arange cdist ones min tqdm zeros empty range len pop list cdist tolist min append argmax range max list k_center_greedy arange format _calc_preds_and_features concatenate print now set argsort sum array len Subset RecordInputs eval DataLoader numpy tuple _LabelSmoothing array tuple initialize _LabelSmoothing ImageFolder initialize tuple _LabelSmoothing array | stanford-futuredata/selection-via-proxy | 3,733 |
stanfordmlgroup/ngboost | ['weather forecasting'] | ['NGBoost: Natural Gradient Boosting for Probabilistic Prediction'] | ngboost/distns/exponential.py examples/experiments/survival_exp.py ngboost/scores.py examples/regression.py ngboost/distns/t.py examples/user-guide/scripts/clean.py examples/multivariate_normal.py ngboost/distns/multivariate_normal.py examples/simulations/regression_sim.py ngboost/distns/utils.py ngboost/distns/categorical.py ngboost/distns/lognormal.py ngboost/api.py examples/classification.py examples/survival.py ngboost/__init__.py ngboost/distns/poisson.py tests/test_distns.py examples/multiclass_classification.py ngboost/distns/cauchy.py ngboost/evaluation.py ngboost/distns/distn.py ngboost/distns/normal.py ngboost/helpers.py tests/test_version.py tests/test_basic.py ngboost/distns/__init__.py tests/test_pickling.py tests/test_score.py tests/conftest.py examples/experiments/regression_exp.py ngboost/learners.py examples/poisson.py examples/simulations/survival_sim.py figures/vis_crps.py ngboost/manifold.py ngboost/ngboost.py figures/vis_mle.py examples/sklearn_cv.py ngboost/distns/laplace.py figures/toy.py figures/toy_single.py simulate_data cov_to_sigma Y_join gen_data gen_data NGBClassifier NGBSurvival NGBRegressor calculate_calib_error calibration_regression plot_pit_histogram calculate_concordance_dead_only plot_calibration_curve calibration_time_to_event calculate_concordance_naive Y_from_censored manifold NGBoost Score CRPScore LogScore CategoricalCRPScore CategoricalLogScore k_categorical Cauchy CauchyFixedVar ClassificationDistn RegressionDistn Distn ExponentialLogScore Exponential ExponentialCRPScore LaplaceLogScore LaplaceCRPScore Laplace LogNormalCRPScoreCensored LogNormalLogScoreCensored LogNormal MVNLogScore get_chol_factor get_tril_idxs MultivariateNormal NormalCRPScore NormalFixedVar NormalFixedVarLogScore NormalLogScore Normal NormalFixedVarCRPScore PoissonLogScore negative_log_likelihood Poisson T TFixedDf TFixedDfFixedVar TLogScore TFixedDfFixedVarLogScore TFixedDfLogScore SurvivalDistnClass pytest_addoption breast_cancer_data pytest_configure pytest_runtest_setup boston_data boston_survival_data test_regression test_classification test_dists_runs_on_examples_crpscore test_categorical test_multivariatenormal test_bernoulli test_survival_runs_on_examples test_dists_runs_on_examples_logscore test_model_save fixture_learners_data estimate_grad_err sample_metric test_dists_metric idfn test_dists_grad estimate_metric_err test_version sort rand cos pi sqrt sin zeros array sqrt diagonal empty values abs randn zeros_like reshape polyfit mean shape linspace enumerate KaplanMeierFitter len index KM_estimate polyfit linspace survival_function_ cdf round array fit xlabel ylabel bar axhline title xlim len plot xlabel ylabel polyfit title ylim linspace legend xlim list range tqdm ones_like reshape float64 check_array astype bool empty tril_indices int exp shape zip zeros array enumerate warn addoption skip addinivalue_line load_boston minimum train_test_split load_boston load_breast_cancer score predict predict_proba pred_dist log_loss NGBClassifier roc_auc_score fit score NGBRegressor pred_dist mean_squared_error predict fit fit pred_dist predict NGBRegressor fit pred_dist predict NGBRegressor fit pred_dist predict NGBSurvival fit predict_proba NGBClassifier predict pred_dist k_categorical len predict_proba pred_dist randint NGBClassifier predict fit randn scipy_distribution hstack NGBRegressor mean pred_dist rv MultivariateNormal predict fit T NGBRegressor NGBSurvival append NGBClassifier fit loads dumps predict stack norm n_params approx_fprime sample flatten d_score manifold_test manifold_test norm metric sample_metric seed estimate_grad_err n_params rand manifold seed n_params rand manifold estimate_metric_err | # NGBoost: Natural Gradient Boosting for Probabilistic Prediction  [](https://opensource.org/licenses/Apache-2.0) [](https://github.com/psf/black) ngboost is a Python library that implements Natural Gradient Boosting, as described in ["NGBoost: Natural Gradient Boosting for Probabilistic Prediction"](https://stanfordmlgroup.github.io/projects/ngboost/). It is built on top of [Scikit-Learn](https://scikit-learn.org/stable/), and is designed to be scalable and modular with respect to choice of proper scoring rule, distribution, and base learner. A didactic introduction to the methodology underlying NGBoost is available in this [slide deck](https://drive.google.com/file/d/183BWFAdFms81MKy6hSku8qI97OwS_JH_/view?usp=sharing). ## Installation ```sh via pip pip install --upgrade ngboost via conda-forge | 3,734 |
stangelid/qt | ['extract aspect'] | ['Extractive Opinion Summarization in Quantized Transformer Spaces'] | src/utils/json-to-dirs.py src/extract.py src/aspect_extract.py src/quantizers.py src/utils/train-spm.py src/qt.py src/train.py src/utils/data.py src/utils/training.py src/encoders.py src/utils/summary.py TransformerDocumentEncoder PositionalEncoding PositionalDocumentEncoding generate_square_subsequent_mask QuantizedTransformerModel TransformerDocumentQuantizer SequenceQuantizer TransformerDocumentQuantizerSoftEMA TransformerDocumentQuantizerEMA SequenceQuantizerSoftEMA SequenceQuantizerEMA ReviewDataset ReviewBucketBatchSampler ReviewCollator spm_train EntityReviewBucketBatchSampler ReviewSummarizationDataset spm_train_sentence_limit spm_train_from_json RougeEvaluator truncate_summary LabelSmoothingLoss lr_calc ResidualCoefficientScheduler float transpose masked_fill format Train format Train load join remove print write close spm_train spm_train_sentence_limit open join cosine_similarity transform enumerate append split | # Opinion Summarization with Quantized Transformers This repository contains the data and code for paper: > **Extractive Opinion Summarization in Quantized Transformer Spaces**,<br/> > Stefanos Angelidis, Reinald Kim Amplayo, Yoshihiko Suhara, Xiaolan Wang, Mirella Lapata, <br/> > _To appear: In Transactions of the Association for Computational Linguistics (TACL)_.<br/> > [arXiv](https://arxiv.org/abs/2012.04443) ## The SPACE corpus <img align="right" src="http://homepages.inf.ed.ac.uk/sangelid/space_logo2.png" width="250px"/> The paper introduces SPACE, a large-scale opinion summarization benchmark for the evaluation of unsupervised summarizers. SPACE is built on TripAdvisor | 3,735 |
steff-farley/AFM-image-segmentation | ['semantic segmentation'] | ['Improving the Segmentation of Scanning Probe Microscope Images using Convolutional Neural Networks'] | adding_noise.py contrastnorm.py binarising.py ModMinks.py getAllImages imgstripe getAllImages dir_operation getAllImages getAllImages calculate_normalised_stats join list isdir print append listdir shape randint makedirs endswith closing pi abs max log open writer count_nonzero shape imread sum concatenate size close square sqrt getAllImages unique label float writerow | steff-farley/AFM-image-segmentation | 3,736 |
stellaxu/DHAN | ['click through rate prediction'] | ['Deep Interest with Hierarchical Attention Network for Click-Through Rate Prediction'] | DHAN_DIEN/DHAN/data_iterator.py DHAN_DIN/utils/2_remap_id.py DHAN_DIN/wide_deep/input.py DHAN_DIN/utils/3_build_dataset.py DHAN_DIEN/DHAN/local_aggretor.py DHAN_DIN/dhan/train.py DHAN_DIN/din/model.py DHAN_DIN/din/model_dice.py DHAN_DIEN/DHAN/split_by_user.py DHAN_DIEN/DHAN/shuffle.py DHAN_DIN/dhan/input.py DHAN_DIN/dhan/Dice.py DHAN_DIN/wide_deep/model.py DHAN_DIEN/DHAN/generate_voc.py DHAN_DIN/din/input.py DHAN_DIN/pnn/model.py DHAN_DIN/din/train.py DHAN_DIN/utils/1_convert_pd.py DHAN_DIEN/DHAN/utils.py DHAN_DIEN/DHAN/Dice.py DHAN_DIEN/DHAN/rnn.py DHAN_DIN/wide_deep/train.py DHAN_DIEN/DHAN/model.py DHAN_DIN/din/Dice.py DHAN_DIN/pnn/train.py DHAN_DIEN/DHAN/train.py DHAN_DIN/dhan/model.py DHAN_DIN/pnn/input.py DHAN_DIEN/DHAN/process_data_electronics.py fopen load_dict unicode_to_utf8 DataIterator dice parametric_relu Model_DHAN Model Model_WideDeep Model_DIEN Model_PNN Model_DIN dynamic_rnn _dynamic_rnn_loop _best_effort_input_batch_size raw_rnn static_rnn _infer_state_dtype static_bidirectional_rnn bidirectional_dynamic_rnn static_state_saving_rnn _rnn_step _transpose_batch_time _reverse_seq main eval prepare_data train test first_attention prelu second_attention VecAttGRUCell din_fcn_attention QAAttGRUCell self_all_attention din_attention self_attention calc_auc din_fcn_shine attention dice parametric_relu DataInput DataInputTest attention_item_1 attention_item Model extract_axis_1 attention_multi_items attention calc_auc _test _auc_arr _eval dice parametric_relu DataInput DataInputTest DataInput DataInputTest calc_auc _auc_arr _eval to_df build_map gen_neg DataInput DataInputTest calc_auc _auc_arr _eval endswith reshape square sigmoid sqrt reduce_mean abs relu get_variable get_shape concatenate transpose concat rank set_shape shape value all is_sequence get_shape _copy_some_through call_cell assert_same_structure flatten set_shape zip pack_sequence_as cond get_shape tuple merge_with unknown_shape stack set_shape reverse_sequence unstack zip append _reverse flatten tuple identity to_int32 value constant output_size _best_effort_input_batch_size tuple while_loop reduce_max _concat flatten shape set_shape zip pack_sequence_as reduce_min state_size is_sequence static_rnn state flatten pack_sequence_as state_size flatten tuple pack_sequence_as _reverse_seq remove seek readlines close shuffle strip mkstemp realpath split TemporaryFile open print astype array zip append max enumerate len calculate prepare_data tolist save zip append calc_auc str GPUOptions str GPUOptions append sorted ones_like isinstance Variable reshape concat transpose where expand_dims shape softmax random_normal equal tensordot dense ones_like isinstance print reshape concat transpose where matmul shape softmax tile expand_dims equal zeros_like concat reduce_max where transpose squeeze reduce_sum matmul shape expand_dims range ones_like format softmax tile equal dense isinstance print reshape divide dense count_nonzero ones_like isinstance print reshape concat transpose where matmul shape cast softmax tile expand_dims equal dense ones_like prelu isinstance reshape concat transpose where matmul shape softmax tile expand_dims equal while_loop transpose TensorArray stack expand_dims while_loop transpose TensorArray stack expand_dims dense ones_like prelu isinstance reshape concat transpose shape tile equal get_shape list batch_normalization range len stack gather_nd range zeros_like concat reduce_max where sequence_mask squeeze reduce_sum matmul expand_dims range ones_like format softmax tile equal dense print reshape divide dense ones_like format sequence_mask zeros_like print reshape concat where matmul softmax tile expand_dims range equal dense count_nonzero matmul layer_norm cast tile dense as_list ones_like sequence_mask print reshape concat where matmul softmax tile len append tolist DataInputTest eval save calc_auc len print append test DataInputTest sorted tolist map dict zip range len randint | stellaxu/DHAN | 3,737 |
stepelu/deep-stable | ['gaussian processes'] | ['Stable behaviour of infinitely wide deep neural networks'] | deep_stable.py norm sample_net sample_stable_net sample_stable gamma_weight gamma_bias sample_mv_stable_discrete tan arctan cos pi uniform sin log append sum array range sample_stable phi range ones norm array array len concatenate phi gamma_weight gamma_bias range sample_mv_stable_discrete | # deep-stable Code accompanying the paper "Stable behaviour of infinitely wide deep neural networks". | 3,738 |
stephenbeckr/AIMS | ['text classification', 'stochastic optimization'] | ['Optimization Methods for Large-Scale Machine Learning', 'Convex Optimization: Algorithms and Complexity'] | CVX_tutorial/handout_cvxpy.py problem4 problem7 problem3 problem2 problem5 print_status problem6 get_vars problem8 problem1 T array print value status Problem Minimize norm Variable solve print_status get_vars Problem Minimize norm Variable solve print_status get_vars Problem Minimize norm Variable solve print_status get_vars norm Minimize Problem value Variable print get_problem1_dual_value solve print_status get_vars norm Minimize T Problem Variable ones solve print_status get_vars sum norm Minimize T Problem Variable ones solve print_status get_vars Problem Minimize norm Variable solve print_status get_vars Problem Minimize norm Variable solve print_status get_vars | # AIMS AIMS South Africa Short Course on Optimization 1 week short-course taught for AIMS South Africa, September 2019 Taught by Stephen Becker (University of Colorado, Applied Mathematics) Details at the [AIMS Spring School on Mathematics of Data Science website](https://aims.ac.za/2019/04/18/spring-school-on-mathematics-of-data-science/) See the [Lipschitz/strong-convexity inequalities](inequalities.pdf) cheat-sheet for the course ## Convex Optimization References There are many great books to suggest. The ones below are all excellent, and these are the books I used most for preparing these notes. - [Convex Optimization](http://www.stanford.edu/~boyd/cvxbook/) by S. Boyd and L. Vandenberghe, (Cambridge U. Press, 2004; available online at Boyd's website) - A popular (and rightly so) introduction to convex optimization, with many examples. This is a great source to get ideas on how to prove that your function is convex (follow the examples and exercises) | 3,739 |
steveash/NETransliteration-COLING2018 | ['transliteration'] | ['Design Challenges in Named Entity Transliteration'] | xlit_s2s_nmt/utils/vocab_utils_test.py xlit_s2s_nmt/inference_test.py xlit_s2s_nmt/scripts/bleu.py xlit_s2s_nmt/attention_model.py xlit_t2t/g2p_problem.py scripts/score.py xlit_t2t/g2p_encoder.py xlit_s2s_nmt/g2p_data.py xlit_s2s_nmt/utils/evaluation_utils.py xlit_s2s_nmt/gnmt_model.py scripts/split_pronunciation.py xlit_s2s_nmt/model_test.py xlit_s2s_nmt/utils/misc_utils.py xlit_s2s_nmt/utils/common_test_utils.py xlit_s2s_nmt/utils/vocab_utils.py xlit_s2s_nmt/utils/misc_utils_test.py scripts/vocab_for_nmt.py xlit_s2s_nmt/utils/iterator_utils_test.py xlit_s2s_nmt/train.py xlit_t2t/params.py scripts/filter_k.py xlit_s2s_nmt/model.py xlit_t2t/g2p.py xlit_t2t/g2p_trainer_utils.py scripts/align_tokens.py scripts/split_for_nmt.py xlit_s2s_nmt/scripts/rouge.py scripts/normalize_text.py xlit_s2s_nmt/g2p_encoder.py xlit_s2s_nmt/inference.py xlit_s2s_nmt/utils/nmt_utils.py xlit_t2t/__init__.py scripts/compute_stats.py xlit_t2t/app.py xlit_s2s_nmt/nmt.py xlit_s2s_nmt/model_helper.py xlit_s2s_nmt/utils/evaluation_utils_test.py xlit_s2s_nmt/utils/iterator_utils.py align align filter normalize fix_flip read_truth_or_response get_percentage read_words get_match_index align align align create_attention_mechanism AttentionModel _create_attention_images_summary Gen G2PData gen_file generate_files GraphemePhonemeEncoder load_create_vocabs build_vocab_list GNMTModel GNMTAttentionMultiCell single_worker_inference _decode_inference_indices multi_worker_inference load_data inference InferenceTest BaseModel Model create_train_model InferModel compute_perplexity load_model EvalModel get_device_str create_emb_for_encoder_and_decoder gradient_clip _cell_list create_infer_model TrainModel create_or_load_model create_eval_model get_initializer create_rnn_cell ExtraArgs _single_cell ModelTest create_or_load_hparams run_main ensure_compatible_hparams add_arguments extend_hparams main create_hparams run_external_eval run_sample_decode _format_results run_internal_eval _internal_eval _external_eval train _get_best_results run_full_eval _sample_decode _get_ngrams compute_bleu _len_lcs _get_ngrams rouge rouge_l_summary_level rouge_n _recon_lcs _split_into_words _lcs rouge_l_sentence_level _union_lcs _f_p_r_lcs _get_word_ngrams create_test_hparams create_test_iterator _clean evaluate _accuracy _rouge _bleu _moses_bleu EvaluationUtilsTest get_iterator BatchedInput get_infer_iterator IteratorUtilsTest debug_tensor check_tensorflow_version format_spm_text format_text print_time print_hparams get_config_proto print_out load_hparams format_bpe_text add_summary safe_exp maybe_parse_standard_hparams save_hparams MiscUtilsTest get_translation decode_and_evaluate check_vocab create_vocab_tables VocabUtilsTest main _get_inputs G2PModel _decode_batch_input_fn make_input_fn create_g2p_gt_map GraphemePhonemeEncoder load_create_vocabs build_vocab_list Gen gen_file GraphemeToPhonemeProblem generate_files make_experiment_fn create_experiment create_experiment_components create_run_config add_problem_hparams run Params str list defaultdict items print write split append most_common enumerate add set print join write split find fix_flip rstrip write lower split rstrip add set append split rstrip defaultdict print append split get enumerate join update sort LuongAttention BahdanauAttention expand_dims stack image transpose gen_file TFRecordWriter close write SerializeToString to_example TFRecordWriter close write SerializeToString to_example GraphemePhonemeEncoder exists build_vocab_list store_to_file time print_out print_time single_worker_inference multi_worker_inference GNMTModel Model create_infer_model AttentionModel inference_indices load_data int min load_data len src_vocab_file tgt_vocab_file Graph src_vocab_file tgt_vocab_file Graph Graph tgt_vocab_file src_vocab_file fixed_size_partitioner BasicLSTMCell print_out DeviceWrapper DropoutWrapper LayerNormBasicLSTMCell GRUCell ResidualWrapper __name__ append print_out single_cell_fn range _cell_list clip_by_global_norm scalar global_norm append time restore tables_initializer print_out run time load_model latest_checkpoint tables_initializer print_out eval global_variables_initializer run safe_exp eval time print_time register add_argument join train_prefix src vocab_prefix share_vocab metrics tgt num_layers check_vocab print_out MakeDirs out_dir add_hparam dev_prefix test_prefix list setattr print_out add_hparam maybe_parse_standard_hparams values override_loaded_hparams metrics ensure_compatible_hparams extend_hparams getattr load_hparams print_hparams maybe_parse_standard_hparams save_hparams ckpt subword_option seed inference_input_file print_out hparams_path inference_list latest_checkpoint inference_output_file MakeDirs random_seed inference_ref_file create_or_load_hparams train_fn jobid inference_fn evaluate metrics num_workers out_dir inference train create_hparams run_main batch_size_placeholder src_placeholder iterator _sample_decode _internal_eval iterator test_prefix iterator _external_eval test_prefix run_external_eval metrics _format_results run_sample_decode run_internal_eval test_prefix num_train_steps initializer batch_size GNMTModel save Session run create_train_model steps_per_stats print_time GFile get_config_proto epoch_step run_internal_eval Model create_infer_model print_out add_summary getattr run_full_eval log_device_placement close FileWriter steps_per_external_eval safe_exp join time run_external_eval metrics graph run_sample_decode isnan load_data AttentionModel out_dir create_eval_model append metrics add_summary compute_perplexity initializer run decode initializer len print_out add_summary randint get_translation run join setattr initializer metrics print_out getattr save out_dir add_summary decode_and_evaluate save_hparams run tuple range Counter len _get_ngrams exp Counter zip float sum range len add set _split_into_words _lcs dict max range tuple _lcs intersection _get_word_ngrams len _len_lcs _split_into_words len _recon_lcs set _split_into_words union len _split_into_words len mean list map zip constant index_table_from_tensor from_tensor_slices index_to_string_table_from_tensor _accuracy _rouge _bleu lstrip strip sub _clean zip append compute_bleu split rouge check_output search group call float constant make_initializable_iterator map get_next lookup cast int32 batching_func constant make_initializable_iterator shard group_by_window shuffle skip map apply get_next lookup filter cast int32 zip batching_func exp print flush decode isinstance print write encode flush sorted list print_out keys values join print_out Exists Exists print_out join print_out name Summary ConfigProto encode append isinstance len time print_out evaluate format_spm_text format_text tolist format_bpe_text encode join basename Exists print_out len index_table_from_file decode interactive evaluate rmtree model_dir G2PModel set_verbosity prepare_datafiles freeze Params INFO makedirs flatten append zip compile info append info encode range EOS_ID len append get_hparams build_model_fn Estimator build_input_fn model_dir model_name info add_problem_hparams problem_name ProfilerHook local_eval_frequency ValidationMonitor dbgprofile create_experiment_components append RunConfig is_chief print data_dir model_dir create_hparams save_metadata abspath make_experiment_fn create_run_config hparams_set | # NETransliteration-COLING2018 This is a repository containing the tensorflow code, datasets, and scripts to reproduce the results for the paper: ``` Merhav, Yuval and Ash, Stephen. "Design Challenges in Named Entity Transliteration" Proceedings of COLING 2018, the 27th International Conference on Computational Linguistics. 2018. ``` This paper evaluates Named Entity Transliteration using two neural methods (Seq2Seq Encoder Decoder and Tensor2Tensor Transformer) against the WFST method (using Phonetisaurus). ## Abstract We analyze some of the fundamental design challenges that impact the development of a multilingual state-of-the-art named entity transliteration system, including curating bi-lingual named entity datasets and evaluation of multiple transliteration methods. We empirically evaluate the transliteration task using the traditional weighted finite state transducer (WFST) approach against two neural approaches: the encoder-decoder recurrent neural network method and the recent, non-sequential Transformer method. In order to improve availability of bi-lingual named entity transliteration datasets, we release personal name bilingual dictionaries mined from Wikidata for English to Russian, Hebrew, Arabic, and Japanese Katakana. Authors: Yuval Merhav ([email protected]) and Stephen Ash ([email protected]) The repo is setup with folders: | 3,740 |
steveli/partial-encoder-decoder | ['time series'] | ['Learning from Irregularly-Sampled Time Series: A Missing Data Perspective'] | time-series/sn_layers.py image/utils.py time-series/flow.py image/celeba_decoder.py image/celeba_pbigan.py image/mnist_pvae.py time-series/time_series.py time-series/toy_pbigan.py image/inception.py image/mnist_pbigan.py time-series/gen_toy_data.py image/mnist_encoder.py time-series/toy_layers.py image/flow.py time-series/spline_cconv.py image/mmd.py image/fid.py time-series/utils.py image/mnist_decoder.py time-series/ema.py time-series/mmd.py image/celeba_fid.py time-series/evaluate.py time-series/toy_pvae.py time-series/vis.py image/celeba_pvae.py time-series/mimic3_pvae.py time-series/tracker.py image/celeba_encoder.py time-series/layers.py image/masked_celeba.py time-series/mimic3_pbigan.py image/celeba_pbigan_fid.py image/visualize.py image/masked_mnist.py dconv_bn_relu ConvDecoder ConvEncoder conv_ln_lrelu CelebAFID GradientPenalty ConvCritic PBiGAN train_pbigan main Data pretrained_misgan_fid gen_fid_file main Sampler ImputationSampler main PVAE train_pvae BaseImputationSampler calculate_activation_statistics get_activations BaseSampler calculate_frechet_distance FID MaskedLinear MADE InverseAutoregressiveFlow Reverse FlowSequential InceptionV3 BlockMaskedCelebA MaskedCelebA IndepMaskedCelebA BlockMaskedMNIST MaskedMNIST IndepMaskedMNIST mmd ConvDecoder ConvEncoder GradientPenalty ConvCritic PBiGAN train_pbigan main main PVAE train_pvae count_parameters make_scheduler mkdir Visualizer EMA Evaluator MaskedLinear MADE InverseAutoregressiveFlow Reverse FlowSequential main gen_data HomogeneousPoissonProcess Classifier Decoder DBlock GridDecoder GridEncoder ResLinearBlock GBlock gan_loss PBiGAN main ConvCritic Encoder main masked_loss PVAE Encoder mmd Classifier InvertibleLinearResNetBlock Decoder DBlock GridDecoder InvertibleLinearResNet GridEncoder ResLinearBlock GBlock gan_loss ContinuousConv1D gen_collate_fn kernel_width TimeSeries split_data kernel_width dconv_bn_relu SeqGeneratorDiscrete conv_ln_lrelu ConvCritic GridCritic Encoder PBiGAN main main PVAE Encoder Tracker make_scheduler count_parameters Rescaler mkdir to_numpy plot_samples Visualizer batch_size zero_grad plot_loss DataLoader flow Path save seed str defaultdict IndepMaskedCelebA mmd Adam strftime pbigan prefix to next is_tensor range epoch format plot mean requires_grad_ grad_penalty lr mkdir manual_seed zip make_scheduler BlockMaskedCelebA float ae latent GradientPenalty Visualizer backward print parameters min_lr step ConvDecoder ConvEncoder parse_args add_argument train_pbigan ArgumentParser load latent batch_size eval flow load_state_dict to ConvDecoder ConvEncoder print exists pretrained_misgan_fid load Data only sorted root_dir batch_size print glob gen_fid_file Path batch_size zero_grad plot_loss DataLoader flow Path save kl_off seed str basicConfig exp defaultdict IndepMaskedCelebA Adam strftime k prefix kl_on to next range pvae epoch format plot impute lr mkdir manual_seed make_scheduler BlockMaskedCelebA empty float ae latent items Visualizer backward print min parameters min_lr step ConvDecoder ConvEncoder train_pvae time format print eval empty atleast_2d print iscomplexobj atleast_1d dot sqrtm trace eye real abs max imag mean cov get_activations t shape sum mm basicConfig BlockMaskedMNIST IndepMaskedMNIST BlockMaskedMNIST IndepMaskedMNIST normal sum HomogeneousPoissonProcess gen_time_series broadcast_to uniform linspace sample empty max range savez_compressed gen_data sum data eval_interval zero_grad dec_ref rescale DataLoader save max enc_ch make_graph log seed cls restore defaultdict cconv_ref str ema_decay mmd Adam strftime pbigan apply GridDecoder prefix save_interval to critic range detach update epoch nz RandomState format EMA Evaluator ema requires_grad_ lr mkdir dis_lr manual_seed Tracker make_scheduler ae min_dis_lr zip tanh time evaluate backward sigmoid parameters split_data min_lr randint step overlap gan_loss len train_k kl pvae ts items kernel_width linspace load TimeSeries train_test_split squeeze TimeSeries shape Rescaler plot_interval plot squash Visualizer SeqGeneratorDiscrete join is_tensor GridSpecFromSubplotSpec subplot plot set_yticks set_xlim add_subplot close GridSpec Subplot set_xticks scatter figure savefig set_ticklabels to_numpy unrescale range set_ylim | steveli/partial-encoder-decoder | 3,741 |
stevenireeves/GP_upsamp | ['optical character recognition'] | ['A Gaussian Process Upsampling Model for Improvements in Optical Character Recognition'] | interp/py_pipeline/kernels.py interp/gptest.py interp/py_wrapper/srwrapper.py interp/py_pipeline/weights.py interp/py_pipeline/gp_conv_sr.py gp_conv_sr matern3 get_k get_ks get_pnt get_weights get_kpnt GPupsamp reshape transpose float32 filter2D swapaxes zeros get_weights range sqrt norm zeros matern3 range zeros matern3 range transpose zeros range get_k get_ks ones min solve get_pnt get_kpnt asarray LoadLibrary shape interpolate zeros array | stevenireeves/GP_upsamp | 3,742 |
stevenkleinegesse/minebed | ['experimental design'] | ['Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation'] | src/minebed/__init__.py src/minebed/static/bed.py src/minebed/lower_bounds.py src/minebed/methods.py setup.py examples/bed_bo_example.py src/minebed/mine.py examples/networks_example.py src/minebed/networks.py examples/bed_sgd_example.py examples/mine_example.py simulator seed_torch sim_linear_torch ma minef_loss minef_gradients compute_weights fun_dfun posterior_density posterior_samples get_GP_optimum indicator_boundaries MINE FullyConnected GradientBasedBED GradientFreeBED BED normal normal_ T reshape len seed str manual_seed_all manual_seed exp model log choice mean tensor range len data permutation exp model reshape mean tensor len T array all indicator_constraints indicator_constraints optimize list product OptLbfgs domain get_bounds append Design_space array enumerate constraints list exp FloatTensor Variable numpy append type array range len compute_weights list reshape choice append sum array range len compute_weights array | stevenkleinegesse/minebed | 3,743 |
stevewongv/InstanceShadowDetection | ['shadow detection'] | ['Instance Shadow Detection'] | tests/test_checkpoint.py detectron2/modeling/proposal_generator/build.py detectron2/evaluation/evaluation/coco_evaluation.py PythonAPI/pysobatools/soba.py detectron2/evaluation/cityscapes_evaluation.py detectron2/utils/visualizer.py detectron2/evaluation/evaluation/pascal_voc_evaluation.py detectron2/utils/collect_env.py detectron2/data/datasets/register_soba.py detectron2/modeling/anchor_generator.py detectron2/data/detection_utils.py projects/LISA/visualize_json_results.py detectron2/modeling/proposal_generator/rpn_outputs.py detectron2/modeling/proposal_generator/rpn.py detectron2/checkpoint/__init__.py projects/LISA/LISA/LISA_rcnn.py tests/test_data_loader.py detectron2/modeling/postprocessing.py detectron2/config/compat.py detectron2/model_zoo/__init__.py detectron2/evaluation/evaluation/testing.py detectron2/evaluation/sem_seg_evaluation.py detectron2/evaluation/lvis_evaluation.py detectron2/utils/registry.py detectron2/modeling/backbone/backbone.py detectron2/modeling/roi_heads/fast_rcnn.py PythonAPI/pysobatools/sobaeval.py detectron2/evaluation/evaluation/cityscapes_evaluation.py tests/test_boxes.py detectron2/data/datasets/lvis.py detectron2/modeling/roi_heads/mask_head.py detectron2/data/samplers/__init__.py detectron2/utils/logger.py detectron2/structures/__init__.py detectron2/modeling/meta_arch/semantic_seg.py detectron2/modeling/meta_arch/retinanet.py detectron2/export/caffe2_export.py detectron2/export/shared.py detectron2/data/samplers/grouped_batch_sampler.py detectron2/layers/roi_align.py setup.py detectron2/modeling/roi_heads/rotated_fast_rcnn.py detectron2/utils/events.py detectron2/layers/roi_align_rotated.py detectron2/utils/video_visualizer.py detectron2/data/samplers/distributed_sampler.py detectron2/modeling/sampling.py detectron2/evaluation/soba_evaluation.py detectron2/utils/__init__.py detectron2/structures/image_list.py detectron2/data/datasets/soba.py detectron2/checkpoint/model_zoo.py projects/LISA/SOAP.py detectron2/evaluation/panoptic_evaluation.py detectron2/layers/__init__.py detectron2/modeling/roi_heads/roi_heads.py detectron2/modeling/backbone/__init__.py docs/conf.py detectron2/data/transforms/transform_gen.py detectron2/modeling/roi_heads/LISA_rcnn.py detectron2/utils/comm.py projects/LISA/predictor.py detectron2/evaluation/testing.py detectron2/structures/instances.py detectron2/modeling/box_regression.py detectron2/solver/lr_scheduler.py detectron2/data/datasets/pascal_voc.py detectron2/export/caffe2_modeling.py detectron2/data/catalog.py detectron2/config/__init__.py detectron2/modeling/test_time_augmentation.py projects/LISA/utils.py tests/test_roi_align.py detectron2/modeling/proposal_generator/rrpn_outputs.py detectron2/modeling/roi_heads/box_head.py detectron2/modeling/meta_arch/__init__.py detectron2/export/c10.py detectron2/export/__init__.py demo/demo.py detectron2/solver/build.py detectron2/export/patcher.py PythonAPI/setup.py detectron2/data/transforms/__init__.py detectron2/config/defaults.py detectron2/export/caffe2_inference.py tests/test_roi_pooler.py tests/test_model_e2e.py detectron2/modeling/poolers.py detectron2/modeling/meta_arch/rcnn.py PythonAPI/pysobatools/cocoeval.py detectron2/checkpoint/catalog.py detectron2/layers/batch_norm.py detectron2/data/datasets/coco.py detectron2/evaluation/__init__.py projects/LISA/LISA/config.py tests/test_sampler.py detectron2/evaluation/evaluation/lvis_evaluation.py detectron2/checkpoint/detection_checkpoint.py projects/LISA/train_net.py detectron2/export/api.py detectron2/structures/keypoints.py detectron2/engine/__init__.py detectron2/utils/serialize.py detectron2/config/config.py detectron2/engine/train_loop.py detectron2/modeling/matcher.py detectron2/data/dataset_mapper.py detectron2/data/datasets/cityscapes.py detectron2/modeling/proposal_generator/proposal_utils.py detectron2/data/datasets/builtin.py detectron2/modeling/roi_heads/cascade_rcnn.py detectron2/data/transforms/transform.py detectron2/modeling/proposal_generator/rrpn.py projects/LISA/__init__.py detectron2/engine/hooks.py detectron2/layers/mask_ops.py tests/test_roi_heads.py demo/predictor.py detectron2/data/datasets/__init__.py detectron2/data/datasets/builtin_meta.py detectron2/modeling/roi_heads/keypoint_head.py detectron2/model_zoo/model_zoo.py tests/test_nms_rotated.py detectron2/data/build.py detectron2/evaluation/rotated_coco_evaluation.py tests/test_anchor_generator.py tests/test_data_transform.py tests/test_rpn.py detectron2/modeling/roi_heads/__init__.py detectron2/modeling/proposal_generator/__init__.py projects/LISA/LISA/LISA_meta_arch.py tests/test_model_zoo.py detectron2/checkpoint/c2_model_loading.py detectron2/__init__.py detectron2/data/datasets/register_coco.py tests/test_mask_ops.py PythonAPI/pysobatools/mask.py detectron2/layers/nms.py detectron2/modeling/meta_arch/build.py tests/test_rotated_boxes.py detectron2/modeling/proposal_generator/LISA_rpn.py detectron2/evaluation/evaluation/sem_seg_evaluation.py detectron2/structures/masks.py PythonAPI/pysobatools/__init__.py detectron2/solver/__init__.py detectron2/evaluation/coco_evaluation.py detectron2/layers/wrappers.py projects/LISA/LISA/__init__.py detectron2/engine/defaults.py detectron2/utils/memory.py tests/test_visualizer.py projects/LISA/visualize_data.py projects/LISA/LISA/LISA_rpn.py projects/LISA/demo.py detectron2/layers/deform_conv.py detectron2/modeling/meta_arch/LISA_meta_arch.py detectron2/structures/rotated_boxes.py detectron2/modeling/backbone/resnet.py detectron2/evaluation/evaluation/panoptic_evaluation.py projects/LISA/defaults.py detectron2/layers/rotated_boxes.py tests/test_box2box_transform.py detectron2/modeling/backbone/fpn.py tests/test_roi_align_rotated.py datasets/prepare_panoptic_fpn.py detectron2/utils/colormap.py detectron2/evaluation/pascal_voc_evaluation.py detectron2/modeling/backbone/build.py detectron2/modeling/__init__.py tests/test_fast_rcnn.py detectron2/evaluation/evaluation/evaluator.py detectron2/modeling/meta_arch/panoptic_fpn.py detectron2/utils/env.py detectron2/evaluation/evaluation/__init__.py tests/test_config.py detectron2/engine/launch.py detectron2/layers/shape_spec.py detectron2/data/datasets/lvis_v0_5_categories.py detectron2/data/__init__.py tests/__init__.py detectron2/evaluation/evaluator.py detectron2/structures/boxes.py detectron2/data/common.py get_model_zoo_configs get_extensions get_version separate_coco_semantic_from_panoptic link_val100 _process_panoptic_to_semantic get_parser setup_cfg VisualizationDemo AsyncPredictor convert_c2_detectron_names convert_basic_c2_names align_and_update_state_dicts Detectron2Handler ModelCatalogHandler ModelCatalog DetectionCheckpointer Detectron2Handler ModelCatalogHandler ModelCatalog upgrade_config downgrade_config _rename _RenameConverter ConverterV2 ConverterV1 guess_version set_global_cfg get_cfg CfgNode build_batch_data_sampler print_instances_class_histogram build_detection_test_loader filter_images_with_few_keypoints build_detection_train_loader load_proposals_into_dataset worker_init_reset_seed get_detection_dataset_dicts trivial_batch_collator filter_images_with_only_crowd_annotations _quantize MetadataCatalog DatasetCatalog Metadata DatasetFromList MapDataset DatasetMapper check_metadata_consistency annotations_to_instances transform_instance_annotations annotations_to_instances_rotated transform_proposals gen_crop_transform_with_instance build_transform_gen check_image_size create_keypoint_hflip_indices SizeMismatchError filter_empty_instances transform_keypoint_annotations read_image register_all_coco register_all_cityscapes register_all_lvis register_all_pascal_voc _get_coco_instances_meta _get_builtin_metadata _get_coco_panoptic_separated_meta load_cityscapes_instances load_cityscapes_semantic cityscapes_files_to_dict load_sem_seg load_coco_json register_lvis_instances get_lvis_instances_meta _get_lvis_instances_meta_v0_5 load_lvis_json load_voc_instances register_pascal_voc merge_to_panoptic register_coco_panoptic_separated register_coco_instances merge_to_panoptic register_soba_panoptic_separated register_soba_instances load_sem_seg load_soba_json RepeatFactorTrainingSampler InferenceSampler TrainingSampler GroupedBatchSampler ExtentTransform Resize_rotated_box ResizeTransform HFlip_rotated_box TransformGen RandomFlip RandomSaturation check_dtype RandomLighting apply_transform_gens RandomContrast Resize RandomCrop ResizeShortestEdge RandomExtent RandomBrightness default_setup DefaultTrainer DefaultPredictor default_argument_parser PeriodicCheckpointer LRScheduler IterationTimer PreciseBN CallbackHook PeriodicWriter AutogradProfiler EvalHook launch _distributed_worker _find_free_port SimpleTrainer HookBase TrainerBase CityscapesEvaluator _evaluate_box_proposals _evaluate_predictions_on_coco COCOEvaluator instances_to_json DatasetEvaluator DatasetEvaluators inference_on_dataset inference_context _evaluate_predictions_on_lvis _evaluate_box_proposals LVISEvaluator COCOPanopticEvaluator _print_panoptic_results PascalVOCDetectionEvaluator parse_rec voc_eval voc_ap RotatedCOCOeval RotatedCOCOEvaluator SemSegEvaluator _evaluate_box_proposals instances_to_json _evaluate_predictions_on_soba SOBAEvaluator verify_results print_csv_format flatten_results_dict CityscapesEvaluator _evaluate_box_proposals _evaluate_predictions_on_coco COCOEvaluator instances_to_json DatasetEvaluator DatasetEvaluators inference_on_dataset inference_context _evaluate_predictions_on_lvis _evaluate_box_proposals LVISEvaluator COCOPanopticEvaluator _print_panoptic_results PascalVOCDetectionEvaluator parse_rec voc_eval voc_ap SemSegEvaluator verify_results print_csv_format flatten_results_dict Caffe2Model add_export_config export_caffe2_model Caffe2KeypointRCNNInference Caffe2RPN Caffe2Compatible Caffe2FastRCNNOutputsInference Caffe2MaskRCNNInference Boxes4or5 Caffe2ROIPooler InstancesList run_and_save_graph _op_stats export_caffe2_detection_model _assign_device_option _export_via_onnx ProtobufDetectionModel ProtobufModel Caffe2GeneralizedRCNN Caffe2RetinaNet set_caffe2_compatible_tensor_mode _cast_to_f32 Caffe2PanopticFPN Caffe2MetaArch assemble_rcnn_outputs_by_name convert_batched_inputs_to_c2_format GenericMixin mock_fastrcnn_outputs_inference ROIHeadsPatcher patch Caffe2CompatibleConverter patch_generalized_rcnn mock_mask_rcnn_inference mock_keypoint_rcnn_inference rename_op_input get_sub_graph_external_input_output to_device IllegalGraphTransformError mock_torch_nn_functional_interpolate save_graph_base identify_reshape_sub_graph alias remove_reshape_for_fc construct_init_net_from_params DiGraph get_params_from_init_net get_pb_arg_valstrings _modify_blob_names _rename_blob group_norm_replace_aten_with_caffe2 _rename_versioned_blob_in_proto get_pb_arg_ints ScopedWS get_pb_arg_vals save_graph get_pb_arg_floats fuse_copy_between_cpu_and_gpu get_pb_arg_vali get_pb_arg_valf _generic_status_identifier onnx_compatibale_interpolate remove_dead_end_ops get_pb_arg BilinearInterpolation check_set_pb_arg infer_device_type fetch_any_blob get_producer_map fuse_alias_placeholder rename_op_output _get_dependency_chain _updater_raise _create_const_fill_op_from_numpy create_const_fill_op get_consumer_map _create_const_fill_op_from_c2_int8_tensor NaiveSyncBatchNorm FrozenBatchNorm2d AllReduce get_norm ModulatedDeformConv DeformConv _ModulatedDeformConv _DeformConv paste_mask_in_image_old pad_masks _do_paste_mask paste_masks_in_image scale_boxes nms_rotated batched_nms_rotated batched_nms ROIAlign _ROIAlign _ROIAlignRotated ROIAlignRotated pairwise_iou_rotated ShapeSpec _NewEmptyTensorOp Conv2d interpolate BatchNorm2d ConvTranspose2d cat RotatedAnchorGenerator build_anchor_generator _create_grid_offsets BufferList DefaultAnchorGenerator Box2BoxTransformRotated Box2BoxTransform Matcher convert_boxes_to_pooler_format assign_boxes_to_levels ROIPooler detector_postprocess decode takeTwo sem_seg_postprocess rect_distance matchor dist compute_iou compute_direction combine_association box_combine encode subsample_labels DatasetMapperTTA GeneralizedRCNNWithTTA Backbone build_backbone LastLevelMaxPool build_retinanet_resnet_fpn_backbone build_resnet_fpn_backbone FPN LastLevelP6P7 _assert_strides_are_log2_contiguous ResNet ResNetBlockBase BottleneckBlock build_resnet_backbone DeformBottleneckBlock make_stage BasicStem build_model LISARCNN combine_semantic_and_instance_outputs PanopticFPN ProposalNetwork GeneralizedRCNN permute_all_cls_and_box_to_N_HWA_K_and_concat permute_to_N_HWA_K RetinaNet RetinaNetHead SemanticSegmentor SemSegFPNHead build_sem_seg_head build_proposal_generator build_proposal_generator build_rpn_head LISARPNHead LISARPN add_ground_truth_to_proposals add_ground_truth_to_proposals_single_image RPN StandardRPNHead build_rpn_head rpn_losses RPNOutputs find_top_rpn_proposals RRPN RRPNOutputs find_top_rrpn_proposals build_box_head FastRCNNConvFCHead _ScaleGradient CascadeROIHeads LightdirectionOutputLayer FastRCNNOutputs fast_rcnn_inference fast_rcnn_losses fast_rcnn_inference_single_image FastRCNNOutputLayers build_keypoint_head keypoint_rcnn_inference KRCNNConvDeconvUpsampleHead keypoint_rcnn_loss RelationROIHeads MaskRCNNConvUpsampleHead mask_rcnn_loss build_mask_head mask_rcnn_inference RROIHeads Res5ROIHeads build_roi_heads ROIHeads select_proposals_with_visible_keypoints select_foreground_proposals StandardROIHeads RROIHeads RotatedFastRCNNOutputs fast_rcnn_inference_single_image_rotated fast_rcnn_inference_rotated get get_checkpoint_url get_config_file _ModelZooUrls build_lr_scheduler build_optimizer WarmupMultiStepLR WarmupCosineLR _get_warmup_factor_at_iter pairwise_iou matched_boxlist_iou BoxMode Boxes ImageList Instances Keypoints _keypoints_to_heatmap heatmaps_to_keypoints BitMasks rasterize_polygons_within_box PolygonMasks polygons_to_bitmask pairwise_iou RotatedBoxes get_env_module collect_torch_env collect_env_info random_color colormap get_local_size synchronize get_world_size get_local_rank reduce_dict _get_global_gloo_group shared_random_seed all_gather get_rank gather _serialize_to_tensor is_main_process _pad_to_largest_tensor setup_environment setup_custom_environment _configure_libraries _import_file seed_all_rng EventStorage TensorboardXWriter get_event_storage JSONWriter CommonMetricPrinter _cached_log_stream log_first_n _find_caller setup_logger log_every_n create_small_table _ColorfulFormatter retry_if_cuda_oom _ignore_torch_cuda_oom Registry PicklableWrapper _DetectedInstance VideoVisualizer VisImage Visualizer GenericMask ColorMode _PanopticPrediction _create_text_labels url_resolver setup autodoc_skip_member default_setup DefaultTrainer DefaultPredictor default_argument_parser get_parser setup_cfg VisualizationDemo AsyncPredictor main setup Trainer compute_ap norm_boxes compute_recall apply_box_deltas compute_overlaps compute_iou resize resize_image generate_pyramid_anchors mold_mask generate_anchors compute_ap_range compute_overlaps_masks denorm_boxes unmold_mask download_trained_weights __main__ non_max_suppression minimize_mask resize_mask extract_bboxes trim_zeros compute_matches expand_mask box_refinement Dataset parse_args output setup dataset_ass_id_map create_instances dataset_id_map add_lisa_config LISARCNN LISAROIHeads build_proposal_generator build_rpn_head LISARPNHead LISARPN Params COCOeval encode decode area toBbox _isArrayLike SOBA SOAPeval Params TestAnchorGenerator random_rotated_boxes TestBox2BoxTransformRotated random_boxes TestBox2BoxTransform TestBoxIOU TestBoxMode TestCheckpointer TestConfigVersioning TestTransformAnnotations TestTransforms FastRCNNTest rasterize_polygons_with_grid_sample TestMaskCropPaste benchmark_paste iou_between_full_image_bit_masks create_model_input get_empty_instance RetinaNetE2ETest ModelE2ETest MaskRCNNE2ETest get_regular_bitmask_instances get_model_zoo TestModelZoo TestNMSRotated ROIAlignTest ROIAlignRotatedTest ROIHeadsTest TestROIPooler TestRotatedBoxesLayer TestRotatedBoxesStructure benchmark_rotated_iou RPNTest TestGroupedBatchSampler TestVisualizer join format strip readlines strftime getenv dirname abspath append get join format glob dirname abspath append join isdir glob unlink realpath rmtree islink symlink dirname exists asarray zeros_like save rgb2id open time format starmap partial print makedirs iter_annotations Pool enumerate join relpath print symlink makedirs merge_from_file confidence_threshold config_file get_cfg merge_from_list opts freeze add_argument ArgumentParser deepcopy deepcopy sorted format convert_basic_c2_names zip getLogger tuple shape startswith info keys cat get_missing_parameters_message getLogger tuple warning max values list sorted view tolist shape convert_c2_detectron_names format info keys enumerate error clone get_unexpected_parameters_message len VERSION upgrade clone range VERSION downgrade clone range VERSION format warning getLogger _get _del _set split clear update getLogger format info len getLogger format info len pop sorted format getLogger set info enumerate list sorted map copy list tabulate arange format chain min log_first_n extend zip_longest colored zeros sum INFO len GroupedBatchSampler _quantize BatchSampler list check_metadata_consistency thing_classes print_instances_class_histogram filter_images_with_few_keypoints from_iterable filter_images_with_only_crowd_annotations RepeatFactorTrainingSampler build_batch_data_sampler format TrainingSampler IMS_PER_BATCH getLogger get_world_size TRAIN DataLoader MapDataset SAMPLER_TRAIN REPEAT_THRESHOLD get_detection_dataset_dicts info DatasetMapper DatasetFromList len DataLoader MapDataset BatchSampler get_detection_dataset_dicts DatasetMapper DatasetFromList InferenceSampler len randint seed_all_rng pop apply_box convert astype Boxes Instances nonempty XYXY_ABS as_tensor clip XYXY_ABS convert transform_keypoint_annotations apply_coords reshape Keypoints from_polygon_masks Boxes Instances tensor PolygonMasks clip Instances tensor clip RotatedBoxes append nonempty get update check_metadata_consistency keypoint_flip_map dict keypoint_names minimum asarray convert astype maximum randint int32 XYXY_ABS str format getLogger error enumerate str RandomFlip MIN_SIZE_TRAIN_SAMPLING info getLogger MIN_SIZE_TEST MIN_SIZE_TRAIN ResizeShortestEdge MAX_SIZE_TRAIN MAX_SIZE_TEST append get join items register_coco_instances _get_builtin_metadata register_coco_panoptic_separated register_lvis_instances join get_lvis_instances_meta items join items format set _get_builtin_metadata register join register_pascal_voc update _get_coco_instances_meta join format partial getLogger glob map info append Pool len append join glob list asarray isinstance Polygon endswith bounds geoms id buffer difference is_empty nonzero unique append XYXY_ABS union chain warn warning Timer getCatIds sorted list append get getRelaIds format XYWH_ABS loadRela zip loadImgs info seconds keys enumerate join get_local_path loadCats len list sorted format zip warn set file2id info append len register set Timer load_imgs get_local_path format seconds sorted list zip join get set get_lvis_instances_meta startswith info LVIS keys append len join parse findall text append find register set register set register set update append copy register set register set warn warning Timer getAssoIds getCatIds sorted list append loadAsso get format XYWH_ABS zip loadImgs info seconds keys enumerate join get_local_path loadCats len width arctan2 cos h pi w new_w sin new_h check_dtype get_transform apply_image append getuid add_argument hash ArgumentParser str read format collect_env_info hasattr join config_file CUDNN_BENCHMARK setup_logger get_world_size get_rank mkdirs abspath info OUTPUT_DIR seed_all_rng socket bind close AF_INET SOCK_STREAM _find_free_port spawn main_func list init_process_group new_group synchronize set_device main_func range pred_masks_rle XYWH_ABS has pred_keypoints convert tolist pred_associations pred_light append XYXY_ABS numpy range len arange zeros_like max pairwise_iou Boxes append sum loadAnns range cat getAnnIds mean float proposal_boxes enumerate reshape sort min zeros as_tensor len pop deepcopy evaluate COCOeval summarize accumulate loadRes evaluate_rela loadRes_rela array int time format str evaluate getLogger min timedelta reset info len eval train training get_ann_ids load_anns pop deepcopy format getLogger LVISResults warn get_results create_small_table print_results info LVISEval run append tabulate info int parse findall text append find arange concatenate size maximum sum max range parse_rec cumsum argmax max sum range eps format astype float minimum reshape maximum voc_ap argsort zeros bool array len pop deepcopy evaluate COCOeval summarize loadRes_asso accumulate loadRes array evaluate_asso join items format getLogger info str getLogger error exit EXPECTED_RESULTS pformat info abs items isinstance freeze defrost is_frozen CN get_caffe2_inputs C2MetaArch export_caffe2_detection_model property onnx_graph_to_caffe2_net get_available_passes optimize apply get items sorted infer_device_type _assign_op_device_option get_ssa deepcopy format remove_reshape_for_fc info construct_init_net_from_params get_params_from_init_net fuse_alias_placeholder fuse_copy_between_cpu_and_gpu _assign_device_option remove_dead_end_ops any encode_additional_info _op_stats colored _export_via_onnx group_norm_replace_aten_with_caffe2 tabulate __name__ format save_graph info get arange keypoint_rcnn_inference pred_classes Boxes int64 zeros to apply get from_tensors image_sizes zip append Tensor named_children isinstance ccc RPN patch ROIPooler device int upsample_filt zeros conv_transpose2d warning isinstance is_in_onnx_export FetchBlob arg get_pb_arg get_pb_arg get_pb_arg get_pb_arg get_pb_arg get_pb_arg format extend MakeArgument warning getattr setattr get_pb_arg update data type NetDef items format isinstance extend warning append type len range enumerate defaultdict append range enumerate len get_ssa get_producer_map deepcopy get_ssa _update_i op reversed zip union deepcopy list _replace_list map output input append partial GetPydotGraph format print write_svg op GetPydotGraphMinimal dirname _modify_blob_names write_png write_pdf makedirs remove format check_set_pb_arg get_pb_arg_vals op get_pb_arg_vali info get_pb_arg decode rename_op_input rename_op_output op extend get_pb_arg_vali append bool enumerate external_output external_input output op zip input range len deepcopy get_ssa get_producer_map rename_op_output _rename_versioned_blob_in_proto get_ssa _rename_versioned_blob_in_proto get_ssa sum format get_all_paths get_producer_map min from_ssa warning get_consumer_map get_ssa op _get_dependency_chain append enumerate join get_ssa format all deepcopy remove get_sub_graph_external_input_output rename_op_output extend info append identify_reshape_sub_graph _fuse_once get_ssa list all extend reversed add set get_consumer_map enumerate isinstance arange grid_sample size expand stack device to split int arange chunk _do_paste_mask device ceil tensor to zeros len fromarray max uint8 min from_numpy resize zeros to numpy array float new_zeros zeros_like nms view size tolist new_zeros nms_rotated min clone to max _output_size tuple meshgrid reshape arange NAME clamp sqrt log2 floor epsilon cat cat pred_boxes has Instances paste_masks_in_image proposal_boxes image_size clip expand min max format items pred_classes box_combine append numpy enumerate split pred_boxes pred_associations Instances tolist shape append scores XYWH_ABS float toBbox zeros enumerate int items reshape convert pred_classes XYXY_ABS numpy len int squeeze min numel NAME ShapeSpec enumerate IN_FEATURES OUT_CHANNELS FPN build_resnet_backbone IN_FEATURES OUT_CHANNELS FPN build_resnet_backbone append block_class range convert_frozen_batchnorm STEM_OUT_CHANNELS make_stage WIDTH_PER_GROUP max DEFORM_NUM_GROUPS FREEZE_AT RES2_OUT_CHANNELS append freeze range OUT_FEATURES DEPTH RES5_DILATION DEFORM_ON_PER_STAGE BasicStem enumerate NORM STRIDE_IN_1X1 parameters DEFORM_MODULATED NUM_GROUPS META_ARCHITECTURE zeros_like tolist argsort item append to shape reshape permute view view NAME NAME HEAD_NAME len ones Instances device image_size log cat len arange count zip sort min Boxes Instances nonempty enumerate image_sizes device append tensor batched_nms full clip cat len smooth_l1_loss to float32 binary_cross_entropy_with_logits arange count zip sort min RotatedBoxes Instances nonempty batched_nms_rotated enumerate image_sizes device append tensor full clip cat len NAME arange smooth_l1_loss size squeeze numel atan2 device cross_entropy view reshape Boxes Instances nonzero batched_nms clip NAME put_scalar cross_entropy get_event_storage view gt_keypoints squeeze numel shape cat append tensor to to_heatmap len detach heatmaps_to_keypoints zip cat split put_scalar arange get_event_storage size numel binary_cross_entropy_with_logits item append to max cat arange sigmoid zip cat split NAME NAME append squeeze gt_classes put_scalar get_event_storage squeeze numel mean unsqueeze any append tensor view reshape RotatedBoxes Instances batched_nms_rotated nonzero clip replace join resource_filename merge_from_file load build_model get_cfg WEIGHTS get_checkpoint_url get_config_file WEIGHT_DECAY_NORM endswith WEIGHT_DECAY_BIAS SGD named_parameters BASE_LR BIAS_LR_FACTOR WEIGHT_DECAY LR_SCHEDULER_NAME clamp min area where zeros max max min area clamp long argmax arange view exp_ clamp squeeze new_zeros ceil float sum max range frPyObjects merge from_numpy deepcopy max polygons_to_bitmask str items defaultdict get_env_module is_available device_count append tabulate range randint len barrier get_world_size format getLogger from_buffer dumps get_rank warning get_backend device to len get_world_size all_gather tensor max zeros cat _serialize_to_tensor _get_global_gloo_group loads zip append max _pad_to_largest_tensor max zip _get_global_gloo_group loads get_rank append _serialize_to_tensor _pad_to_largest_tensor randint all_gather get_world_size seed int set_rng_state format from_bytes get_state getLogger strftime getpid info urandom spec_from_file_location exec_module module_from_spec get int setUseOpenCL get setup_custom_environment _configure_libraries endswith setup_environment _import_file import_module setFormatter join format _cached_log_stream getLogger addHandler StreamHandler Formatter mkdirs _ColorfulFormatter dirname colored DEBUG setLevel f_back _getframe f_code _find_caller log isinstance _find_caller log tuple tabulate zip getattr replace add_transform add_config_value connect merge_from_file config_file get_cfg merge_from_list default_setup opts freeze verify_results update test_with_TTA setup build_model print resume_or_load test WEIGHTS ENABLED Trainer register_hooks eval_only keys is_main_process zeros array range minimum maximum zeros range compute_iou T astype float32 dot sum astype delete float32 compute_iou append astype float32 astype float32 log dtype min pad resize randint max pad astype resize zeros bool range astype resize zeros bool range zeros bool astype resize arange concatenate reshape flatten sqrt meshgrid array append generate_anchors range len ones trim_zeros compute_overlaps_masks range len arange concatenate cumsum compute_matches astype float32 maximum sum range len compute_ap format print mean append compute_overlaps set argmax max len print array array add_argument ArgumentParser show join format print waitKey imshow save asarray XYWH_ABS convert Boxes Instances XYXY_ABS CN shape sum arange grid_sample from_numpy shape meshgrid to append randn clamp rand Boxes benchmark manual_seed is_available cat merge_from_file get_cfg get_config_file BitMasks rand Boxes Instances to BitMasks rand Boxes Instances to is_available stack benchmark append | # Instance Shadow Detection (CVPRโ 20) [Tianyu Wang](https://stevewongv.github.io)\*, [Xiaowei Hu](https://xw-hu.github.io)\*, Qiong Wang, Pheng-Ann Heng, and [Chi-Wing Fu](http://www.cse.cuhk.edu.hk/~cwfu/) (\* Joint first authors.) [[`openaccess`](http://openaccess.thecvf.com/content_CVPR_2020/papers/Wang_Instance_Shadow_Detection_CVPR_2020_paper.pdf)][[`arXiv`](https://arxiv.org/abs/1911.07034)] [[`BibTeX`](#CitingLISA)] **News: Our new work on instance shadow detection was accepted in CVPR 2021 as Oral presentation, check [here](https://github.com/stevewongv/SSIS)!**  Instance shadow detection aims to find shadow instances paired with object instances. We present a dataset, a deep framework, and an evaluation metric to approach this new task. This repo is implemented on [Detectron2](https://github.com/facebookresearch/detectron2). ## Dependences * python>=3.6 * torch (tested on 1.3.0+cu100 and 1.12.0+cu113) | 3,744 |
stevewongv/SPANet | ['rain removal', 'single image deraining'] | ['Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset'] | SPANet.py randomcrop.py dataset.py cal_ssim.py main.py irnn.py create_window gaussian _ssim SSIM ssim TrainValDataset TestDataset cunnex irnn Stream run_train_val ensure_dir Session run_test RandomHorizontallyFlip RandomRotation RandomResizedCrop RandomCrop RandomVerticallyFlip Spacial_IRNN conv1x1 Bottleneck conv3x3 SPANet Attention SAM Tensor Variable contiguous unsqueeze pow conv2d create_window size type_as get_device cuda is_cuda cuda_stream makedirs inf_batch zero_grad DataParallel load_checkpoints Session multi_gpu log_name save_mask tensorboard save_checkpoints next get_dataloader eval info net train_data_path backward write train step val_log_name data inf_batch imwrite DataParallel load_checkpoints heatmap clip Session multi_gpu transpose append get_dataloader update test_data_path format compare_ssim astype mean start eval ensure_dir net enumerate print numpy compare_psnr | stevewongv/SPANet | 3,745 |
stringtron/quantative_style | ['style transfer'] | ['Improving Style Transfer with Calibrated Metrics'] | Baed_E_scripts/EBase/__init__.py Baed_E_scripts/EBase/tools.py TOOLS Cov_Mean VGG | stringtron/quantative_style | 3,746 |
strongman1995/Fast-Adversarial-Watermark-Attack-on-OCR | ['optical character recognition'] | ['FAWA: Fast Adversarial Watermark Attack on Optical Character Recognition (OCR) Systems'] | cleverhans/attacks/spsa.py cleverhans/experimental/certification/tests/nn_test.py cleverhans/attacks/carlini_wagner_l2.py utils_tf.py cleverhans/plot/image.py basic_grad.py cleverhans/model_zoo/cnn_lstm_ctc_ocr.py cleverhans/attacks/spatial_transformation_method.py cleverhans/plot/pyplot_image.py cleverhans/initializers.py wm_grad.py cleverhans/attacks/elastic_net_method.py test.py cleverhans/attacks/carlini_wagner_l2.bak.py cleverhans/attacks/attack.py cleverhans/dataset.py cleverhans/devtools/autopep8_all.py cleverhans/experimental/certification/dual_formulation.py cleverhans/attacks/lbfgs.py cleverhans/model_zoo/soft_nearest_neighbor_loss/SNNL_regularized_train.py cleverhans/experimental/certification/certify.py cleverhans/devtools/list_files.py cleverhans/__init__.py cleverhans/attacks/noise.py cleverhans/plot/save_pdf.py cleverhans/model_zoo/soft_nearest_neighbor_loss/SNNL_regularized_model.py cleverhans/confidence_report.py cleverhans/attacks_tf.py cleverhans/utils.py cleverhans/attacks/__init__.py cleverhans/attacks/deep_fool.py cleverhans/canary.py cleverhans/attack_bundling.py cleverhans/attacks/momentum_iterative_method2.py cleverhans/utils_mnist.py cleverhans/model_zoo/soft_nearest_neighbor_loss/__init__.py cleverhans/picklable_model.py cleverhans/attacks/basic_iterative_method.py cleverhans/experimental/certification/tests/optimization_test.py cleverhans/model_zoo/basic_cnn.py cleverhans/evaluation.py cleverhans/devtools/checks.py cleverhans/devtools/tests/test_format.py cleverhans/attacks/virtual_adversarial_method.py cleverhans/attacks/semantic.py cleverhans/devtools/version.py cleverhans/model_zoo/madry_lab_challenges/cifar10_model.py wm_opt.py cleverhans/experimental/certification/utils.py cleverhans/attacks/cwl2.py long_attack.py cleverhans/model_zoo/madry_lab_challenges/__init__.py paragraph_attack.py cleverhans/attacks/fast_gradient_method.py cleverhans/compat.py cleverhans/augmentation.py cleverhans/attacks/madry_et_al.py cleverhans/utils_keras.py cleverhans/experimental/certification/optimization.py basic_opt.py cleverhans/model_zoo/madry_lab_challenges/make_cifar10_joblib.py cleverhans/model_zoo/__init__.py cleverhans/plot/success_fail.py cleverhans/attacks/momentum_iterative_method.py cleverhans/utils_keras_tf.py ocr.py cleverhans/loss.py util.py cleverhans/train.py cleverhans/utils_tfe.py cleverhans/attacks_tfe.py cleverhans/experimental/certification/tests/dual_formulation_test.py cleverhans/utils_pytorch.py cleverhans/experimental/certification/nn.py cleverhans/plot/__init__.py cleverhans/serial.py cleverhans/attacks/max_confidence.py cleverhans/model_zoo/all_convolutional.py cleverhans/model_zoo/deep_k_nearest_neighbors/dknn.py cleverhans/attacks/projected_gradient_descent.py cleverhans/utils_tf.py cleverhans/devtools/mocks.py cleverhans/attacks/saliency_map_method.py cleverhans/model.py cleverhans/attacks/fast_feature_adversaries.py cleverhans/plot/pyplot_defaults.py remove.py cleverhans/experimental/certification/tests/utils_test.py show invert transpose cvt2raw filter_word show invert transpose gen_wm RGB2Hex cvt2raw get_text_mask cvt2rgb dumpRotateImage sort_box model charRec get_line show invert transpose extend preprocess cvt2raw attack find_new_word SaltAndPepper contrast_brightness_image clearNoise getPixel cvt2Image save gen_watermark_color gen_text clip show sparse_tuple_from dense_to_sparse eval_asr transpose gen_wm eval_distortion predict addGaussianNoise plot attach_img rotate_whole_img cvt2raw load_similar scale get_argparse cvt4 invert trans_back gen_watermark mul model_train div clip_by_value assert_less_equal infer_devices dense_to_sparse assert_greater_equal tf_model_load clip_eta kl_with_logits model_loss get_available_gpus jacobian_graph l2_batch_normalize model_argmax assert_equal initialize_uninitialized_global_variables model_eval batch_eval op_with_scalar_cast jacobian_augmentation train silence find_wm_pos gen_wm RGB2Hex get_text_mask cvt2rgb show invert transpose cvt2raw filter_word jacobian UnrolledGradientDescent saliency_map pgd_attack apply_perturbations UnrolledOptimizer fgsm UnrolledAdam fgm Attack FastGradientMethod BasicIterativeMethod fixed_max_confidence_recipe unfinished_attack_configs bundle_examples_with_goal bundle_attacks Misclassify single_run_max_confidence_recipe AttackConfig _WrongConfidenceFactory run_batch_with_goal _ExtraCriteriaFactory basic_max_confidence_recipe MaxConfidence save random_search_max_confidence_recipe spsa_max_confidence_recipe bundle_attacks_with_goal AttackGoal _CriteriaFactory batch_augment random_crop_and_flip random_shift run_canary softmax_cross_entropy_with_logits _wrap reduce_function make_confidence_report make_confidence_report_bundled ConfidenceReport ConfidenceReportEntry print_stats MNIST HWDB Factory data_mnist data_cifar10 CIFAR10 maybe_download_file data_hwdb Dataset download_and_parse_mnist_file _AttackFactory class_and_confidence correctness_and_confidence _check_x batch_eval batch_eval_multi_worker accuracy _CorrectFactory _CorrectAndProbFactory _ClassAndProbFactory run_attack _check_y HeReLuNormalInitializer LossMixUp WeightedSum SNNLCrossEntropy MixUp Loss CrossEntropy FeaturePairing WeightDecay LossCrossEntropy LossFeaturePairing wrapper_warning_logits CallableModelWrapper Model NoSuchLayerError wrapper_warning ResidualWithGroupNorm Softmax Sigmoid TanH GroupNorm ReLU Flatten Add Layer Dropout BatchNorm LeakyReLU PicklableModel GlobalAveragePool MLP ELU Tanh PerImageStandardize ResidualWithBatchNorm Linear Conv2D Print SELU PicklableVariable load NoRefModel save train avg_grads get_log_level safe_zip ordered_union to_categorical grid_visual deep_copy create_logger get_logits_over_interval deterministic_dict TemporaryLogLevel set_log_level random_targets pair_visual batch_indices other_classes shell_call AccuracyReport linear_extrapolation_plot _ArgsWrapper KerasModelWrapper cnn_model conv_2d KerasModelWrapper cnn_model conv_2d data_mnist download_and_parse_mnist_file maybe_download_mnist_file convert_pytorch_model_to_tf _py_func_with_gradient mul model_train div clip_by_value assert_less_equal infer_devices dense_to_sparse assert_greater_equal tf_model_load clip_eta kl_with_logits model_loss get_available_gpus jacobian_graph l2_batch_normalize model_argmax assert_equal initialize_uninitialized_global_variables model_eval batch_eval op_with_scalar_cast jacobian_augmentation train silence model_eval train model_argmax Attack arg_type BasicIterativeMethod CWL2 ZERO CarliniWagnerL2 CWL2 ZERO CarliniWagnerL2 CWL2 ZERO CarliniWagnerL2 deepfool_attack deepfool_batch DeepFool ElasticNetMethod ZERO EAD FastFeatureAdversaries optimize_linear_pos FastGradientMethod fgm optimize_linear LBFGS LBFGS_impl MadryEtAl MaxConfidence MomentumIterativeMethod MomentumIterativeMethod2 Noise ProjectedGradientDescent jsma_batch SaliencyMapMethod jsma_symbolic Semantic SpatialTransformationMethod TensorOptimizer spm TensorGradientDescent projected_optimization margin_logit_loss _apply_transformation _project_perturbation SPSAAdam _apply_black_border TensorAdam SPSA parallel_apply_transformations vatm VirtualAdversarialMethod CleverHansTest list_files _list_files SimpleDataset random_feed_dict dev_version append_dev_version update_whitelist test_format_pep8 main DualFormulation NeuralNetwork load_network_from_checkpoint Optimization lanczos_decomp initialize_dual eigen_tridiagonal eig_one_step diag minimum_eigen_vector DualFormulationTest NeuralNetworkTest OptimizationTest UtilsTest ModelAllConvolutional ModelHWCNN ModelChiOCR ModelOCRCNN ModelBasicCNN LSTMOCR DkNNModel plot_reliability_diagram main make_basic_picklable_cnn dknn_tutorial _stride_arr _relu Softmax make_wresnet ResNet _decay Linear Flatten _batch_norm _conv _residual Conv2D Input _global_avg_pool Layer main ModelBasicCNN main SNNL_example show as_pil make_grid save get_logits_over_interval pair_visual linear_extrapolation_plot grid_visual save_pdf plot_report_from_path make_curve plot_report append enumerate GeneratorFromStrings ones invert list shape sorted int radians warpAffine list fabs cos getRotationMatrix2D dot sin array dumpRotateImage int keras_densenet convert degrees atan2 enumerate dumpRotateImage int convert degrees atan2 cfg_from_file text_detect sort_box charRec reshape zero_padding zip upper istitle choice abs range set_title set_xlabel grid add_subplot set_ylabel twinx figure legend savefig format astype asarray len extend zip range enumerate getpixel getPixel range Draw point fromarray int ANTIALIAS reshape astype float32 resize array shape dtype zeros addWeighted int range randint int range randint join truetype Draw text new imshow save array open int truetype join Draw text new imshow save open array len int truetype join Draw text new imshow save open array len truetype Draw text new rotate reshape getRotationMatrix2D warpAffine add_argument ArgumentParser softmax_cross_entropy_with_logits inputs op warn reduce_mean variables_initializer len global_variables run RandomState warn AdamOptimizer fprop _ArgsWrapper argmax equal _ArgsWrapper warn update run minimum get_shape list maximum reduce_sum square sqrt div clip_by_value xrange len RandomState minimize warn model_loss AdamOptimizer _ArgsWrapper get_available_gpus warn list_local_devices cast_clip is_scalar dtype cast append xrange gradients update get_shape list min vstack zip range RETR_TREE uint8 CHAIN_APPROX_SIMPLE ones findContours min astype hstack rectangle cvt2raw erode dilate remove_small_objects abs max append warn inputs warn minimum maximum warn argmax int list fill_diagonal discard reshape warn set abs max range len update reshape warn other_classes zeros sum enumerate run warn to_float str one_hot ones bundle_attacks ProjectedGradientDescent copy AttackConfig int32 Noise range append to_float str one_hot ones bundle_attacks ProjectedGradientDescent copy AttackConfig int32 Noise range append to_float str one_hot ones bundle_attacks ProjectedGradientDescent copy AttackConfig int32 Noise range append Noise bundle_attacks AttackConfig str correctness_and_confidence copy ConfidenceReport mean ConfidenceReportEntry info zeros bundle_attacks_with_goal str get_criteria start mean run_batch_with_goal save info request_examples time hasattr get_criteria params print_progress attack new_wins ConfidenceReportEntry save get_attack_config run_attack enumerate print print_stats str min mean info append str zeros_like astype ConfidenceReport mean new_wins ConfidenceReportEntry info save range len to_float str one_hot ones bundle_attacks copy AttackConfig int32 append SPSA range pad Graph time warn op_func stop_gradient softmax_cross_entropy_with_logits_v2 f hasattr get_set run_recipe set_log_level getattr factory max_val callable dataset_factory Session INFO mean sum print maximum Semantic time correctness_and_confidence get_set run_attack print set_log_level set_random_seed ConfidenceReport MaxConfidence ConfidenceReportEntry save print_stats dataset_factory factory Session INFO join urlretrieve gettempdir isfile maybe_download_file join open expand_dims to_categorical download_and_parse_mnist_file print reshape to_categorical astype shape load_data join get_image_names_labels get_images charset_size to_categorical _check_x _CorrectFactory batch_eval_multi_worker _check_y _check_x min batch_eval_multi_worker _ClassAndProbFactory append max _check_y _check_x min batch_eval_multi_worker _CorrectAndProbFactory max _check_y _AttackFactory _check_x batch_eval_multi_worker _check_y infer_devices int str update debug extend ceil run_canary run zip append float range enumerate len update str debug dict run zip append range len split warn warn dump batch_size randint get_next avg_grads xrange run infer_devices str list ema_decay placeholder append ceil range update shuffle initialize_uninitialized_global_variables info float nb_epochs int time evaluate print run_canary int32 ExponentialMovingAverage global_variables_initializer callable len append add_n zip len int list range remove zeros ravel warn sum to_categorical astype choice other_classes shape int32 xrange zeros argmax warn warn warn warn setLevel setFormatter getLogger addHandler StreamHandler Formatter DEBUG setLevel OrderedDict sorted keys append len join list debug group match range compile len copy Sequential model Activation add join warn warn MNIST warn get_default_graph getrandbits out_features gradient assign Saver save apply_gradients filename eager train_dir batch_indices zip get_params join Variable int str batch_size Variable debug min get_probs range assign generate ceil zeros float eager len Variable get_probs eager append tuple dtype as_np_dtype deepfool_attack sum norm clip inf debug squeeze model_argmax copy flatten shape info zeros abs array range run to_float dtype stop_gradient dense_to_sparse softmax_cross_entropy_with_logits optimize_linear gradients assert_greater_equal ctc_loss reduce_max reduce_sum cast assert_less_equal clip_by_value append equal to_float get_shape list mul reduce_max equal maximum reduce_sum square sign sqrt stop_gradient abs range len to_float get_shape list minimum mul reduce_max equal maximum reduce_sum square sign sqrt stop_gradient abs range len int value fill_diagonal constant ones reshape while_loop float32 warn cast int32 floor bool to_float one_hot reduce_max reduce_sum warn resize_images convert_to_tensor min astype rotate translate sqrt pad int32 float to_float list product reduce_max parallel_apply_transformations reduce_sum choice map_fn stack gather_nd linspace zip stop_gradient get_probs argmax equal einsum convert_to_tensor reshape map_fn _apply_black_border tile dtype init_state nest while_loop flatten shape project_perturbation cast assert_less_equal random_uniform no_op join isdir _list_files abspath pardir endswith listdir append isdir astype md5 update sorted list_files dev_version extend join relpath append shell_call pardir str time adv_class num_classes sizes reshape print verbosity model_json load_network_from_checkpoint set_verbosity input_shapes info initialize_dual init_dual_file output_shapes range checkpoint get_tensor load_checkpoint transpose reshape append keys get_variable_to_shape_map str num_hidden_layers astype float32 item append range get_variable norm constant slice reshape concat vector_prod_fn reduce_sum scalar_mul random_uniform zeros range abs argmax argmin eigh_tridiagonal norm reshape transpose square matmul vector_prod_fn reduce_sum eig_one_step range l2_normalize MLP subplots tick_params argmax max str multiply set_xlabel shape bar twinx savefig append sum plot tight_layout mean zip xlim print set_ylabel set_ylim MNIST get_set debug get_shape append trainable_variables l2_loss ResNet checkpoint_dir latest_checkpoint exit set_log_level DEBUG Session do_eval gradients imscatter SNNLCrossEntropy set_random_seed sign CrossEntropy DEBUG SNNL_factor Session run str placeholder set_log_level title savefig fit_transform get_logits RandomState ModelBasicCNN get_set MNIST AccuracyReport reshape float32 fprop figure train SNNL_example mkstemp close shell_call save fromarray dtype min issubdtype max floating int concatenate shape sqrt ceil zeros float split show squeeze pause add_subplot axis set_window_title imshow figure ion enumerate ioff show add_subplot axis set_window_title imshow figure range get_logits l2_normalize reshape float lin_space placeholder expand_dims generate FastGradientMethod show use plot xlabel ylabel set_window_title clf savefig figure linspace legend xlim argmax range gcf PdfPages close savefig load plot_report max plot concatenate make_curve xlabel print ylabel get_color array str sorted isinstance warn confidence correctness append float len | strongman1995/Fast-Adversarial-Watermark-Attack-on-OCR | 3,747 |
stupidZZ/FCN_Text | ['scene text detection'] | ['Multi-Oriented Text Detection with Fully Convolutional Networks'] | ProposalGeneration/getMser.py TextRegionFCN_Caffe/CAFFE/solve.py computeMSER max MSER BoxPoints reshape min int0 minAreaRect detect zeros array range len | stupidZZ/FCN_Text | 3,748 |
stwisdom/urnn | ['sequential image classification'] | ['Full-Capacity Unitary Recurrent Neural Networks'] | memory_problem.py custom_layers.py recon_timitpred.py mnist.py util.py custom_optimizers.py models.py optimizations.py fftconv.py timit_prediction.py download_and_unzip_matlab_code.py RMSprop_and_natGrad CuIFFTOp sc_complex_dot_batched bptrs BatchedComplexDotOp CuFFTOp to_complex_gpuarray conv2d_fft ScikitsCudaOp mult_and_reduce conv3d_fft main LossHistory times_reflection complex_RNN compute_cost_t initialize_data_nodes initialize_matrix_np initialize_matrix times_unitary do_fft do_ifft LSTM initialize_unitary times_reflection_sub vec_permutation tanhRNN initialize_complex_RNN_layer IRNN times_diag rms_prop gradient_descent_momentum clipped_gradients gradient_descent GPUArray complex64 copy ndim range bptrs gpudata _global_cublas_handle complex64 shape lower cublasCgemmBatched max shape batched_complex_dot reshape dimshuffle set_subtensor reshape shape eq cufft cast mult_and_reduce zeros cuifft mod set_subtensor reshape ifelse shape eq cufft cast mult_and_reduce zeros cuifft getopt permutation to_categorical Sequential LossHistory RMSprop_and_natGrad Activation exists open iteritems ModelCheckpoint exit add shape update dump RandomState astype test_on_batch uRNN Dense load_weights compile load read evaluate print reshape EarlyStopping fit load_data LSTM complex_RNN_wrapper makedirs asarray concatenate float32 sqrt uniform sqrt uniform asarray reshape cufft sqrt dimshuffle cuifft reshape sqrt dimshuffle dimshuffle concatenate dot inc_subtensor sum outer dot inc_subtensor sum outer categorical_crossentropy clip dimshuffle float32 sigmoid mean sqrt softmax shared sum binary_crossentropy seed compute_cost_t RandomState initialize_data_nodes dimshuffle initialize_matrix identity scan mean dot tile shared zeros seed compute_cost_t RandomState initialize_data_nodes dimshuffle initialize_matrix scan mean dot tile shared zeros cos scan seed dimshuffle ones sin shared sum RandomState concatenate mean sqrt softmax tile compute_cost_t initialize_data_nodes initialize_matrix float32 dot zeros asarray permutation times_unitary initialize_matrix concatenate astype float32 uniform shared asarray floatX initialize_unitary astype sqrt uniform shared times_reflection do_fft do_ifft dot vec_permutation times_diag times_unitary cos scan seed dimshuffle sin shared sum initialize_complex_RNN_layer range asarray RandomState concatenate astype mean sqrt softmax tile compute_cost_t initialize_data_nodes initialize_matrix initialize_unitary float32 dot zeros len range zip | stwisdom/urnn | 3,749 |
subhc/SPNet | ['few shot learning', 'semantic segmentation'] | ['Semantic Projection Network for Zero- and Few-Label Semantic Segmentation'] | train.py libs/caffe_pb2.py libs/models/deeplabv3plus.py libs/models/__init__.py libs/models/deeplabv2.py eval.py libs/models/deeplabv3.py libs/utils/__init__.py libs/utils/metric2.py libs/datasets/__init__.py libs/utils/loss.py libs/models/resnet.py convert.py libs/utils/metric.py libs/datasets/cocostuff.py libs/models/msc.py libs/utils/crf.py main parse_caffemodel translate_layer_name main get_params poly_lr_scheduler resize_target main RandomImageSampler get_parent_class CocoStuff164k _CocoStuff LoaderZLS CocoStuff10k get_dataset _ASPPModule DeepLabV2 DeepLabV3 _ASPPModule DeepLabV3Plus MSC _Bottleneck _ResBlock _ConvBatchNormReLU DeepLabV3Plus_ResNet101_MSC DeepLabV2S_ResNet101_MSC init_weights DeepLabV2_ResNet101_MSC DeepLabV3_ResNet101_MSC dense_crf CrossEntropyLoss2d _fast_hist scores _fast_hist scores_gzsl scores data list format NetParameter eps isinstance blobs print name dilation OrderedDict moving_average_fraction type array layer len layer_block_branch replace split get items list parse_caffemodel isinstance print translate_layer_name FloatTensor OrderedDict ljust eval DeepLabV2_ResNet101_MSC save view_as state_dict genfromtxt model set_grad_enabled DataLoader DataParallel interpolate device argmax cuda open str view dense_crf transpose exit shape dirname load_state_dict append to current_device Dict range asarray scores replace concatenate astype softmax zip enumerate load join get_device_name uint8 scores_gzsl tqdm zeros numpy array len named_modules parameters isinstance Conv2d float int32 resize zeros numpy enumerate INIT_MODEL zero_grad OPTIMIZER abspath copy2 currentframe ITER_MAX strftime add iter poly_lr_scheduler set_postfix next copytree CrossEntropyLoss SummaryWriter format LR param_groups add_histogram size DeepLab grad copy train requires_grad getargvalues MovingAverageValueMeter backward add_scalar named_parameters freeze_bn isfile resize_target RandomImageSampler step ITER_SIZE makedirs items list isinstance isinstance Conv2d bias kaiming_normal_ modules BatchNorm2d weight constant_ Linear addPairwiseGaussian DenseCRF2D reshape addPairwiseBilateral ascontiguousarray inference unary_from_softmax setUnaryEnergy reshape list range nanmean dict zip zeros sum diag zeros zip | subhc/SPNet | 3,750 |
sudatta0993/Dynamic-Congestion-Prediction | ['video captioning'] | ['Top-down Visual Saliency Guided by Captions'] | src/main/python/model_test/generate_demand.py src/main/python/model_test/generate_io_curves.py src/main/python/graph_cnn_lib/models.py src/test/python/model_test/test_read_json.py src/main/python/model_test/calculate_link_demand_and_congestion.py src/test/python/model_test/test_dynamic_control_comparison.py src/test/python/model_test/test_run_scenarios.py src/main/python/model_test/plot_curves.py src/main/python/graph_cnn_lib/graph.py src/main/python/bay_area_simplified_freeway_network/generate_trajectory_clustering_adjacency.py src/main/python/bay_area_simplified_freeway_network/generate_shortest_path_adjacency.py src/test/python/model_test/test_simple_h_w_demand_func.py src/main/python/1NN.py src/main/python/lstm.py src/main/python/graph_cnn_lstm.py src/main/python/model_test/generate_model_data.py src/test/python/model_test/test_dynamic_control.py src/main/python/model_test/run_scenarios.py src/main/python/graph_cnn_lib/coarsening.py src/main/python/model_test/queue_spillover.py src/main/python/random_forest.py src/main/python/bay_area_simplified_freeway_network/generate_model_data.py src/main/python/model_test/route_choice.py rmse plot_loss_vs_iter plot_comparison get_train_val_data get_cnn_graph_input get_input_features_batch spatial_attention plot_comparison temporal_attention get_LSTM_training_output define_loss_and_optimizer get_LSTM_training_input plot_loss_vs_iter temporal_attention_pred add_input_features_first_diff get_input_features_data LSTM plot_spatial_attention plot_temporal_attention plot_data_first_few_days get_input_data get_output_data rmse get_input_features_data write_csv get_header get_congestion get_link_counts get_arrival_counts get_od_counts run node_graph write_csv shortest_path_adjacency add_sp_edges shortest_path_graph run create_route_adjacency calculate_prob_dist write_csv get_W_sp cluster_trajectories calculate_OD_adjacency calculate_OD_cluster_prob_dist dtw get_trips run perm_adjacency compute_perm coarsen perm_data metis_one_level metis plot_spectrum grid distance_lshforest replace_random_edges lmax adjacency laplacian distance_sklearn_metrics lanczos rescale_L chebyshev fourier distance_scipy_spatial temporal_attention base_model cnn_lstm temporal_attention_pred LSTM plot_spatial_attention plot_temporal_attention spatial_attention get_link_demand get_congestion_marginal_impact get_cumulative_congestion_value nn_smoothen get_link_congestion no_demand simple_h_w_demand_func generate_initial_demand get_total_toll_collected get_links_output_curve get_congestion_links_input_curve_from_demand get_freeway_links_input_curve_after_diverging get_congestion_links_input_curve_after_toll get_congestion_links_input_curve_after_merging get_header write_csv plot_fundamental_diagrams plot_demand_congestion plot_io_curves check_queue_spillover update_alternate_route_io_curves find_route_switch_indices check_route_choice calculate_cumulative_diverted_curve update_best_route_io_curves find_best_route_tts Parameters run test_run_scenarios test_run_scenarios test_read_json test_run_scenarios test_simple_h_w_demand_func show arange plot xlabel ylabel legend show arange plot xlabel ylabel int delete copy as_matrix append head range len plot_spectrum adjacency nnz show str csr_matrix perm_data range fill_diagonal format astype copy T print loadtxt sort coarsen float32 spy distance_scipy_spatial len show twinx subplots plot reduce_mean minimize reduce_sum squared_difference dynamic_rnn MultiRNNCell BasicLSTMCell transpose matmul bias_add append bias_add range matmul str print mean sqrt append sum range str print dot mean sqrt zeros sum range zeros range append as_matrix get_input_features_batch randn concat copy mean add_input_features_first_diff append range len reshape get_input_features_data reshape flatten as_matrix zeros range show str atleast_2d xlabel colorbar imshow title set_visible show str xlabel ylabel colorbar imshow title int int flatten zeros range len zeros range int len zeros transpose range len zeros transpose range len zeros range len average zeros range len append str range len str get_congestion get_link_counts get_arrival_counts get_od_counts randint sep range zeros len run DiGraph int add_node open int add_weighted_edges_from open float add_node node_graph add_sp_edges zeros all_pairs_dijkstra_path_length range close shortest_path_adjacency write_csv shortest_path_graph loadtxt hstack vstack len zeros min inf range KMeans predict fit sum values int range list norm fill_diagonal subtract keys full create_route_adjacency get_W_sp print cluster_trajectories calculate_OD_adjacency calculate_OD_cluster_prob_dist get_trips setdiag perm_adjacency tocsr format tocoo eliminate_zeros print compute_perm shape nnz metis enumerate list permutation csr_matrix eliminate_zeros squeeze argsort shape diagonal metis_one_level append sum max range find zeros bool range int32 list extend append max range enumerate len len shape zeros empty enumerate tocoo hstack argsort shape coo_matrix vstack len meshgrid reshape empty linspace sort pdist squareform sort pairwise_distances kneighbors LSHForest fit exp setdiag reshape multiply mean shape repeat coo_matrix int setdiag tocsr tolil eliminate_zeros shape uniform zip randint triu nnz squeeze size identity sqrt sum diags toarray eigs sort eig eigh eigsh show list format plot ylim figure legend xlim fourier range enumerate dtype diag_H dot shape basis empty range shape identity dtype dot shape empty range average range len append nn_smoothen range append float nn_smoothen range append float nn_smoothen range range append no_demand simple_h_w_demand_func range append Series DataFrame range count_nonzero int str plot_io_curves DataFrame Series min copy float argmax max range diff zeros sum range Series copy zeros DataFrame range DataFrame range values range copy DataFrame fillna values columns str plot xlabel len close ylabel savefig congestion_links_length freeway_links_length float range file_directory subplots arange plot set_xlabel close set_ylabel twinx dirname legend savefig makedirs subplots arange plot set_xlabel makedirs close set_ylabel twinx dirname legend savefig range set_ylim len columns print min copy apply any range fillna len array next range zeros range DataFrame range range enumerate update_alternate_route_io_curves find_route_switch_indices print calculate_cumulative_diverted_curve update_best_route_io_curves find_best_route_tts max get_links_output_curve plot_congestion_io_curves plot_demand_congestion plot_demand_congestion_curves plot_demand_congestion_marginal_impact_curves get_congestion_links_input_curve_after_toll toll_curves generate_initial_demand get_total_toll_collected num_bins get_congestion_links_input_curve_from_demand get_freeway_links_input_curve_after_diverging check_queue_spillover plot_fundamental_diagrams num_zones get_congestion_marginal_impact check_route_choice implement_toll get_cumulative_congestion_value copy min_intervals get_congestion_links_input_curve_after_merging file_directory incident_prob plot_io_curves min makedirs get_curves_data get_link_congestion plot_route_choice_io_curves | # Dynamic-Congestion-Prediction This code is the repository for implementing algorithms for real-time prediction of macroscopic congestion from network state variables using Deep Learning. The corresponding work is detailed in the following papers: * Sudatta Mohanty, Michael Cassidy, Alexey Pozdnukhov, *Real-Time Macroscopic Congestion Prediction Using Deep Learning*, Transportation Research Part c, 2017 (in preparation) * Sudatta Mohanty, Alexey Pozdnukhov, *GCN-LSTM Framework For Real-Time Macroscopic Congestion Prediction*, Bay Area Machine Learning Symposium (BayLearn), 2017 (accepted) There is implementation of Graph Convolutional Network (GCN) based on the opensource codebase corresponding to: * Michaรซl Defferrard, Xavier Bresson, Pierre Vandergheynst, [Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering](https://arxiv.org/abs/1606.09375), Neural Information Processing Systems (NIPS), 2016. The Neural Attention Framework used is based on the concepts discussed in: * Vasili Ramanishka, Abir Das, Jianming Zhang, and Kate Saenko, [Top-down Visual Saliency Guided by Captions](https://arxiv.org/abs/1612.07360), Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 3,751 |
sudy/coling2018 | ['information retrieval', 'stock market prediction'] | ['Learning Target-Specific Representations of Financial News Documents For Cumulative Abnormal Return Prediction'] | ignite/metrics/categorical_accuracy.py ignite/contrib/metrics/regression/__init__.py ignite/metrics/epoch_metric.py torchtext/datasets/imdb.py torchtext/data/utils.py ignite/contrib/handlers/__init__.py abrt_code/transformer.py abrt_code/utils.py abrt_code/microf1.py ignite/contrib/metrics/regression/mean_error.py ignite/handlers/terminate_on_nan.py ignite/contrib/metrics/roc_auc.py ignite/contrib/metrics/average_precision.py ignite/_utils.py ignite/contrib/handlers/param_scheduler.py abrt_code/main.py ignite/metrics/mean_pairwise_distance.py ignite/metrics/metrics_lambda.py torchtext/vocab.py stance_code/new_model.py torchtext/data/field.py ignite/contrib/metrics/__init__.py torchtext/data/example.py ignite/contrib/metrics/regression/maximum_absolute_error.py abrt_code/NestNestedField.py ignite/metrics/accuracy.py ignite/handlers/early_stopping.py torchtext/data/batch.py ignite/contrib/handlers/tqdm_logger.py torchtext/data/iterator.py ignite/_six.py torchtext/datasets/nli.py ignite/metrics/mean_squared_error.py torchtext/utils.py torchtext/data/dataset.py ignite/contrib/metrics/regression/manhattan_distance.py torchtext/datasets/sequence_tagging.py ignite/contrib/metrics/regression/mean_normalized_bias.py ignite/engine/engine.py ignite/engines/__init__.py torchtext/datasets/snli.py ignite/metrics/top_k_categorical_accuracy.py ignite/handlers/timing.py stance_code/utils.py stance_code/baselines.py torchtext/data/__init__.py ignite/metrics/root_mean_squared_error.py torchtext/datasets/__init__.py ignite/metrics/recall.py ignite/exceptions.py ignite/engine/__init__.py ignite/contrib/metrics/regression/fractional_bias.py stance_code/main.py torchtext/__init__.py torchtext/datasets/translation.py stance_code/model.py abrt_code/auc.py ignite/handlers/checkpoint.py ignite/handlers/__init__.py abrt_code/baselines.py ignite/metrics/mean_absolute_error.py stance_code/transformer.py ignite/metrics/binary_accuracy.py torchtext/data/pipeline.py ignite/contrib/metrics/regression/mean_absolute_relative_error.py torchtext/datasets/trec.py ignite/metrics/loss.py ignite/__init__.py torchtext/datasets/babi.py ignite/contrib/engines/__init__.py ignite/contrib/engines/tbptt.py ignite/metrics/metric.py ignite/metrics/__init__.py abrt_code/new_model.py torchtext/datasets/language_modeling.py ignite/metrics/running_average.py ignite/engines/engine.py stance_code/base_model.py abrt_code/model.py ignite/metrics/precision.py torchtext/datasets/sst.py AUC HNetwork SequentialRepr AttNet Attention BaseHNetwork get_model_name evaluate init_logger load_dataset parse_args get_model run_test run Microf1 TargetedHNetwork NestNestedField TransEncoder PositionalEncoding PositionwiseFeedForward make_model clones LayerNorm Encoder MultiHeadedAttention SublayerConnection attention EncoderLayer softmax_with_mask sequence_mask MyVectors BatchNorm Bottle NotComputableError with_metaclass apply_to_tensor _to_hours_mins_secs apply_to_type convert_tensor to_onehot create_supervised_tbptt_trainer _detach_hidden Tbptt_Events ConcatScheduler CosineAnnealingScheduler CyclicalScheduler ParamScheduler LinearCyclicalScheduler ProgressBar AveragePrecision average_precision_compute_fn ROC_AUC roc_auc_compute_fn FractionalBias ManhattanDistance MaximumAbsoluteError MeanAbsoluteRelativeError MeanError MeanNormalizedBias Events State Engine create_supervised_trainer create_supervised_evaluator _prepare_batch Events State Engine create_supervised_trainer create_supervised_evaluator _prepare_batch ModelCheckpoint EarlyStopping TerminateOnNan Timer Accuracy BinaryAccuracy CategoricalAccuracy EpochMetric Loss MeanAbsoluteError MeanPairwiseDistance MeanSquaredError Metric MetricsLambda Precision Recall RootMeanSquaredError RunningAverage TopKCategoricalAccuracy HNetwork HLNetwork BaseNetwork TargetedHNetwork AttNet ConditionEncode Attention CNNText SequentialRepr BaseRepr get_model_name evaluate init_logger load_dataset parse_args get_model run_test run TargetedHNetwork SequentialRepr BaseHNetwork AttNet HNEncoder TCEncoder TransEncoder PositionalEncoding PositionwiseFeedForward make_model clones LayerNorm Encoder MultiHeadedAttention SublayerConnection attention EncoderLayer softmax_with_mask sequence_mask reporthook unicode_csv_reader utf_8_encoder download_from_url Vectors FastText SubwordVocab _infer_shape Vocab GloVe _default_unk_index CharNGram _short_str Batch rationed_split TabularDataset stratify check_split_ratio Dataset Example NestedField ReversibleField LabelField Field SubwordField RawField pool BPTTIterator BucketIterator batch Iterator Pipeline is_tokenizer_serializable get_torch_version RandomShuffler get_tokenizer dtype_to_attr _spacy_tokenize interleave_keys _split_tokenizer BABI20 BABI20Field IMDB PennTreebank LanguageModelingDataset WikiText2 WikiText103 NLIDataset SNLI ParsedTextField MultiNLI ShiftReduceField CoNLL2000Chunking UDPOS SequenceTaggingDataset ParsedTextField SNLI ShiftReduceField SST WMT14 TranslationDataset Multi30k IWSLT TREC add_argument ArgumentParser setFormatter getLogger addHandler StreamHandler Formatter setLevel INFO model vocab NestNestedField splits len NestedField Field build_vocab get metrics run load format evaluate warning load_state_dict info create_supervised_trainer COMPLETED save device create_supervised_evaluator seed argv Adam init_logger load_dataset add_event_handler nll_loss resume manual_seed info setattr run_test join get_model_name EarlyStopping parameters ModelCheckpoint get_model dropout size transpose matmul masked_fill softmax deepcopy PositionwiseFeedForward Encoder xavier_uniform_ parameters c MultiHeadedAttention EncoderLayer unsqueeze max masked_fill softmax divmod Mapping isinstance Sequence zeros size to Engine register_events numpy activation numpy activation to items list Engine to attach to_variable GloVe split warn from_pretrained get items list print startswith process_response Session utf_8_encoder reader PY2 len seek split join format hasattr isinstance getattr typename sum isinstance len append set int list tuple round rnd range len append len batch_size_fn list shuffle batch random_shuffler load MosesTokenizer ToktokTokenizer callable __version__ split split | sudy/coling2018 | 3,752 |
sueqian6/ACL2019-Reducing-Gender-Bias-in-Word-Level-Language-Models-Using-A-Gender-Equalizing-Loss-Function | ['data augmentation', 'text generation'] | ['Reducing Gender Bias in Word-Level Language Models with a Gender-Equalizing Loss Function'] | Language Models/model_embedding_reg/model.py Language Models/generate.py Language Models/training_cda.py Language Models/preprocess.py Language Models/model.py Language Models/model_embedding_reg/training.py Language Models/model_embedding_reg/data_v3.py Language Models/model_embedding_reg/generate_reg.py Language Models/training_L2reg.py Language Models/data_v3.py Language Models/training.py Language Models/model_embedding_reg/preprocess.py Dictionary Corpus generateData generateFile RNNModel read_preprocessed_file encode_sentences load_preprocesed_dataset save_worker read_preprocessed_file_as_str preprocess_dataset preprocess_worker parse_arguments preprocess_file transform_token read_vocab is_valid_token write_preprocessed_file repackage_hidden get_batch evaluate getGenderIdx load_doc Custom_Loss train batchify repackage_hidden get_batch evaluate getGenderIdx load_doc Custom_Loss train batchify repackage_hidden get_batch evaluate getGenderIdx load_doc Custom_Loss train batchify Dictionary Corpus generateData generateFile RNNModel read_preprocessed_file encode_sentences load_preprocesed_dataset save_worker read_preprocessed_file_as_str preprocess_dataset preprocess_worker parse_arguments preprocess_file transform_token read_vocab is_valid_token write_preprocessed_file repackage_hidden load_glove_to_dict get_batch evaluate glove_dict_to_tensor bias_regularization_encoder bias_regularization_decoder train batchify to init_hidden str format print eval generateFile documents range text set add transform_token append split c_uint pack_into sizeof create_string_buffer sum enumerate len append append iter_unpack iter_unpack read_vocab join listdir enumerate join format basename replace splitext preprocess_file encode_sentences write_preprocessed_file fit_on_texts abspath Pool list sorted append walk Tokenizer format insert close imap_unordered splitext enumerate join items print makedirs len add_argument ArgumentParser size narrow contiguous Tensor isinstance bptt view Variable min len eval init_hidden repackage_hidden data batch_size model add_ zero_grad clip exp bptt range format get_batch size item clip_grad_norm enumerate time log_interval criterion backward print parameters init_hidden len read close open split print sum alpha print update set cuda dictionary len append float range split FloatTensor len bias_regularization_encoder bias_reg_encoder view bias_reg_en_factor dictionary bias_reg_decoder bias_reg_var_ratio bias_reg_de_factor bias_regularization_decoder svd sum norm view cumsum min append weight range cat svd sum norm view cumsum min append weight range cat | # Reducing-Gender-Bias-in-Language-Models ## Introduction This is a project for DS-GA 1012 Natural Language Understanding and Computational Semantics at New York University. Our purpose is to reduce gender bias in language models. It has been accepted to appear at ACL2019 student research workshop. We have also been invited to present at the 1st workshop on gender bias in NLP at ACL2019. Paper link: https://arxiv.org/abs/1905.12801 ## Dataset The dataset we use is Daily Mails. https://cs.nyu.edu/~kcho/DMQA/ We use 5% of the whole dataset. The subsample can be found in Data/Sample Stories. ## Authors * **Yusu Qian** * * **Urwa Muaz** * | 3,753 |
sueqian6/Reducing-Gender-Bias-in-Word-Level-Language-Models-Using-A-Gender-Equalizing-Loss-Function | ['data augmentation', 'text generation'] | ['Reducing Gender Bias in Word-Level Language Models with a Gender-Equalizing Loss Function'] | Language Models/model_embedding_reg/model.py Language Models/generate.py Language Models/training_cda.py Language Models/preprocess.py Language Models/model.py Language Models/model_embedding_reg/training.py Language Models/model_embedding_reg/data_v3.py Language Models/model_embedding_reg/generate_reg.py Language Models/training_L2reg.py Language Models/data_v3.py Language Models/training.py Language Models/model_embedding_reg/preprocess.py Dictionary Corpus generateData generateFile RNNModel read_preprocessed_file encode_sentences load_preprocesed_dataset save_worker read_preprocessed_file_as_str preprocess_dataset preprocess_worker parse_arguments preprocess_file transform_token read_vocab is_valid_token write_preprocessed_file repackage_hidden get_batch evaluate getGenderIdx load_doc Custom_Loss train batchify repackage_hidden get_batch evaluate getGenderIdx load_doc Custom_Loss train batchify repackage_hidden get_batch evaluate getGenderIdx load_doc Custom_Loss train batchify Dictionary Corpus generateData generateFile RNNModel read_preprocessed_file encode_sentences load_preprocesed_dataset save_worker read_preprocessed_file_as_str preprocess_dataset preprocess_worker parse_arguments preprocess_file transform_token read_vocab is_valid_token write_preprocessed_file repackage_hidden load_glove_to_dict get_batch evaluate glove_dict_to_tensor bias_regularization_encoder bias_regularization_decoder train batchify to init_hidden str format print eval generateFile documents range text set add transform_token append split c_uint pack_into sizeof create_string_buffer sum enumerate len append append iter_unpack iter_unpack read_vocab join listdir enumerate join format basename replace splitext preprocess_file encode_sentences write_preprocessed_file fit_on_texts abspath Pool list sorted append walk Tokenizer format insert close imap_unordered splitext enumerate join items print makedirs len add_argument ArgumentParser size narrow contiguous Tensor isinstance bptt view Variable min len eval init_hidden repackage_hidden data batch_size model add_ zero_grad clip exp bptt range format get_batch size item clip_grad_norm enumerate time log_interval criterion backward print parameters init_hidden len read close open split print sum alpha print update set cuda dictionary len append float range split FloatTensor len bias_regularization_encoder bias_reg_encoder view bias_reg_en_factor dictionary bias_reg_decoder bias_reg_var_ratio bias_reg_de_factor bias_regularization_decoder svd sum norm view cumsum min append weight range cat svd sum norm view cumsum min append weight range cat | sueqian6/Reducing-Gender-Bias-in-Word-Level-Language-Models-Using-A-Gender-Equalizing-Loss-Function | 3,754 |
sufengniu/segan_multi | ['speech enhancement'] | ['SEGAN: Speech Enhancement Generative Adversarial Network'] | discriminator.py make_tfrecords.py model_multi.py generator.py inference.py ops.py bnorm.py main.py data_loader.py model.py VBN pre_emph de_emph read_and_decode discriminator AEGenerator Generator pre_emph_test main pre_emph_test main create_dir _int64_feature encoder_proc read_and_slice _bytes_feature slice_signal main Model SEAE SEGAN_IV SEGAN_III SEGAN_I leakyrelu minmax_normalize minmax_denormalize tensor_summary prelu repeat_elements average_gradients batch_to_time atrous_conv1d nn_deconv conv1d conv2d gaussian_noise_layer highway time_to_batch deconv downconv histogram_summary sample_random_walk audio_summary residual_block variables_on_gpu0 scalar_summary reshape concat zeros range read TFRecordReader decode_raw float32 pre_emph set_shape int32 cast parse_single_example as_list int expand_dims pre_emph float32 placeholder seed print save_path name __flags synthesis_path ConfigProto append makedirs makedirs int list zip append range read slice_signal join zip print write SerializeToString tostring read_and_slice Example split len join unlink out_file splitext random_normal zeros range reshape randn scalar histogram audio xavier_initializer expand_dims format _linear f sigmoid range as_list get_shape xavier_initializer as_list print get_shape as_list split conv1d repeat_elements xavier_initializer get_shape expand_dims get_variable concat reduce_mean zip append expand_dims | sufengniu/segan_multi | 3,755 |
sugarruy/hashstash | ['image retrieval'] | ['Evade Deep Image Retrieval by Stashing Private Images in the Hash Space'] | HashNet/pytorch/src/myRetrieval.py HashNet/pytorch/src/publicVariables.py HashNet/pytorch/src/myEvaluation.py HashNet/pytorch/src/myPreData.py HashNet/pytorch/src/loss.py HashNet/pytorch/src/myExtractCodeLabel.py HashNet/pytorch/src/myLoss.py HashNet/pytorch/src/publicFunctions.py HashNet/pytorch/src/myVerifyClass.py HashNet/pytorch/src/data_list.py HashNet/pytorch/src/myNetwork.py HashNet/pytorch/src/myTrain.py HashNet/pytorch/src/myClustering.py HashNet/pytorch/src/myGetAdv.py HashNet/pytorch/src/lr_schedule.py HashNet/pytorch/src/network.py make_dataset default_loader accimage_loader ImageList pil_loader pairwise_loss multistep_lr_scheduler step_lr_scheduler inv_lr_scheduler mean_average_precision get_dsets_loader_coco get_dsets_loader_nus_wide trans_train_resize_cifar10 trans_train_resize_imagenet get_dsets_loader_places365 get_output_code_label_list_by_dset get_dsets_loader_cifar10 get_dsets_loader_imagenet get_dsets_loader_fashion_mnist get_dsets_loader_by_dataset trans_train_resize_mnist get_dsets_loader get_trans_img get_adv_untarget get_adv_cluster_circle_loss get_adv_cluster_circle_loss_dbscan get_round_adv cal_class_code_variance emptySpaceLoss_3sigma tanhfunc_torch expfunc_torch masked_adv_loss cal_class_code_center clusterCentersLoss emptySpaceLoss_away clusterCircleLoss_tanh emptySpaceLoss_weighted clusterCircleLoss_exp clusterCircleLoss_lambda clusterCircleLoss pairwise_loss emptySpaceLoss AlexNetFc IncResV2 InceptionV3 ResNetFc ResNext VGGFc InceptionV4 create_file_for_train_by_folderpath one_hot count_by_query_result show_img get_imgs_num_by_class_from_NPimgs get_retrieval_result_by_query_code get_img_num_by_class_from_img get_multi_labels_from_vector load_ori_dsets plot_by_result cal_intra_class_dis get_query_result_num_by_class adv_class_verify_mnist adv_class_verify adv_class_verify_cifar10 transform_adv_img AlexNetFc ResNetFc VGGFc get_dsets make_one_hot load_model_class len sum exp Variable t masked_select float mm log param_groups param_groups param_groups T arange cumsum astype dot argsort append sum range trans_train MNIST FashionMNIST readlines DataLoader CIFAR10 ImageList get_dsets_loader_by_dataset get_dsets_loader_by_dataset get_dsets_loader_by_dataset get_dsets_loader_by_dataset get_dsets_loader_by_dataset get_dsets_loader_by_dataset get_dsets_loader_by_dataset Tensor model print Variable unsqueeze zeros float argmax cuda range len sum time model Variable backward print abs grad sign unsqueeze array numpy cuda loss detach SavedCluster loss_fun model zero_grad SGD unsqueeze get_circle_vars abs cuda step exit sum poly_fit range detach time backward print Variable clamp zeros numpy array loss_fun model zero_grad SGD polyfit unsqueeze get_circle_vars abs cuda step sum range detach backward Variable print clamp SavedDBscanCluster zeros numpy array asarray moveaxis round masked_select mean zeros range reshape zeros range reshape var t pow mm mean mm t pow mean sum sum print reshape mm t pow mean index_select abs cuda sum print reshape mm t pow mean numpy index_select abs cuda cat t pow mean numpy mm sum print mm stack numpy abs cuda diag sum Variable print stack numpy abs cuda sum Variable print stack numpy abs cuda sum print mm stack numpy abs cuda diag list arange replace astype write close open sample listdir array range len imshow imread append range argwhere subplot asarray size min imshow range print reshape transpose matmul mean append zeros range transpose matmul argwhere append expand_dims range int reshape zeros max range count_by_query_result get_retrieval_result_by_query_code numpy sign zeros cuda range get_img_num_by_class_from_img MNIST FashionMNIST readlines CIFAR10 ImageList upsample unsqueeze load model_class eval transform_adv_img argmax MNIST get_dsets_loader_nus_wide trans_train_resize_cifar10 FashionMNIST get_dsets_loader_places365 get_dsets_loader_imagenet CIFAR10 trans_train_resize_mnist Inc_v4 AlexNetFc Inception ResNetFc ResNext IncRes_v2 VGGFc zeros range | sugarruy/hashstash | 3,756 |
suhruthGit/Unity3DML | ['unity'] | ['Unity: A General Platform for Intelligent Agents'] | ml-agents-envs/mlagents/envs/communicator_objects/unity_rl_input_pb2.py ml-agents/mlagents/trainers/components/reward_signals/curiosity/model.py ml-agents-envs/mlagents/envs/communicator_objects/agent_action_pb2.py ml-agents-envs/mlagents/envs/communicator_objects/unity_to_external_pb2.py gym-unity/gym_unity/envs/__init__.py ml-agents/mlagents/trainers/learn.py ml-agents-envs/mlagents/envs/communicator_objects/custom_observation_pb2.py ml-agents/mlagents/trainers/meta_curriculum.py ml-agents/mlagents/trainers/tests/test_barracuda_converter.py ml-agents/mlagents/trainers/ppo/models.py utils/validate_meta_files.py ml-agents/mlagents/trainers/trainer_controller.py ml-agents/mlagents/trainers/components/bc/model.py ml-agents/mlagents/trainers/tests/test_curriculum.py ml-agents-envs/mlagents/envs/communicator.py ml-agents-envs/mlagents/envs/communicator_objects/custom_reset_parameters_pb2.py ml-agents-envs/mlagents/envs/communicator_objects/engine_configuration_pb2.py ml-agents/mlagents/trainers/tests/test_ppo.py ml-agents-envs/mlagents/envs/tests/test_rpc_communicator.py ml-agents/mlagents/trainers/components/reward_signals/__init__.py ml-agents-envs/mlagents/envs/communicator_objects/agent_info_pb2.py ml-agents-envs/setup.py ml-agents/mlagents/trainers/tests/mock_brain.py ml-agents-envs/mlagents/envs/action_info.py ml-agents-envs/mlagents/envs/rpc_communicator.py ml-agents/mlagents/trainers/tests/test_bcmodule.py ml-agents/mlagents/trainers/tests/test_trainer_controller.py ml-agents/mlagents/trainers/components/reward_signals/reward_signal_factory.py ml-agents/setup.py ml-agents/mlagents/trainers/barracuda.py ml-agents-envs/mlagents/envs/tests/test_envs.py ml-agents/mlagents/trainers/sac/policy.py ml-agents-envs/mlagents/envs/env_manager.py ml-agents/mlagents/trainers/ppo/trainer.py ml-agents-envs/mlagents/envs/tests/test_timers.py ml-agents-envs/mlagents/envs/communicator_objects/unity_rl_output_pb2.py ml-agents-envs/mlagents/envs/communicator_objects/unity_rl_initialization_output_pb2.py ml-agents-envs/mlagents/envs/communicator_objects/unity_input_pb2.py ml-agents/mlagents/trainers/tests/test_meta_curriculum.py ml-agents/mlagents/trainers/components/reward_signals/curiosity/signal.py ml-agents-envs/mlagents/envs/subprocess_env_manager.py ml-agents/mlagents/trainers/bc/trainer.py ml-agents-envs/mlagents/envs/tests/test_brain.py ml-agents/mlagents/trainers/curriculum.py ml-agents/mlagents/trainers/tests/test_policy.py ml-agents/mlagents/trainers/ppo/policy.py ml-agents/mlagents/trainers/tests/test_learn.py ml-agents/mlagents/trainers/tests/test_demo_loader.py utils/validate_versions.py ml-agents/mlagents/trainers/models.py ml-agents-envs/mlagents/envs/communicator_objects/brain_parameters_pb2.py ml-agents/mlagents/trainers/tests/test_simple_rl.py ml-agents-envs/mlagents/envs/policy.py ml-agents/mlagents/trainers/exception.py gym-unity/gym_unity/tests/test_gym.py ml-agents/mlagents/trainers/buffer.py ml-agents/mlagents/trainers/tensorflow_to_barracuda.py ml-agents-envs/mlagents/envs/communicator_objects/unity_to_external_pb2_grpc.py ml-agents-envs/mlagents/envs/mock_communicator.py ml-agents/mlagents/trainers/tests/test_rl_trainer.py ml-agents-envs/mlagents/envs/timers.py gym-unity/setup.py ml-agents-envs/mlagents/envs/communicator_objects/unity_message_pb2.py ml-agents-envs/mlagents/envs/environment.py ml-agents-envs/mlagents/envs/communicator_objects/custom_action_pb2.py ml-agents/mlagents/trainers/bc/policy.py ml-agents-envs/mlagents/envs/simple_env_manager.py ml-agents-envs/mlagents/envs/communicator_objects/environment_parameters_pb2.py ml-agents-envs/mlagents/envs/base_unity_environment.py ml-agents/mlagents/trainers/trainer_util.py ml-agents/mlagents/trainers/tests/test_trainer_util.py ml-agents-envs/mlagents/envs/communicator_objects/unity_output_pb2.py ml-agents/mlagents/trainers/components/reward_signals/extrinsic/signal.py ml-agents/mlagents/trainers/sac/trainer.py ml-agents-envs/mlagents/envs/communicator_objects/compressed_observation_pb2.py ml-agents-envs/mlagents/envs/sampler_class.py ml-agents/mlagents/trainers/tests/test_sac.py ml-agents-envs/mlagents/envs/exception.py ml-agents/mlagents/trainers/sac/models.py ml-agents-envs/mlagents/envs/communicator_objects/command_pb2.py ml-agents-envs/mlagents/envs/communicator_objects/space_type_pb2.py ml-agents/mlagents/trainers/components/reward_signals/gail/model.py ml-agents-envs/mlagents/envs/communicator_objects/header_pb2.py ml-agents/mlagents/trainers/rl_trainer.py ml-agents/mlagents/trainers/tests/test_reward_signals.py ml-agents-envs/mlagents/envs/brain.py ml-agents/mlagents/trainers/components/reward_signals/gail/signal.py ml-agents/mlagents/trainers/ppo/multi_gpu_policy.py ml-agents/mlagents/trainers/tests/test_multigpu.py ml-agents/mlagents/trainers/demo_loader.py ml-agents/mlagents/trainers/components/bc/module.py ml-agents/mlagents/trainers/tests/test_trainer_metrics.py ml-agents-envs/mlagents/envs/tests/test_sampler_class.py ml-agents/mlagents/trainers/tests/test_buffer.py ml-agents/mlagents/trainers/trainer.py ml-agents-envs/mlagents/envs/tests/test_subprocess_env_manager.py ml-agents/mlagents/trainers/bc/models.py ml-agents/mlagents/trainers/bc/offline_trainer.py ml-agents/mlagents/trainers/tf_policy.py ml-agents/mlagents/trainers/tests/test_bc.py ml-agents-envs/mlagents/envs/communicator_objects/demonstration_meta_pb2.py ml-agents-envs/mlagents/envs/communicator_objects/unity_rl_initialization_input_pb2.py ml-agents/mlagents/trainers/trainer_metrics.py VerifyVersionCommand UnityGymException ActionFlattener UnityEnv create_mock_vector_braininfo test_gym_wrapper test_multi_agent test_branched_flatten setup_mock_unityenvironment test_gym_wrapper_visual create_mock_brainparams VerifyVersionCommand BarracudaWriter fuse print_known_operations compress Build sort lstm write fuse_batchnorm_weights trim mean gru Model summary Struct parse_args to_json rnn BufferException Buffer Curriculum make_demo_buffer load_demonstration demo_to_buffer CurriculumError MetaCurriculumError TrainerError CurriculumLoadingError CurriculumConfigError create_environment_factory CommandLineOptions create_sampler_manager parse_command_line run_training prepare_for_docker_run try_create_meta_curriculum main MetaCurriculum EncoderType LearningModel LearningRateSchedule AllRewardsOutput RLTrainer get_layer_shape pool_to_HW flatten sqr_diff process_layer process_model get_layer_rank slow_but_stable_topological_sort get_attr basic_lstm ModelBuilderContext order_by get_epsilon get_tensor_dtype replace_strings_in_list debug embody by_op get_tensor_dims strided_slice remove_duplicates_from_list axis_to_barracuda by_name locate_actual_output_node convert strides_to_HW get_tensor_data very_slow_but_stable_topological_sort gru TFPolicy UnityPolicyException UnityTrainerException Trainer TrainerController TrainerMetrics TrainerFactory initialize_trainer load_config _load_config BehavioralCloningModel OfflineBCTrainer BCPolicy BCTrainer BCModel BCModule create_reward_signal RewardSignal CuriosityModel CuriosityRewardSignal ExtrinsicRewardSignal GAILModel GAILRewardSignal PPOModel get_devices MultiGpuPPOPolicy PPOPolicy PPOTrainer get_gae discount_rewards SACPolicyNetwork SACTargetNetwork SACNetwork SACModel SACPolicy SACTrainer create_mock_pushblock_brain create_buffer simulate_rollout create_mock_3dball_brain make_brain_parameters create_mock_banana_brain setup_mock_unityenvironment create_mock_braininfo create_mock_brainparams setup_mock_env_and_brains test_barracuda_converter test_bc_export bc_dummy_config test_bc_trainer_step test_bc_trainer_add_proc_experiences test_cc_bc_model test_dc_bc_model test_visual_cc_bc_model test_bc_trainer_end_episode test_bc_policy_evaluate dummy_config test_visual_dc_bc_model create_bc_trainer sac_dummy_config test_bcmodule_rnn_update test_bcmodule_update ppo_dummy_config create_policy_with_bc_mock test_bcmodule_dc_visual_update test_bcmodule_defaults test_bcmodule_rnn_dc_update test_buffer_sample construct_fake_buffer assert_array fakerandint test_buffer test_buffer_truncate test_curriculum_load_invalid_json location default_reset_parameters test_init_curriculum_bad_curriculum_raises_error test_curriculum_load_missing_file test_init_curriculum_happy_path test_increment_lesson test_curriculum_load_good test_get_config test_load_demo test_load_demo_dir basic_options test_docker_target_path test_run_training test_env_args test_commandline_args test_init_meta_curriculum_happy_path test_increment_lessons_with_reward_buff_sizes default_reset_parameters MetaCurriculumTest test_increment_lessons measure_vals reward_buff_sizes test_set_all_curriculums_to_lesson_num test_get_config test_set_lesson_nums test_init_meta_curriculum_bad_curriculum_folder_raises_error more_reset_parameters test_create_model dummy_config test_average_gradients test_update basic_mock_brain test_take_action_returns_action_info_when_available basic_params test_take_action_returns_nones_on_missing_values test_take_action_returns_empty_with_no_agents test_trainer_increment_step test_trainer_update_policy test_rl_functions test_ppo_model_dc_vector_rnn test_ppo_model_cc_vector_rnn test_add_rewards_output test_ppo_policy_evaluate test_ppo_model_cc_visual dummy_config test_ppo_model_dc_vector test_ppo_model_dc_visual test_ppo_get_value_estimates test_ppo_model_cc_vector test_gail_dc_visual sac_dummy_config reward_signal_update reward_signal_eval test_extrinsic test_curiosity_cc test_gail_rnn test_gail_cc ppo_dummy_config create_policy_mock test_curiosity_dc curiosity_dummy_config test_curiosity_visual test_curiosity_rnn gail_dummy_config create_mock_all_brain_info create_rl_trainer test_clear_update_buffer dummy_config test_rl_trainer create_mock_brain create_mock_policy test_sac_update_reward_signals create_sac_policy_mock test_sac_model_dc_visual test_sac_cc_policy test_sac_visual_policy test_sac_model_cc_vector_rnn test_sac_model_dc_vector test_sac_model_cc_vector dummy_config test_sac_model_dc_vector_rnn test_sac_model_cc_visual test_sac_rnn_policy test_sac_save_load_buffer test_sac_dc_policy test_simple_sac clamp test_simple_ppo Simple1DEnvironment _check_environment_trains test_initialization_seed test_take_step_if_not_training test_start_learning_trains_until_max_steps_then_saves basic_trainer_controller test_take_step_adds_experiences_to_trainer_and_trains dummy_config trainer_controller_with_take_step_mocks trainer_controller_with_start_learning_mocks test_start_learning_trains_forever_if_no_train_model TestTrainerMetrics test_initialize_ppo_trainer dummy_offline_bc_config_with_override test_load_config_invalid_yaml dummy_offline_bc_config test_initialize_invalid_trainer_raises_exception dummy_bad_config dummy_config test_load_config_missing_file test_load_config_valid_yaml test_initialize_trainer_parameters_override_defaults VerifyVersionCommand ActionInfo BaseUnityEnvironment safe_concat_lists safe_concat_np_ndarray CameraResolution BrainParameters BrainInfo Communicator UnityEnvironment EnvManager EnvironmentStep SamplerException UnityWorkerInUseException UnityException UnityCommunicationException UnityTimeOutException UnityEnvironmentException UnityActionException MockCommunicator Policy RpcCommunicator UnityToExternalServicerImplementation MultiRangeUniformSampler UniformSampler SamplerFactory SamplerManager GaussianSampler Sampler SimpleEnvManager worker EnvironmentResponse UnityEnvWorker StepResponse SubprocessEnvManager EnvironmentCommand TimerNode hierarchical_timer get_timer_root get_timer_tree reset_timers set_gauge timed GaugeNode TimerStack UnityToExternalProtoServicer add_UnityToExternalProtoServicer_to_server UnityToExternalProtoStub test_from_agent_proto_nan test_from_agent_proto_inf test_from_agent_proto_fast_path test_initialization test_reset test_returncode_to_signal_name test_close test_step test_handles_bad_filename test_rpc_communicator_checks_port_on_create test_rpc_communicator_create_multiple_workers test_rpc_communicator_close test_empty_samplers sampler_config_1 check_value_in_intervals incorrect_uniform_sampler test_incorrect_sampler test_sampler_config_1 sampler_config_2 incorrect_sampler_config test_incorrect_uniform_sampler test_sampler_config_2 mock_env_factory SubprocessEnvManagerTest MockEnvWorker test_timers decorated_func main extract_version_string check_versions create_mock_vector_braininfo sample UnityEnv setup_mock_unityenvironment step create_mock_brainparams create_mock_vector_braininfo UnityEnv setup_mock_unityenvironment step create_mock_brainparams setup_mock_unityenvironment create_mock_vector_braininfo create_mock_brainparams UnityEnv create_mock_vector_braininfo sample UnityEnv setup_mock_unityenvironment step create_mock_brainparams Mock list Mock array range join isdir print replaceFilenameExtension add_argument exit verbose source_file ArgumentParser target_file sqrt topologicalSort list hasattr layers addEdge Graph print inputs set len list hasattr layers print filter match trim_model compile data layers print tensors float16 replace layers dumps data dtype layers isinstance print name tensors inputs outputs shape zip array_without_brackets to_json globals Build array_equal pool reduce Build tanh mad tanh mul Build concat add sigmoid sub mad _ tanh mul Build concat add sigmoid mad print sorted keys Buffer reset_local_buffers number_visual_observations append_update_buffer append range enumerate make_demo_buffer load_demonstration join read suffix isdir endswith BrainParametersProto from_agent_proto DemonstrationMetaProto ParseFromString AgentInfoProto isfile append from_proto listdir _DecodeVarint32 parse_args add_argument ArgumentParser start_learning fast_simulation create_sampler_manager sampler_file_path put reset_parameters lesson load_config keep_checkpoints str docker_target_name load_model multi_gpu TrainerController save_freq trainer_config_path run_id num_envs format create_environment_factory no_graphics try_create_meta_curriculum TrainerFactory curriculum_folder base_port env_args SubprocessEnvManager train_model env_path pop SamplerManager load_config set_all_curriculums_to_lesson_num MetaCurriculum reset_parameters chmod format basename isdir glob copyfile copytree prepare_for_docker_run replace seed Process join parse_command_line getLogger print debug num_runs run_training start Queue info cpu randint setLevel range append endswith len print HasField hasattr get_attr isinstance get_attr tensor_shape ndarray isinstance shape int_val bool_val float_val ListFields name ndarray isinstance str tensor_content ndarray product isinstance get_tensor_dtype print get_tensor_dims unpack int_val bool_val array float_val enter append add set Build mul sub insert Build tolist append range len locate_actual_output_node name find_tensor_by_name split locate_actual_output_node name lstm find_tensor_by_name find_forget_bias split get_layer_shape id Struct tensor get_layer_rank layer_ranks hasattr name patch_data rank input_shapes out_shapes input get_attr append replace_strings_in_list tensors embody astype op inputs zip enumerate print float32 patch_data_fn model_tensors map_ignored_layer_to_its_input co_argcount len items list hasattr get_tensors name print process_layer eval slow_but_stable_topological_sort ModelBuilderContext sort assign_ids pop range insert len layers verbose Struct process_model open print_known_operations fuse compress node GraphDef Model dims_to_barracuda_shape insert get_tensor_dims inputs MessageToJson ParseFromString cleanup_layers read memories print sort write trim summary print_supported_ops update format SACTrainer OfflineBCTrainer PPOTrainer copy brain_name get check_config rcls list_local_devices list zeros_like size reversed range append discount_rewards CameraResolution Mock list ones array range brain_name pop create_buffer brain sequence_length append range vector_action_space_size Buffer ones number_visual_observations append_update_buffer shape append sum range enumerate setup_mock_unityenvironment mock_env create_mock_braininfo create_mock_brainparams create_mock_brainparams create_mock_brainparams create_mock_brainparams join remove _get_candidate_names convert _get_default_tempdir dirname abspath isfile next create_bc_trainer export_model create_mock_pushblock_brain Mock BCTrainer simulate_rollout mock_env dirname abspath setup_mock_unityenvironment policy create_mock_braininfo create_mock_3dball_brain update_policy create_bc_trainer increment_step agents process_experiences step create_bc_trainer add_experiences end_episode agents process_experiences step create_bc_trainer add_experiences BCPolicy evaluate close reset MockCommunicator reset_default_graph UnityEnvironment reset_default_graph reset_default_graph reset_default_graph reset_default_graph mock_env dirname abspath setup_mock_unityenvironment create_mock_braininfo create_policy_with_bc_mock close ppo_dummy_config create_mock_3dball_brain update items list close create_policy_with_bc_mock create_mock_3dball_brain update items list close create_policy_with_bc_mock create_mock_3dball_brain update items list close create_mock_banana_brain create_policy_with_bc_mock update items list close create_mock_banana_brain create_policy_with_bc_mock flatten list range len append range Buffer get_batch construct_fake_buffer assert_array append_update_buffer make_mini_batch reset_agent array sample_mini_batch construct_fake_buffer append_update_buffer construct_fake_buffer truncate_update_buffer append_update_buffer Curriculum Curriculum Curriculum dumps StringIO StringIO make_demo_buffer load_demonstration dirname abspath make_demo_buffer load_demonstration dirname abspath MagicMock basic_options MagicMock parse_command_line parse_command_line MetaCurriculum assert_has_calls MetaCurriculumTest increment_lessons assert_called_with MetaCurriculumTest increment_lessons assert_called_with assert_not_called MetaCurriculumTest set_all_curriculums_to_lesson_num MetaCurriculumTest dict update MetaCurriculumTest reset_default_graph MultiGpuPPOPolicy create_mock_brainparams reset_default_graph create_mock_brainparams update Mock reset_default_graph MultiGpuPPOPolicy create_mock_brainparams MagicMock TFPolicy basic_mock_brain basic_params BrainInfo get_action MagicMock TFPolicy basic_mock_brain basic_params BrainInfo get_action MagicMock TFPolicy basic_mock_brain ActionInfo basic_params BrainInfo get_action evaluate close reset MockCommunicator PPOPolicy reset_default_graph UnityEnvironment get_value_estimates items list close reset MockCommunicator PPOPolicy reset_default_graph UnityEnvironment reset_default_graph reset_default_graph reset_default_graph reset_default_graph reset_default_graph reset_default_graph assert_array_almost_equal array discount_rewards Mock increment_step BrainParameters assert_called_with PPOTrainer simulate_rollout update_policy policy PPOTrainer setup_mock_env_and_brains AllRewardsOutput BrainParameters PPOTrainer add_rewards_outputs update SACPolicy PPOPolicy setup_mock_env_and_brains reset evaluate model simulate_rollout _execute_model prepare_update update_dict make_mini_batch create_policy_mock reward_signal_update reward_signal_eval reward_signal_update reward_signal_eval create_policy_mock dirname abspath create_policy_mock reward_signal_update reward_signal_eval create_policy_mock reward_signal_update reward_signal_eval create_policy_mock reward_signal_update reward_signal_eval create_policy_mock reward_signal_update reward_signal_eval create_policy_mock reward_signal_update reward_signal_eval create_policy_mock reward_signal_update reward_signal_eval create_mock_brainparams RLTrainer dummy_config create_mock_brain Mock list create_mock_all_brain_info create_rl_trainer values end_episode construct_curr_info episode_steps create_mock_braininfo create_mock_policy add_experiences items list construct_fake_buffer create_rl_trainer clear_update_buffer append_update_buffer SACPolicy setup_mock_env_and_brains update evaluate create_sac_policy_mock simulate_rollout close update_buffer reset reset_default_graph create_sac_policy_mock simulate_rollout close update_reward_signals reset_default_graph update evaluate create_sac_policy_mock simulate_rollout close update_buffer reset reset_default_graph update evaluate create_sac_policy_mock simulate_rollout update_buffer reset reset_default_graph update evaluate create_sac_policy_mock simulate_rollout close update_buffer reset reset_default_graph reset_default_graph reset_default_graph reset_default_graph reset_default_graph reset_default_graph reset_default_graph str Mock SACTrainer save_model simulate_rollout len dummy_config policy setup_mock_env_and_brains Simple1DEnvironment _check_environment_trains Simple1DEnvironment _check_environment_trains TrainerController assert_called_with MagicMock basic_trainer_controller start_learning assert_called_once MagicMock assert_not_called trainer_controller_with_start_learning_mocks trainer_controller_with_start_learning_mocks start_learning MagicMock assert_called_once MagicMock basic_trainer_controller assert_called_once Mock MagicMock current_all_brain_info EnvironmentStep advance outputs assert_not_called trainer_controller_with_take_step_mocks assert_called_once_with previous_all_brain_info assert_called_once Mock MagicMock current_all_brain_info EnvironmentStep advance outputs assert_not_called trainer_controller_with_take_step_mocks assert_called_once_with previous_all_brain_info dummy_offline_bc_config dummy_offline_bc_config_with_override BrainParametersMock dummy_config BrainParametersMock dummy_bad_config _load_config StringIO extend copy items list value EnvironmentResponse external_brains payload text get_timer_root reset_timers put reset _send_response reset_parameters StepResponse env_factory step memory action perf_counter push reset method_handlers_generic_handler add_generic_rpc_handlers assert_called from_agent_proto AgentInfoProto extend assert_called from_agent_proto extend assert_not_called AgentInfoProto assert_not_called from_agent_proto AgentInfoProto extend UnityEnvironment close MockCommunicator UnityEnvironment close MockCommunicator reset str local_done print agents step close MockCommunicator UnityEnvironment len UnityEnvironment close MockCommunicator close RpcCommunicator close RpcCommunicator close RpcCommunicator SamplerManager sample_all sampler_config_1 sampler_config_2 SamplerManager SamplerManager sample_all incorrect_uniform_sampler incorrect_sampler_config set_gauge replace endswith add set walk join print extract_version_string set values | suhruthGit/Unity3DML | 3,757 |
sujoyp/subgoal-discovery | ['imitation learning'] | ['Learning from Trajectories via Subgoal Discovery'] | subgoal-discovery/subgoals/gen_new_labels.py subgoal-discovery/subgoals/main.py subgoal-discovery/subgoals/load_data.py subgoal-discovery/subgoals/options.py subgoal-discovery/subgoals/train.py subgoal-discovery/subgoals/utils.py subgoal-discovery/subgoals/model.py subgoal-discovery/subgoals/vis.py subgoal-discovery/subgoals/test.py gen_new_labels Dataset get_c ConvModel MLPModel weights_init_mlp weights_init normalized_columns_initializer test CASL OnCL MILL train getAssignment dist get_labels write_to_file DTW load getAssignment num_subgoals model_name save append path_to_trajectories numpy enumerate Variable mean load_data save model_name zeros numpy cat size randn xavier_uniform_ weight __name__ fill_ normal_ __name__ fill_ concatenate print mean log_value load_data array Variable log_softmax mean sum range max norm transpose mm softmax sum cuda range pow sum batch_size print backward CASL MILL zero_grad log_value load_data step str close write open zeros astype int enumerate zeros dist range len | sujoyp/subgoal-discovery | 3,758 |
sumeetsk/maxgap_bandit | ['outlier detection'] | ['MaxGap Bandit: Adaptive Algorithms for Approximate Ranking'] | streetview_data/generate_data.py simulated_data/animation_movie.py simulated_data/generate_data.py stopping_times/stopping_times_plot.py stopping_times/generate_data.py simulated_data/mistake_probability_plot.py streetview_data/mistake_probability_plot.py stopping_times/utils/utils.py simulated_data/pulls_plot.py LUCB right_gap_ub_fixedpos Random Env single_sim left_gap_ub get_left_gap_ub get_right_gap_ub calculate_ci Elimination testrun left_gap_ub_fixedpos UCB get_best_lower_bound right_gap_ub Top2UCB Random Env single_sim testrun Elimination UCB MaxGap alg_stop_gap compute_hardness get_active_arms right_gap_ub_fixedpos left_gap_ub get_left_gap_ub get_right_gap_ub calculate_ci left_gap_ub_fixedpos get_best_lower_bound right_gap_ub LUCB right_gap_ub_fixedpos Random Env single_sim left_gap_ub get_left_gap_ub get_right_gap_ub calculate_ci Elimination testrun left_gap_ub_fixedpos UCB get_best_lower_bound right_gap_ub sqrt log min max range len min float max range len left_gap_ub_fixedpos max min float max range len right_gap_ub_fixedpos max append range left_gap_ub append range right_gap_ub update deepcopy Env get_data get_arm pull_arm range seed eval testrun len has_stopped print sorted sorted min append argmax max range len len len range len print | sumeetsk/maxgap_bandit | 3,759 |
sumitsk/MOGP-AL | ['active learning', 'gaussian processes'] | ['Near-Optimal Active Learning of Multi-Output Gaussian Processes'] | env.py run.py agent.py test.py models.py utils.py arguments.py Agent Master get_args JuraEnv HadamardMTGP HadamardMTGPModel entropy_from_var to_torch normalize entropy_from_cov zero_mean_unit_variance compute_rmse load_data vec_to_one_hot_matrix to_numpy compute_mae parse_args add_argument ArgumentParser zeros max read_pickle values mean std | # Near-Optimal Active Learning of Multi-Output Gaussian Processes ## Installation This is the implementation of **Near-Optimal Active Learning of Multi-Output Gaussian Processes** paper (https://arxiv.org/abs/1511.06891). This repository uses the Intrinsic Coregionalization Model (ICM) instead of Convolved MOGP model used in the paper. ### Requirements: * [GPyTorch](https://github.com/cornellius-gp/gpytorch) (Beta Release) * [PyTorch](https://pytorch.org/) * [Pandas](https://pandas.pydata.org/) After installing the listed dependencies, simply clone this package to run scripts. ## Getting Started See `run.py` script to setup the Jura dataset used in the paper and perform active learning with MOGP. You can setup certain arguments from command line. Simply execute the following to start the training. | 3,760 |
sumitsk/algp | ['active learning', 'gaussian processes'] | ['Active Learning with Gaussian Processes for High Throughput Phenotyping'] | env.py graph_utils.py map.py run.py agent.py models.py utils.py arguments.py Agent get_args FieldEnv opposite_headings edge_cost in_between get_down_and_up_nodes find_merge_to_node lower_bound_path_cost get_heading path_cost Map LinearLatentFunction ExactGPModel NonLinearLatentFunction GPR IdentityLatentFunction render_naive_strategy compare_maxent snr_test path_to_sample_count run_demo compare_all_strategies entropy_from_cov find_shortest_path compute_mean_normalized_rmse compute_mae to_numpy is_valid_cell generate_gaussian_data generate_phenotype_data normal_dist_kldiv normalize compute_range_normalized_rmse generate_mixed_data compute_iqr load_dataframe zero_mean_unit_variance find_equi_sample_path manhattan_distance compute_iqr_normalized_rmse euclidean_distance predictive_distribution to_torch load_data_from_pickle draw_path generate_lineplots load_data vec_to_one_hot_matrix compute_rmse compute_metric join str add_argument exit id warn eval rename ArgumentParser input parse_args save_dir exists makedirs opposite_headings get_heading in_between min vstack array sum max range len full range len Agent exp FieldEnv named_parameters dict item append range arange test_Y FieldEnv compute_mae pilot_survey Agent list from_dict set_trace append range predict run_greedy_ipp mean tile zip run_naive generate_lineplots reset prediction_vs_distance len arange test_Y FieldEnv flatten compute_mae pilot_survey Agent list from_dict set_trace append range predict mean zip run_ipp generate_lineplots reset prediction_vs_distance len FieldEnv reset run_ipp Agent FieldEnv render_naive squeeze int concatenate squeeze hstack vstack read_pickle max len concatenate squeeze hstack flatten read_pickle unique values len exp arange reshape transpose square maximum uniform meshgrid zeros sum range exp arange concatenate reshape transpose square maximum range uniform meshgrid randint sum zeros sum T generate_gaussian_data concatenate append randint range zeros item zeros max mean std compute_rmse compute_rmse compute_rmse T inv dot trace len cov_mat T entropy_from_cov inv mean dot abs range arrow len show subplots xlabel squeeze set_xlim ylabel lineplot legend min array | sumitsk/algp | 3,761 |
sumuzhao/CycleGAN-Music-Style-Transfer | ['style transfer'] | ['Symbolic Music Genre Transfer with CycleGAN'] | style_classifier.py Testfile.py ops.py convert_clean.py module.py utils.py main.py write_midi.py model.py converter get_midi_path midi_filter make_sure_path_exists get_midi_info get_merged main main cyclegan PhraseGenerator generator_midinet discriminator_midinet generator_musegan_bar softmax_criterion PhraseDiscriminator generator_resnet discriminator_classifier abs_criterion generator_unet BarGenerator generator_musegan_phase sce_criterion mae_criterion discriminator_musegan_phase discriminator_musegan_bar discriminator BarDiscriminator lrelu to_chroma_tf batch_norm relu linear to_binary_tf to_binary deconv2d_musegan conv2d_musegan conv2d deconv2d instance_norm Classifer to_binary get_bar_piano_roll get_image load_test_data save_images center_crop load_train_data load_npy_data ImagePool merge_images get_rand_samples save_midis get_now_datetime transform inverse_transform imread load_midi_data imsave get_sample_shape merge set_piano_roll_to_instrument write_piano_rolls_to_midi write_piano_roll_to_midi makedirs endswith join walk append time format time_signature_changes sort denominator estimate_beat_start numerator get_tempo_changes is_drum get_merged_pianoroll tracks Track append enumerate join Multitrack PrettyMIDI from_pretty_midi make_sure_path_exists get_midi_info save get_merged join get_midi_path format print copyfile midi_filter make_sure_path_exists len checkpoint_dir sample_dir test_dir ConfigProto makedirs as_list slice reduce_max logical_and equal reshape reduce_max float32 reduce_sum stack cast reduce_min reduce_max logical_and equal reshape delete concatenate imread imresize int imresize concatenate uniform ceil imread fliplr PrettyMIDI reshape concatenate load concatenate zeros enumerate int round center_crop concatenate reshape append zeros write_piano_rolls_to_midi range choice strftime pop list concatenate reshape sort len astype index nonzero Note append float range diff set_piano_roll_to_instrument Instrument PrettyMIDI write append set_piano_roll_to_instrument Instrument print PrettyMIDI write append range len | # Symbolic Music Genre Transfer with CycleGAN - Built a CycleGAN-based model to realize music style transfer between different musical domains. - Added extra discriminators to regularize generators to achieve clear style transfer and preserve original melody, which made our model learn more high-level features. - Trained several genre classifiers separately, and combined them with subjective judgement to have more convincing evaluations. **Note**: Recently I'm trying to refactorize this project in TensorFlow2.0. For those interested please go to [CycleGAN-Music-Style-Transfer-Refactorization](https://github.com/sumuzhao/CycleGAN-Music-Style-Transfer-Refactorization). ## Paper [Symbolic Music Genre Transfer with CycleGAN](https://arxiv.org/pdf/1809.07575.pdf) Paper accepted at 30th International Conference on Tools with Artificial Intelligence (ICTAI), Volos, Greece, November 2018. ## Music Samples www.youtube.com/channel/UCs-bI_NP7PrQaMV1AJ4A3HQ | 3,762 |
sunalbert/Sequential-patch-based-segmentation | ['medical image segmentation', 'semantic segmentation'] | ['Interactive Medical Image Segmentation via Point-Based Interaction and Sequential Patch Learning'] | utils/NaiveDataset.py modules/TimeDistributed.py utils/visualize.py modules/ConvRNN.py utils/Sampler.py modules/Model.py test_params.py test.py utils/tools.py pre_process.py utils/plot.py utils/post_process.py utils/Logger.py modules/blocks.py set_patch _extract_patches load_img encode_records get_coordinate direction_extract _get_patch inference find_red integrate get_coor repackage_hidden DownBlock ConvRNNBlock UpBlock ConvRNNCell ConvRNN init_weights MultiLevelModel SkipConnecRNNModel SkipConnecModel TimeDistributed remove get_learning_rate adjust_learning_rate Logger remove_comments empty backup_project_as_zip write_list_to_file open image_to_tensor CustomizedDataset tensor_to_image run_check_dataset label_to_tensor tensor_to_label flush plot tick post_process bwdist get_curvature convergence level_set sussman sussman_sign mask2phi im2double show_curve_and_phi RandomSamplerWithLength backup_project_as_zip visulize_gt imread any range extend direction_extract append _get_patch array range _extract_patches load_img glob print get_coordinate shape save zip append zeros array set_patch range len append shape range int rint astype centroid mean label find_red regionprops post_process integrate reinit_hidden output_dir save cuda str test_data_dir squeeze visulize_gt from_numpy load_state_dict imread expand_dims imsave range glob astype direction_extract eval float net load uint8 get_coor print Variable makedirs float32 sigmoid zeros numpy SkipConnecRNNModel len isinstance out_channels Conv2d bias sqrt zero_ norm_ ConvTranspose2d append strip dirname makedirs exists rmtree isdir makedirs make_archive replace param_groups param_groups from_numpy expand_dims astype float32 type astype float32 FloatTensor numpy astype numpy astype str CustomizedDataset print squeeze tensor_to_image shape zip range imsave tensor_to_label update items list format clear replace plot print sort xlabel ylabel mean clf savefig append type keys values set_axis_off draw pause imshow contour cla float astype bwdist im2double shape array ravel_multi_index inf zeros_like concatenate roll sqrt sussman_sign max clip flatnonzero abs sum flatnonzero subplots abs astype logical_and get_curvature convergence ion savefig sussman mask2phi float sum max show_curve_and_phi len deepcopy level_set canny gray2rgb square dilation | # Sequential-patch-based-segmentation ## Data Preparation test image(name.png) and corresponding ground truth(name_1.bmp) in the same folder. The shape of test image should be (296, 296) ## How to test Set your test parameters in test_params.py file and run test.py to get the predictions. | 3,763 |
sungsoo-ahn/genetic-expert-guided-learning | ['imitation learning'] | ['Guiding Deep Molecular Optimization with Genetic Exploration'] | run_pretrain.py model/genetic_operator/mutate.py get_logp_stats.py run_gegl_constrained.py model/genetic_expert.py util/smiles/dataset.py get_low_scoring_dataset.py model/genetic_operator/crossover.py util/smiles/function.py util/storage/recorder.py util/chemistry/rd_filter.py runner/gegl_trainer.py model/neural_apprentice.py util/chemistry/standard_benchmarks.py util/smiles/char_dict.py runner/guacamol_generator.py run_gegl.py runner/pretrain_trainer.py util/chemistry/benchmarks.py util/storage/priority_queue.py reproduce GeneticOperatorHandler SmilesGenerator SmilesGeneratorHandler crossover mol_ok crossover_ring crossover_non_ring ring_OK cut_ring cut change_atom mutate delete_atom add_ring append_atom change_bond_order insert_atom delete_cyclic_bond GeneticExpertGuidedLearningTrainer GeneticExpertGuidedLearningGenerator PreTrainer ThresholdedImprovementScoringFunction penalized_logp_cyclebasis _penalized_logp_cyclebasis load_benchmark similarity_constrained_penalized_logp_atomrings _penalized_logp_atomrings penalized_logp_atomrings similarity_constrained_penalized_logp_cyclebasis RDFilter valsartan_smarts amlodipine_rings perindopril_rings decoration_hop zaleplon_with_other_formula logP_benchmark similarity_cns_mpo hard_fexofenadine hard_osimertinib hard_cobimetinib pioglitazone_mpo ranolazine_mpo start_pop_ranolazine isomers_c9h10n2o2pf2cl qed_benchmark similarity smarts_with_other_target cns_mpo weird_physchem sitagliptin_replacement median_tadalafil_sildenafil isomers_c7h8n2o2 tpsa_benchmark isomers_c11h24 scaffold_hop median_camphor_menthol SmilesCharDictionary load_forbidden_symbols load_char_idx load_encode_dict load_dataset filter_by_score process_smis smis_to_actions MaxRewardPriorityQueue unravel_elems StorageElement Recorder unravel_elems RecorderElement crossover mutate FragmentOnBonds GetSubstructMatches MolFromSmarts choice MolFromSmarts choice GetSubstructMatches FragmentOnBonds range GetMolFrags AtomRings max MolFromSmarts HasSubstructMatch SanitizeMol randn mol_ok MolFromSmarts ReactionFromSmarts cut_ring append range mol_ok ReactionFromSmarts append cut range crossover_ring crossover_non_ring MolToSmiles Kekulize range replace list range choice replace list range choice choice change_atom delete_atom add_ring append append_atom choice ReactionFromSmarts change_bond_order insert_atom Kekulize RunReactants range delete_cyclic_bond calculateScore AtomRings MolLogP max Graph GetAdjacencyMatrix MolLogP calculateScore max cycle_basis uniform_specification RdkitScoringFunction uniform_specification RdkitScoringFunction uniform_specification ThresholdedImprovementScoringFunction RdkitScoringFunction TanimotoScoringFunction uniform_specification ThresholdedImprovementScoringFunction RdkitScoringFunction TanimotoScoringFunction get uniform_specification uniform_specification uniform_specification ClippedScoreModifier TanimotoScoringFunction uniform_specification RdkitScoringFunction ArithmeticMeanScoringFunction ClippedScoreModifier mean_cls TanimotoScoringFunction uniform_specification RdkitScoringFunction ClippedScoreModifier mean_cls TanimotoScoringFunction uniform_specification RdkitScoringFunction ClippedScoreModifier TanimotoScoringFunction uniform_specification RdkitScoringFunction ArithmeticMeanScoringFunction uniform_specification ArithmeticMeanScoringFunction RdkitScoringFunction uniform_specification ArithmeticMeanScoringFunction TanimotoScoringFunction uniform_specification ClippedScoreModifier TanimotoScoringFunction uniform_specification RdkitScoringFunction uniform_specification RdkitScoringFunction uniform_specification uniform_specification uniform_specification mean_cls TanimotoScoringFunction uniform_specification RdkitScoringFunction TanimotoScoringFunction uniform_specification RdkitScoringFunction TanimotoScoringFunction MolFromSmiles IsomerScoringFunction TanimotoScoringFunction uniform_specification RdkitScoringFunction logP tpsa uniform_specification IsomerScoringFunction TanimotoScoringFunction MolFromSmiles SMARTSScoringFunction logP RdkitScoringFunction tpsa bertz uniform_specification uniform_specification GeometricMeanScoringFunction TanimotoScoringFunction MolFromSmiles TanimotoScoringFunction uniform_specification mol_weight RdkitScoringFunction uniform_specification ArithmeticMeanScoringFunction TanimotoScoringFunction SMARTSScoringFunction uniform_specification ArithmeticMeanScoringFunction TanimotoScoringFunction SMARTSScoringFunction ClippedScoreModifier TanimotoScoringFunction uniform_specification RdkitScoringFunction GeometricMeanScoringFunction set str list with_suffix filter allowed filter_by_score list pool set list max_smi_len zeros range enumerate len list map zip | sungsoo-ahn/genetic-expert-guided-learning | 3,764 |
sunguanxiong/my_dwt | ['template matching', 'instance segmentation', 'semantic segmentation'] | ['Deep Watershed Transform for Instance Segmentation'] | DN/lossFunction.py DN/train_direction.py DN/ioUtils.py E2E/forward.py E2E/forward_e2e.py E2E/io_utils.py WTN/ioUtils.py E2E/network_init.py WTN/depth_model.py E2E/model_io.py E2E/post_process.py WTN/train_depth.py WTN/lossFunction.py E2E/main.py DN/direction_model.py E2E/e2e_model.py E2E/train.py E2E/loss_function.py Network read_ids read_mat Batch_Feeder write_mat countTotal countCorrect angularErrorTotal exceedingAngleThreshold countTotalWeighted angularErrorLoss train_model initialize_model checkSaveFlag modelSaver forward_model Network forward_model initialize_model forward_model read_ids image_scaling ssProcess pad read_mat write_mat Batch_Feeder countTotal modelTotalLoss countCorrect depthCELoss2 countTotalWeighted depthCELoss checkSaveFlag modelSaver get_model watershed_cut train_model Network read_ids read_mat Batch_Feeder write_mat countTotal modelTotalLoss countCorrect depthCELoss2 countTotalWeighted depthCELoss train_model initialize_model checkSaveFlag modelSaver forward_model save countTotal angularErrorTotal get_collection add_to_collection add_n join split savemat run join exists astype float32 zeros uint8 astype float32 get_collection depthCELoss2 countTotalWeighted add_to_collection add_n print list uint16 astype remove_small_holes int32 label zeros remove_small_objects keys binary_dilation | ## Deep Watershed Transform Performs instance level segmentation detailed in the following paper: Min Bai and Raquel Urtasun, Deep Watershed Transformation for Instance Segmentation, in CVPR 2017. Accessible at https://arxiv.org/abs/1611.08303. This page is still under construction. ## Dependencies Developed and tested on Ubuntu 14.04 and 16.04. 1) TensorFlow www.tensorflow.org 2) Numpy, Scipy, and Skimage (sudo apt-get install python-numpy python-scipy python-skimage) ## Inputs 1) Cityscapes images (www.cityscapes-dataset.com). | 3,765 |
sunjesse/shape-attentive-unet | ['medical image segmentation', 'semantic segmentation'] | ['SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation'] | radam.py data/u.py models/mynn.py lib/utils/data/distributed.py lib/nn/modules/tests/test_numeric_batchnorm.py lib/nn/modules/tests/test_sync_batchnorm.py models/GSConv.py lib/utils/data/sampler.py loss.py lib/utils/th.py lib/nn/__init__.py train.py lib/utils/data/dataloader.py misc_functions.py models/custom_functions.py lib/utils/data/__init__.py lib/utils/__init__.py test_and_pack.py models/__init__.py lib/nn/modules/batchnorm.py lib/nn/modules/unittest.py utils.py lib/utils/data/dataset.py models/models.py data/augmentations.py lib/nn/parallel/__init__.py lib/nn/modules/replicate.py vanilla_backprop.py guided_backprop.py lib/nn/modules/__init__.py lib/nn/parallel/data_parallel.py models/attention_blocks.py smoothgrad.py AttrDict.py models/adaptive_avgmax_pool.py models/norm.py config.py data/ac17_dataloader.py lib/nn/modules/comm.py data/crop_and_pad_augmentations.py models/resnet.py data/test_loader.py AttrDict assert_and_infer_cfg GuidedBackprop dice_loss ImageBasedCrossEntropyLoss2d CrossEntropyLoss2d LabelSmoothSoftmaxCE DualLoss save_class_activation_images recreate_image save_gradient_images get_positive_negative_saliency convert_to_grayscale get_example_params format_np_output preprocess_image save_image apply_colormap_on_image AdamW RAdam PlainRAdam generate_smooth_grad undo_crop visualize_result evaluate save_as_nifti round_num main resample_to_orig eval adjust_learning_rate checkpoint main train group_weight create_optimizers process_range colorEncode AverageMeter accuracy intersectionAndUnion parse_devices unique NotSupportedCliException find_recursive VanillaBackprop AC17_2DLoad AC17Data augment_gamma PaddingCenterCropTest CenterCrop RandomCrop RandomSized AdjustGamma RandomErasing AdjustHue RandomRotate PaddingCenterCrop RandomVerticallyFlip AdjustBrightness AdjustContrast RandomHorizontallyFlip AdjustSaturation FreeScale Compose RandomTranslate ComposeTest RandomSizedCrop Scale random_crop get_lbs_for_random_crop center_crop get_lbs_for_center_crop pad_nd_image_and_seg crop AC17Test rotate_coords_3d elastic_deform_coordinates_2 pad_nd_image scale_coords center_crop_2D_image mask_random_squares resize_image_by_padding_batched random_crop_2D_image create_random_rotation create_matrix_rotation_z_3d center_crop_2D_image_batched find_entries_in_array illumination_jitter convert_seg_image_to_one_hot_encoding_batched random_crop_3D_image convert_seg_image_to_one_hot_encoding generate_elastic_transform_coordinates resize_image_by_padding transpose_channels rotate_coords_2d uniform mask_random_square create_matrix_rotation_2d generate_noise create_matrix_rotation_x_3d convert_seg_to_bounding_box_coordinates random_crop_3D_image_batched center_crop_3D_image_batched interpolate_img get_range_val general_cc_var_num_channels random_crop_2D_image_batched elastic_deform_coordinates create_matrix_rotation_y_3d uncenter_coords center_crop_3D_image resize_multichannel_image create_zero_centered_coordinate_mesh resize_segmentation _sum_ft SynchronizedBatchNorm2d _unsqueeze_ft _SynchronizedBatchNorm SynchronizedBatchNorm1d SynchronizedBatchNorm3d SyncMaster FutureResult SlavePipe execute_replication_callbacks CallbackContext DataParallelWithCallback patch_replication_callback TorchTestCase as_numpy handy_var NumericTestCase SyncTestCase handy_var _find_bn _async_copy_stream UserScatteredDataParallel dict_gather _async_copy DictGatherDataParallel async_copy_to _get_stream user_scattered_collate mark_volatile as_variable as_numpy DataLoaderIter _set_SIGCHLD_handler default_collate _worker_manager_loop DataLoader _worker_loop ExceptionWrapper pin_memory_batch random_split ConcatDataset Subset TensorDataset Dataset DistributedSampler SubsetRandomSampler WeightedRandomSampler RandomSampler BatchSampler SequentialSampler Sampler AdaptiveAvgMaxPool2d adaptive_avgmax_pool2d pooling_factor conv1x1 SEResNetBottleneck SEBottleneck SpatialAttentionBlock _MRF convbnrelu Bottleneck conv3x3 batchnorm DualAttBlock SEModule conv2d_same numerical_gradients_2d gradient_central_diff calc_pad_same convTri compute_normal compute_normal_2 compute_grad_mag compute_single_sided_diferences t GatedSpatialConv2d HighFrequencyGatedSpatialConv2d Conv2dPad CenterBlock SegmentationModule ConvRelu SAUNet conv1x1_bn_relu SegmentationModuleBase conv3x3 conv3x3_bn_relu ModelBuilder SkipConv DecoderBlock initialize_weights Norm2d initialize_weights Norm2d ResNet resnet50 Bottleneck load_url conv3x3 resnet18 BasicBlock resnet101 batch_weighting syncbn print immutable BatchNorm2d sum tuple sigmoid mean unsqueeze softmax float type range cat ndimension percentile sum min expand_dims abs clip join save_image min makedirs join save_image apply_colormap_on_image makedirs fromarray uint8 color_map new size astype alpha_composite copy convert get_cmap uint8 transpose astype repeat expand_dims fromarray save isinstance format_np_output unsqueeze_ Variable transpose thumbnail float32 float enumerate transpose round range copy max maximum preprocess_image convert alexnet generate_gradients Variable normal_ item zeros range fromarray int uint8 size crop astype round_num max zeros_like shape resize range undo_crop join uint8 imwrite min astype result max join str print Nifti1Image eye to_filename update visualize zeros_like visualize_result synchronize AverageMeter perf_counter tqdm eval save_as_nifti save_test_path cpu cuda range resample_to_orig AC17 SegmentationModule evaluate ComposeTest print set_device DataLoader ModelBuilder cuda build_unet DualLoss gpu update format num_class as_numpy print synchronize AverageMeter intersectionAndUnion average sum cuda enumerate num_class zero_grad num_epoch lr_encoder adjust_learning_rate cuda running_lr_encoder lr_pow append range update format param_groups mean item float enumerate time backward print max_iters AverageMeter average step segmentation_module len format ckpt print save state_dict _ConvNd isinstance bias _BatchNorm modules append weight Linear RAdam Adam group_weight SGD running_lr_encoder param_groups cos lr_encoder num_epoch num_class patch_replication_callback num_epoch UserScatteredDataParallel load2D range Compose start_epoch eval checkpoint create_optimizers named_parameters train append join filter walk concatenate cumsum sort flatten argsort shape nonzero empty zeros astype unique float sum histogram copy list map strip groups match func append split std min mean uniform power float max range append randint range len append range len dtype list get_lbs_for_random_crop tuple shape pad any get_lbs_for_center_crop zeros range len pad_nd_image tuple random append meshgrid range gaussian_filter len tuple astype range len list shape unique zeros enumerate list unique zeros range enumerate random append array range gaussian_filter len random array append abs max range gaussian_filter len create_matrix_rotation_z_3d reshape identity create_matrix_rotation_y_3d shape create_matrix_rotation_x_3d len reshape create_matrix_rotation_2d shape deepcopy range dtype astype map_coordinates unique zeros enumerate random gaussian_filter arange array zeros max len shape array len shape array len shape array len shape array len shape randint len shape randint len shape randint len shape randint len list ones tuple reshape shape array max list ones tuple reshape array max array array array array normal dot shape array range max deepcopy sum grey_dilation tuple min power sqrt any gaussian_gradient_magnitude append zeros abs array range gaussian_filter len pop int max lb astype extend copy argwhere append array range enumerate dtype astype unique resize zeros enumerate dtype list astype resize zeros range isinstance orig_type uniform normalvariate type list shape pad array range len randint get_range_val range copy range mask_random_square list hasattr __data_parallel_replicate__ modules enumerate len replicate data isinstance size sum modules isinstance is_tensor record_stream isinstance Sequence Mapping cuda zip len zip len device_count Stream Mapping Sequence isinstance is_tensor Mapping Sequence is_tensor isinstance Sequence Variable Mapping seed init_fn get set_num_threads _set_worker_signal_handlers collate_fn manual_seed get isinstance set_device put pin_memory_batch sum list isinstance Sequence new Mapping type zip _new_shared is_tensor Mapping is_tensor isinstance Sequence SIGCHLD signal getsignal randperm sum print max_pool2d avg_pool2d cat shape pad conv2d calc_pad_same conv2d_same shape repeat Tensor cuda clone shape gradient_central_diff list reversed shape pad conv2d repeat Tensor cuda range cat remainder print numerical_gradients_2d set_trace pi sign convTri atan remainder print numerical_gradients_2d set_trace pi sign convTri atan mul numerical_gradients_2d convTri sqrt max show normal print imshow float GatedSpatialConv2d gconv MODEL getattr layer fill_ isinstance modules zero_ BatchNorm2d weight kaiming_normal load_url ResNet load_state_dict load_url ResNet load_state_dict load_url ResNet load_state_dict join format urlretrieve write makedirs | sunjesse/shape-attentive-unet | 3,766 |
sunlab-osu/REDS2 | ['relation extraction'] | ['Leveraging 2-hop Distant Supervision from Table Entity Pairs for Relation Extraction'] | model/__init__.py utils/util.py base/base_trainer.py train.py logger/visualization.py model/encoder.py model/selector.py trainer/__init__.py logger/logger.py data_loader/data_loaders.py model/loss.py utils/__init__.py trainer/trainer.py train_finetune.py test.py logger/__init__.py parse_config.py model/metric.py model/model.py base/__init__.py base/base_model.py base/base_data_loader.py model/embedding.py _set_by_path ConfigParser _get_opt_name _update_config _get_by_path main get_instance main get_instance main get_optim BaseDataLoader BaseModel BaseTrainer cust_collate_fn BaseNytLoader _cat_collate_fn cust_batch_sampler load_word_dict load_rel_dict BaseNytDataset setup_logging WriterTensorboardX WordEmbedding WordPosEmbedding PosEmbedding PCNNEncoder CNNEncoder get_importance cross_entropy non_na_accuracy accuracy auc TablePCNNAttModel_v1 BasePCNNAttModel BaseCNNAttModel BagAttention BagAttention_v1 assign_to_device Trainer ensure_dir read_json write_json Timer _set_by_path target _get_opt_name getattr flags startswith isinstance BaseNytLoader DataParallel save device list load_state_dict input to load_rel_dict update get_instance eval resume load_word_dict set_default_tensor_type load join items print subset len seed lr_scheduler train Trainer optim getattr manual_seed float pretrained append state_dict get_optim requires_grad named_parameters format print rand shape stack append zeros array len print len list isinstance Sequence type zip Tensor Mapping str basicConfig format list items print read_json dictConfig Path is_file unsqueeze sum softmax log_softmax float unsqueeze diagonal Tensor Mapping isinstance mkdir Path | # REDS2: Relation Extraction with 2-hop DS. Code and dataset for our paper "Leveraging 2-hop Distant Supervision from Table Entity Pairs for Relation Extraction" (EMNLP'19). Please kindly cite the following paper if you find this repo useful. ## Dataset ### Source Data * NYT10: originally released by [Riedel et al. (2010)](http://iesl.cs.umass.edu/riedel/ecml/). We use the processed version from [OpenNRE](https://github.com/thunlp/OpenNRE). * WikiTable: released by [Bha-gavatula et al. (2015)](http://websail-fe.cs.northwestern.edu/TabEL/#content-code) ### Data Format We follow the data format of [OpenNRE](https://github.com/thunlp/OpenNRE), with minor modification for training/testing data under our setting. #### Training & Testing Data ``` | 3,767 |
sunniesuhyoung/DST | ['image morphing', 'style transfer'] | ['WarpGAN: Automatic Caricature Generation', 'Neural Best-Buddies: Sparse Cross-Domain Correspondence', 'Style Transfer by Relaxed Optimal Transport and Self-Similarity', 'Deformable Style Transfer'] | cleanpoints.py NBB/main.py NBB/algorithms/neural_best_buddies.py NBB/util/util.py warp.py loss.py vggfeatures.py utils_pyr.py utils_plot.py styletransfer.py NBB/models/vgg19_model.py utils_misc.py NBB/options/options.py main.py utils_save.py NBB/util/draw_correspondence.py utils_keypoints.py NBB/util/MLS.py NBB/algorithms/feature_metric.py remove_crossing line intersection get_target_pts pairwise_distances_sq_l2 remd_loss moment_loss pairwise_distances_cos TV rgb_to_yuv content_loss distmat DST gen_dst_pts_keypoints init_keypoint_params pil_resize_long_edge_to sample_indices pil_to_tensor spatial_feature_extract pil_loader plot_warped_content plot_content plot_style plot_intermediate plot_naively_warped_stylized plot_naively_warped_content convert_image plot_DSToutput save_plots syn_lap_pyr laplacian tensor_resample dec_lap_pyr save_loss save_points VGG16_Extractor interpolate_bilinear apply_warp umeyama apply_interpolation image_warp phi sharpWarp solve_interpolation pairwise_squared_distance_matrix cross_squared_distance_matrix normalize_per_pix normalize_tensor response stdv_channels gaussian error_map mean_channels patch_distance stretch_tensor_0_to_1 identity_map sparse_semantic_correspondence vgg19 define_Vgg19 PerceptualLoss Options color_map draw_correspondence draw_dots draw_circle draw_square draw_points MLS read_points batch2im varname save_image read_image get_transform diagnose_network mkdirs tensor2im save_map_image downsample_map read_mask stretch_image feature2images binary2color_image save_tensor_as_mat mkdir map2image info save_final_image grad2image print_numpy upsample_map umeyama clamp transpose matmul inverse float cat line min delete intersection append max range sqrt transpose mm view transpose mm view sqrt pairwise_distances_sq_l2 pairwise_distances_cos to mm device size transpose mean distmat sum transpose min mean distmat max t mean mm mean data apply_warp syn_lap_pyr plot_intermediate random zero_grad SGD moment_loss interpolate init_keypoint_params max seed list remd_loss save_points Adam RMSprop content_loss append gen_dst_pts_keypoints to range detach extractor format size shuffle mean save_loss dec_lap_pyr item save_plots backward Variable clamp print clone TV spatial_feature_extract step arange umeyama transpose size matmul inverse append float range cat len cat BICUBIC resize int flatten sqrt floor ceil randint meshgrid max view size add_ astype float32 int32 mul_ device append to range clip cat len uint8 numpy astype clip set_aspect format plot arrow clamp set_axis_off close divide tight_layout imshow clf savefig convert_image numpy range makedirs plot_warped_content plot_content plot_style apply_warp plot_naively_warped_stylized clamp clone mean plot_naively_warped_content convert_image plot_DSToutput to numpy cat makedirs set_aspect plot arrow set_axis_off close tight_layout imshow clf savefig range set_aspect plot arrow set_axis_off close tight_layout imshow clf savefig range set_aspect plot arrow set_axis_off close tight_layout imshow clf savefig range set_aspect plot arrow set_axis_off close tight_layout imshow clf savefig range set_aspect plot set_axis_off close tight_layout imshow clf savefig range set_aspect plot loadtxt set_axis_off close tight_layout mean imshow clf savefig range pil_loader len append range laplacian tensor_resample range tensor_resample len plot xlabel multiply tolist axvline ylabel close clf savefig legend append max makedirs makedirs svd T ones matrix_rank mean dot eye sum diag interpolate_bilinear time arange reshape size apply_interpolation stack permute meshgrid solve_interpolation to mul transpose matmul unsqueeze to sum reshape transpose matmul size phi solve pairwise_squared_distance_matrix to cat size phi matmul cat cross_squared_distance_matrix dtype int unbind clamp size reshape apply shape unsqueeze floor append gather cuda size image_warp clone size sum size sum min max fill_ pow max sum mean_channels size sum copy_ Tensor transpose repeat exp floor identity_map vgg19 cuda pad tile pad floor range tile join color_map draw_dots draw_circle draw_square save_image tensor2im range len fromarray join str color_map size len draw_circle draw_square save resize tensor2im range open append open split get_transform convert append Resize BICUBIC join save_image tensor2im int join binary2color_image pow upsample_map map2image save_image Upsample AvgPool2d zeros transpose numpy tile stretch_image transpose tile zeros numpy range zeros numpy maximum range transpose numpy stretch_image transpose numpy tile transpose numpy array tile amin amax print parameters fromarray save print numpy savemat print join search print float64 flatten astype mkdir makedirs print shape array open | sunniesuhyoung/DST | 3,768 |
sunset1995/HorizonNet | ['data augmentation', 'semantic segmentation'] | ['Manhattan Room Layout Reconstruction from a Single 360 image: A Comparative Study of State-of-the-art Methods', 'HorizonNet: Learning Room Layout with 1D Representation and Pano Stretch Data Augmentation'] | misc/post_proc.py train.py misc/gen_txt_structured3d.py misc/utils.py misc/zind_prepare_dataset.py dataset.py inference.py preprocess.py misc/pano_lsd_align.py eval_cuboid.py misc/structured3d_prepare_dataset.py layout_viewer.py misc/structured3d_extract_zip.py misc/panostretch.py model.py eval_general.py visualize_a_data cor2xybound cor_2_1d PanoCorBonDataset find_occlusion sort_xy_filter_unique gen_reg_from_xy eval_3diou test prepare_gtdt_pairs tri2halfspace xyzlst2halfspaces layout_2_depth test_general inference augment augment_undo find_N_peaks ConvCompressH Resnet Densenet wrap_lr_pad GlobalHeightConv GlobalHeightStage lr_pad LR_PAD HorizonNet feed_forward gen_pairs uv2xy visualize_pano_stretch v2coory _uv_tri u2coorx pano_connect_points coory2v uv_tri uv_meshgrid pano_stretch coorx2u panoEdgeDetection sphereHoughVote xyz2uvN _insideRange computeUVN uv2xyzN warpImageFast multi_linspace refitLineSegmentB icosahedron2sphere findMainDirectionEMA computeUVN_vec assignVanishingType combineEdgesN rotatePanorama separatePano lsdWrap curveFitting uv2xyzN_vec imgLookAt edgeFromImg2Pano _intersection paintParameterLine np_coor2xy _get_rot_rad mean_percentile get_rot_rad np_x_u_solve_y infer_coory vote np_xy2coor get_z1 gen_ww_general get_gpid np_y_u_solve_x gen_ww np_coorx2u get_gpid_idx gen_ww_cuboid np_coory2v fuv2img gpid_two_split np_refine_by_fix_z prepare_dataset load_trained_model adjust_learning_rate save_model group_weight run show_statistic label_iterator arange extend pi pano_connect_points interp sort_xy_filter_unique zeros range len argsort int max unique uv2xy len intersects coory2v append LineString range coorx2u uv2xy tan mean sqrt coory2v abs coorx2u uint8 reshape astype zeros numpy cross append range tri2halfspace HalfspaceIntersection tan concatenate hstack volume np_coory2v copy sqrt zeros sum array xyzlst2halfspaces len gen_reg_from_xy eval_3diou concatenate cumsum mean sqrt pano_connect_points infer_coory append zeros sum range glob sorted dict append tan arange cos float32 pi cor_2_1d repeat sin zeros abs str get_z1 np_coor2xy print Polygon layout_2_depth min area maximum mean append abs len argsort maximum_filter int roll round append numpy flip int roll startswith append numpy flip enumerate len tuple pi round clip FloatTensor to range visualize_a_data hstack mean stack augment net gen_ww int print float32 zeros np_refine_by_fix_z len named_modules int Sequential reduce setattr LR_PAD split FloatTensor to net binary_cross_entropy_with_logits l1_loss append join listdir root float64 astype pi stack meshgrid range tan cos uv_meshgrid sin _uv_tri tan cos sin uv2xy tan arctan2 v2coory float64 min astype sqrt coory2v floor ceil max coorx2u arctan arctan2 v2coory cos pi u2coorx sqrt stack coory2v uv_tri sin coorx2u LINE_AA polylines putText astype FONT_HERSHEY_SIMPLEX pano_connect_points range arctan array cos sin arctan cos copy roll repeat sin sum int hstack pi sqrt arcsin int cos zeros sin arange cos astype sin zeros len min shape stack floor ceil max T reshape float64 hstack inv xyz2uvN pi warpImageFast shape meshgrid zeros range uv2xyzN tan arctan concatenate reshape warpImageFast pi sqrt nonzero sin meshgrid zeros range ones_like int COLOR_RGB2GRAY line zeros_like concatenate ceil lsd range cvtColor T tan norm reshape hstack cos cross shape sqrt tile sin array xyz2uvN pi _insideRange vstack computeUVN argmax abs max clip uv2xyzN ones logical_and append sum range arccos hstack copy stack norm min zeros _intersection array len list T norm sqrt unique tile append sum array range len svd norm sum array norm clip arccos print reshape curveFitting xyz2uvN copy cross vstack zeros sum max range len arange sphereHoughVote xyz2uvN pi sign vstack linspace argmax abs clip ones argmin sin icosahedron2sphere sum range arccos setdiff1d hstack copy print reshape len arange pi vstack clip argmin multi_linspace sum arcsin range computeUVN_vec arccos hstack stack norm reshape uv2xyzN_vec min repeat zeros len ones reshape curveFitting hstack pi copy linspace computeUVN zeros range uv2xyzN len reshape hstack xyz2uvN astype pi copy linspace int32 computeUVN zeros max range uv2xyzN len arange pi vstack refitLineSegmentB array append range findMainDirectionEMA assignVanishingType combineEdgesN concatenate copy stack separatePano lsdWrap enumerate edgeFromImg2Pano zeros paintParameterLine arctan2 reshape map_coordinates meshgrid range tan cos np_coory2v sin array np_coorx2u sin cos sqrt arctan arctan2 percentile sort mean pdist squareform median argmax len tan np_coory2v mean_percentile tan np_coory2v arctan2 tan np_coory2v arctan2 zeros astype roll arange cumsum mean argmax len pi arctan2 int np_coor2xy sort hstack PCA len get_gpid _get_rot_rad mean append round range fit append range vote insert len mean np_y_u_solve_x vote append np_x_u_solve_y range np_coorx2u gen_ww_cuboid np_coor2xy hstack argmin gen_ww_general get_gpid roll append array range np_xy2coor len join tqdm symlink listdir in_root makedirs _ConvNd isinstance bias _BatchNorm modules GroupNorm append weight Linear cur_iter running_lr param_groups max_iters lr_pow warmup_lr lr warmup_iters float max OrderedDict save load Net load_state_dict items load join label_iterator print astype append array open load join LANCZOS arctan2 resize label_iterator pi outdir indir sqrt save width sum array open | sunset1995/HorizonNet | 3,769 |
superkido511/AdaMod-Keras | ['stochastic optimization'] | ['An Adaptive and Momental Bound Method for Stochastic Learning'] | AdaMod.py AdaMod | superkido511/AdaMod-Keras | 3,770 |
superlouis/GATGNN | ['graph attention'] | ['Global Attention based Graph Convolutional Neural Networks for Improved Materials Property Prediction'] | gatgnn/pytorch_early_stopping.py train.py gatgnn/utils.py gatgnn/model.py predict.py gatgnn/evaluate.py gatgnn/data.py evaluate.py gatgnn/file_setter.py GaussianDistance DATA_normalizer AtomCustomJSONInitializer CIF_Dataset ELEM_Encoder CIF_Lister AtomInitializer METRICS use_property COMPOSITION_Attention CLUSTER_Attention GATGNN GAT_Crystal EarlyStopping torch_MAE set_model_properties torch_accuracy load_metrics output_training print squeeze to_csv copyfile dropna read_csv size float max print tabulate load open | superlouis/GATGNN | 3,771 |
superlxt/RPNet-Pytorch | ['semantic segmentation'] | ['Residual Pyramid Learning for Single-Shot Semantic Segmentation'] | train.py data/__init__.py metric/__init__.py args.py test.py metric/confusionmatrix.py metric/iou.py data/camvid.py data/cityscapes.py metric/metric.py transforms.py utils.py main.py data/utils.py models/rpnet.py get_arguments train predict test load_dataset Test Train LongTensorToRGBPIL PILToLongTensor batch_transform load_checkpoint imshow_batch save_checkpoint dataaug CamVid Cityscapes enet_weighing remap median_freq_balancing get_files pil_loader ConfusionMatrix IoU Metric DownsamplerBlock RPNet non_bottleneck_1d add_argument ArgumentParser batch_transform print float size Compose index imshow_batch DataLoader color_encoding ignore_unlabeled dataset_dir save_dir weighing dataset next array len LambdaLR save_checkpoint RPNet Train save_dir cuda ignore_unlabeled print_step name Adam epochs run_epoch CrossEntropyLoss range format eval resume zip keys print load_checkpoint index parameters IoU step Test len format print_step print predict index keys dict imshow_batch next cuda zip IoU run_epoch ignore_unlabeled CrossEntropyLoss Test len data batch_transform model Variable Compose imshow_batch cuda cpu max show subplots transpose imshow numpy name join save_dir save load join load_state_dict warpAffine uint8 transpose astype float32 from_numpy randint numpy flip range OrderedDict OrderedDict append sort join walk open zeros_like isinstance Image zip array flatten numpy log flatten median bincount numpy | superlxt/RPNet-Pytorch | 3,772 |
supersidor/cartracking | ['multiple object tracking'] | ['Simple Online and Realtime Tracking'] | utils/utils.py utils/datasets.py object_tracker.py utils/parse_config.py models.py sort.py YOLOLayer create_modules Darknet EmptyLayer detect_image KalmanBoxTracker iou Sort convert_bbox_to_z associate_detections_to_trackers convert_x_to_bbox parse_args ImageFolder ListDataset parse_data_config parse_model_config compute_ap build_targets bbox_iou_numpy to_categorical weights_init_normal load_classes bbox_iou non_max_suppression pop int YOLOLayer Sequential ZeroPad2d MaxPool2d add_module Conv2d ModuleList EmptyLayer Upsample append BatchNorm2d LeakyReLU sum enumerate unsqueeze_ Variable Compose min type float round minimum maximum float sqrt linear_assignment iou concatenate reshape append zeros empty enumerate add_argument ArgumentParser rstrip strip open startswith append split dict strip split open data normal_ __name__ constant_ concatenate size maximum sum range clamp min max minimum eps expand_dims maximum data sort new squeeze size shape unsqueeze cuda unique bbox_iou append max is_cuda cat enumerate int fill_ FloatTensor ones concatenate size range unsqueeze bbox_iou zeros argmax log | # pytorch_objectdetecttrack Object detection in images, and tracking across video frames Full story at: https://towardsdatascience.com/object-detection-and-tracking-in-pytorch-b3cf1a696a98 References: 1. YOLOv3: https://pjreddie.com/darknet/yolo/ 2. Erik Lindernoren's YOLO implementation: https://github.com/eriklindernoren/PyTorch-YOLOv3 3. YOLO paper: https://pjreddie.com/media/files/papers/YOLOv3.pdf 4. SORT paper: https://arxiv.org/pdf/1602.00763.pdf 5. Alex Bewley's SORT implementation: https://github.com/abewley/sort | 3,773 |
sutd-visual-computing-group/dag-gans | ['data augmentation'] | ['On Data Augmentation for GAN Training'] | pytorch/examples/biggan/cifar/rotation-cropping-translation-cutout/BigGAN_DAG.py pytorch/examples/biggan/cifar/rotation/BigGAN_DAG.py tensorflow/config.py tensorflow/utils.py pytorch/examples/biggan/cifar/rotation-cropping/BigGAN_DAG.py pytorch/examples/biggan/cifar/rotation-cropping-translation-cutout/DAG_Augmentation.py pytorch/examples/biggan/cifar/rotation-cropping/train_fns.py pytorch/examples/biggan/cifar/rotation-cropping-translation-cutout/train_fns.py pytorch/examples/wgan-gp/gandag_cifar10.py pytorch/examples/cyclegan/cycle_gan_dag_model.py pytorch/examples/biggan/cifar/rotation-cropping/DAG_Augmentation.py pytorch/examples/cyclegan/util.py pytorch/examples/cyclegan/networks.py pytorch/config.py pytorch/examples/biggan/cifar/rotation/DAG_Augmentation.py pytorch/utils.py pytorch/dag.py pytorch/examples/biggan/cifar/rotation/train_fns.py tensorflow/dag.py DAG augmenting_data rotation fliprot cropping G_D Generator G_arch Discriminator D_arch croptr rand_cutout cropbr rotate180 flipv rotate90 rand_saturation croptl DAG_Augment rand_translation fliphv rotate270 cropbl fliph rand_contrast crop rand_brightness GAN_training_function save_and_sample test dummy_training_function G_D Generator G_arch Discriminator D_arch croptr rand_cutout cropbr rotate180 flipv rotate90 rand_saturation croptl DAG_Augment rand_translation fliphv rotate270 cropbl fliph rand_contrast crop rand_brightness GAN_training_function save_and_sample test dummy_training_function G_D Generator G_arch Discriminator D_arch croptr rand_cutout cropbr rotate180 flipv rotate90 rand_saturation croptl DAG_Augment rand_translation fliphv rotate270 cropbl fliph rand_contrast crop rand_brightness GAN_training_function save_and_sample test dummy_training_function CycleGANDAGModel get_norm_layer NLayerDiscriminator_Dag Identity GANLoss ResnetGenerator ResnetBlock define_D define_D_dag UnetGenerator UnetSkipConnectionBlock PixelDiscriminator init_weights get_scheduler init_net NLayerDiscriminator PixelDiscriminator_Dag cal_gradient_penalty define_G print_numpy diagnose_network mkdirs mkdir transform_image save_image tensor2im inf_train_gen get_inception_score Generator G_loss_func Discriminator calc_gradient_penalty generate_image D_loss_func DAG get_n_augments_from_policy rotation image_crop fliprot augmenting_data cropping append flip append flip clone shape interpolate append range print exit contiguous f clone permute split shape clone shape shape shape shape size rand mean size rand mean size rand arange clamp size pad permute meshgrid randint arange ones clamp size unsqueeze meshgrid randint accumulate_standing_stats save_weights mkdir interp_sheet zip cpu save_image sample_sheet print min accumulate_standing_stats mean eval save_weights train get_inception_metrics max log BatchNorm2d partial InstanceNorm2d LambdaLR CosineAnnealingLR ReduceLROnPlateau StepLR print apply init_weights to DataParallel ResnetGenerator UnetGenerator get_norm_layer NLayerDiscriminator PixelDiscriminator get_norm_layer PixelDiscriminator_Dag get_norm_layer NLayerDiscriminator_Dag view size rand grad mean requires_grad_ netD data isinstance transpose tile Tensor numpy print parameters fromarray shape BICUBIC save resize print float64 astype flatten shape mkdir makedirs flip view Variable size rand mean netD cuda mean calc_gradient_penalty netD mean netD format save_images view randn Variable add netG numpy cuda randn Variable concatenate transpose astype xrange append numpy cuda train_gen range len pi rotate flip_left_right flip_up_down resize_bilinear crop_to_bounding_box as_list int image_crop | sutd-visual-computing-group/dag-gans | 3,774 |
suvarna-kadam/Oct2018_Demo | ['few shot learning', 'active learning'] | ['Few-Shot Learning with Graph Neural Networks'] | data/__init__.py test.py data/omniglot.py data/parser.py data/generator.py main.py data/mini_imagenet.py train adjust_learning_rate _init_ train_batch test_one_shot Generator MiniImagenet Omniglot get_image_paths system exp_name makedirs LongTensor backward Variable forward nll_loss metric_nn numpy argmax cuda get_task_batch batch_size train_batch zero_grad SoftmaxModule test_one_shot iterations adjust_learning_rate dataset_root save cuda exp_name str create_models load_model Generator Adam range format print cprint parameters step param_groups int dec_lr argmax int get_task_batch format Variable Generator cprint IOStream metric_nn batch_size_test eval numpy dataset_root train forward cuda range exp_name join filter append walk split | # Few-Shot Learning with Graph Neural Networks Implementation of [Few-Shot Learning with Graph Neural Networks](https://arxiv.org/pdf/1711.04043.pdf) on Python3, Pytorch 0.3.1 ## Mini-Imagenet ### Download the dataset Create **images.zip** file and copy it inside ```mini_imagenet``` directory: . โโโ ... โโโ datasets โโโ compressed | 3,775 |
suyash/ContextualDecomposition | ['sentiment analysis'] | ['Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs'] | cd/acd.py cd/conv_1d.py cd/conv_2d.py cd/lstm.py cd/layers/__init__.py cd/cd_test.py cd/sst_eval.py cd/layers/conv.py cd/layers_test.py cd/layers/pool.py cd/acd_test.py cd/prepare_sst_dict.py cd/preprocess.py cd/cd.py conv1d_acd_decomposition acd_1d_decomposition agglomerate_acd_1d_decomposition lstm_acd_decomposition create_mask lstm_score conv1d_score LSTMACDDecompositionTest cnn_net_decomposition _decomp_three act_decomposition conv1d_decomposition max_pool1d_decomposition _decomp_two lstm_decomposition CNNDecomposition MaxPool1DDecompositionTest LSTMDecompositionTest CNN1DDecompositionTest main prepare_model prepare_dataset prepare_decomp_model prepare_model prepare_pure_conv_model main train MaxPool2DTest Conv2DTest DenseTest main prepare_model main preprocess_dataset create_inv_table prepare_datasets create_table main Conv2D MaxPool2D Dense Activation sum abs max score size argmin create_mask nan append label argmax array range lstm_decomposition numpy matmul embedding_lookup size weights sum items size argmin unique append label argmax max range len cnn_net_decomposition numpy matmul embedding_lookup size weights append range len tanh _decomp_three matmul sigmoid _decomp_two zeros range split f abs conv1d reshape squeeze max_pool_with_argmax shape gather expand_dims concat act_decomposition conv1d_decomposition shape max_pool1d_decomposition append append Input enumerate load prepare_datasets SparseCategoricalCrossentropy value set_seed join fit Adam conv_layers prepare_model SparseCategoricalAccuracy loads save summary steps_per_epoch compile len Input Input load ExponentialDecay SparseCategoricalCrossentropy join compile TensorBoard EarlyStopping Adam prepare_model SparseCategoricalAccuracy repeat save summary batch fit train decode list defaultdict items sorted map info split range len range len map padded_batch create_table preprocess_dataset cache shuffle map repeat AUTOTUNE prefetch batch load_model create_table evaluate preprocess_dataset model_dir filter batch | suyash/ContextualDecomposition | 3,776 |
svip-lab/FastMVSNet | ['depth estimation'] | ['Fast-MVSNet: Sparse-to-Dense Multi-View Stereo With Learned Propagation and Gauss-Newton Refinement'] | fastmvsnet/utils/torch_utils.py fastmvsnet/networks.py fastmvsnet/solver.py fastmvsnet/nn/conv.py fastmvsnet/config.py fastmvsnet/test.py fastmvsnet/dataset.py fastmvsnet/utils/eval_file_logger.py fastmvsnet/train.py fastmvsnet/functions/functions.py fastmvsnet/nn/functional.py fastmvsnet/utils/checkpoint.py fastmvsnet/utils/feature_fetcher.py fastmvsnet/utils/tensorboard_logger.py fastmvsnet/nn/mlp.py fastmvsnet/nn/freeze_weight.py fastmvsnet/nn/linear.py fastmvsnet/utils/metric_logger.py fastmvsnet/utils/file_logger.py fastmvsnet/utils/preprocess.py fastmvsnet/nn/init.py fastmvsnet/utils/io.py tools/depthfusion.py fastmvsnet/model.py fastmvsnet/utils/logger.py load_cfg_from_file DTU_Test_Set DTU_Train_Val_Set build_data_loader cal_less_percentage PointMVSNetMetric PointMVSNetLoss cal_valid_less_percentage build_pointmvsnet FastMVSNet VolumeConv Valid_MAELoss ImageConv PropagationNet MAELoss build_scheduler build_optimizer group_weight register_optimizer_builder main parse_args test_model test train_model validate_model main parse_args train get_pixel_grids get_propability_map Deconv2d Conv3d Deconv3d Conv2d Deconv2d_gn Conv1d Conv2d_gn _unfreeze_all_params unfreeze_by_patterns freeze_params freeze_bn unfreeze_modules freeze_by_patterns freeze_modules unfreeze_params _freeze_all_params encode_one_hot pdist pdist2 smooth_cross_entropy init_uniform set_eps set_bn init_bn FC SharedMLP MLP Checkpointer save_points depth2pts_np get_pixel_grids_np eval_file_logger FeatureGradFetcher FeatureFetcher ProjectUVFetcher PointGrad test_feature_fetching save_points depth2pts file_logger write_cam_dtu load_pfm write_pfm mkdir load_cam_dtu shutdown_logger setup_logger AverageMeter MetricLogger scale_dtu_input norm_image crop_dtu_input scale_image mask_depth_image scale_camera TensorboardLogger get_knn_3d set_random_seed read_gipuma_dmb mvsnet_to_gipuma_dmb depth_map_fusion fake_colmap_normal write_gipuma_dmb mvsnet_to_gipuma_cam mkdir mvsnet_to_gipuma probability_filter probability_filter2 merge_from_other_cfg tensor tensor DataLoader DTU_Test_Set DTU_Train_Val_Set BATCH_SIZE sum list abs size expand float type sum list abs size expand interpolate float type PointMVSNetMetric PointMVSNetLoss FastMVSNet optim TYPE hasattr print list append named_parameters lr_scheduler TYPE hasattr add_argument ArgumentParser time MetricLogger getLogger __len__ train load time format replace info build_model getLogger test_model WEIGHT build_data_loader Checkpointer cuda format replace cpu load_cfg_from_file config_file freeze setup_logger test merge_from_list device_count mkdir info opts parse_args OUTPUT_DIR getLogger model zero_grad file_logger values MetricLogger metric_fn sum update format info add_scalars enumerate time backward extend __len__ loss_fn train step time MetricLogger getLogger __len__ train CHECKPOINT_PERIOD getLogger set_random_seed TensorboardLogger validate_model save build_scheduler cuda str build_optimizer VAL_PERIOD range get VAL_METRIC format build_model WEIGHT build_data_loader info load train_model time MAX_EPOCH RNG_SEED summary_str Checkpointer global_avg step train named_modules isinstance named_parameters eval BatchNorm2d print search named_parameters items list print search eval _freeze_all_params append freeze_modules freeze_params startswith named_parameters print search named_parameters items list _unfreeze_all_params print search eval append startswith print named_parameters transpose sum baddbmm transpose sum baddbmm unsqueeze size scatter new_zeros ones_like log_softmax mean shape unsqueeze scatter zeros_ ones_ weight bias modules isinstance xavier_uniform_ weight zeros_ bias modules isinstance imwrite arange write_pfm clip write_cam_dtu save_points squeeze sum format copy mkdir tile depth2pts_np keys enumerate join int savez print reshape numpy array split reshape transpose inv matmul get_pixel_grids_np concatenate reshape astype linspace meshgrid float savetxt print feature_fetcher matmul unsqueeze inverse savetxt allclose numpy cuda join list format print save_points size transpose clone savetxt mkdir depth2pts numpy range view concatenate resize reshape size transpose clone matmul copy unsqueeze inverse device to makedirs zeros float range split str close write range open decode list rstrip reshape map groups match flipud fromfile float open byteorder write close tostring flipud encode open setFormatter join format getLogger addHandler StreamHandler Formatter setLevel INFO FileHandler mean var astype float32 expand_dims THRESH_TOZERO threshold THRESH_TOZERO_INV copy len range scale_camera scale_image int floor range len seed manual_seed_all manual_seed list topk view to clamp size conv3d expand permute device zeros float sum range reshape shape squeeze write_gipuma_dmb str load_cam_dtu write close matmul range open ones_like read_gipuma_dmb reshape squeeze multiply float32 where shape write_gipuma_dmb tile join format imwrite mvsnet_to_gipuma_dmb fake_colmap_normal mkdir mvsnet_to_gipuma_cam resize imread range join format write_pfm resize range join format write_pfm resize range print join system str | # Fast-MVSNet PyTorch implementation of our CVPR 2020 paper: [Fast-MVSNet: Sparse-to-Dense Multi-View Stereo With Learned Propagation and Gauss-Newton Refinement](https://arxiv.org/pdf/2003.13017.pdf) Zehao Yu, [Shenghua Gao](http://sist.shanghaitech.edu.cn/sist_en/2018/0820/c3846a31775/page.htm) ## How to use ```bash git clone [email protected]:svip-lab/FastMVSNet.git ``` ### Installation | 3,777 |
svip-lab/Indoor-SfMLearner | ['depth estimation', 'superpixels'] | ['P$^{2}$Net: Patch-match and Plane-regularization for Unsupervised Indoor Depth Estimation', 'PยฒNet: Patch-match and Plane-regularization for Unsupervised Indoor Depth Estimation'] | networks/depth_decoder.py datasets/extract_svo_point.py train_geo.py datasets/scannet_dataset.py evaluation/nyuv2_eval_depth.py inference_single_image.py networks/particalconv.py networks/pose_cnn.py networks/__init__.py extract_superpixel.py layers.py options.py evaluation/scannet_eval_depth.py utils.py evaluation/nyuv2_eval_norm.py evaluation/scannet_eval_pose.py datasets/nyu_dataset.py networks/pose_decoder.py datasets/__init__.py trainer_geo.py networks/network.py networks/resnet_encoder.py evaluation/__init__.py extract_superpixel images2seg undistort parse_args prepare_model_for_test inference rot_from_axisangle BackprojectDepth get_smooth_loss compute_depth_errors upsample Project3D SSIM_sparse Conv3x3 get_translation_matrix SSIM transformation_from_parameters disp_to_depth ConvBlock MonodepthOptions is_nan mat_3x3_det inv_SE3 compute_errors Trainer mat_3x3_inv print_notification has_nan sec_to_hm sec_to_hm_str normalize_image readlines download_model_if_doesnt_exist extract_points PixelSelector NYUDataset NYUTestDataset h5_loader pil_loader ScannetTestDepthDataset ScannetTestPoseDataset pil_loader batch_post_process_disparity prepare_model_for_test compute_errors evaluate evaluate prepare_model_for_test compute_errors batch_post_process_disparity compute_normal_errors depth_2_normal batch_post_process_disparity prepare_model_for_test compute_errors evaluate compute_pose_errors prepare_model_for_test evaluate DepthDecoder get_norm_layer PixelDiscriminator Identity GANLoss ResnetGenerator ResnetBlock define_D UnetGenerator UnetSkipConnectionBlock NLayerDiscriminatorPartial init_weights get_scheduler init_net ResNetDiscriminator NLayerDiscriminator cal_gradient_penalty define_G PartialConv2d PoseCNN PoseDecoder ResnetEncoder ResNetMultiImageInput resnet_multiimage_input array join zip img_as_float rgb2gray resize felzenszwalb imread sobel undistort append join savez add_argument ArgumentParser load join print eval model_name ResnetEncoder load_state_dict DepthDecoder print image_path prepare_model_for_test device rot_from_axisangle transpose clone matmul get_translation_matrix to view norm squeeze cos unsqueeze sin to mean abs mean sqrt abs max log print format mat_3x3_det zeros view shape view size contiguous astype float32 device to cat maximum mean sqrt abs log data float int sec_to_hm join format urlretrieve print quit makedirs COLOR_RGB2GRAY data_as astype float32 main cvtColor transpose File array log10 meshgrid shape linspace num_ch_enc format num_layers load_weights_folder expanduser format NYUTestDataset std print readlines prepare_model_for_test data_path mean DataLoader median array clamp flip cross normalize size arccos pi mean cpu clip BackprojectDepth ScannetTestDepthDataset minimum T arccos pi dot sqrt trace sum PoseDecoder height ScannetTestPoseDataset width BatchNorm2d partial InstanceNorm2d LambdaLR CosineAnnealingLR ReduceLROnPlateau StepLR print apply init_weights to DataParallel ResnetGenerator UnetGenerator get_norm_layer NLayerDiscriminator PixelDiscriminator get_norm_layer NLayerDiscriminatorPartial view size rand grad mean requires_grad_ netD load_url cat load_state_dict ResNetMultiImageInput | svip-lab/Indoor-SfMLearner | 3,778 |
svjack/PhotoWCT | ['image stylization'] | ['A Closed-form Solution to Photorealistic Image Stylization'] | WCT/train_edit.py WCT/coral.py WCT/model_edit.py WCT/stylize.py merge_pics_segs/merge.py WCT/wct_edit.py WCT/vgg_normalised.py WCT/ops.py WCT/torchfile.py WCT/utils.py zip_image_seg matSqrt_numpy coral_numpy single_unpooling_func WCTModel test_ resize_mask feature_map_lookedup stacklized_one_hot torch_decay Conv2DReflect unpooling wct_np wct_style_swap style_swap pad_reflect adain wct_tf main image_to_pixel_map l3_assign colors_map load tds_Hash_reader hashable_uniq_dict mycontainer T7ReaderException register_handler T7Reader tds_Vec_reader add_storage_reader add_notimpl_reader TorchObject add_tensor_reader train batch_gen get_img get_img_seg_random_crop resize_to center_crop_to save_img center_crop image_to_pixel_map preserve_colors_np get_img_ori get_img_random_crop swap_filter_fit get_files get_img_crop l3_assign colors_map test_ vgg_from_t7 single_pooling_func WCT fromarray list asarray uint8 format glob print transpose convert astype open mkdir save sample range len dot svd T T reshape mean dot shape eye moveaxis std expand_dims stacklized_one_hot unstack resize_mask WCTModel reshape resize_images gather reshape transpose squeeze float32 matmul reduce_sum greater shape reduce_mean pow unstack cast eye int32 expand_dims diag svd T reshape transpose squeeze mean dot sqrt shape expand_dims sum diag reshape transpose squeeze float32 matmul reduce_sum greater shape reduce_mean pow unstack cast eye int32 style_swap expand_dims diag conv2d_transpose one_hot extract_image_patches l2_normalize ones reshape transpose divide reduce_sum deconv_output_length shape conv2d stack tile argmax sqrt batch_normalization moments list shape l3_assign_vec reshape passes out_path style_size concat random preserve_colors_np get_files list basename resize_to center_crop len adain style_path get_img_ori crop_size keep_colors range predict format concatenate imresize content_path astype hstack choice splitext alpha ss_alpha get_img time join isdir print save_img float32 WCT swap5 makedirs append range read_obj read_int hashable_uniq_dict range read_obj read_int asarray replace astype float32 choice get_files zeros append join listdir uint8 astype imsave imread dstack asarray open resize_to max imresize round get_img resize_to get_img randint resize_to asarray resize_to concatenate randint open uint8 coral_numpy clip range dwt2 modules transpose identity conv2d pad_reflect unstack append kH relu map_fn stack enumerate load int nOutputPlane reshape max_pool_with_argmax bias add_to_collection print trainable_variables pprint vgg_from_t7 | svjack/PhotoWCT | 3,779 |
swanjing/Contextual-Bandits-Active-Learning | ['active learning'] | ['libact: Pool-based Active Learning in Python'] | libact/query_strategies/uniform_bandits_active_learning.py libact/query_strategies/bandits/algorithms/parameter_noise_sampling.py libact/query_strategies/bandits/algorithms/uniform_sampling.py libact/query_strategies/bandits/algorithms/linear_full_posterior_sampling.py libact/query_strategies/multilabel/__init__.py libact/query_strategies/multi_bandits_active_learning.py libact/query_strategies/tests/test_quire.py libact/query_strategies/query_by_committee.py libact/query_strategies/density_weighted_meta.py libact/query_strategies/random_sampling.py libact/query_strategies/bandits/core/dataset.py libact/query_strategies/tests/test_realdata.py libact/query_strategies/tests/utils.py libact/labelers/__init__.py libact/query_strategies/variance_reduction.py libact/query_strategies/multiclass/tests/test_hierarchical_sampling.py libact/query_strategies/bandits/algorithms/neural_bandit_model.py libact/models/multilabel/binary_relevance.py libact/query_strategies/tests/test_density_weighted_meta.py libact/base/interfaces.py docs/conf.py libact/labelers/interactive_labeler.py libact/models/perceptron.py libact/models/sklearn_adapter.py libact/labelers/tests/test_labelers.py libact/query_strategies/bandits/data/synthetic_data_sampler.py libact/query_strategies/tests/test_hintsvm.py libact/query_strategies/bandits/core/model.py libact/query_strategies/hintsvm.py libact/query_strategies/bandits/core/contextual_dataset.py libact/query_strategies/multiclass/mdsp.py libact/query_strategies/__init__.py libact/query_strategies/tests/test_uncertainty_sampling.py libact/models/svm.py libact/query_strategies/bandits/algorithms/multitask_gp.py libact/query_strategies/bandits/algorithms/bb_alpha_divergence_model.py libact/query_strategies/bandits/algorithms/posterior_bnn_sampling.py libact/utils/tests/test_criteria.py libact/query_strategies/multilabel/multilabel_with_auxiliary_learner.py libact/query_strategies/representative_sampling.py libact/query_strategies/bandits/algorithms/fixed_policy_sampling.py libact/query_strategies/bandits/core/bayesian_nn.py libact/base/tests/test_dataset.py libact/query_strategies/bandits/algorithms/bootstrapped_bnn_sampling.py libact/models/multilabel/dummy_clf.py libact/models/multilabel/tests/test_binary_relevance.py libact/query_strategies/bandits/core/bandit_algorithm.py libact/utils/multilabel/__init__.py libact/query_strategies/multiclass/tests/test_iris.py libact/query_strategies/bandits/algorithms/neural_linear_sampling.py libact/query_strategies/multiclass/expected_error_reduction.py libact/query_strategies/multilabel/tests/test_multilabel_realdata.py libact/query_strategies/multiclass/__init__.py libact/__init__.py libact/query_strategies/multiclass/hierarchical_sampling.py libact/query_strategies/multilabel/adaptive_active_learning.py libact/query_strategies/bandits/algorithms/__init__.py libact/query_strategies/tests/test_variance_reduction.py libact/query_strategies/bandits/data/data_sampler.py libact/query_strategies/contextual_bandits_active_learning.py libact/query_strategies/quire.py libact/models/logistic_regression.py libact/query_strategies/multiclass/active_learning_with_cost_embedding.py libact/query_strategies/multilabel/maximum_margin_reduction.py libact/query_strategies/multilabel/cost_sensitive_reference_pair_encoding.py libact/models/__init__.py libact/utils/__init__.py libact/query_strategies/active_learning_by_learning.py libact/query_strategies/density_weighted_uncertainty_sampling.py libact/query_strategies/multilabel/binary_minimization.py libact/query_strategies/bandits/algorithms/variational_neural_bandit_model.py libact/labelers/ideal_labeler.py libact/models/multilabel/__init__.py libact/query_strategies/uncertainty_sampling.py libact/query_strategies/bandits/algorithms/bf_variational_neural_bandit_model.py libact/query_strategies/bandits/core/contextual_bandit.py libact/base/dataset.py skip_private_member setup import_scipy_mat import_libsvm_sparse Dataset DatasetBiome ProbabilisticModel Labeler QueryStrategy ContinuousModel Model MultilabelModel TestDatasetMethods IdealLabeler InteractiveLabeler TestDatasetMethods LogisticRegression Perceptron SklearnAdapter SklearnProbaAdapter SVM _fit_model BinaryRelevance DummyClf BinaryRelevanceTestCase ActiveLearningByLearning Exp4P ContextualBanditsActiveLearning DensityWeightedMeta DensityWeightedLogisticRegression DWUS HintSVM Exp4P MultiBanditsActiveLearning QueryByCommittee QUIRE RandomSampling UncertaintySampling UniformBanditsActiveLearning _E _Phi VarianceReduction log_gaussian BBAlphaDivergence analytic_kl log_gaussian BfVariationalNeuralBanditModel BootstrappedBNNSampling FixedPolicySampling LinearFullPosteriorSampling MultitaskGP NeuralBanditModel NeuralLinearPosteriorSampling ParameterNoiseSampling PosteriorBNNSampling UniformSampling VariationalNeuralBanditModel analytic_kl log_gaussian BanditAlgorithm BayesianNN ContextualBandit run_contextual_bandit ContextualDataset DataHandler1 DataHandler3 DataHandler2 DataHandlerBiome get_dataset get_MNIST get_CIFAR10 get_handler get_SVHN get_FashionMNIST get_Biome Net1 NetBiome Net3 Net2 get_net one_hot sample_statlog_data sample_albl_data sample_jester_data sample_stock_data remove_underrepresented_classes sample_census_data classification_to_bandit_problem sample_mushroom_data sample_covertype_data sample_adult_data safe_std sample_wheel_bandit_data sample_contextual_data sample_linear_data sample_sparse_linear_data ActiveLearningWithCostEmbedding EER HierarchicalSampling _smacof_single_p MDSP smacof_p HierarchicalSamplingTestCase IrisTestCase _calc_approx_err AdaptiveActiveLearning BinaryMinimization BinaryCLF CSRPE CostSensitiveReferencePairEncoding MaximumLossReductionMaximalConfidence MultilabelWithAuxiliaryLearner MultilabelRealdataTestCase DensityWeightedMetaTestCase UncertaintySamplingTestCase QUIRETestCase RealdataTestCase UncertaintySamplingTestCase run_qs init_toyexample VarianceReductionTestCase run_qs inherit_docstring_from calc_cost seed_random_state pairwise_f1_score pairwise_rank_loss MultiLabelCriteriaTestCase startswith connect load_svmlight_file list loadmat shuffle zip reshape array train Dataset estVar predict_real copy sigmoid vstack append train Dataset range len log_prob kl_divergence MVNDiag square log pi square log update context ContextualBandit vstack feed_data empty range enumerate MNIST test_data train_labels train_data test_labels FashionMNIST test_data train_labels train_data test_labels data labels from_numpy SVHN from_numpy test_data train_labels CIFAR10 train_data array test_labels load arange close shuffle tensor open drop concat get_dummies list columns one_hot ones reshape choice range max read_csv normal shuffle dot uniform argmax argmax array shuffle remove_underrepresented_classes astype shuffle remove_underrepresented_classes as_matrix get_dummies sample drop remove_underrepresented_classes as_matrix get_dummies sample drop sample remove_underrepresented_classes as_matrix drop load close sample argmax array open mean zeros max safe_std list print astype dict unique zip normal dot uniform argmax array normal multiply flatten dot uniform zeros argmax array normal uniform stack append argmax array range T check_random_state euclidean_distances ones reshape print inv rand copy ravel dot IsotonicRegression sum check_symmetric range fit_transform list check_random_state hasattr check_array argmin copy warn zip _smacof_single_p randint max range train max predict_real copy Dataset concatenate update list make_query zip append label range RandomState isinstance sum sum astype | swanjing/Contextual-Bandits-Active-Learning | 3,780 |
swarooprm/DQI | ['active learning'] | ['DQI: Measuring Data Quality in NLP'] | p6.py p3.py p4g.py param7.py p4.py p4b.py func2 amaxelements func main parameter4 parameter4 parameter4 find_ngrams get_embeddings_from_id_tensors cosine_similarity_n_space var list Series tqdm similarity nlp append range len remove range len list tqdm similarity nlp append amaxelements abs range len list to_csv similarity tqdm nlp split append DataFrame range len add_argument output_path dataset_path ArgumentParser parameter4 parse_args read_csv len abs int list ndarray print min tqdm shape cosine_similarity range tqdm | swarooprm/DQI | 3,781 |
swathic5/Depth-estimation-using-neural-networks | ['depth estimation'] | ['Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields'] | libs/vlfeat-0.9.18/docsrc/mdoc.py libs/matconvnet_20141015/utils/proto/caffe_pb2.py libs/matconvnet_20141015/utils/proto/vgg_caffe_pb2.py libs/vlfeat-0.9.18/docsrc/wikidoc.py libs/vlfeat-0.9.18/docsrc/doxytag.py libs/vlfeat-0.9.18/docsrc/formatter.py libs/matconvnet_20141015/utils/import-caffe.py libs/matconvnet_20141015/utils/proto/caffe_old_pb2.py libs/vlfeat-0.9.18/docsrc/webdoc.py bilinear_interpolate blobproto_to_array get_output_size keyboard NetParameter LayerConnection BlobProto BlobProtoVector LayerParameter FillerParameter Datum SolverParameter SolverState BlobProto BlobProtoVector PowerParameter LayerParameter FillerParameter V0LayerParameter InnerProductParameter ConvolutionParameter SolverState WindowDataParameter HDF5OutputParameter ConcatParameter DataParameter SolverParameter NetParameter PoolingParameter DropoutParameter Datum MemoryDataParameter LRNParameter ImageDataParameter InfogainLossParameter HDF5DataParameter NetParameter EvalHistoryIter LayerConnection BlobProto BlobProtoVector LayerParameter FillerParameter Datum EvalHistory SolverParameter SolverState Doxytag Terminal Lexer B PL L lex Formatter DL BL E extract towiki depth_first breadCrumb MFile Node runcmd xscan wikidoc usage update print f_locals interact copy reshape asarray astype clip bullet indent inner_content PL group match DL BL len pid Popen waitpid children group lstrip match startswith append open join addMFile addChildNode print sort MFile Node match listdir __next__ prev runcmd join wikidoc print print insert print readlines close len writelines append range exists open | Demo - https://www.youtube.com/watch?v=YO5Zcw_0VP8 This project is an extended version of Fayao Liu's published work - https://bitbucket.org/fayao/dcnf-fcsp (https://arxiv.org/pdf/1502.07411.pdf) I am citing their work. On top of their work, I have built a GUI using Matlab guide to better show the results. I have also extended the test samples to use more images from datasets. Please download trained model files from - https://drive.google.com/drive/folders/1pgLLw2o2vuZo3zMdCSbRAmLT6Pu3hvyu?usp=sharing Dependencies: Matlab 2019 version A machine with GPU available Cuda 10 GCC 6.3x VLFeat MatConvNet library is used to build the network. The library is compiled with above dependencies, so if you are running with anything different, be sure to recompile it using the information at http://www.vlfeat.org/matconvnet/install/#compiling | 3,782 |
swathikirans/GSM | ['action recognition'] | ['Gate-Shift Networks for Video Action Recognition'] | model_zoo/models/slim/nets/cifarnet.py model_zoo/models/differential_privacy/multiple_teachers/train_teachers.py model_zoo/models/slim/datasets/dataset_factory.py model_zoo/models/textsum/seq2seq_attention_model.py model_zoo/models/slim/datasets/download_and_convert_flowers.py model_zoo/models/slim/nets/inception_v4.py test_models.py model_zoo/models/im2txt/im2txt/show_and_tell_model_test.py model_zoo/models/im2txt/im2txt/ops/image_embedding.py model_zoo/models/video_prediction/prediction_train.py model_zoo/models/street/python/decoder.py model_zoo/models/differential_privacy/multiple_teachers/analysis.py model_zoo/models/swivel/prep.py model_zoo/models/autoencoder/Utils.py model_zoo/models/inception/inception/slim/slim.py model_zoo/inceptionv4/tensorflow_dump.py model_zoo/models/slim/nets/alexnet.py model_zoo/models/differential_privacy/privacy_accountant/tf/accountant.py data_scripts/process_dataset_something.py model_zoo/models/slim/preprocessing/vgg_preprocessing.py model_zoo/models/slim/nets/inception_v3_test.py model_zoo/models/slim/nets/resnet_v2_test.py model_zoo/__init__.py model_zoo/models/slim/datasets/download_and_convert_cifar10.py model_zoo/models/im2txt/im2txt/configuration.py model_zoo/models/textsum/beam_search.py model_zoo/models/slim/preprocessing/preprocessing_factory.py model_zoo/models/textsum/data.py model_zoo/models/inception/inception/imagenet_data.py model_zoo/models/inception/inception/slim/scopes.py model_zoo/models/syntaxnet/syntaxnet/beam_reader_ops_test.py model_zoo/models/im2txt/im2txt/run_inference.py model_zoo/models/street/python/vgsl_model_test.py model_zoo/models/swivel/wordsim.py model_zoo/models/im2txt/im2txt/ops/image_processing.py model_zoo/models/street/python/vgslspecs_test.py model_zoo/models/neural_gpu/data_utils.py model_zoo/models/swivel/glove_to_shards.py model_zoo/models/street/python/nn_ops.py data_scripts/extract_frames_diving48.py model_zoo/models/resnet/resnet_main.py model_zoo/models/slim/nets/resnet_v2.py model_zoo/models/im2txt/im2txt/inference_utils/vocabulary.py model_zoo/models/slim/datasets/imagenet.py model_zoo/inceptionresnetv2/tensorflow_dump.py model_zoo/models/inception/inception/slim/inception_test.py model_zoo/models/slim/deployment/model_deploy.py model_zoo/models/slim/nets/inception_resnet_v2.py model_zoo/models/textsum/data_convert_example.py model_zoo/models/slim/nets/vgg_test.py model_zoo/models/video_prediction/prediction_input.py model_zoo/models/street/python/vgsl_eval.py model_zoo/models/inception/inception/slim/scopes_test.py model_zoo/models/autoencoder/autoencoder_models/Autoencoder.py model_zoo/models/inception/inception/slim/ops_test.py model_zoo/models/differential_privacy/dp_sgd/per_example_gradients/per_example_gradients.py model_zoo/models/textsum/batch_reader.py model_zoo/models/slim/nets/inception.py model_zoo/models/differential_privacy/multiple_teachers/train_student.py model_zoo/models/inception/inception/slim/losses.py model_zoo/bninception/caffe_pb2.py model_zoo/models/syntaxnet/syntaxnet/parser_eval.py model_zoo/models/slim/nets/inception_v3.py model_zoo/models/slim/nets/inception_utils.py model_zoo/models/differential_privacy/privacy_accountant/python/gaussian_moments.py model_zoo/models/neural_programmer/data_utils.py model_zoo/models/swivel/nearest.py model_zoo/models/autoencoder/MaskingNoiseAutoencoderRunner.py model_zoo/models/syntaxnet/syntaxnet/reader_ops_test.py model_zoo/models/inception/inception/slim/collections_test.py model_zoo/models/slim/deployment/model_deploy_test.py dataset.py model_zoo/models/im2txt/im2txt/ops/image_embedding_test.py model_zoo/models/transformer/cluttered_mnist.py model_zoo/models/street/python/vgsl_input.py model_zoo/models/differential_privacy/multiple_teachers/deep_cnn.py model_zoo/models/textsum/seq2seq_attention.py model_zoo/models/neural_programmer/parameters.py model_zoo/models/neural_programmer/neural_programmer.py model_zoo/models/swivel/vecs.py model_zoo/models/compression/encoder.py model_zoo/models/syntaxnet/syntaxnet/text_formats_test.py model_zoo/models/differential_privacy/dp_sgd/dp_optimizer/utils.py CosineAnnealingLR.py model_zoo/models/inception/inception/data/build_imagenet_data.py model_zoo/models/im2txt/im2txt/train.py main.py model_zoo/models/inception/inception/data/preprocess_imagenet_validation_data.py model_zoo/bninception/parse_caffe.py model_zoo/models/swivel/swivel.py model_zoo/models/inception/inception/inception_eval.py model_zoo/models/im2txt/im2txt/show_and_tell_model.py model_zoo/models/slim/nets/inception_v1.py model_zoo/inceptionv4/pytorch_load.py model_zoo/models/autoencoder/AutoencoderRunner.py model_zoo/models/street/python/errorcounter_test.py model_zoo/bninception/pytorch_load.py model_zoo/models/transformer/example.py model_zoo/models/inception/inception/data/process_bounding_boxes.py datasets_video.py download_models.py model_zoo/models/differential_privacy/dp_sgd/dp_optimizer/dp_pca.py data_scripts/process_dataset_diving.py opts.py model_zoo/models/autoencoder/VariationalAutoencoderRunner.py model_zoo/models/im2txt/im2txt/data/build_mscoco_data.py model_zoo/models/inception/inception/slim/losses_test.py model_zoo/models/lm_1b/data_utils.py model_zoo/models/syntaxnet/syntaxnet/graph_builder.py model_zoo/models/im2txt/im2txt/inference_utils/inference_wrapper_base.py model_zoo/models/syntaxnet/syntaxnet/parser_trainer.py model_zoo/models/slim/nets/overfeat.py model_zoo/models/namignizer/data_utils.py model_zoo/models/resnet/resnet_model.py model_zoo/models/video_prediction/lstm_ops.py model_zoo/models/inception/inception/data/build_image_data.py ops/__init__.py model_zoo/models/slim/nets/inception_v1_test.py model_zoo/models/differential_privacy/multiple_teachers/metrics.py model_zoo/models/lm_1b/lm_1b_eval.py model_zoo/models/syntaxnet/syntaxnet/lexicon_builder_test.py model_zoo/models/slim/train_image_classifier.py model_zoo/models/video_prediction/prediction_model.py model_zoo/models/inception/inception/slim/ops.py model_zoo/models/swivel/text2bin.py model_zoo/models/street/python/vgslspecs.py model_zoo/models/textsum/seq2seq_lib.py model_zoo/models/namignizer/model.py model_zoo/models/inception/inception/slim/inception_model.py model_zoo/models/im2txt/im2txt/evaluate.py model_zoo/models/street/python/decoder_test.py model_zoo/models/textsum/seq2seq_attention_decode.py model_zoo/models/neural_gpu/neural_gpu.py model_zoo/models/compression/decoder.py model_zoo/models/slim/datasets/flowers.py model_zoo/models/street/python/vgsl_train.py model_zoo/models/differential_privacy/multiple_teachers/utils.py model_zoo/models/inception/inception/imagenet_train.py model_zoo/models/inception/inception/slim/variables.py model_zoo/models/slim/datasets/dataset_utils.py model_zoo/models/slim/nets/inception_resnet_v2_test.py model_zoo/models/slim/download_and_convert_data.py model_zoo/models/slim/nets/resnet_utils.py model_zoo/models/transformer/spatial_transformer.py model_zoo/models/inception/inception/inception_model.py model_zoo/models/slim/datasets/mnist.py model_zoo/models/im2txt/im2txt/inference_utils/caption_generator_test.py model_zoo/models/slim/preprocessing/cifarnet_preprocessing.py model_zoo/inceptionresnetv2/pytorch_load.py model_zoo/models/inception/inception/flowers_train.py model_zoo/models/slim/preprocessing/inception_preprocessing.py model_zoo/models/im2txt/im2txt/ops/inputs.py model_zoo/models/street/python/errorcounter.py model_zoo/models/differential_privacy/multiple_teachers/aggregation.py model_zoo/models/slim/nets/resnet_v1.py model_zoo/bninception/layer_factory.py model_zoo/models/slim/nets/lenet.py model_zoo/models/slim/nets/nets_factory.py model_zoo/models/slim/nets/resnet_v1_test.py model_zoo/models/slim/datasets/download_and_convert_mnist.py model_zoo/models/syntaxnet/syntaxnet/structured_graph_builder.py model_zoo/models/slim/nets/inception_v4_test.py model_zoo/models/street/python/vgsl_model.py model_zoo/models/autoencoder/autoencoder_models/DenoisingAutoencoder.py model_zoo/models/slim/datasets/cifar10.py model_zoo/models/im2txt/im2txt/inference_wrapper.py model_zoo/models/slim/nets/overfeat_test.py model_zoo/models/neural_programmer/model.py model_zoo/models/slim/nets/alexnet_test.py model_zoo/models/autoencoder/AdditiveGaussianNoiseAutoencoderRunner.py model_zoo/models/street/python/shapes_test.py model_zoo/models/differential_privacy/dp_sgd/dp_optimizer/sanitizer.py model_zoo/models/inception/inception/image_processing.py model_zoo/models/slim/nets/inception_v2.py model_zoo/models/autoencoder/autoencoder_models/VariationalAutoencoder.py model_zoo/models/differential_privacy/multiple_teachers/input.py model_zoo/models/inception/inception/slim/variables_test.py model_zoo/models/inception/inception/flowers_data.py gsm.py model_zoo/models/neural_programmer/nn_utils.py model_zoo/models/transformer/tf_utils.py model_zoo/models/differential_privacy/dp_sgd/dp_mnist/dp_mnist.py model_zoo/models/slim/nets/inception_v2_test.py model_zoo/models/compression/msssim.py average_scores.py model_zoo/models/neural_gpu/neural_gpu_trainer.py model_zoo/models/syntaxnet/syntaxnet/conll2tree.py model_zoo/models/slim/nets/vgg.py model_zoo/models/resnet/cifar_input.py model_zoo/models/street/python/shapes.py model_zoo/models/inception/inception/dataset.py model_zoo/models/slim/preprocessing/lenet_preprocessing.py model_zoo/models/inception/inception/imagenet_eval.py model_zoo/models/inception/inception/imagenet_distributed_train.py model_zoo/models/syntaxnet/syntaxnet/graph_builder_test.py model_zoo/models/differential_privacy/dp_sgd/dp_optimizer/dp_optimizer.py model_zoo/models/slim/eval_image_classifier.py model_zoo/models/syntaxnet/syntaxnet/load_parser_ops.py model_zoo/models/slim/nets/nets_factory_test.py ops/basic_ops.py models.py model_zoo/models/namignizer/names.py model_zoo/models/im2txt/im2txt/inference_utils/caption_generator.py model_zoo/models/inception/inception/flowers_eval.py model_zoo/models/inception/inception/inception_train.py model_zoo/models/neural_programmer/wiki_data.py transforms.py model_zoo/models/inception/inception/inception_distributed_train.py compute_acc AverageMeter accuracy WarmupCosineLR VideoRecord VideoDataset return_dataset return_diving48 return_something download_file_from_google_drive gsmModule VideoModel AverageMeter accuracy eval_video Stack IdentityTransform RandomRotation GroupCenterCrop GroupNormalize GroupOverSample ToTorchFormatTensor GroupFiveCrops GroupScale GroupRandomSizedCrop GroupRandomHorizontalFlip GroupRandomCrop GroupMultiScaleCrop ReductionParameter ROIPoolingParameter HingeLossParameter BatchReductionParameter BlobProto BlobProtoVector NetStateRule LayerParameter PowerParameter FillerParameter ArgMaxParameter SegDataParameter InnerProductParameter V0LayerParameter ConvolutionParameter SolverState EltwiseParameter LossParameter SliceParameter WindowDataParameter DummyDataParameter HDF5OutputParameter TanHParameter TransformationParameter SoftmaxParameter ConcatParameter DataParameter SPPParameter ParamSpec SolverParameter MVNParameter ContrastiveLossParameter NetState NetParameter BiasParameter PoolingParameter DropoutParameter Datum VideoDataParameter SigmoidParameter BlobShape ExpParameter AccuracyParameter LogParameter ThresholdParameter MemoryOptimizationParameter MemoryDataParameter BNParameter LRNParameter ImageDataParameter ReLUParameter ReshapeParameter InfogainLossParameter ScaleParameter V1LayerParameter HDF5DataParameter PReLUParameter FlattenParameter PythonParameter build_relu build_bn build_gsm build_pooling build_linear build_dropout build_conv get_basic_layer parse_expr CaffeVendor InceptionV3 InceptionV3_gsm BNInception BNInception_gsm test_block35 load_conv2d_nobn load_block8 Mixed_6a test_conv2d inceptionresnetv2 load_block17 InceptionResnetV2 test_mixed_7a test_conv2d_nobn Mixed_5b load_linear test_mixed_5b test_mixed_6a test_block17 load_mixed_6a load_mixed_7a test BasicConv2d load_block35 Block35 load Block17 Block8 load_mixed_5b Mixed_7a test_block8 load_conv2d dump_block17 dump_mixed_6a dump_logits dump_block35 dump_mixed_5b dump_conv2d dump_block8 dump_mixed_7a dump_conv2d_nobn make_padding Mixed_4a test_conv2d load_mixed_7 load_mixed_4a_7a load_mixed_5 Mixed_5a load_linear Inception_C InceptionV4 Reduction_B load_mixed_6 test BasicConv2d test_mixed_4a_7a Reduction_A load Inception_B Inception_A Mixed_3a inceptionv4 load_conv2d dump_mixed_5 dump_mixed_7 dump_logits dump_mixed_4a_7a dump_conv2d make_padding dump_mixed_6 get_random_block_from_data standard_scale get_random_block_from_data standard_scale get_random_block_from_data standard_scale xavier_init min_max_scale get_random_block_from_data Autoencoder AdditiveGaussianNoiseAutoencoder MaskingNoiseAutoencoder VariationalAutoencoder main get_output_tensor_names get_input_tensor_names main get_output_tensor_names main _SSIMForMultiScale MultiScaleSSIM _FSpecialGauss main Eval MnistInput Train DPGradientDescentOptimizer ComputeDPPrincipalProjection AmortizedGaussianSanitizer NetworkParameters BuildNetwork SoftThreshold GenerateBinomialTable LayerParameters VaryRate BatchClipByL2norm GetTensorOpName ConvParameters AddGaussianNoise Conv2DPXG MatMulPXG Interface AddPXG PerExampleGradients PXGRegistry _ListUnion aggregation_most_frequent labels_from_probs noisy_max logmgf_exact compute_q_noisy_max smoothed_sens compute_q_noisy_max_approx main logmgf_from_counts sens_at_k train_op_fun loss_fun _input_placeholder train inference_deeper inference _variable_with_weight_decay _variable_on_cpu softmax_preds moving_av ld_svhn extract_mnist_labels partition_dataset ld_mnist unpickle_cifar_dic create_dir_if_needed image_whitening ld_cifar10 extract_mnist_data extract_svhn extract_cifar10 maybe_download accuracy main ensemble_preds train_student prepare_student_data main train_teacher batch_indices integral_bounded_mp integral_inf_mp _compute_delta compute_log_moment compute_b_mp cropped_ratio distributions distributions_mp _to_np_float64 _compute_eps compute_b pdf_gauss_mp integral_bounded pdf_gauss compute_a_mp get_privacy_spent integral_inf compute_a GaussianMomentsAccountant AmortizedAccountant MomentsAccountant DummyAccountant TrainingConfig ModelConfig main run_once evaluate_model run InferenceWrapper main ShowAndTellModel ShowAndTellModelTest ShowAndTellModel main _process_dataset _process_image_files _int64_feature Vocabulary _bytes_feature_list _create_vocab _load_and_process_metadata _process_caption _bytes_feature ImageDecoder _to_sequence_example main _int64_feature_list Caption TopN CaptionGenerator FakeVocab CaptionGeneratorTest FakeModel InferenceWrapperBase Vocabulary inception_v3 InceptionV3Test process_image distort_image parse_sequence_example batch_with_dynamic_pad prefetch_input_data Dataset FlowersData main main ImagenetData main main main image_preprocessing batch_inputs inputs parse_example_proto distorted_inputs distort_color eval_image decode_jpeg distort_image train evaluate _eval_once inference _activation_summaries loss _activation_summary train _average_gradients _tower_loss ImageCoder _convert_to_example _process_image_files _process_image _int64_feature _process_dataset _is_cmyk _find_image_files _build_bounding_box_lookup _find_human_readable_labels _build_synset_lookup _find_image_bounding_boxes _bytes_feature _float_feature main _process_image_files_batch _is_png ImageCoder _convert_to_example _process_image_files _process_dataset _int64_feature _find_image_files _bytes_feature _is_png main _process_image_files_batch _process_image BoundingBox FindNumberBoundingBoxes GetInt ProcessXMLAnnotation GetItem get_variables_by_name get_variables CollectionsTest inception_v3 inception_v3_parameters InceptionTest l2_regularizer cross_entropy_loss l1_loss l1_l2_regularizer l1_regularizer l2_loss RegularizersTest LossesTest CrossEntropyLossTest one_hot_encoding batch_norm dropout fc max_pool _two_element_tuple conv2d flatten repeat_op avg_pool FCTest ConvTest FlattenTest DropoutTest OneHotEncodingTest AvgPoolTest BatchNormTest MaxPoolTest _current_arg_scope _add_op add_arg_scope _get_arg_stack arg_scope has_arg_scope func2 func1 ArgScopeTest variable_device global_step variable get_unique_variable get_variables_by_name add_variable get_variables_to_restore VariableDeviceChooser get_variables VariablesTest GetVariablesByNameTest GlobalStepTest CharsVocabulary LM1BDataset get_batch Vocabulary _SampleModel _SampleSoftmax _LoadModel _DumpSentenceEmbedding main _DumpEmb _EvalModel read_names _letter_to_number name_to_batch namignizer_iterator NamignizerModel decode init_data get_batch to_symbol accuracy to_id add pad print_out safe_exp tanh_cutoff quantize NeuralGPU sigmoid_cutoff relaxed_distance check_for_zero conv_linear conv_gru quantize_weights_op _custom_id_grad relaxed_average make_dense initialize animate multi_test evaluate single_test main train interactive exact_match complete_wiki_processing perform_word_cutoff word_dropout word_lookup get_max_entry generate_feed_dict convert_to_int_2d_and_pad pick_one add_special_words construct_vocab partial_match partial_column_match convert_to_bool_and_pad group_by_max exact_column_match return_index check_processed_cols list_join Graph LSTMCell apply_dropout get_embedding Parameters WikiExample simple_normalize TableInfo is_number WikiQuestionLoader WikiQuestionGenerator final_normalize correct_unicode is_date is_nan_or_inf full_normalize strip_accents build_input main train evaluate ResNet main main _configure_learning_rate _configure_optimizer _get_init_fn main _add_variables_summaries _get_variables_to_train get_split get_dataset download_and_uncompress_tarball image_to_tfexample write_label_file int64_feature bytes_feature read_label_file has_labels _add_to_tfrecord _download_and_uncompress_dataset _get_output_filename _clean_up_temporary_files run _dataset_exists _convert_dataset run _clean_up_temporary_files _get_filenames_and_classes _get_dataset_filename ImageReader _add_to_tfrecord _extract_labels _get_output_filename _download_dataset _extract_images _clean_up_temporary_files run get_split get_split create_readable_names_for_imagenet_labels get_split _gather_clone_loss deploy _add_gradients_summaries _optimize_clone create_clones optimize_clones DeploymentConfig _sum_clones_gradients DeploymentConfigTest DeployTest OptimizeclonesTest BatchNormClassifier CreatecloneTest LogisticClassifier alexnet_v2 alexnet_v2_arg_scope AlexnetV2Test cifarnet_arg_scope cifarnet inception_resnet_v2_arg_scope inception_resnet_v2 block8 block35 block17 InceptionTest inception_arg_scope inception_v1_base inception_v1 InceptionV1Test inception_v2_base _reduced_kernel_size_for_small_input inception_v2 InceptionV2Test inception_v3 _reduced_kernel_size_for_small_input inception_v3_base InceptionV3Test inception_v4 block_reduction_b inception_v4_base block_inception_b block_inception_c block_reduction_a block_inception_a InceptionTest lenet lenet_arg_scope get_network_fn NetworksTest overfeat overfeat_arg_scope OverFeatTest Block conv2d_same subsample resnet_arg_scope stack_blocks_dense resnet_v1_152 resnet_v1_101 bottleneck resnet_v1_200 resnet_v1_50 resnet_v1 ResnetUtilsTest ResnetCompleteNetworkTest create_test_input resnet_v2_50 resnet_v2_200 resnet_v2_101 resnet_v2_152 bottleneck resnet_v2 ResnetUtilsTest ResnetCompleteNetworkTest create_test_input vgg_16 vgg_arg_scope vgg_a vgg_19 VGG16Test VGGATest VGG19Test preprocess_image preprocess_for_train preprocess_for_eval distorted_bounding_box_crop preprocess_for_train preprocess_for_eval preprocess_image distort_color apply_with_random_selector preprocess_image get_preprocessing _aspect_preserving_resize preprocess_for_train _crop _central_crop _smallest_size_at_least _mean_image_subtraction preprocess_for_eval preprocess_image _random_crop Decoder DecoderTest _testdata ComputeErrorRates AddErrors CountWordErrors CountErrors ComputeErrorRate ErrorcounterTest lstm_layer _variable_lstm_shape _variable_lstm_grad rnn_helper rotate_dimensions tensor_dim transposing_reshape tensor_shape DataTest _rand ShapesTest VGSLSpecs _rand VgslspecsTest main _ImageProcessing ImageInput _ReadExamples VGSLImageModel _ParseInputSpec _PadLabels2d Train _ParseOutputSpec _PadLabels3d Eval _AddRateToSummary InitNetwork _rand VgslModelTest _testdata main make_shard_files main write_vocab_and_sums compute_coocs words create_vocabulary write_shards main count_matrix_input write_embeddings_to_disk embeddings_with_init SwivelModel write_embedding_tensor_to_disk main read_marginals_file go Vecs evaluate ParsingReaderOpsTest main to_dict GreedyParser BatchedSparseToDense EmbeddingLookupFeatures GraphBuilderTest LexiconBuilderTest main Eval RewriteContext OutputPath WriteStatus Train RewriteContext main Eval StageName ParsingReaderOpsTest AddCrossEntropy StructuredGraphBuilder TextFormatsTest Batcher BeamSearch Hypothesis Pad SnippetGen Ids2Words GetExFeatureText Vocab ToSentences ExampleGen GetWordIds main _binary_to_text _text_to_binary main _Train _RunningAvgLoss _Eval BSDecoder DecodeIO Seq2SeqAttentionModel _extract_argmax_and_embed sampled_sequence_loss sequence_loss_by_example linear transformer batch_transformer linear conv2d dense_to_one_hot bias_variable weight_variable basic_conv_lstm_cell init_state build_tfrecord_input construct_model scheduled_sample cdna_transformation stp_transformation dna_transformation main peak_signal_to_noise_ratio Model mean_squared_error ConsensusModule SegmentConsensus Identity topk size t eq mul_ append sum max sum join get get_confirm_token save_response_content Session expand_as view test_crops reshape size copy softmax net split parse_expr Conv2d MaxPool2d AvgPool2d gsmModule parse_expr load_url InceptionResnetV2 load_state_dict ones size File close from_numpy permute from_numpy File close permute t File close from_numpy load_conv2d load_conv2d_nobn load_conv2d load_conv2d load_conv2d_nobn load_conv2d load_conv2d load_conv2d_nobn load_conv2d load_block8 load_mixed_5b load_mixed_6a load_mixed_7a load_block35 load_block17 load_linear range load_conv2d transpose_ sum data ones print Variable File close dist mean from_numpy softmax imread forward std transpose_ register_forward_hook File close from_numpy transpose_ register_forward_hook File close from_numpy test_conv2d branch0 conv2d test_conv2d branch0 test_conv2d_nobn test_conv2d branch0 conv2d test_conv2d branch0 test_conv2d_nobn test_conv2d conv2d test_conv2d branch0 test_conv2d_nobn decode exit get_shape get_operation_by_name File system close eval create_dataset get_attr make_padding get_tensor_by_name get_shape get_operation_by_name File system close eval create_dataset get_attr make_padding get_tensor_by_name print get_operation_by_name File close eval create_dataset get_tensor_by_name dump_conv2d dump_conv2d dump_conv2d_nobn dump_conv2d dump_conv2d dump_conv2d_nobn dump_conv2d dump_conv2d dump_conv2d_nobn load_url load_state_dict InceptionV4 load_conv2d load_conv2d load_conv2d load_conv2d load_mixed_6 load_mixed_7 load_mixed_4a_7a load_mixed_5 eval zeros test_conv2d dump_conv2d dump_conv2d dump_conv2d dump_conv2d transform fit randint len sqrt transform fit append format range print output_directory iteration MkDir append format range packbits asarray BytesIO reshape savez_compressed exp float64 reshape min astype mean shape _FSpecialGauss fftconvolve ones size _SSIMForMultiScale append array range MultiScaleSSIM placeholder string expand_dims decode_png read TFRecordReader string_input_producer reshape float32 cast parse_single_example shuffle_batch decode_png batch update batch_size hidden_layer_num_units projection_dimensions NetworkParameters eval_data_path save_path default_gradient_l2norm_bound num_hidden_layers Train num_training_steps LayerParameters ConvParameters training_data_path range append self_adjoint_eig l2_normalize slice sanitize transpose reshape matmul shape top_k rsplit patch_size layer_parameters input_size with_bias weight_decay num_units projection_dimensions name matmul conv2d relu in_channels sqrt truncated_normal Variable reshape max_pool gradient_l2norm_bound num_outputs zeros bias_gradient_l2norm_bound conv_parameters zeros range append pop list isinstance inputs extend set OrderedDict append union pxg_rule list gradients zip Interface OrderedDict _ListUnion append pxg_registry shape argmax len int asarray labels_from_probs reshape shape bincount zeros argmax range int asarray labels_from_probs reshape shape bincount zeros argmax range argmax array exp argmax array len pow exp log compute_q_noisy_max print logmgf_from_counts sorted exp max sens_at_k input_is_counts log str list getcwd shape delta astype max_examples moments noise_eps maybe_download load counts_file min indices_file int32 beta array mul add_to_collection _variable_on_cpu l2_loss truncated_normal_initializer lrn max_pool sparse_softmax_cross_entropy_with_logits int64 reduce_mean cast add_to_collection get_collection ExponentialMovingAverage apply int trainable_variables learning_rate batch_size name scalar_summary apply nb_teachers apply_gradients moving_av ExponentialMovingAverage exponential_decay float epochs_per_decay histogram_summary batch_size _input_placeholder inference_deeper deeper reset_default_graph softmax ExponentialMovingAverage Saver ceil inference variables_to_restore zeros len MakeDirs urlretrieve st_size endswith print stat append ones print maximum mean sqrt shape std range len load close open unpickle_cifar_dic reshape extractall swapaxes save append data_dir hstack image_whitening vstack extract_svhn maybe_download data_dir image_whitening extract_cifar10 maybe_download data_dir extract_mnist_data extract_mnist_labels maybe_download int len float argmax len str print deeper teachers_max_steps teachers_dir zeros range softmax_preds ld_svhn noisy_max str lap_scale ld_mnist print data_dir accuracy ld_cifar10 ensemble_preds softmax_preds str print accuracy prepare_student_data deeper max_steps train_dir ld_svhn str softmax_preds partition_dataset ld_mnist train_dir print accuracy ld_cifar10 deeper max_steps len int inf quad quad int format print binom ceil range format print distributions b_fn integral_bounded integral_inf log compute_a quad quad int integral_inf_mp format print distributions_mp ceil int integral_inf_mp format integral_bounded_mp print distributions_mp b_fn compute_a_mp ceil log exp min write float min write log assert_array_less compute_b_mp isinf compute_a_mp compute_a assert_allclose int time exp flush info batch_size add add_summary ceil num_eval_examples range Summary run latest_checkpoint checkpoint_dir info Graph MakeDirs info eval_dir run vocab_file Vocabulary Graph Glob len extend finalize input_files info split inception_checkpoint_file TrainingConfig input_file_pattern MakeDirs train ModelConfig train_dir FeatureLists SequenceExample decode_jpeg Features int join arange TFRecordWriter print astype write SerializeToString close output_dir _to_sequence_example range flush len seed int Thread join print min astype shuffle Coordinator start num_threads ImageDecoder append range len update Vocabulary print sort Counter dict word_counts_output_file len word_tokenize extend lower end_word append join setdefault print ImageMetadata append int val_captions_file _process_dataset train_captions_file val_shards _create_vocab train_shards _load_and_process_metadata val_image_dir output_dir test_shards train_image_dir list l2_regularizer summarize_activation values resize_images random_crop mul resize_image_with_crop_or_pad image_summary convert_image_dtype sub distort_image parse_single_sequence_example enqueue fatal string_input_producer len FIFOQueue cast append range add_queue_runner size Glob info QueueRunner read extend float32 RandomShuffleQueue scalar_summary split batch_join slice ones reduce_max reduce_sum add reduce_mean sub append expand_dims reduce_min scalar_summary evaluate eval_dir Exists DeleteRecursively FlowersData join Server ClusterSpec ImagenetData target batch_size batch_size mul decode_jpeg sub eval_image image_size distort_image update concat transpose cast VarLenFeature parse_single_example expand_dims values num_replicas_to_aggregate len _activation_summaries value batch_size reshape concat sparse_to_dense cross_entropy_loss range name zero_fraction sub scalar_summary histogram_summary REGULARIZATION_LOSSES name get_collection apply average add_n ExponentialMovingAverage sub TOWER_NAME inference LOSSES_COLLECTION loss scalar_summary concat reduce_mean zip append expand_dims Example print _is_cmyk cmyk_to_rgb png_to_jpeg _is_png decode_jpeg int join _convert_to_example arange _process_image TFRecordWriter print astype write SerializeToString close output_directory range flush len ImageCoder Thread Coordinator start append seed list print Glob extend shuffle range len append append basename print _process_image_files _find_image_files _find_human_readable_labels _find_image_bounding_boxes labels_file readlines split print readlines append float split imagenet_metadata_file train_directory _build_bounding_box_lookup validation_directory _build_synset_lookup bounding_box_file validation_shards labels_file iter BoundingBox parse height ymin FindNumberBoundingBoxes min ymax xmin xmax GetInt getroot width append float max range GetItem get_shape assert_is_compatible_with get_shape TensorShape isinstance num_elements pop add_to_collection get_collection _get_arg_stack add update append copy isinstance _add_op append add_to_collection get_collection VARIABLES name NodeDef callable device GLOBAL_STEP get_collection append list set list ones min float32 int32 zeros next range len exp get_batch ckpt _LoadModel error write isnan eval pbtxt enumerate run _SampleSoftmax ckpt ones _LoadModel word_to_char_ids id_to_word write float32 num_samples int32 zeros range pbtxt run ckpt ones _LoadModel reshape size write float32 int32 zeros save_dir range pbtxt run join ckpt ones _LoadModel len write float32 int32 zeros save_dir range pbtxt run _SampleModel sentence input_data CharsVocabulary prefix _DumpSentenceEmbedding LM1BDataset _DumpEmb _EvalModel namedtuple tolist lower sum array read_csv list reshape map choice zeros sum range zeros list map reshape append max range len time rand_pair rand_dup_pair rand_kvsort_pair rand_rev2_pair spec print_out append float range rand_search_pair choice pad append array write flush decode task_print min range exp sigmoid tanh conv_lin sigmoid_cutoff tanh minimum maximum add_n range len append trainable_variables assign relaxed_average init_data kh noclass MkDir set_random_seed kw max_grad_norm forward_max uniform_unit_scaling_initializer max run seed restore niclass rx_step print_out curriculum_bound append initialize_all_variables cutoff range max_length train_dir nconvs height pull dropout get_checkpoint_state NeuralGPU lr set_initializer random_seed pull_incr join jobid min model_checkpoint_path mode nmaps split restore get_batch accuracy print_out append float step min print_out single_test low_batch_size float max range split batch_size zeros_like set_xticklabels text set_yticks grid add_axes imshow set_zorder set_xticks figure save append range FuncAnimation split batch_size interactive range len number_columns deepcopy isinstance Number question word_column_names word_columns append word_ids number_column_names len dummy_token max_entry_length append range len tolist max_elements range len append range len append range len append range len append range len append get_max_entry range len range len exact_match number_lookup_matrix word_exact_match float64 original_nc_names word_print_answer word_group_by_max calc_answer column_names number_columns sorted columns list unk_token ones tolist max_number_cols column_match_token max_entry_length word_columns convert_to_int_2d_and_pad entry_match_token append ordinal_question number_print_answer word_lookup_matrix range number_group_by_max string_question replace original_nc original_wc_names question_attention_mask original_wc partial_match question max_word_cols max_elements ordinal_question_one number_column_exact_match partial_column_match number_column_names is_lookup group_by_max convert_to_bool_and_pad exact_column_match question_length check_processed_cols number_exact_match word_column_names word_column_exact_match zeros is_bad_example len unk_token print entry_match_token entry_match_token_id column_match_token dummy_token column_match_token_id append word_ids len pop remove keys list append range len append reshape range dropout sigmoid tanh bias_add matmul str join strip_accents strip sub correct_unicode sub final_normalize simple_normalize strip sub lower strip float range len concat enqueue image_summary string_input_producer resize_image_with_crop_or_pad transpose FIFOQueue cast range sparse_to_dense per_image_whitening random_crop add_queue_runner random_flip_left_right slice Glob QueueRunner FixedLengthRecordReader read decode_raw uint8 reshape float32 dequeue_many int32 RandomShuffleQueue Stop build_graph dataset argmax Summary run prepare_or_wait_for_session add Supervisor train_dir SummaryWriter build_input ResNet mean info flush train_data_path add_summary mode build_graph eval_dir Saver dataset argmax max Session Summary run eval_once restore eval_batch_count add sleep range start_queue_runners SummaryWriter build_input eval_data_path get_checkpoint_state ResNet info log_root flush model_checkpoint_path add_summary mode HParams dataset_dir set_verbosity INFO int sync_replicas num_epochs_per_decay batch_size MomentumOptimizer AdagradOptimizer GradientDescentOptimizer AdamOptimizer RMSPropOptimizer AdadeltaOptimizer FtrlOptimizer name get_model_variables append scalar_summary histogram_summary checkpoint_path latest_checkpoint get_model_variables checkpoint_exclude_scopes IsDirectory startswith info append train_dir extend get_collection TRAINABLE_VARIABLES join TFRecordReader TFExampleDecoder read_label_file has_labels join urlretrieve st_size print extractall stat join join index split reshape join urlretrieve st_size print extractall stat join Remove DeleteRecursively download_and_uncompress_tarball list print _get_output_filename write_label_file dict zip _clean_up_temporary_files range len append join listdir isdir int write ceil float flush len _get_dataset_filename range seed shuffle _dataset_exists _convert_dataset _get_filenames_and_classes print print _extract_images _extract_labels print join urlretrieve _download_dataset format urlretrieve readlines len split create_readable_names_for_imagenet_labels write_label_file scope scalar_summary _gather_clone_loss REGULARIZATION_LOSSES get_collection add_n _sum_clones_gradients len SUMMARIES get_collection set scope create_clones UPDATE_OPS append add_n zip global_norm isinstance name IndexedSlices info append values histogram_summary batch_norm as_list prediction_fn hasattr default_image_size pad to_float random_crop random_flip_left_right image_summary random_brightness pad random_contrast expand_dims to_float resize_image_with_crop_or_pad expand_dims image_summary random_uniform to_float resize_image_with_crop_or_pad sub div pack greater_equal slice to_int32 logical_and with_dependencies Assert shape rank equal greater_equal reshape logical_and with_dependencies extend Assert shape rank random_uniform append range equal len append _crop range split convert_to_tensor to_float to_int32 greater cond convert_to_tensor resize_bilinear squeeze shape set_shape _smallest_size_at_least expand_dims _aspect_preserving_resize set_shape random_uniform set_shape _aspect_preserving_resize subtract sum Counter test_count fn truth_count fp merge_with with_rank list range tensor_shape get_shape rotate_dimensions reshape transpose len get_shape append tensor_dim range len num_steps eval_interval_secs decoder graph_def_file model_str eval_data Eval batch_join sparse_tensor_to_dense string_input_producer batch_size reshape Glob identity image_summary int64 cast _ReadExamples deserialize_many_sparse int32 append range read TFRecordReader reader serialize_sparse reshape parse_single_example _ImageProcessing mul float32 sub set_shape cast decode_png ReplicaDeviceSetter startswith ErrorRates Decoder Build rfind VGSLImageModel find tensor_shape reshape _PadLabels2d int match group compile int match group compile Summary add_summary task ps_tasks initial_learning_rate master num_preprocess_threads learning_rate_halflife final_learning_rate optimizer_type train_data max_steps join read pack seek SEEK_END shard_size print tell size write SEEK_SET any unpack output_dir range flush open shard_size makedirs max_vocab seek SEEK_END setdefault print tell sort words write SEEK_SET min len flush enumerate join seek SEEK_END setdefault shard_size flush_coocs tell min write SEEK_SET enumerate window_size output_dir open range flush len join read items seek shard_size name sort write close unlink Example output_dir range flush len vocab write_vocab_and_sums write_shards read string_input_producer reshape concat WholeFileReader parse_single_example batch sparse_to_dense values run row_embedding print col_embedding input_base_path output_base_path write_embedding_tensor_to_disk flush output_base_path spearmanr list _get_dict OrderedDict append token range len fill float32 constant diag convert_to_tensor embedding_lookup concat unpack_sparse_features join TaskSpec file_pattern resource_dir input part slim_model document_sink batch_size GreedyParser StructuredGraphBuilder string values run list restore len map placeholder feature_size resource_dir info model_path AddEvaluation time AddSaver task_context RewriteContext split OutputPath name add join OutputPath WriteStatus save max output_path slim_model GreedyParser StructuredGraphBuilder word_embeddings report_every Eval values run list AddTraining name node map append pretrained_params OutputPath info AddEvaluation time AddSaver AddPretrainedEmbeddings output_path split projectivize_training_set OutputPath compute_lexicon RewriteContext slice reshape cond append range glob read shuffle open len append WordToId split index len SnippetGen join in_file read feature FromString write close out_file append open pack readlines SerializeToString extend len write close Example out_file open split _binary_to_text _text_to_binary min write add add_summary Summary build_graph eval_dir Saver Session restore tolist sleep train_dir eval_interval_secs SummaryWriter NextBatch get_checkpoint_state info log_root flush join Ids2Words run_eval_step model_checkpoint_path add_summary _RunningAvgLoss vocab_path beam_size abstract_key max_abstract_sentences BSDecoder Seq2SeqAttentionModel max_article_sentences _Eval Batcher set_random_seed data_path _replace DecodeLoop _Train Vocab article_key random_seed as_list zeros random_normal zeros array arange state_initializer dtype pack set_shape list init_state use_state batch_size concat floor set_shape parse_single_example str TFRecordReader string_input_producer data_dir resize_image_with_crop_or_pad cast append range Glob decode_jpeg batch join int read reshape min resize_bicubic train_val_split float32 sequence_length zeros len to_float exp to_int32 int32 zip bool round array convert_to_tensor fully_connected float32 transformer append array range int relu fully_connected reshape squeeze concat depthwise_conv2d reduce_sum tile zip append expand_dims split int relu slice concat reduce_sum pad append expand_dims range gather int range random_shuffle Saver save restore get_collection event_log_dir initialize_all_variables start_queue_runners SummaryWriter flush InteractiveSession num_iterations pretrained_model add_summary VARIABLES | swathikirans/GSM | 3,783 |
sweetcocoa/DeepComplexUNetPyTorch | ['speech enhancement'] | ['Phase-aware Speech Enhancement with Deep Complex U-Net'] | train.py DCUNet/source_separator.py estimate_directory.py DCUNet/sedataset.py DCUNet/utils.py evaluation.py DCUNet/unet.py DCUNet/criterion.py DCUNet/complex_nn.py DCUNet/noisedataset.py DCUNet/__init__.py DCUNet/inference.py DCUNet/metric.py train_dcunet.py DCUNet/constant.py get_arg get_dataset ComplexConv2d ComplexConvTranspose2d ComplexBatchNorm2d dotproduct weighted_signal_distortion_ratio_loss WeightedSDR any_audio_inference pesq_metric PESQ NoiseDataset SEDataset ApplyMask STFT ISTFT SourceSeparator Decoder Encoder UNet angle get_spectrogram_axis istft _get_freq_values get_audio_by_magphase magphase realimag cut_padding _get_time_values get_snr load_audio EasyDict update __dict__ ckpt print add_argument ArgumentParser parse_args RandomState test_signal SEDataset NoiseDataset shuffle train_noise train_signal get_wav test_noise loss_sdr pow squeeze inference_one_audio isinstance pad randint range len expand_dims read T permute realimag istft _get_time_values _get_freq_values int view pad device zeros float range irfft pow angle stack cos sin mean log10 | sweetcocoa/DeepComplexUNetPyTorch | 3,784 |
sweichwald/tidybench | ['time series'] | ['Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values'] | tidybench/lasar.py tidybench/__init__.py examples/toy.py tidybench/utils.py tidybench/qrbs.py tidybench/slarac.py tidybench/selvar.py lassovar lasar qrbs selvar slarac varmodel common_pre_post_processing standardise int lassovar reshape choice shape round abs aggregate_lags resample copy shape vstack zeros range full LassoLarsCV fit int Ridge concatenate stack floor quantile sum slvar int reshape choice shape round abs varmodel aggregate_lags int T arange resample choice vstack floor zeros max copy | sweichwald/tidybench | 3,785 |
swook/GazeML | ['gaze estimation'] | ['Deep Pictorial Gaze Estimation'] | src/core/summary_manager.py src/datasources/frames.py src/elg_demo.py src/models/dpg.py src/elg_train.py src/core/time_manager.py src/models/__init__.py src/dpg_train.py src/util/heatmap.py src/core/checkpoint_manager.py src/datasources/__init__.py src/models/elg.py src/datasources/unityeyes.py src/core/data_source.py src/core/model.py src/core/live_tester.py src/datasources/video.py src/util/gazemap.py setup.py src/datasources/webcam.py src/core/__init__.py src/util/gaze.py src/datasources/hdf5.py _record_frame _visualize_output CheckpointManager BaseDataSource LiveTester BaseModel SummaryManager TimeManager Timer get_landmarks_predictor _get_opencv_xml _get_dlib_data_file FramesSource get_face_detector HDF5Source UnityEyes Video Webcam DPG estimate_gaze_from_landmarks ELG _tf_mse draw_gaze tensorflow_angular_error_from_vector vector_to_pitchyaw tensorflow_angular_error_from_pitchyaw pitchyaw_to_vector mean_angular_error angular_error from_gaze2d gaussian_2d get time write shape VideoWriter record_video VideoWriter_fourcc release put_nowait draw_gaze _dtime polylines tuple asmatrix drawMarker resize round clip all fullscreen imshow shape pad array append WND_PROP_FULLSCREEN arcsin range get asarray amax concatenate COLOR_GRAY2BGR astype copy mean record_video setWindowProperty empty enumerate clear int time norm join namedWindow equalizeHist print reshape putText rectangle WINDOW_FULLSCREEN int32 fliplr cvtColor len basename mkdir relpath basename mkdir relpath cnn_face_detection_model_v1 _get_dlib_data_file shape_predictor _get_dlib_data_file len arange minimize cos pi sin success arcsin flip clip x multiply empty cos sin arctan2 reshape divide empty arcsin norm multiply divide sum clip LINE_AA arrowedLine tuple COLOR_GRAY2BGR astype int32 sin cvtColor int asarray ellipse arctan2 abs astype cos degrees int32 sin append arcsin float round zeros circle expand_dims exp arange | swook/GazeML | 3,786 |
syb7573330/PointGrow | ['point cloud generation'] | ['PointGrow: Autoregressively Learned Point Cloud Generation with Self-Attention'] | train_unconditional.py provider.py models/unconditional_model_saca_a.py generate_unconditional.py models/conditional_model_im.py utils/ops.py generate_conditional_one_hot.py utils/im_util.py train_conditional_one_hot.py utils/sample_pc_from_obj.py train_conditional_im.py models/conditional_model_one_hot.py generate_conditional_im.py models/unconditional_model_saca_b.py generatePointClouds generatePointClouds generatePointClouds samplePoint farthestPointSampler shuffleConditionData loadPC shuffleData calTriangleArea voxelizeData calc_distances train log_string get_learning_rate get_bn_decay train log_string get_learning_rate train log_string get_learning_rate get_model get_loss placeholder_inputs contextAwarenessOp get_model get_loss placeholder_inputs contextAwarenessOp get_model get_loss placeholder_inputs contextAwarenessOp get_model get_loss placeholder_inputs contextAwarenessOp imread imsave imresize batch_norm_template _variable_with_weight_decay batch_norm_for_conv2d conv2d conv2d_cond max_pool2d get_weights _variable_on_cpu sample_pc_from_obj load shuffle list range len shuffle list range len astype int32 array sqrt random minimum calc_distances append zeros range print write flush exponential_decay maximum minimum exponential_decay int32 float32 placeholder value value multiply concat contextAwarenessOp conv2d_cond zeros expand_dims range append reduce_mean add_to_collection sparse_softmax_cross_entropy_with_logits reshape conv2d int reduce_sum fromarray uint8 ANTIALIAS resize save toimage multiply add_to_collection _variable_on_cpu l2_loss lower _variable_with_weight_decay zeros int samplePoint farthestPointSampler random searchsorted split append zeros calTriangleArea range len | syb7573330/PointGrow | 3,787 |
syfafterzy/PCB_RPP | ['person retrieval', 'person re identification'] | ['Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)'] | PCB.py reid/datasets/duke.py reid/models/__init__.py reid/evaluation_metrics/ranking.py reid/utils/serialization.py reid/utils/progress/progress/bar.py reid/utils/progress/progress/__init__.py RPP.py reid/feature_extraction/database.py reid/utils/progress/setup.py reid/feature_extraction/__init__.py reid/__init__.py reid/evaluators.py reid/utils/progress/progress/helpers.py reid/evaluation_metrics/classification.py reid/models/resnet_rpp.py reid/utils/progress/progress/counter.py reid/datasets/market.py reid/utils/meters.py reid/feature_extraction/cnn.py reid/utils/data/sampler.py reid/utils/data/__init__.py reid/utils/data/transforms.py reid/utils/data/preprocessor.py reid/utils/progress/progress/spinner.py reid/utils/osutils.py reid/utils/progress/test_progress.py reid/utils/__init__.py reid/models/resnet.py reid/evaluation_metrics/__init__.py reid/utils/data/dataset.py reid/trainers_partloss.py reid/datasets/__init__.py reid/utils/logging.py get_data main get_data main pairwise_distance evaluate_all extract_features Evaluator Trainer BaseTrainer Duke Market names create accuracy mean_ap _unique_sample cmc extract_cnn_feature FeatureDatabase ResNet resnet50 resnet152 resnet34 resnet18 resnet101 ResNet resnet50_rpp names create Logger AverageMeter mkdir_if_missing load_checkpoint copy_state_dict read_json save_checkpoint write_json to_numpy to_torch Dataset _pluck Preprocessor RandomIdentitySampler RectScale RandomSizedRectCrop sleep FillingSquaresBar FillingCirclesBar IncrementalBar ChargingBar ShadyBar PixelBar Bar Countdown Stack Counter Pie SigIntMixin WriteMixin WritelnMixin PieSpinner MoonSpinner Spinner PixelSpinner LineSpinner Progress Infinite join create gallery Compose query num_train_ids DataLoader Preprocessor Normalize train workers batch_size SGD Trainer get_data query save_checkpoint Logger arch dataset cuda seed create hasattr data_dir logs_dir map load_state_dict width module range state_dict manual_seed_all update height format Evaluator set resume manual_seed join gallery evaluate print load_checkpoint parameters adjust_lr train epochs update extract_cnn_feature time format val print AverageMeter OrderedDict eval avg zip enumerate len list view mm expand t cat sum addmm_ values len print format mean_ap topk size t eq mul_ expand_as append sum max zeros list items choice asarray arange defaultdict astype argsort shape _unique_sample int32 zip append to_numpy range zeros enumerate len asarray arange astype average_precision_score argsort shape int32 append to_numpy range to_torch remove model Variable register_forward_hook OrderedDict eval cpu append makedirs dirname mkdir_if_missing join copy dirname save mkdir_if_missing load format print isfile data items list isinstance print size set copy_ add keys state_dict is_tensor list map split append enumerate | syfafterzy/PCB_RPP | 3,788 |
t-maho/SurFree | ['adversarial attack'] | ['SurFree: a fast surrogate-free black-box attack'] | main.py surfree.py get_model get_args get_imagenet_labels Basis SurFree dict eval PyTorchModel is_available Tensor cuda get add_argument ArgumentParser | t-maho/SurFree | 3,789 |
t-shinozaki/convcp | ['time series'] | ['Biologically-Motivated Deep Learning Method using Hierarchical Competitive Learning'] | model/lenet_cp_wl.py model/lenet.py model/mnist_cp_l.py model/mnist_cp.py convcp/functions/convolution_2d_cp.py train_cifar_cp.py prep_data.py train_alex.py model/alex.py test_alex_top5.py model/lenet_cp_512.py train_alex_cp.py convcp/functions/wsa.py model/alex_cp.py model/lenet_cp_256.py convcp/add_forward_grad.py model/lenet_cp_128.py model/mnist.py model/lenet_cp.py convcp/links/convolution_2d_cp.py model/lenet_cp_128_wl.py train_cifar.py handler read_image handler label2array read_image plot_rf handler label2array read_image plot_rf label2array plot_rf label2array plot_rf forward_grad Convolution2DCPFunction convolution_2d_cp WSA wsa Convolution2DCP CP BP CP BP CP BP CP BP CP BP CP BP CP BP CP BP CP BP CP BP CP BP join size convert transpose resize root crop open terminate exit subplot transpose astype axis mean imshow savefig int32 figure range std clip FLIP_LEFT_RIGHT randint ones data use _check_old_style_gradient add_cand _check_grad_type tuple creator_node inputs get_variable_or_none set heappop any is_debug Device enumerate len Convolution2DCPFunction apply | t-shinozaki/convcp | 3,790 |
t-systems-on-site-services-gmbh/coocop | ['image augmentation'] | ['Improved Image Augmentation for Convolutional Neural Networks by Copyout and CopyPairing'] | setup.py coocop/coocop_test.py coocop/coocop.py coocop/__init__.py CopyPairing Copyout test_CopyPairing_buffer_first test_Copyout_buffer_full test_Copyout_internal_vars test_CopyPairing_buffer_full test_CopyPairing_on_epoch_begin test_Copyout_buffer_first test_CopyPairing_call test_Copyout_call Copyout shape rand coo Copyout rand coo Copyout rand range coo Copyout CopyPairing on_epoch_begin shape cop rand CopyPairing cop rand CopyPairing cop rand CopyPairing range | t-systems-on-site-services-gmbh/coocop | 3,791 |
tabacof/adv_vae | ['adversarial attack'] | ['Adversarial Images for Variational Autoencoders'] | read_write_model.py mnist_vae.py write_model_data train_epoch kld test_epoch show_mnist bernoullisample adv_test latent_gaussian_x_bernoulli read_model_data write_model read_model mean sum set_all_param_values join join get_all_param_values train_model range test_model range exp set_title set_xticklabels set_yticklabels reshape grid add_subplot imshow tick_params show str list function adv_mean_log_var set_value astype float32 get_value flatten show_mnist set_ylabel figure adv_plot zip fmin_l_bfgs_b savefig set_all_param_values join join get_all_param_values | tabacof/adv_vae | 3,792 |
taconite/DDD-Differentiable-Dual-Decomposition | ['semantic segmentation'] | ['End-to-end Training of CNN-CRF via Differentiable Dual-Decomposition'] | lib/models/sync_bn/__init__.py lib/core/loss.py lib/core/inference.py lib/core/config.py lib/dataset/MNIST.py lib/models/aspp.py lib/layers/__init__.py lib/dataset/__init__.py lib/models/sync_bn/inplace_abn/src/setup.py lib/layers/test.py lib/models/sync_bn/inplace_abn/__init__.py lib/utils/vis.py lib/dataset/pascal_voc.py lib/core/evaluate.py image_segmentation/train_voc.py lib/models/sync_bn/inplace_abn/bn.py image_segmentation/validate_voc.py lib/models/sync_bn/inplace_abn/functions.py lib/dataset/pascal_ctx.py lib/layers/dp-extension/setup.py lib/models/seg_block4_resnet.py lib/models/__init__.py lib/utils/schedulers.py lib/core/function.py lib/utils/utils.py lib/models/seg_aspp_xception.py image_segmentation/train_cityscapes.py lib/models/seg_aspp_resnet.py lib/dataset/cityscapes.py lib/layers/fixed_point_iteration.py lib/utils/augmentations.py main parse_args reset_config main parse_args reset_config main parse_args reset_config get_model_name update_config _update_dict update_dir gen_config _fast_hist calc_IoU _print_name_value validate AverageMeter test train get_final_preds _softmax _assert_no_grad CrossEntropy2D CityScapes MNIST PASCALContext pascalVOC DPFunction FixedPointIteration FixedPointIterationGap4 FixedPointIterationGapN FixedPointIterationFast DDPFunction FixedPointIterationGap2 generate_all_states ASPP Bottleneck conv3x3 Bottleneck_CAFFE BasicBlock get_seg_net SegResNet Block SegXception get_seg_net SeparableConv2d Bottleneck conv3x3 Bottleneck_CAFFE BasicBlock get_seg_net SegResNet InPlaceABN InPlaceABNSync ABN _act_forward _count_samples _broadcast_shape InPlaceABNSync InPlaceABN _reduce _check _act_backward AdjustHue RandomHorizontallyFlip RandomTranslate AdjustSaturation CenterCrop RandomRotate FreeScale RandomSizedCrop Compose Scale RandomCrop RandomVerticallyFlip AdjustBrightness AdjustContrast PadByStride AdjustGamma RandomScale WarmUpLR PolynomialLR ConstantLR get_mesh get_10x_params get_optimizer get_1x_params create_logger evalpotential save_checkpoint generate_heatmaps get_source get_01x_params get_pascal_labels vis_segments add_argument parse_known_args cfg ArgumentParser update_config workers gpus validate PolynomialLR TRAIN_SET create_logger MultiStepLR DataLoader NE_GAMMA_L save_checkpoint LR_FACTOR save copy2 cuda get_optimizer NE_GAMMA_U max_iter len LR_STEP ROOT NE_ITER_RATIO dirname parse_args range state_dict NE_GAMMA_EXP format TEST_SET Compose close cfg ENABLED NAME END_EPOCH pformat Normalize info float last_epoch join DETERMINISTIC BEGIN_EPOCH train step BENCHMARK reset_config list OrderedDict load_state_dict startswith keys load isinstance MODEL_FILE items list array isinstance dict items list isinstance join PRETRAINED ROOT COCO_BBOX_FILE DATA_DIR NAME format EXTRA reshape list range nanmean dict zip zeros sum diag model clip_grad_norm_ zero_grad NE_GAMMA_L DEBUG cuda NE_GAMMA_U max_iter TRAIN_BN view NE_ITER_RATIO append detach update NE_GAMMA_EXP val format size mean eval stack item USE_PAIRWISE_LOSS info float enumerate last_epoch join time norm criterion backward LEARN_PAIRWISE_TERMS add_scalar isinstance AverageMeter LEARN_OUTPUT_TEMPERATURE parameters LEARN_GAMMA Tensor step len eval AverageMeter eval AverageMeter join list info keys values len exp max argmax _softmax append range copy PRETRAINED NUM_LAYERS init_weights STYLE INIT_DECONVS SegResNet SegXception fn append size enumerate size enumerate elu_forward slope leaky_relu_forward elu_backward slope leaky_relu_backward DATASET basicConfig format get_model_name replace getLogger print addHandler strftime StreamHandler SUBSET LOG_DIR mkdir Path setLevel OUTPUT_DIR INFO named_modules Parameter isinstance parameters gamma named_modules Parameter isinstance parameters gamma named_modules Parameter isinstance parameters gamma AdamW Adamax Adam SGD parameters join save zeros sqrt reshape meshgrid reshape array linspace rand floor exp arange maximum zeros max range meshgrid zeros arange get_pascal_labels | taconite/DDD-Differentiable-Dual-Decomposition | 3,793 |
taesiri/my-mlagents-envs | ['unity'] | ['Unity: A General Platform for Intelligent Agents'] | ml-agents/mlagents/trainers/components/reward_signals/curiosity/model.py ml-agents-envs/mlagents_envs/communicator_objects/command_pb2.py ml-agents/mlagents/trainers/run_experiment.py ml-agents-envs/mlagents_envs/mock_communicator.py ml-agents-envs/mlagents_envs/communicator_objects/unity_to_external_pb2.py ml-agents-envs/mlagents_envs/communicator.py gym-unity/gym_unity/envs/__init__.py ml-agents-envs/mlagents_envs/communicator_objects/brain_parameters_pb2.py ml-agents/mlagents/trainers/learn.py ml-agents/mlagents/trainers/tests/test_sampler_class.py ml-agents/mlagents/trainers/meta_curriculum.py ml-agents/mlagents/trainers/tests/test_barracuda_converter.py ml-agents/mlagents/trainers/ppo/models.py ml-agents-envs/mlagents_envs/side_channel/raw_bytes_channel.py gym-unity/gym_unity/__init__.py utils/validate_meta_files.py ml-agents/mlagents/trainers/trainer_controller.py ml-agents/mlagents/trainers/components/bc/model.py ml-agents/mlagents/trainers/tests/test_curriculum.py ml-agents/mlagents/trainers/action_info.py ml-agents/mlagents/trainers/tests/test_ppo.py ml-agents/mlagents/tf_utils/__init__.py ml-agents/mlagents/trainers/components/reward_signals/__init__.py ml-agents-envs/setup.py ml-agents-envs/mlagents_envs/side_channel/engine_configuration_channel.py ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_output_pb2.py ml-agents/mlagents/trainers/tests/mock_brain.py ml-agents/mlagents/trainers/tests/test_bcmodule.py ml-agents/mlagents/trainers/tests/test_trainer_controller.py ml-agents/mlagents/trainers/components/reward_signals/reward_signal_factory.py ml-agents-envs/mlagents_envs/rpc_utils.py ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_initialization_output_pb2.py ml-agents/setup.py ml-agents/mlagents/trainers/barracuda.py ml-agents/mlagents/trainers/env_manager.py ml-agents/mlagents/trainers/sac/policy.py ml-agents/mlagents/trainers/ppo/trainer.py ml-agents-envs/mlagents_envs/communicator_objects/agent_action_pb2.py ml-agents-envs/mlagents_envs/tests/test_rpc_communicator.py ml-agents-envs/mlagents_envs/tests/test_envs.py ml-agents/mlagents/trainers/brain.py ml-agents-envs/mlagents_envs/side_channel/float_properties_channel.py ml-agents/mlagents/trainers/tests/test_meta_curriculum.py ml-agents/mlagents/trainers/components/reward_signals/curiosity/signal.py ml-agents/mlagents/trainers/simple_env_manager.py ml-agents-envs/mlagents_envs/exception.py ml-agents/mlagents/trainers/curriculum.py ml-agents/mlagents/trainers/tests/test_policy.py ml-agents/mlagents/trainers/ppo/policy.py ml-agents-envs/mlagents_envs/communicator_objects/unity_message_pb2.py ml-agents/mlagents/trainers/tests/test_learn.py ml-agents-envs/mlagents_envs/communicator_objects/agent_info_pb2.py ml-agents/mlagents/trainers/tests/test_demo_loader.py ml-agents-envs/mlagents_envs/communicator_objects/observation_pb2.py utils/validate_versions.py ml-agents-envs/mlagents_envs/tests/test_rpc_utils.py ml-agents/mlagents/trainers/models.py ml-agents-envs/mlagents_envs/tests/test_timers.py ml-agents/mlagents/trainers/__init__.py ml-agents-envs/mlagents_envs/communicator_objects/custom_reset_parameters_pb2.py ml-agents-envs/mlagents_envs/communicator_objects/agent_info_action_pair_pb2.py ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_input_pb2.py ml-agents-envs/mlagents_envs/timers.py ml-agents/mlagents/trainers/tests/test_simple_rl.py ml-agents/mlagents/trainers/exception.py gym-unity/gym_unity/tests/test_gym.py ml-agents/mlagents/tf_utils/tf.py ml-agents/mlagents/trainers/buffer.py ml-agents-envs/mlagents_envs/side_channel/side_channel.py ml-agents/mlagents/trainers/tests/test_subprocess_env_manager.py ml-agents/mlagents/trainers/subprocess_env_manager.py ml-agents/mlagents/trainers/tensorflow_to_barracuda.py ml-agents/mlagents/trainers/agent_processor.py ml-agents/mlagents/trainers/policy.py ml-agents-envs/mlagents_envs/communicator_objects/engine_configuration_pb2.py ml-agents/mlagents/trainers/tests/test_rl_trainer.py ml-agents-envs/mlagents_envs/rpc_communicator.py ml-agents-envs/mlagents_envs/communicator_objects/demonstration_meta_pb2.py ml-agents-envs/mlagents_envs/__init__.py gym-unity/setup.py ml-agents/mlagents/trainers/tests/__init__.py ml-agents-envs/mlagents_envs/communicator_objects/unity_output_pb2.py ml-agents-envs/mlagents_envs/communicator_objects/space_type_pb2.py ml-agents/mlagents/trainers/trainer_util.py ml-agents/mlagents/trainers/tests/test_trainer_util.py ml-agents/mlagents/trainers/components/reward_signals/extrinsic/signal.py ml-agents/mlagents/trainers/sac/trainer.py ml-agents/mlagents/trainers/sampler_class.py ml-agents/mlagents/trainers/tests/test_sac.py ml-agents/mlagents/trainers/trajectory.py ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_initialization_input_pb2.py ml-agents-envs/mlagents_envs/base_env.py ml-agents-envs/mlagents_envs/communicator_objects/header_pb2.py ml-agents/mlagents/trainers/sac/models.py ml-agents/mlagents/trainers/tests/test_stats.py ml-agents/mlagents/trainers/components/reward_signals/gail/model.py ml-agents/mlagents/trainers/rl_trainer.py ml-agents/mlagents/trainers/tests/test_reward_signals.py ml-agents/mlagents/trainers/components/reward_signals/gail/signal.py ml-agents-envs/mlagents_envs/tests/test_side_channel.py ml-agents/mlagents/trainers/ppo/multi_gpu_policy.py ml-agents/mlagents/trainers/tests/test_multigpu.py ml-agents/tests/yamato/standalone_build_tests.py ml-agents-envs/mlagents_envs/environment.py ml-agents/mlagents/trainers/demo_loader.py ml-agents/tests/yamato/editmode_tests.py ml-agents/mlagents/trainers/components/bc/module.py ml-agents-envs/mlagents_envs/communicator_objects/unity_input_pb2.py ml-agents/mlagents/trainers/tests/test_buffer.py ml-agents/mlagents/trainers/trainer.py ml-agents/mlagents/trainers/tests/test_agent_processor.py ml-agents-envs/mlagents_envs/communicator_objects/unity_to_external_pb2_grpc.py ml-agents/mlagents/trainers/brain_conversion_utils.py ml-agents/tests/yamato/yamato_utils.py ml-agents/mlagents/trainers/stats.py ml-agents/mlagents/trainers/tf_policy.py ml-agents/mlagents/trainers/tests/test_trajectory.py VerifyVersionCommand UnityGymException ActionFlattener UnityEnv test_gym_wrapper test_multi_agent create_mock_group_spec test_branched_flatten setup_mock_unityenvironment test_gym_wrapper_visual create_mock_vector_step_result VerifyVersionCommand set_warnings_enabled ActionInfo AgentManager AgentProcessor AgentManagerQueue BarracudaWriter fuse print_known_operations compress Build sort lstm write fuse_batchnorm_weights trim mean gru Model summary Struct parse_args to_json rnn BrainParameters CameraResolution group_spec_to_brain_parameters BufferException AgentBuffer Curriculum make_demo_buffer load_demonstration demo_to_buffer get_demo_files get_global_agent_id EnvManager EnvironmentStep SamplerException TrainerConfigError CurriculumError TrainerError MetaCurriculumError CurriculumLoadingError CurriculumConfigError RunOptions create_environment_factory create_sampler_manager parse_command_line run_training prepare_for_docker_run try_create_meta_curriculum run_cli main _create_parser get_version_string MetaCurriculum EncoderType LearningModel LearningRateSchedule Policy RLTrainer main parse_command_line MultiRangeUniformSampler UniformSampler SamplerFactory SamplerManager GaussianSampler Sampler SimpleEnvManager StatsWriter StatsSummary StatsReporter TensorboardWriter CSVWriter worker EnvironmentResponse UnityEnvWorker StepResponse SubprocessEnvManager EnvironmentCommand get_layer_shape pool_to_HW flatten sqr_diff process_layer process_model get_layer_rank slow_but_stable_topological_sort get_attr basic_lstm ModelBuilderContext order_by get_epsilon get_tensor_dtype replace_strings_in_list debug embody by_op get_tensor_dims strided_slice remove_duplicates_from_list axis_to_barracuda by_name locate_actual_output_node convert strides_to_HW get_tensor_data very_slow_but_stable_topological_sort gru TFPolicy UnityPolicyException UnityTrainerException Trainer TrainerController TrainerFactory initialize_trainer load_config _load_config AgentExperience Trajectory SplitObservations BCModel BCModule create_reward_signal RewardSignal CuriosityModel CuriosityRewardSignal ExtrinsicRewardSignal GAILModel GAILRewardSignal PPOModel get_devices MultiGpuPPOPolicy PPOPolicy PPOTrainer get_gae discount_rewards SACPolicyNetwork SACTargetNetwork SACNetwork SACModel SACPolicy SACTrainer create_mock_pushblock_brain create_mock_batchedstep simulate_rollout make_brain_parameters setup_mock_brain make_fake_trajectory create_mock_banana_brain create_batchedstep_from_brainparams create_mock_brainparams create_mock_3dball_brain test_agent_manager_queue test_agentprocessor test_agent_manager create_mock_brain create_mock_policy test_barracuda_converter sac_dummy_config test_bcmodule_rnn_update test_bcmodule_update ppo_dummy_config test_bcmodule_constant_lr_update create_policy_with_bc_mock test_bcmodule_dc_visual_update test_bcmodule_defaults test_bcmodule_rnn_dc_update test_buffer_sample construct_fake_buffer test_num_experiences assert_array fakerandint test_buffer test_buffer_truncate test_curriculum_load_invalid_json default_reset_parameters test_load_bad_curriculum_file_raises_error test_curriculum_load_missing_file test_get_parameters test_init_curriculum_happy_path test_increment_lesson test_curriculum_load_good test_edge_cases test_load_demo test_load_demo_dir basic_options test_docker_target_path test_run_training test_env_args test_commandline_args test_increment_lessons_with_reward_buff_sizes test_increment_lessons measure_vals reward_buff_sizes test_set_all_curriculums_to_lesson_num test_get_config test_set_lesson_nums test_simple_metacurriculum test_curriculum_config test_create_model dummy_config test_average_gradients test_update basic_mock_brain test_take_action_returns_action_info_when_available basic_params test_take_action_returns_nones_on_missing_values test_take_action_returns_empty_with_no_agents test_trainer_increment_step test_trainer_update_policy test_min_visual_size test_process_trajectory test_rl_functions test_ppo_model_dc_vector_rnn test_ppo_model_cc_vector_rnn test_ppo_policy_evaluate test_ppo_model_cc_visual dummy_config test_ppo_model_dc_vector test_ppo_model_dc_visual test_ppo_get_value_estimates test_normalization test_ppo_model_cc_vector test_gail_dc_visual sac_dummy_config reward_signal_update reward_signal_eval test_extrinsic test_curiosity_cc test_gail_rnn test_gail_cc ppo_dummy_config create_policy_mock test_curiosity_dc curiosity_dummy_config test_curiosity_visual test_curiosity_rnn gail_dummy_config FakeTrainer create_rl_trainer dummy_config test_rl_trainer create_mock_brain test_clear_update_buffer test_sac_update_reward_signals create_sac_policy_mock test_process_trajectory test_sac_model_dc_visual test_sac_cc_policy test_sac_visual_policy test_sac_model_cc_vector_rnn test_sac_model_dc_vector test_sac_model_cc_vector dummy_config test_sac_model_dc_vector_rnn test_sac_model_cc_visual test_sac_rnn_policy test_sac_save_load_buffer test_sac_dc_policy test_empty_samplers sampler_config_1 check_value_in_intervals incorrect_uniform_sampler test_incorrect_sampler test_sampler_config_1 sampler_config_2 incorrect_sampler_config test_incorrect_uniform_sampler test_sampler_config_2 test_simple_sac clamp test_simple_ppo Simple1DEnvironment _check_environment_trains test_tensorboard_writer test_stat_reporter_text test_stat_reporter_add_summary_write test_csv_writer mock_env_factory SubprocessEnvManagerTest MockEnvWorker test_initialization_seed test_take_step_if_not_training test_start_learning_trains_until_max_steps_then_saves basic_trainer_controller test_take_step_adds_experiences_to_trainer_and_trains trainer_controller_with_take_step_mocks trainer_controller_with_start_learning_mocks test_start_learning_trains_forever_if_no_train_model test_initialize_ppo_trainer test_handles_no_default_section test_load_config_invalid_yaml test_initialize_invalid_trainer_raises_exception dummy_bad_config dummy_config test_load_config_missing_file test_load_config_valid_yaml test_initialize_trainer_parameters_override_defaults test_raise_if_no_config_for_brain dummy_config_with_override test_trajectory_to_agentbuffer test_split_obs np_zeros_no_float64 np_array_no_float64 _check_no_float64 np_ones_no_float64 main clean_previous_results TestResults parse_results main get_unity_executable_path get_base_path VerifyVersionCommand StepResult ActionType AgentGroupSpec BatchedStepResult BaseEnv Communicator UnityEnvironment UnityObservationException UnityWorkerInUseException UnityException UnityCommunicationException UnityTimeOutException UnityEnvironmentException UnityActionException MockCommunicator RpcCommunicator UnityToExternalServicerImplementation agent_group_spec_from_proto _generate_split_indices process_pixels observation_to_np_array batched_step_result_from_proto _process_vector_observation _process_visual_observation TimerNode hierarchical_timer get_timer_root get_timer_tree reset_timers set_gauge timed GaugeNode TimerStack UnityToExternalProtoServicer add_UnityToExternalProtoServicer_to_server UnityToExternalProtoStub EngineConfigurationChannel EngineConfig FloatPropertiesChannel RawBytesChannel SideChannelType SideChannel test_initialization test_reset test_returncode_to_signal_name test_close test_step test_handles_bad_filename test_rpc_communicator_checks_port_on_create test_rpc_communicator_create_multiple_workers test_rpc_communicator_close test_batched_step_result_from_proto generate_compressed_proto_obs test_agent_group_spec_from_proto test_vector_observation test_action_masking_continuous test_process_visual_observation test_action_masking_discrete_1 test_process_pixels test_process_visual_observation_bad_shape test_action_masking_discrete test_action_masking_discrete_2 generate_compressed_data test_process_pixels_gray generate_list_agent_proto generate_uncompressed_proto_obs test_raw_bytes test_int_channel test_float_properties IntChannel test_timers decorated_func main set_version extract_version_string check_versions sample UnityEnv create_mock_group_spec create_mock_vector_step_result setup_mock_unityenvironment step UnityEnv create_mock_group_spec create_mock_vector_step_result setup_mock_unityenvironment step setup_mock_unityenvironment UnityEnv create_mock_group_spec create_mock_vector_step_result sample UnityEnv create_mock_group_spec create_mock_vector_step_result setup_mock_unityenvironment step tuple CONTINUOUS range DISCRETE list array range set_verbosity join isdir print replaceFilenameExtension add_argument exit verbose source_file ArgumentParser target_file sqrt topologicalSort list hasattr layers addEdge Graph print inputs set len list hasattr layers print filter match trim_model compile data layers print tensors float16 replace layers dumps data dtype layers isinstance print name tensors inputs outputs shape zip array_without_brackets to_json globals Build array_equal pool reduce Build tanh mad tanh mul Build concat add sigmoid sub mad _ tanh mul Build concat add sigmoid mad print sorted keys is_action_discrete sum get_agent_step_result resequence_and_append done obs from_observations reward batched_step_result_from_proto vector_actions AgentBuffer append reset_agent vector_observations array visual_observations enumerate make_demo_buffer load_demonstration group_spec_to_brain_parameters isdir isfile get_demo_files add_argument_group add_argument ArgumentParser parse_args start_learning target_frame_rate create_sampler_manager EngineConfig trainer_config lesson keep_checkpoints docker_target_name sampler_config load_model multi_gpu TrainerController save_freq width quality_level run_id CSVWriter num_envs create_environment_factory height no_graphics try_create_meta_curriculum add_writer curriculum_config base_port env_args TrainerFactory SubprocessEnvManager time_scale train_model TensorboardWriter env_path pop SamplerManager MetaCurriculum set_all_curricula_to_lesson_num chmod format basename isdir glob copyfile copytree prepare_for_docker_run replace seed getLogger print debug _asdict run_training dumps set_warnings_enabled cpu randint setLevel get_version_string parse_command_line run_cli add_argument ArgumentParser RunOptions experiment_config_path load_config FloatPropertiesChannel get_property_dict_copy get_timer_root reset_timers put _send_response StepResponse list _generate_all_results set_actions set_property action set_configuration EngineConfigurationChannel external_brains payload items EnvironmentResponse reset step endswith len print HasField hasattr get_attr isinstance get_attr tensor_shape ndarray isinstance shape int_val bool_val float_val ListFields name ndarray isinstance str tensor_content ndarray product isinstance get_tensor_dtype print get_tensor_dims unpack int_val bool_val array float_val enter append add set Build mul sub insert Build tolist append range len locate_actual_output_node name find_tensor_by_name split locate_actual_output_node name lstm find_tensor_by_name find_forget_bias split get_layer_shape id Struct tensor get_layer_rank layer_ranks hasattr name patch_data rank input_shapes out_shapes input get_attr append replace_strings_in_list tensors embody astype op inputs zip enumerate print float32 patch_data_fn model_tensors map_ignored_layer_to_its_input co_argcount len items list hasattr get_tensors name print process_layer eval slow_but_stable_topological_sort ModelBuilderContext sort assign_ids pop range insert len layers verbose Struct process_model open print_known_operations fuse compress node GraphDef Model dims_to_barracuda_shape insert get_tensor_dims inputs MessageToJson ParseFromString cleanup_layers read memories print sort write trim summary print_supported_ops update str min_lesson_length format SACTrainer copy warning PPOTrainer get check_config rcls list_local_devices list zeros_like size reversed range append discount_rewards Mock CameraResolution arange ones append array range ones AgentExperience append zeros range len vector_action_space_size pop number_visual_observations to_agentbuffer make_fake_trajectory vector_observation_space_size create_mock_brainparams create_mock_brainparams create_mock_brainparams create_mock_brainparams create_mock_brainparams zeros Mock Mock create_mock_batchedstep ActionInfo publish_trajectory_queue AgentProcessor range create_mock_policy add_experiences AgentManager create_mock_policy Mock get_nowait AgentManagerQueue put join remove _get_candidate_names convert _get_default_tempdir dirname abspath isfile next dirname abspath create_policy_with_bc_mock ppo_dummy_config create_mock_3dball_brain update items list create_policy_with_bc_mock create_mock_3dball_brain update items list create_policy_with_bc_mock current_lr create_mock_3dball_brain update items list create_policy_with_bc_mock create_mock_3dball_brain update items list create_mock_banana_brain create_policy_with_bc_mock update items list create_mock_banana_brain create_policy_with_bc_mock flatten list range len append range AgentBuffer resequence_and_append get_batch construct_fake_buffer assert_array make_mini_batch AgentBuffer reset_agent array resequence_and_append sample_mini_batch construct_fake_buffer AgentBuffer resequence_and_append construct_fake_buffer AgentBuffer truncate resequence_and_append construct_fake_buffer AgentBuffer Curriculum Curriculum Curriculum dumps StringIO StringIO load_demonstration demo_to_buffer dirname abspath load_demonstration demo_to_buffer dirname abspath dirname abspath MagicMock basic_options MagicMock parse_command_line parse_command_line MetaCurriculum increment_lessons Mock MetaCurriculum assert_called_with increment_lessons assert_not_called MetaCurriculum assert_called_with MetaCurriculum set_all_curricula_to_lesson_num MetaCurriculum loads MetaCurriculum Simple1DEnvironment _check_environment_trains reset_default_graph MultiGpuPPOPolicy create_mock_brainparams reset_default_graph create_mock_brainparams update Mock reset_default_graph MultiGpuPPOPolicy create_mock_brainparams MagicMock TFPolicy AgentGroupSpec basic_mock_brain basic_params get_action empty MagicMock TFPolicy basic_mock_brain BatchedStepResult basic_params get_action array MagicMock TFPolicy basic_mock_brain ActionInfo BatchedStepResult basic_params get_action array list evaluate group_spec_to_brain_parameters agent_id close get_agent_group_spec get_step_result reset MockCommunicator PPOPolicy reset_default_graph UnityEnvironment get_value_estimates items list next_obs to_agentbuffer make_fake_trajectory BrainParameters PPOPolicy reset_default_graph values get_batched_value_estimates reset_default_graph reset_default_graph reset_default_graph reset_default_graph reset_default_graph reset_default_graph assert_array_almost_equal array discount_rewards Mock brain_name _increment_step BrainParameters assert_called_with add_policy PPOTrainer _update_policy simulate_rollout brain_name setup_mock_brain add_policy PPOTrainer create_policy list values brain_name subscribe_trajectory_queue put advance make_fake_trajectory BrainParameters AgentManagerQueue add_policy PPOTrainer create_policy brain_name make_fake_trajectory _process_trajectory BrainParameters add_policy zeros PPOTrainer range create_policy run setup_mock_brain update SACPolicy PPOPolicy simulate_rollout evaluate_batch brain model simulate_rollout brain prepare_update _execute_model update_dict make_mini_batch create_policy_mock reward_signal_update reward_signal_eval reward_signal_update reward_signal_eval create_policy_mock dirname abspath create_policy_mock reward_signal_update reward_signal_eval create_policy_mock reward_signal_update reward_signal_eval create_policy_mock reward_signal_update reward_signal_eval create_policy_mock reward_signal_update reward_signal_eval create_policy_mock reward_signal_update reward_signal_eval create_policy_mock reward_signal_update reward_signal_eval FakeTrainer dummy_config create_mock_brain list create_rl_trainer end_episode episode_steps values items list construct_fake_buffer create_rl_trainer clear_update_buffer setup_mock_brain SACPolicy update list evaluate brain create_sac_policy_mock simulate_rollout agent_id create_batchedstep_from_brainparams reset_default_graph brain simulate_rollout create_sac_policy_mock update_reward_signals reset_default_graph update list evaluate brain create_sac_policy_mock simulate_rollout agent_id create_batchedstep_from_brainparams reset_default_graph update list evaluate brain create_sac_policy_mock simulate_rollout agent_id create_batchedstep_from_brainparams reset_default_graph update resequence_and_append list evaluate brain create_sac_policy_mock simulate_rollout agent_id AgentBuffer create_batchedstep_from_brainparams reset_default_graph reset_default_graph reset_default_graph reset_default_graph reset_default_graph reset_default_graph reset_default_graph str SACTrainer save_model brain simulate_rollout num_experiences setup_mock_brain add_policy brain_name create_policy SACTrainer make_brain_parameters SamplerManager sample_all sampler_config_1 sampler_config_2 SamplerManager SamplerManager sample_all incorrect_uniform_sampler incorrect_sampler_config Simple1DEnvironment _check_environment_trains Simple1DEnvironment _check_environment_trains clear assert_called_once_with Mock get_stats_summaries add_stat add_writer StatsReporter float range write_stats clear Mock write_text add_writer StatsReporter assert_called_once_with TrainerController assert_called_with MagicMock start_learning assert_called_once MagicMock assert_not_called start_learning assert_called_once MagicMock MagicMock assert_called_once MagicMock advance EnvironmentStep add assert_not_called assert_called_once_with assert_called_once MagicMock advance EnvironmentStep add assert_not_called assert_called_once_with BrainParametersMock BrainParametersMock TrainerFactory BrainParameters brain_name generate TrainerFactory BrainParameters _load_config StringIO append from_observations range ones items list to_agentbuffer add set make_fake_trajectory extract_stack filename get __old_np_array _check_no_float64 get _check_no_float64 __old_np_zeros get __old_np_ones _check_no_float64 join remove mkdir rmdir exists documentElement getAttribute parse join clean_previous_results parse_results get_unity_executable_path print exit returncode get_base_path copy2 exists tuple vector_action_size mean reshape array data compressed_data reshape process_pixels shape array mean nan_to_num isnan warning array warning _process_vector_observation _process_visual_observation ones cast append sum _generate_split_indices discrete_action_branches astype is_action_discrete observation_shapes enumerate dot isnan nan_to_num any split bool array len range len perf_counter push reset method_handlers_generic_handler add_generic_rpc_handlers UnityEnvironment close MockCommunicator obs n_agents close get_agent_group_spec get_step_result reset MockCommunicator zip UnityEnvironment observation_shapes obs zip ones n_agents step close get_agent_group_spec get_step_result MockCommunicator set_actions zeros UnityEnvironment observation_shapes UnityEnvironment close MockCommunicator close RpcCommunicator close RpcCommunicator close RpcCommunicator list extend ObservationProto AgentInfoProto append prod range len fromarray uint8 BytesIO astype save ObservationProto generate_compressed_data extend shape ObservationProto shape tolist extend generate_compressed_data process_pixels rand generate_compressed_data process_pixels rand _process_vector_observation generate_list_agent_proto enumerate generate_compressed_proto_obs rand extend AgentInfoProto _process_visual_observation generate_uncompressed_proto_obs generate_compressed_proto_obs rand AgentInfoProto extend AgentGroupSpec CONTINUOUS batched_step_result_from_proto generate_list_agent_proto range AgentGroupSpec batched_step_result_from_proto DISCRETE generate_list_agent_proto action_mask AgentGroupSpec batched_step_result_from_proto DISCRETE generate_list_agent_proto action_mask AgentGroupSpec batched_step_result_from_proto DISCRETE generate_list_agent_proto action_mask AgentGroupSpec CONTINUOUS batched_step_result_from_proto generate_list_agent_proto action_mask BrainParametersProto agent_group_spec_from_proto extend _parse_side_channel_message _generate_side_channel_data send_int IntChannel FloatPropertiesChannel _parse_side_channel_message _generate_side_channel_data get_property set_property _parse_side_channel_message _generate_side_channel_data RawBytesChannel encode send_raw_data get_and_clear_received_messages set_gauge replace endswith add set walk join print extract_version_string set values print join | taesiri/my-mlagents-envs | 3,794 |
taichi-dev/taichi | ['physical simulations'] | ['DiffTaichi: Differentiable Programming for Physical Simulation'] | python/taichi/ui/scene.py tests/python/test_no_activate.py tests/python/test_tuple_assign.py python/taichi/ui/utils.py benchmarks/misc/run.py misc/test_gpu_async.py python/taichi/examples/algorithm/mciso_advanced.py misc/visualize_quant_types.py misc/idle_hello.py misc/benchmark_tensor_access.py tests/python/test_native_functions.py python/taichi/types/compound_types.py misc/appveyor_filter.py benchmarks/fill_sparse.py tests/python/test_indices_assert.py tests/python/test_scalar_op.py misc/benchmark_compile.py python/taichi/__main__.py tests/python/test_rescale.py tests/python/test_ast_refactor.py tests/python/test_assign.py python/taichi/examples/rendering/cornell_box.py tests/python/test_struct.py benchmarks/benchmark_async.py tests/python/test_test.py tests/python/test_fp_flush_to_zero.py python/taichi/ui/staging_buffer.py tests/python/test_tensor_dimensionality.py misc/upload_release.py tests/python/test_fill.py misc/fetch_active_contributors.py python/taichi/_testing.py python/taichi/examples/simulation/physarum.py python/taichi/ui/gui.py python/taichi/lang/ndrange.py tests/python/test_memory.py python/taichi/linalg/sparse_solver.py python/taichi/aot/record.py tests/python/test_reduction.py python/taichi/examples/features/sparse/tutorial.py benchmarks/misc/membound_cases.py tests/python/test_field.py python/taichi/ui/imgui.py misc/visualize_state_flow_graph.py misc/benchmark_reduction.py tests/python/test_expr_dict.py tests/python/test_custom_type_atomics.py benchmarks/utils.py python/taichi/examples/algorithm/marching_squares.py tests/python/test_pow.py tests/python/test_print.py tests/python/test_global_thread_idx.py tests/python/test_arg_alignment.py tests/python/test_compare.py python/taichi/examples/ggui_examples/mass_spring_3d_ggui.py tests/python/test_customized_grad.py misc/async_mgpcg.py python/taichi/ui/window.py python/taichi/examples/ggui_examples/fem128_ggui.py python/taichi/examples/rendering/sdf_renderer.py python/taichi/profiler/__init__.py python/taichi/examples/features/sparse/taichi_dynamic.py python/taichi/_lib/utils.py tests/python/test_offload.py python/taichi/lang/ast/ast_transformer.py tests/python/test_numpy_io.py tests/python/test_while.py tests/python/test_lexical_scope.py tests/python/test_numpy.py tests/python/test_ndrange.py python/taichi/lang/common_ops.py misc/code_format.py tests/python/test_stop_grad.py tests/python/test_immediate_layout.py tests/python/test_eig.py tests/python/test_exception.py tests/python/test_sort.py python/taichi/lang/expr.py tests/python/test_packed_size.py python/taichi/types/__init__.py tests/python/test_complex_struct.py tests/python/fuse_test_template.py benchmarks/minimal.py tests/python/test_mesh.py tests/python/test_ad_if.py tests/python/test_async.py tests/python/test_local_atomic_opt.py tests/python/test_global_store_grad.py python/taichi/examples/simulation/nbody.py python/taichi/examples/autodiff/simple_derivative.py python/taichi/lang/_ndarray.py misc/test_async_weaken_access.py tests/python/test_function_parameter_by_value.py tests/python/test_listgen.py tests/python/test_snode_layout_inspection.py misc/format_server.py tests/python/test_f16.py python/taichi/lang/source_builder.py tests/python/test_ad_for.py python/taichi/examples/features/gui/fullscreen.py python/taichi/lang/util.py misc/test_without_init.py python/taichi/linalg/sparse_matrix.py tests/python/test_dynamic.py tests/python/test_nested_kernel_error.py misc/benchmark_reduction_tmps.py python/taichi/ui/__init__.py tests/python/test_types.py python/taichi/examples/simulation/inital_value_problem.py tests/python/test_binding.py python/taichi/examples/simulation/fractal.py scripts/generate_pylint_tags.py python/taichi/lang/exception.py python/taichi/profiler/kernelmetrics.py tests/python/test_image_io.py misc/benchmark_scatter_bls.py tests/python/test_ad_demote_dense.py tests/python/test_matrix.py misc/make_changelog.py python/taichi/tools/patterns.py tests/python/test_external_func.py tests/python/test_div.py tests/python/test_abs.py python/taichi/examples/features/sparse/explicit_activation.py tests/python/test_custom_float_time_integration.py misc/demo_oob_ub.py tests/python/test_local_atomics.py tests/python/test_custom_float_exponents.py tests/python/test_arg_load.py python/taichi/examples/algorithm/print_offset.py python/taichi/examples/minimal.py python/taichi/examples/simulation/euler.py misc/save_new_version.py python/taichi/linalg/__init__.py python/taichi/examples/simulation/game_of_life.py tests/python/test_copy_from.py tests/python/test_type_check.py scripts/run_clang_tidy.py python/taichi/examples/autodiff/minimization.py tests/python/test_svd.py python/taichi/examples/features/io/export_ply.py tests/python/test_sparse_basics.py tests/python/test_matrix_different_type.py python/taichi/lang/matrix.py misc/test_memory_pool.py python/taichi/examples/algorithm/mgpcg.py python/taichi/examples/simulation/mpm128.py misc/benchmark_bit_struct_stores.py benchmarks/async_cases.py tests/python/test_arg_check.py tests/python/test_element_wise.py python/taichi/examples/ggui_examples/mass_spring_game_ggui.py tests/python/test_lang.py python/taichi/tools/np2ply.py python/taichi/ad.py tests/python/test_torch_io.py tests/python/test_trailing_bits.py misc/sparse_matrix.py python/taichi/tools/image.py tests/python/test_materialize_check.py benchmarks/mpm2d.py tests/python/test_clear_all_gradients.py tests/python38/test_ast_refactor.py python/taichi/examples/features/sparse/taichi_sparse.py python/taichi/examples/simulation/mass_spring_game.py tests/python/test_callable_template_mapper.py tests/python/test_serial_execution.py tests/python/test_fuse_dense.py tests/python/test_ad_offload.py tests/python/test_sync.py tests/python/test_classfunc.py tests/python/test_scope_errors.py python/taichi/lang/ast/symbol_resolver.py python/taichi/lang/kernel_impl.py tests/python/test_gc.py python/taichi/examples/simulation/stable_fluid.py ci/Dockerfile_generator.py tests/python/test_continue.py tests/python/test_optimization.py python/taichi/lang/ops.py misc/ci_download.py python/taichi/examples/simulation/waterwave.py python/taichi/examples/rendering/simple_uv.py benchmarks/fill_dense.py tests/python/test_for_break.py python/taichi/tools/diagnose.py python/taichi/lang/struct.py tests/python/test_ndarray.py tests/run_tests.py tests/python/test_atomic.py misc/test_gui.py python/taichi/_logging.py tests/python/test_indices.py python/taichi/_misc.py python/taichi/lang/impl.py tests/python/test_aot.py tests/python/test_mod.py tests/python/test_struct_for_dynamic.py python/taichi/examples/ggui_examples/mpm128_ggui.py tests/python/test_offload_cross.py tests/python/test_runtime.py misc/test_poly_timed.py tests/python/test_struct_for.py misc/test_print.py python/taichi/tools/util.py python/taichi/examples/simulation/mpm3d.py tests/python/test_ad_basics.py tests/python/test_return.py python/taichi/types/annotations.py python/taichi/lang/__init__.py misc/minimal_timed.py setup.py misc/demo_launch_overhead.py tests/python/test_non_taichi_types_in_kernel.py python/taichi/examples/algorithm/laplace.py misc/demo_listgen.py tests/python/test_static.py python/taichi/lang/mesh.py tests/python/test_mpm88.py python/taichi/__init__.py tests/python/test_kernel_templates.py misc/ci_setup.py python/taichi/examples/rendering/rasterizer.py python/taichi/examples/simulation/pbf2d.py python/taichi/examples/simulation/vortex_rings.py tests/python/test_grouped.py python/taichi/examples/simulation/comet.py tests/python/test_ssa.py tests/python/test_sparse_multi_tree.py python/taichi/aot/module.py python/taichi/examples/features/gui/gui_widgets.py python/taichi/_lib/__init__.py python/taichi/lang/meta.py python/taichi/lang/field.py tests/python/test_custom_float_shared_exp.py tests/python/test_spmv.py tests/python/test_struct_for_intermediate.py python/taichi/examples/simulation/mpm88.py tests/python/test_bitmasked.py tests/python/test_fields_builder.py tests/python/test_custom_float.py tests/python/test_threading.py tests/python/test_expr_list.py misc/test_grid_stride_loop.py python/taichi/tools/video.py python/taichi/lang/shell.py tests/python/test_function.py python/taichi/lang/snode.py tests/python/test_debug.py benchmarks/async_advection.py tests/python/test_cli.py tests/python/test_fuse_dynamic.py tests/python/test_offset.py tests/python/test_random.py benchmarks/misc/membound.py python/taichi/examples/ggui_examples/fractal3d_ggui.py python/taichi/profiler/kernelprofiler.py misc/count_tags.py tests/python/test_bit_array_vectorization.py python/taichi/lang/ast/checkers.py tests/python/test_ggui.py tests/python/test_custom_struct.py tests/python/test_sparse_matrix.py python/taichi/examples/simulation/ad_gravity.py python/taichi/ui/constants.py python/taichi/lang/quant_impl.py python/taichi/snode/__init__.py python/taichi/lang/ast/ast_transformer_utils.py benchmarks/memory_bound.py misc/demo_constant_fold.py python/taichi/lang/any_array.py misc/benchmark_parallel_compilation.py python/taichi/ui/camera.py tests/python/test_module_import.py python/make_release.py tests/python/test_no_grad.py misc/copyright.py python/taichi/examples/ggui_examples/mpm3d_ggui.py python/taichi/examples/features/gui/keyboard.py tests/python/test_bls_assume_in_range.py python/taichi/examples/autodiff/regression.py python/taichi/lang/sort.py benchmarks/misc/utils.py python/taichi/examples/simulation/fem99.py tests/python/test_torch_ad.py python/taichi/examples/simulation/fem128.py tests/python/test_get_external_tensor_shape.py tests/python/test_kernel_arg_errors.py tests/python/test_sfg.py tests/python/test_syntax_errors.py tests/python/test_empty.py tests/python/test_linalg.py python/taichi/snode/snode_tree.py tests/python/test_mpm_particle_list.py tests/python/bls_test_template.py python/taichi/examples/rendering/taichi_logo.py tests/python/test_bit_struct.py python/taichi/examples/features/io/export_mesh.py misc/spMv_linear_solve.py python/taichi/lang/kernel_arguments.py benchmarks/summarize_async.py python/taichi/lang/runtime_ops.py tests/python/test_gui.py tests/python/test_new_allocator.py tests/python/test_bit_operations.py tests/python/test_loop_unique.py tests/python/test_sparse_linear_solver.py tests/python/test_ast_resolver.py tests/python/test_bls.py python/taichi/ui/ui.py tests/python/test_parallel_range_for.py tests/python/test_ad_atomic.py misc/generate_ir_design_doc.py python/taichi/examples/simulation/implicit_mass_spring.py tests/python/test_loops.py tests/python/test_bit_array.py tests/python/test_basics.py misc/ci_check_pr_title.py python/taichi/examples/simulation/mpm_lagrangian_forces.py python/taichi/main.py python/taichi/lang/ast/__init__.py misc/demo_record_kernel_group.py tests/python/test_sparse_deactivate.py python/taichi/examples/features/sparse/taichi_bitmasked.py misc/demo_excepthook.py tests/python/test_custom_int.py python/taichi/snode/fields_builder.py python/taichi/lang/enums.py tests/python/test_constant_fold.py benchmarks/run.py python/taichi/aot/__init__.py tests/python/test_short_circuit.py python/taichi/examples/features/gui/gui_image_io.py tests/python/test_unary_ops.py tests/python/test_struct_for_non_pot.py misc/benchmark_bls.py python/taichi/examples/simulation/odop_solar.py tests/python/test_loop_grad.py python/taichi/examples/algorithm/mgpcg_advanced.py python/taichi/lang/ast/transform.py tests/python/test_ptr_assign.py tests/python/test_cast.py tests/python/test_internal_func.py tests/python/test_sparse_parallel.py tests/python/examples/algorithm/test_laplace.py python/taichi/lang/linalg_impl.py tests/python/test_assert.py tests/python/test_for_group_mismatch.py python/taichi/types/primitive_types.py python/taichi/examples/simulation/mpm99.py python/taichi/tools/__init__.py tests/python/test_oop.py tests/python/test_sparse_activate.py misc/benchmark_rebuild_graph.py tests/python/test_global_buffer_misalined.py tests/python/test_stencils.py python/taichi/lang/type_factory_impl.py python/taichi/_funcs.py python/taichi/lang/tape.py tests/python/test_cuda_internals.py python/taichi/examples/ggui_examples/stable_fluid_ggui.py python/taichi/tools/cc_compose.py python/taichi/examples/features/io/export_videos.py tests/python/test_tensor_reflection.py python/taichi/ui/canvas.py remove_files_with_extension BuildPy Clean CMakeExtension CMakeBuild EggInfo get_os_name remove_tmp get_python_executable simple_advection fill_scalar fill_array mpm_splitted chain_copy increments deep_hierarchy multires autodiff sparse_saxpy stencil_reduction benchmark_flat_range benchmark_nested_range_blocked benchmark_root_listgen benchmark_nested_range benchmark_nested_struct benchmark_nested_struct_listgen_16x16 benchmark_flat_struct benchmark_nested_struct_listgen_8x8 benchmark_nested_struct benchmark_nested_struct_fill_and_clear benchmark_memcpy benchmark_memset benchmark_saxpy benchmark_sscal benchmark_fill_scalar benchmark_range benchmark_struct TaichiBenchmark Case Suite benchmark_async get_benchmark_dir CaseImpl MemoryBound saxpy init_const membound_benchmark fill reduction BenchmarksInfo main BenchmarkSuites dump2json geometric_mean get_commit_hash dtype_size scaled_repeat_times md_table_header size2str arch_name datatime_with_format dtype2str _apply_color error warn Parser info main success AvailableColors format_plain_text has_suffix format_file find_clang_format_bin format_py_file main loud_sync update_x print_rTr restrict reduce smooth compute_Ap apply_preconditioner update_beta init update_p iterate update_alpha update_r prolongate foo test_unary grad_test substep foo fill reduce fill reduce laplace get_old_ver execute_command test_installation get_path_separator get_default_directory_name set_env get_os_name check_command_existence get_username get_shell_rc_name append_to_shell_rc get_shell_name Installer get_python_executable FileActionResult work_on_file WorkStats is_interested_ext work CommentStyle make_notice print_progress get_ctime_year main check_and_modify print_table calc_pi func0 func2 func1 func3 compute_div func test do_some_works compute_loss print_active_contributors TaichiFormatServer run extract_doc yml_to_md func main load_pr_tags p fill fill copy fill func load_inputs test_poly grad_test func test_without_init upload_taichi_version upload_artifact real_to_str fetch_bs serialize_i32 draw_coord f serialize_f32 set_vals reorder test_multiple_listgens test_activation_demotion test_fusion_range test_write_after_read test_fusion download grad_for grad_replaced timer TaichiMain main register registerableCLI _randn randn _matrix_cross2d _matrix_cross3d _matrix_outer_product _matrix_transpose set_logging_level is_logging_effective _get_logging approx get_rel_eps TestParam make_temp_file test allclose expected_archs Module KernelTemplate record_action_config record_action_hint record_action_entry start_recording stop_recording RecordKernelGroup p main laplace touch march get_vertex gauss MCISO MCISO_Example update_x restrict reduce smooth compute_Ap apply_preconditioner init update_p update_r prolongate paint MGPCG_Example MGPCG fill reduce gradient_descent update regress poly render paint fill_rgba move_particles place_pos paint check_activity sparse_api_demo activate paint_all_pixels paint_active_pixels make_lists scatter activate paint sparse_struct_for init_pos init_mesh advance render update_U paint_mouse_ball paint_triangles xw wx yx compute_sdf quat_mul xz dot xy compute_normal zx Julia quat_conj xyz set_indices step set_vertices init_scene render substep attract main new_particle render reset substep show_options init_vols CubeVolume render set_all_unused substep init set_color_by_material init_cube_vol subtract_gradient TexPair advect divergence pressure_jacobi enhance_vorticity backtrace apply_impulse MouseDataGen reset bilerp sample step vorticity lerp intersect_sphere mis_power_heuristic dot_or_zero intersect_aabb_transformed sample_brdf visible_to_light compute_brdf_pdf refract sample_direct_light intersect_light tonemap mat_mul_vec reflect render sample_ray_dir schlick intersect_aabb compute_area_light_pdf intersect_scene mat_mul_point intersect_plane sample_area_light make_box_transform_matrices TriangleRasterizer make_nested sdf intersect_light next_hit render ray_march out_dir sdf_normal paint paint init substep advance compute_U rand_unit_2d rand_unit_3d render substep generate update_Q calc_dt is_interior_cell sign is_interior_x_face set_ic paint is_interior_y_face w_to_q compute_F_thinc thinc copy_to_old q_to_w mc_lim compute_W compute_F_muscl is_boundary_y_face cosh HLLC_flux set_bc is_boundary_x_face get_cell_pos init_pos init_mesh paint_phi advance update_U init_pos init_mesh update_U advance complex_sqr paint calc_rule get_count init run Cloth init paint main new_particle substep attract reset substep T substep init substep init initialize substep g2p initialize mesh p2g compute_total_energy compute_T grid_op main update compute_force initialize SolarSystem poly6_value round_up epilogue prologue is_in_grid init_particles run_pbf render confine_position_to_boundary substep move_board print_stats main compute_scorr get_cell spiky_gradient step sense init subtract_gradient MouseDataGen copy_divergence bilerp TexPair divergence solve_pressure_sp_mat solve_pressure_jacobi enhance_vorticity apply_impulse sample lerp vorticity fill_laplacian_matrix pressure_jacobi apply_pressure backtrace reset step advect compute_u_single integrate_vortex init_tracers compute_u_full advect update create_wave gradient visualize_wave reset laplacian AnyArray AnyArrayAccess TaichiOperations Layout TaichiCompilationError TaichiSyntaxError InvalidOperationError Expr make_var_list make_expr_group SNodeHostAccess SNodeHostAccessor ScalarField Field static_assert ti_print zero stop_grad PyTaichi local_subscript_with_offset get_runtime one index_nd wrap_scalar current_cfg ti_assert global_subscript_with_offset expr_init_list ti_int ndarray static field make_constant_expr_i32 insert_expr_stmt_if_ti_func make_constant_expr begin_frontend_struct_for _Root subscript default_cfg ti_float expr_init_local_tensor inside_kernel static_print create_field_member _clamp_unsigned_to_range call_internal _UninitializedRootFieldsBuilder axes materialize_callback ti_format expr_init reset begin_frontend_if expr_init_func grouped mesh_relation_access decl_scalar_ret SparseMatrixEntry decl_sparse_matrix decl_any_arr_arg decl_scalar_arg SparseMatrixProxy Kernel KernelArgError Func KernelDefError _BoundedDifferentiableMethod _get_global_vars pyfunc _kernel_impl kernel data_oriented _get_tree_and_ctx func TaichiCallableTemplateMapper _inside_class eig2x2 svd svd2d polar_decompose polar_decompose2d sym_eig2x2 polar_decompose3d svd3d Vector VectorNdarray MatrixType _MatrixFieldElement Matrix MatrixNdarray _IntermediateMatrix MatrixField MeshElementField MeshElementFieldProxy MeshReorderedScalarFieldProxy MeshReorderedMatrixFieldProxy MeshAttrType MeshRelationAccessProxy MeshBuilder TriMesh Mesh MeshMetadata MeshInstance TetMesh MeshElement ext_arr_to_matrix fill_ndarray fill_tensor fill_ndarray_matrix fill_matrix snode_deactivate_dynamic ext_arr_to_tensor clear_gradients ndarray_to_ext_arr ndarray_to_ndarray tensor_to_tensor ext_arr_to_ndarray ndarray_matrix_to_ext_arr clear_loss vector_to_image matrix_to_ext_arr snode_deactivate tensor_to_image ext_arr_to_ndarray_matrix tensor_to_ext_arr vector_to_fast_image ndrange GroupedNDRange mul mod bit_and writeback_binary cos unary logical_not random bit_cast raw_div cmp_ne raw_mod floor atomic_add assign _binary_operation cmp_ge round abs log max bit_xor atomic_or ti_max rsqrt is_taichi_expr tan wrap_if_not_expr exp cmp_gt atomic_max ternary bit_shl stack_info bit_not add select cast sin _unary_operation ceil atomic_xor binary floordiv neg cmp_eq asin atomic_and ti_any sqrt atomic_sub bit_or atomic_min _ternary_operation tanh ti_min bit_shr ti_all cmp_lt min atan2 pow sub cmp_le acos truediv bit_sar Quant async_flush sync _shell_pop_print SNode deactivate length rescale_index get_addr is_active append activate sort_stage parallel_sort SourceBuilder Struct _IntermediateStruct StructField StructType TapeImpl TypeFactory to_taichi_type get_clangpp has_clangpp in_python_scope is_taichi_class in_taichi_scope has_pytorch python_scope to_pytorch_type taichi_scope to_numpy_type cook_dtype ScalarNdarray Ndarray NdarrayHostAccessor NdarrayHostAccess deactivate_all_snodes print_kernel_profile_info polar_decompose check_version stat_write benchmark collect_kernel_profile_metrics svd set_kernel_profile_metrics _SpecialConfig loop_unique _EnvironmentConfigurator get_host_arch_list benchmark_plot print_memory_profile_info block_local clear_all_gradients is_extension_supported sym_eig query_kernel_profile_info clear_kernel_profile_info eig cache_read_only is_arch_supported init mesh_local adaptive_arch_select assume_in_range no_activate try_check_version prepare_sandbox reset kernel_profiler_total_time Tape ASTTransformer build_stmts Builder VariableScopeGuard NonStaticStatus print_ast LoopScopeAttribute LoopStatus NonStaticScopeGuard LoopScopeGuard ASTTransformerContext KernelSimplicityASTChecker ASTResolver transform_tree SparseMatrixBuilder SparseMatrix SparseSolver get_predefined_cupti_metrics CuptiMetric KernelProfiler StatisticalResult get_default_kernel_profiler FieldsBuilder SNodeTree main ComposerCC ComposerBase main imwrite imresize imdisplay imshow imread cook_image_to_bytes PLYWriter taichi_logo core_veci dot_to_pdf get_traceback clear_profile_info set_gdb_trigger get_kernel_stats core_vec warning print_profile_info deprecated obsolete dump_dot get_ffmpeg_path make_video ffmpeg_common_args accelerate_video crop_video VideoManager mp4_to_gif interpolate_frames scale_video ArgAnyArray ext_arr Template vector matrix CompoundType struct Camera Canvas hex_to_rgb rgb_to_hex GUI Gui gen_normals_kernel get_normals_field Scene gen_normals_kernel_indexed gen_normals copy_vertices_to_vbo validate_input_field copy_colors_to_vbo to_u8_rgba copy_image_f32_to_u8 copy_to_vbo fill_vbo get_vbo_field copy_image_u8_to_u8 copy_texcoords_to_vbo copy_normals_to_vbo make_camera vec_to_euler euler_to_vec get_field_info Window package_root in_docker import_ti_core get_dll_name require_version check_exists compare_version locale_encode get_core_shared_object _print_taichi_header is_ci get_os_name print_red_bold at_startup run_tidy merge_replacement_files get_tidy_invocation check_clang_apply_replacements_binary main make_absolute apply_fixes find_compilation_database _test_python _test_cpp test bls_test_template bls_particle_grid template_fuse_reduction template_fuse_dense_x2y2z test_abs test_ad_reduce test_mod test_ad_precision_1 test_unary test_poly test_pow test_ad_precision_2 test_atan2 test_frac grad_test test_atan2_f64 test_obey_kernel_simplicity test_cast test_ad_frac test_size1 test_violate_kernel_simplicity1 test_violate_kernel_simplicity2 test_minmax test_ad_rand test_pow_f64 if_has_autograd test_trigonometric test_ad_demote_dense test_ad_fibonacci test_double_for_loops_more_nests test_complex_body test_ad_sum_local_atomic test_ad_power test_triple_for_loops_bls test_ad_sum test_double_for_loops test_ad_fibonacci_index test_integer_stack test_ad_global_ptr test_ad_if_parallel test_ad_if_nested test_stack test_ad_if_simple test_ad_if_parallel_complex test_ad_if_parallel_complex_f64 test_ad_if_mutable test_ad_if_parallel_f64 test_ad_if test_offload_order test_record test_opengl_8_ssbo test_opengl_exceed_max_ssbo test_mpm99_aot test_mpm88_aot test_save test_mpm88_ndarray test_non_dense_snode test_ret_write test_arg_read test_argument_error test_ext_arr test_arg_load_f64 test_arg_load test_assert_ok test_static_assert_message test_assert_message_formatted test_static_assert_vector_n_ok test_assert_message test_static_assert_data_type_ok test_assert_basic test_assert_minimal test_static_assert_is_static test_assign_assign test_assign_unpack test_assign_basic test_assign_ann_over test_assign_chained_unpack test_assign_ann test_assign_chained test_ast_resolver_direct_import test_ast_resolver_wrong_ti test_ast_resolver_chain test_ast_resolver_alias test_ast_resolver_basic test_listgen_opt_with_offsets test_simple test_numpy test_atomic_add_with_local_store_simplify2 test_atomic_xor_expr_evaled test_local_atomic_with_if test_atomic_add_with_if_simplify test_atomic_add_global_i32 test_atomic_and_expr_evaled test_atomic_add_demoted test_atomic_add_expr_evaled test_atomic_or_expr_evaled test_atomic_min_max_uint test_atomic_add_with_local_store_simplify1 test_atomic_max_expr_evaled test_atomic_sub_expr_evaled run_atomic_add_global_case test_atomic_add_global_f32 test_atomic_min_expr_evaled test_python_access test_while_global_load test_simple test_if test_range_loops test_datatype_string test_if_global_load test_binding test_bitmasked_listgen_bounded test_basic_packed _test_sparsity_changes test_sparsity_changes_packed test_huge_bitmasked test_basic test_bitmasked_2d_power_of_two test_bitmasked_offset_child _test_basic test_deactivate test_bitmasked_bitmasked test_bitmasked_then_dense test_root_deactivate test_sparsity_changes test_2D_bit_array test_1D_bit_array test_vectorized_struct_for test_offset_load test_evolve test_bit_sar test_bit_shl test_bit_shr test_bit_struct test_simple_array test_custom_int_full_struct test_bit_struct_struct_for test_custom_int_load_and_store test_multiple_inputs test_gather_1d test_gather_3d test_gather_2d test_scatter_2d test_scatter_1d_trivial test_scatter_1d test_simple_2d test_gather_2d_nonsquare _test_bls_stencil test_gather_1d_trivial test_simple_1d test_bls_large_block test_scattering_offset test_scattering test_gathering test_scattering_two_pointer_levels test_gathering_offset test_callable_template_mapper_numpy test_callable_template_mapper test_cast_f64 test_cast_default_fp test_cast_uint_to_float test_cast_float_to_uint test_cast_default_ip test_cast_within_while test_bit_cast test_custom_int_extension test_cast_f32 test_int_extension test_classfunc test_clear_all_gradients test_compare_basics test_compare_equality test_chain_compare test_no_duplicate_eval test_no_duplicate_eval_func test_static_in test_non_static_in test_complex_pointer test_complex_dense test_constant_fold test_for_continue test_unconditional_continue test_kernel_continue_in_nested_if_3 test_kernel_continue_in_nested_if_2 test_kernel_continue_in_nested_if test_while_continue test_kernel_continue test_scalar test_shfl_down test_do_nothing test_active_mask test_customized_kernels_indirect test_decorated_primal_is_taichi_kernel test_decorated_primal_missing_decorator test_customized_kernels_grad test_customized_kernels_tape test_customized_kernels_oop test_customized_kernels_oop2 test_custom_float test_custom_matrix_rotation test_custom_float_implicit_cast test_cache_read_only test_custom_float_truncation test_custom_float_atomic_demotion test_custom_float_precision test_custom_float_signed test_custom_float_unsigned test_shared_exponent_add test_negative test_shared_exponents test_shared_exponent_borrow test_custom_float_time_integration test_custom_int_implicit_cast test_struct_type test_copy_struct_in_taichi_scope test_struct_fill test_copy_python_scope_struct_to_taichi_scope test_local_struct_assign test_compound_type_implicit_cast test_struct_whole_access test_copy_struct_field_element_to_taichi_scope test_struct_member_access test_struct_assign test_matrix_type test_custom_float_atomics test_custom_int_atomics test_custom_int_atomics_b64 test_not_out_of_bound_dynamic test_cpu_debug_snode_reader test_not_out_of_bound_with_offset test_cpu_debug_snode_writer_out_of_bound test_cpu_debug_snode_reader_out_of_bound test_not_out_of_bound test_out_of_bound_with_offset test_out_of_bound test_cpu_debug_snode_writer_out_of_bound_negative test_cpu_debug_snode_reader_out_of_bound_negative test_out_of_bound_dynamic test_div_default_ip test_true_div _test_floor_div test_floor_div test_floor_div_pythonic _test_true_div _test_sym_eig2x2 test_eig2x2 _eigen_vector_equal test_sym_eig2x2 _test_eig2x2_real _test_eig2x2_complex test_unary test_ternary_i test_writeback_binary_f test_writeback_binary_i test_binary_i _c_mod test_binary_f test_empty test_empty_args test_super_long_line test_tab test_exception_multiline test_exception_from_func test_dictcomp_multiple_ifs test_expr_dict_field test_expr_dict_basic test_expr_list_basic test_listcomp_multiple_ifs test_source_builder_from_source test_source_builder_from_file test_snode_read_write test_unary_op test_to_torch test_fractal_f16 test_from_numpy test_atomic_add_f16 test_extra_unary_promote test_rand_promote test_float16 test_atomic_min_f16 test_binary_op test_to_numpy test_arg_f16 test_atomic_max_f16 test_cast_f32_to_f16 test_from_torch test_binary_extra_promote test_cast_f64_to_f16 test_scalar_field test_vector_field test_matrix_field test_field_name test_field_copy_from_with_non_filed_object test_field_needs_grad test_default_fp test_field_copy_from test_default_ip test_scalr_field_from_numpy_with_mismatch_shape test_field_copy_from_with_mismatch_shape test_scalr_field_from_numpy test_fields_builder_destroy test_fields_builder_dense test_fields_with_shape test_fields_builder_pointer test_fill_scalar test_fill_matrix_scalar test_fill_matrix_matrix test_for_break2 test_for_break3 test_for_break_complex test_for_break test_struct_for_mismatch2 _test_ndrange_for_mismatch2 _test_ndrange_for_mismatch _test_static_ndrange_for_mismatch _test_grouped_ndrange_for_mismatch test_struct_for_mismatch _test_grouped_struct_for_mismatch test_ftz_f32 test_ftz_f64 test_missing_return_annotation test_failing_multiple_return test_function_with_return test_function_without_return test_missing_arg_annotation test_default_templates test_call_expressions test_experimental_templates test_function_with_multiple_last_return test_python_function test_pass_by_value test_static_for_continue test_assert_message_formatted test_static_grouped_for test_recreate_variable test_for_break test_while_continue test_static_assign_element test_static_for test_while_break test_ifexp test_default_template_args_on_func test_chain_compare test_grouped_struct_for test_sparse_matrix_builder test_boolop test_struct_for test_func test_range_for_three_arguments test_dictcomp_fail test_dict test_range_for_single_argument test_single_compare test_func_default_value test_func_default_value_fail test_static_grouped_for_continue test_func_in_python_func test_static_ifexp test_static_for_break test_assert_message test_ndarray test_dictcomp test_if test_range_for_two_arguments test_augassign test_format_print test_static_assign test_for_continue test_grouped_static_for_cast test_grouped_ndrange_for test_ndrange_for test_taichi_other_than_ti test_while test_raise test_static_if test_return test_binop test_static_grouped_for_break test_unaryop test_scalar_argument test_listcomp test_compare_fail test_cli_gif test_cli_exit_one_with_bogus_command_provided test_cli_run test_cli_benchmark test_cli_video_crop test_cli_debug test_cli_example test_cli_exit_one_with_no_command_provided test_cli_video test_cli_regression test_cli_video_scale test_cli_video_speed patch_sys_argv_helper test_cli_can_dispatch_commands_to_methods_correctly test_dense_dynamic_len test_dynamic2 test_append_ret_value test_dynamic test_append test_dynamic_matrix test_dense_dynamic test_dynamic_activate test_length test_fuse_dense_x2y2z test_no_fuse_sigs_mismatch test_fuse_reduction test_nested_subscript test_loop_var_life test_meta_zero_one test_simple2 test_local_atomics test_recreate test_norm test_loop_var_life_double_iters test_mpm_particle_list_no_leakage_packed test_mpm_particle_list_no_leakage MPMSolver test_parallel_range_for test_pointer_is_active test_pointer2_packed test_pointer_direct_place test_pointer2 test_pointer _test_pointer2 test_fuse_dynamic_x2y2z benchmark_fuse_dynamic_x2y2z test_block_async test_pointer_gc _test_block_gc test_dynamic_gc test_block test_fuse_allocator_state test_get_external_tensor_shape_access_numpy test_get_external_tensor_shape_access_torch test_get_external_tensor_shape_access_ndarray test_get_external_tensor_shape_sum_numpy get_temp_png test_geometry_3d test_set_image test_geometry_2d test_imgui write_temp_image verify_image test_global_buffer_misalignment test_global_thread_idx test_grouped test_vector_index test_grouped_ndrange_0d test_static_grouped_func test_static_grouped_ndrange 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_test_type_assign_argument test_type_field64 test_type_assign_argument64 test_type_operator64 test_type_assign_argument _test_type_field test_unary_op test_binary_op test_subscript test_f64_trig _test_op test_break test_while test_laplace test_namedexpr startswith platform rmtree join endswith join remove listdir show int Vector GUI field benchmark init to_numpy range log set_image advect template_fuse_dense_x2y2z template_fuse_reduction benchmark field benchmark field int place field benchmark log benchmark field place benchmark field int initialize benchmark field place initialize field benchmark append range int place initialize pointer field benchmark i root range log field field place field place field place field place field place field place field fill place field field field field field field benchmark field range benchmark field range __name__ clear_kernel_profile_info func query_kernel_profile_info range scaled_repeat_times field dtype_size scaled_repeat_times init_const field dtype_size scaled_repeat_times init_const field dtype_size get join dump2json BenchmarkSuites print getcwd get_commit_hash run datatime_with_format BenchmarksInfo save add_suites_info append makedirs default_options __dict__ reversed arch_name value print print _apply_color print _apply_color print _apply_color list format partial parent os add_argument map Parser info parse_args success endswith format print GREEN RESET_ALL YELLOW file format_plain_text FormatFile sorted isdir glob find_diff_or_empty set Repo match diff format format_plain_text endswith print system find_clang_format_bin format_py_file ndrange pi sin grouped grouped grouped grouped grouped list restrict smooth reversed fill range prolongate print update_x print_rTr copy_from reduce compute_Ap apply_preconditioner update_beta update_p update_alpha update_r print time sync range place f32 field grad func time format print print_profile_info grad_test svd list exp static T Vector f32 min identity sqrt ndrange cast max range block_dim block_dim iter_commits Repo parse startswith get_shell_name print system exit print get_shell_rc_name execute_command format append_to_shell_rc str format check_output format split append format INSERTED_NOTICE MODIFIED_NOTICE search group make_notice start lower get_ctime_year range format write append print_progress check_and_modify join time format work_on_file WorkStats isdir sorted print check problematic_files paths opened_file_num isfile walk len docs exit ArgumentParser print items sorted list list static range static_assert func3 func2 func1 print print list static range get items sorted list json print set append print HTTPServer serve_forever join print strip len dirname startswith range find items list join dirname abspath load_pr_tags strip isupper iter_commits lower keys enumerate find print range range range impl print time print_profile_info grad_test i32 field json print getenv raise_for_status post split getenv exit extend check_call Vector list range reversed pack line range circle range len dense place sync i32 field foo bar i init dense place sync i32 pointer field foo bar i init range sync p i32 field init s place hello sync i32 field foo bar init fill place sync i32 restrict field init hasattr dir add set getattr TaichiMain cos random sqrt tau log default_fp static_assert static arch get get_rel_eps max isinstance mkstemp close get update partial arch_from_name set add filter startswith split expected_archs items list record_action_entry record_action_entry set laplace range norm Vector grouped gauss Vector list Vector static get_vertex ndrange atomic_add range reshape array int32 int snode get_addr int range static range static range max Vector cos random grouped Vector Vector format Vector deactivate print rescale_index is_active activate range print is_active ndrange ndrange append length range parent rotation2d Vector sin ndrange rescale_index print format cols range cross determinant trace abs log list static norm_sqr dot normalized range n Vector cols ndrange inverse range ndrange Vector range Vector get_cursor_pos circles paint_mouse_ball paint_triangles triangles dot quat_mul range quat_mul Vector quat_conj ndrange Vector ndrange norm Vector static min grouped max ndrange dot normalized norm range Vector range range PRESS get_events is_pressed get_canvas attract RMB begin show running render substep circles lines Window get_cursor_pos set_background_color fill SHIFT int text end slider_float new_particle zero transpose Matrix range zero int grouped block_dim Vector range Matrix Vector Matrix int isinstance volume material set_all_unused init_cube_vol range len Vector range init_vols begin set_color_by_material button end slider_float init checkbox color_edit_3 array range len point_light particles scene track_user_inputs set_camera ambient_light Vector max min sample bilerp backtrace Vector bilerp exp norm Vector sample y x sample y x sample sample sample max min normalized subtract_gradient cur print pressure_jacobi swap divergence enhance_vorticity apply_impulse to_numpy nxt sum range vorticity advect fill transpose inv array pi dot normalized Vector Vector dot sqrt Vector max dot Vector int list Vector static min max range mat_mul_vec mat_mul_point intersect_aabb intersect_aabb intersect_plane intersect_sphere Vector intersect_light intersect_aabb_transformed normalized intersect_scene dot intersect_light Vector random Vector random pi cross sqrt dot max sample_area_light Vector mis_power_heuristic dot_or_zero sample_brdf visible_to_light compute_brdf_pdf compute_area_light_pdf refract Vector schlick sample_brdf dot reflect compute_brdf_pdf max sample_ray_dir intersect_scene normalized sqrt dot Vector norm_sqr Vector random pi cross sqrt normalized int floor make_nested norm Vector min abs max sdf list Vector static range sdf_normal Vector int ray_march intersect_light next_hit out_dir Vector taichi_logo ndrange advance random pi rand_unit_2d random sqrt norm parent deactivate no_activate int norm rand_unit_2d static random rand_unit_3d atomic_add range int norm grouped q_to_w get_cell_pos Vector w_to_q Vector Vector sqrt Vector max min mc_lim list Vector static is_interior_y_face w_to_q is_boundary_y_face is_interior_x_face HLLC_flux range is_boundary_x_face tanh exp min sign cosh max list thinc static Vector is_interior_y_face w_to_q is_interior_cell is_boundary_y_face is_interior_x_face HLLC_flux abs range is_boundary_x_face atomic_min sqrt q_to_w is_interior_cell static atomic_max min sqrt atomic_min max to_numpy triangles complex_sqr static calc_rule get_count append linspace shape cos range sin GUI line to_numpy circle Vector range y Matrix x Matrix range compute_T mesh range compute_T inverse trace determinant log list Vector y static i32 cast float range x Vector normalized list Vector y static i32 Matrix cast float range x g2p initialize p2g reshape grid_op Vector random pi sqrt norm range norm Vector poly6_value norm list Vector static random range Vector static is_in_grid ndrange grouped atomic_add confine_position_to_boundary get_cell range compute_scorr spiky_gradient confine_position_to_boundary epilogue range substep prologue clear show rect to_numpy list Vector static random range print to_numpy init_particles run_pbf move_board print_stats random grouped Vector list sense ndrange cast ndrange grouped grouped copy_divergence solve apply_pressure cur cur pressure_jacobi swap nxt range solve_pressure_jacobi solve_pressure_sp_mat norm Vector Vector range Vector range compute_u_full range range ndrange exp ndrange laplacian pow sqrt gradient norm_sqr append make_id_expr range isinstance entries local_tensor_proxy push_back ptr ExprGroup hasattr isinstance Arch DataType ndrange Matrix isinstance entries isinstance loop_range ptr is_taichi_class int ndarray get_attribute entries isinstance is_taichi_class tuple size ptr is_primal element_shape AnyArrayAccess make_expr_group _IntermediateMatrix len getattr func append bits iinfo warn isinstance clear PyTaichi reset_default_compile_config kernels __p get_traceback append needs_grad global_new set_is_primal ptr make_id_expr set_name Expr set_grad cook_dtype create_field_member place Number isinstance set_grad len Number isinstance vars2entries create_print fused_string add_separators items format isinstance insert Expr enumerate append split ptr create_assert_stmt hasattr hasattr isinstance len ndrange isinstance ptr isinstance decl_arg cook_dtype decl_arg cook_dtype decl_arr_arg cook_dtype len cook_dtype Func _inside_class Func _inside_class join parse template_slot_locations isinstance args Name _get_global_vars getsourcefile return_type getsourcelines annotation func dedent returns enumerate getclosurevars _getframe strip match print Kernel _inside_class sqrt Matrix svd zero Matrix polar_decompose2d sqrt cast sifakis_svd_f32 zero tuple sifakis_svd_f64 expr_init assign range Vector zero rows identity cols trace normalized cast determinant Vector zero identity cols sqrt trace normalized cast determinant svd2d static polar_decompose2d static property grouped grouped fill grouped grouped grouped list static grouped m range n static_assert int static min ndrange max f32 cast grouped list static f32 cast grouped range n grouped grouped grouped grouped list static grouped m range n list static grouped m range n list static grouped m range n Expr ScalarField static grouped list static grouped m range n grouped deactivate parent grouped deactivate join format_list enumerate append append append cook_dtype is_taichi_class cook_dtype is_taichi_class is_taichi_expr Expr make_rand_expr cook_dtype logical_not stack_info ptr expr_assign len len info Vector isinstance min len shape I range n insert_append make_expr_group ptr expr_init ptr insert_activate make_expr_group ptr insert_deactivate make_expr_group min range print int sync sort_stage has_pytorch Type isinstance DataType print_info clear_info set_metrics set_metrics materialize print_memory_profiler_info get_runtime reset_snode_access_flag join print mkdtemp rmtree mkdir register python_version system get_version_minor dumps get_version_major Request get_version_patch startswith add_header encode join today check_version get_repo_dir exists makedirs i32 experimental_real_function f64 warn short_circuit_operators set_tmp_dir print_preprocessed _deepcopy set_default_ip list _SpecialConfig set_default_fp kernel_profiler _EnvironmentConfigurator f32 dir gdb_trigger add create_program getattr trace materialize_runtime get Thread use_gles locale_encode cfg start lower adaptive_arch_select FieldsBuilder enable_excepthook set_gdb_trigger info type keys set_kernel_profiler_mode excepthook set_logging_level arch_from_name print i64 prepare_sandbox reset _register_signal_handlers len ptr insert_snode_access_flag ptr get_field_members warn insert_snode_access_flag ptr get_field_members insert_snode_access_flag ptr get_field_members read_only default_fp default_fp default_fp default_fp materialize clear_loss clear_all_gradients materialize visit finalized_roots deactivate_all finalized_roots run_benchmark subplots warning max show list set_title bar get_repo_dir legend range gcf set_xticklabels normalize_to_lowest annotate keys enumerate join set_size_inches suptitle subplots_adjust set_xticks len get setdefault arch_name startswith arch get is_arch_supported warn print to_source info print_ast warn items try_print check_output executable startswith to_numpy uint8 astype reshape get_ipython to_numpy astype int32 data ascontiguousarray shape cook_image_to_bytes data ndarray ascontiguousarray C_memcpy to_numpy Vector2i tuple isinstance Vector3i Vector3d Vector2d isinstance Vector4f tuple Vector4d Vector3f Vector2f join format_list print RESET_ALL YELLOW BRIGHT set_core_trigger_gdb_when_crash system system system get_ffmpeg_path system remove sorted imwrite endswith makedirs append imread listdir range enumerate len join remove isinstance print len system copy ffmpeg_common_args mkdir rmdir range enumerate Release Move Press field normalized range atomic_add Vector normalized range gen_normals_kernel get_normals_field gen_normals_kernel_indexed field list static range list static range hasattr copy_to_vbo validate_input_field n copy_to_vbo validate_input_field n copy_to_vbo validate_input_field n copy_to_vbo validate_input_field fill_vbo n int list static min max range list static range copy_image_f32_to_u8 field shape copy_image_u8_to_u8 n dtype hasattr Scalar ptr Matrix TaichiVulkan TaichiCuda m TaichiX64 FieldInfo n Vector cos sin normalized cos acos asin package_root join setdlopenflags getdlopenflags set_lib_dir locale_encode realpath dirname package_root join print BRIGHT RESET_ALL RED set_core_state_python_imported print get_version_string map split join compare_version get_llvm_version_string print get_commit_hash get_repo_dir exists get_version_string print exit isabs append mkstemp close get join iglob close extend safe_load open check_call append style call format get config communicate get_tidy_invocation checks header_filter extra_arg clang_tidy_binary quiet append task_done extra_arg_before Popen checks check_clang_apply_replacements_binary cpu_count search check_call put open Lock merge_replacement_files mkdtemp quiet find_compilation_database Thread files start Queue apply_fixes compile load j export_fixes fix rmtree build_path len join print warn check_call reset dirname abspath exists cpu_count verbose abspath exists coverage failed_first dirname append get files marks keys join fail_fast print min show_output cov_append rerun cpp add_argument exit _test_cpp ArgumentParser arch parse_args exclusive place axes i32 create_block check field print_kernel_profile_info deactivate_all range populate place ij i32 check_s max p2g f32 field pointer from_numpy p2g_naive deactivate_all range insert g2p sort check_m array g2p_naive time sync x_to_y_to_z i32 x_to_y print min field y_to_z benchmark range sync time inc i32 print min field benchmark reset range place f32 field grad lazy_grad func range func field range grad default_fp print i32 place field grad_test grad_test grad_test place i32 field grad func2 func lazy_grad grad_test grad_test grad_test grad_test place f32 field grad func lazy_grad place f32 field grad func lazy_grad place f32 field grad func lazy_grad func f32 field f64 grad lazy_grad f32 field f64 lazy_grad field field float32 astype from_numpy to_numpy range f32 field grad compute_sum i32 f32 field grad range compute_sum i32 f32 field grad range i32 f32 field grad power range fib i32 print f32 field grad fill range int fib f32 field grad fill range task print f32 field grad range i32 print f32 field grad fill int_stack range i32 f32 field double_for grad fill range i32 f32 field double_for grad fill range complex i32 f32 field grad fill range f32 field grad fill range triple_for f32 field grad func lazy_grad f32 field grad func lazy_grad f32 field grad lazy_grad func fill range f32 field grad func lazy_grad f32 field grad func lazy_grad field f64 grad func lazy_grad f32 field grad func lazy_grad field f64 grad func lazy_grad func f32 field field dense place i field field ndarray init ndarray field f32 ndarray i32 field func i32 set_i32 place field place i32 f32 field set_f32 set_i32 set_f64 place set_i64 i32 f32 field place ones f32 field set_f32 range set_gdb_trigger assert_formatted field func func f32 field func f32 field func func_basic func_unpack func_chained func_chained_unpack func_assign func_ann init body init body init body init body namedtuple fake_ti init body double field range zeros inc range place inc sync field range sorted place print field func zip to_numpy i32 run_atomic_add_global_case f32 run_atomic_add_global_case test1 u64 field test0 i32 place field func place i32 field func range place i32 field func range place i32 field func range place i32 field func range field test i32 place field func i32 place field func i32 place field func i32 place field func i32 place field func i32 place field func i32 func i32 range field func i32 field if_test f32 field if_test2 range i32 fill field range i32 field range run serialize mul print make_binary_op_expr make_global_store_stmt core add init make_const_expr_i32 place i32 field i bitmasked sum run _test_basic _test_basic place i32 f32 field func place i32 f32 field func place i32 f32 field func count place i32 field func count dense place deactivate i32 field i bitmasked is_active run place i32 field i bitmasked run _test_sparsity_changes _test_sparsity_changes place i32 field i func bitmasked place ij field init bitmasked run dense place i32 field i bitmasked is_active deactivate_all run int place field set_val verify_val int place field set_val verify_val int place ij assign_vectorized pointer field verify init int place ij assign_vectorized pointer field verify init int place ij pointer field verify evolve_naive init evolve_vectorized range range range int place field __wrapped__ set_val verify_val int place field __wrapped__ from_numpy set_val verify_val array range len int place field test_single_bit_struct i32 i64 i16 i8 array place pointer field assign i fixed range place range copy populate place range copy populate bls_test_template _test_bls_stencil _test_bls_stencil _test_bls_stencil _test_bls_stencil _test_bls_stencil _test_bls_stencil _test_bls_stencil _test_bls_stencil place range copy populate place ij pointer field foo bls_particle_grid bls_particle_grid bls_particle_grid bls_particle_grid bls_particle_grid place i32 f32 field TaichiCallableTemplateMapper place i32 f32 field TaichiCallableTemplateMapper i32 field func i32 field func init init i32 field func i32 func1 f32 field func2 field run_cast_u32 run_cast_i32 int place run_cast_uint field i16 u16 run_cast_int fill Foo place f32 field lazy_grad clear_all_gradients range i32 place field func i32 place field func i32 place field func i32 field func i32 place field func dense set_z place ij set_b i32 set_y field set_w set_c set_x set_a range set_d set_z place ij set_b i32 set_y pointer field set_w set_c set_x set_a range set_d i32 field to_numpy range run i32 field to_numpy range run i32 field to_numpy range run i32 field to_numpy range run i32 field run i32 field run i32 field run i32 copy_from field test test test place f32 field lazy_grad place f32 field grad lazy_grad forward place f32 field lazy_grad A lazy_grad A lazy_grad place f32 field lazy_grad place f32 field lazy_grad foo fixed place field place rotate_18_degrees field get_scalar_field fixed range int place field foo custom_float int place field test custom_float custom_float int place field custom_float int place field custom_float int place field custom_float int place field int place field foo custom_float int place field foo custom_float int place field custom_float range int place inc field foo custom_float range custom_float int place field int place field pi advance get_scalar_field custom_float range append foo int place field place run_python_scope field run_taichi_scope init range place run_python_scope field run_taichi_scope init range fill_each field fill_all fill_elements range vector place run_python_scope i32 f32 field run_taichi_scope range vector init_taichi_scope init_python_scope run_python_scope field run_taichi_scope fill struct range vector run_python_scope field init run_taichi_scope fill struct range vector i2f_python_scope f2i_taichi_scope f2i_python_scope struct i2f_taichi_scope vector struct run_python_scope run_taichi_scope Struct test field test test foo int place field foo int place field int place field foo custom_float f32 field init set_gdb_trigger f32 field set_gdb_trigger f32 field set_gdb_trigger f32 field set_gdb_trigger f32 field set_gdb_trigger i32 field set_gdb_trigger i32 field func set_gdb_trigger i32 place field place i32 field func set_gdb_trigger set_gdb_trigger i32 field init set_gdb_trigger i32 field func field func field func i32 _test_floor_div f32 i32 f32 _test_true_div i64 field f32 func set_default_ip i32 range field func norm assert_allclose eig field eigen_solve astype argsort _eigen_vector_equal assert_allclose eig field eigen_solve astype argsort _eigen_vector_equal assert_allclose eig field eigen_solve astype argsort _eigen_vector_equal assert_allclose wrapped wrapped f32 field float32 from_numpy func to_numpy array i32 field from_numpy int32 func to_numpy array f32 field float32 from_numpy func to_numpy array i32 field from_numpy int32 func to_numpy array i32 f32 field float32 from_numpy int32 func to_numpy array i32 field from_numpy int32 func to_numpy array func arange func print getframeinfo currentframe getframeinfo print filename currentframe lineno getframeinfo print filename currentframe lineno getframeinfo print filename currentframe lineno f32 field i32 field range i32 field range from_source join from_file mkdtemp rmtree print field f16 print field float16 f16 field init to_numpy range arange field from_numpy init to_numpy range to_torch f16 print field init range to_torch from_torch field float16 init to range to_numpy field f16 add field f16 init foo field f16 foo field f16 foo field foo field f16 field paint foo field foo field foo field field isinstance field isinstance field isinstance from_numpy empty field empty field isinstance field func field init field init append field range fill copy_from field field zeros field f32 field assign_field_single assign_field_multiple range place f32 field finalize FieldsBuilder assign_field_single assign_field_multiple range place f32 field finalize FieldsBuilder assign_field_single assign_field_multiple_range_for assign_field_multiple_struct_for range place i32 field fill range place i32 field fill range place i32 Matrix field fill range place i32 field func range place i32 field func range place i32 field func range place i32 field func range f32 field f32 field f32 field foo field foo field i32 field run i32 field run i32 field run i32 field run i32 field i32 A field field run_func run_func i32 field verify run_kernel i32 task field foo f32 field range i32 f32 field foo range i32 range field foo i32 range field foo Vector i32 field foo range range foo i32 field i32 range field foo i32 range field foo i32 range field foo i32 range field foo i32 range field foo i32 range field foo i32 field f32 field func range i32 range field func i32 range field foo i32 range field foo i32 range field foo i32 range field foo foo foo place f32 field func i32 field func func i32 range field foo range i32 field range ndarray i32 ones range run SparseMatrixBuilder fill range build place f32 field deepcopy argv place f32 field range place f32 field func range place range field func place i32 sort field func append range place i32 f32 field get_len func place i32 field func range place i32 field skip func range place i32 field func range place i32 dynamic field i func init to_numpy template_fuse_dense_x2y2z template_fuse_reduction inc_by i32 field to_numpy inc_i range i32 place inc field place i32 f32 field test test2 range place i32 f32 field test test2 range test i32 field range test int is_integral field func fill step MPMSolver step MPMSolver i32 field fill to_numpy range place i32 f32 field func place i32 f32 field func place i32 print f32 field func _test_pointer2 _test_pointer2 foo place place time sync i32 x_to_y print min field y_to_z range benchmark_fuse_dynamic_x2y2z build_grid place sync ij move pointer field init deactivate_all range _test_block_gc _test_block_gc place dynamic field i deactivate_all range place ij pointer field deactivate_all range place sync pointer field i to_numpy deactivate_y activate_y enumerate ones func enumerate ones sum func ones func enumerate i32 ndarray func enumerate mkstemp get_temp_png remove write_image str get_temp_png remove parent write_image mean shape imread range len Vector i32 f32 field Window destroy render get_canvas write_temp_image range verify_image i32 get_canvas position make_camera init_mesh f32 field from_numpy render init_particles_1 lookat range Window destroy int set_camera init_particles_0 Scene write_temp_image array verify_image f32 field Window destroy init_img render get_canvas write_temp_image range verify_image Window destroy render write_temp_image range verify_image range test i32 field func place i32 field test range place i32 field test range place i32 field test range place i32 field test range place i32 field test range i32 field test i32 field test range field p2g show GUI field make_temp_file set_image sum imread paint remove imwrite reshape field make_temp_file from_numpy randint imread remove imwrite field astype make_temp_file from_numpy to_numpy_type remove imwrite field randint make_temp_file astype from_numpy to_numpy_type max astype float32 imresize place f32 field place f32 field physical_index_position fill range f32 field func i32 field test print range test sleep test test test_cpu test_cpu place inc inc2 i32 f32 field range place f32 field lazy_grad range fill aTob place range place aTob field fill range my_test dummy func field range init place f32 field sqrt init range place field init place field init place transpose f32 field range place field polar V range wrapped place inc field range int invert inv field from_numpy to_numpy assert_almost_equal empty range _test_mat_inverse_size range fill sqrt field range fill field range fill field range range field func range field func field func field func fill field range place i32 print field fill to_numpy range place i32 field fill to_numpy range f32 field func f32 field func f32 field func f32 field func f32 field func f32 field func i32 field func i32 field func i32 field func i32 field func i32 field func i32 field func f32 field func f32 field func place f32 field lazy_grad func range place f32 field astype lazy_grad int32 func range i32 place field paint i32 field test i32 field test i32 place field test place i32 field test range f32 field func place f32 field grad lazy_grad func range place f32 field grad lazy_grad func range inc_y place range inc_y place range inc_y place range place inc_y_z range place prepare_x inc_y_z range i32 field i32 place field get_scalar_field ops ops ops value field ops value field print Vector y Matrix atan2 z w func max x from_numpy field run from_numpy field run func2 func1 empty func3 i32 func1 field func2 func4 i32 field func Vector field Matrix field f32 field func Vector test i32 Vector field test test dense place i32 f32 field pointer get_scalar_field i root check_stride place i32 field get_scalar_field materialize place i32 field get_scalar_field materialize place i32 f32 field get_scalar_field materialize place i32 f32 field get_scalar_field materialize place i32 f32 field get_scalar_field materialize verify field init len verify init len int place field get_scalar_field verify init custom_float len i32 field range place build foo load_meta to_numpy Tet sum place vert_vert verts cell_cell build cell_vert vert_cell load_meta fill link Tet cells _test_mesh_for _test_mesh_for _test_mesh_for _test_mesh_for vector place i32 verts range build from_numpy foo load_meta link Tet array to_numpy len sum place build foo load_meta edges fill link Tet cells place build from_numpy foo load_meta to_numpy Tet array range len place i32 verts field range build foo load_meta fill link Tet to_numpy len field func field func func func i32 range field func func field substep fill to_numpy range run_mpm88_test run_mpm88_test test_ndarray test_numpy place f32 field func range place f32 field func range ndarray isinstance _test_scalar_ndarray _test_scalar_ndarray ndarray isinstance _test_vector_ndarray _test_vector_ndarray ndarray isinstance _test_matrix_ndarray _test_matrix_ndarray ndarray init ndarray init ndarray init ndarray init ndarray i32 ones range run ndarray i32 ones range run _test_ndarray_2d _test_ndarray_2d i32 copy_from ndarray _test_ndarray_copy_from_ndarray _test_ndarray_copy_from_ndarray i32 deepcopy ndarray i32 fill ndarray init deepcopy f32 ndarray range _test_ndarray_deepcopy _test_ndarray_deepcopy ndarray i32 ones f32 from_numpy fill _test_ndarray_numpy_io _test_ndarray_numpy_io i32 ndrange ndarray range _test_matrix_ndarray_python_scope _test_matrix_ndarray_python_scope i32 ndarray func _test_matrix_ndarray_taichi_scope _test_matrix_ndarray_taichi_scope i32 ndarray func _test_matrix_ndarray_taichi_scope_struct_for _test_matrix_ndarray_taichi_scope_struct_for i32 ndarray range i32 ndarray range i32 ndarray func i32 ndarray func i32 zeros ndarray func _test_compiled_functions _test_compiled_functions i32 ndarray _test_arg_not_match _test_arg_not_match i32 ndarray f64 _test_size_in_bytes _test_size_in_bytes f32 ndarray ndarray init f32 field func range f32 field func range f32 field func range i32 range field func f32 field func range range field func f32 field init f32 field range init i32 field range init i32 range field func func touch place f32 field MyList func place initialize dynamic f32 field i func range place f32 field grad field array place test_numpy i32 field array range float32 with_data_type float64 with_data_type int32 with_data_type int64 with_data_type place test_numpy i32 field empty range place test_numpy i32 transpose field empty range place test_numpy i32 field empty range i32 place empty field array range test_numpy empty test_numpy func1 func2 ndrange zeros range place i32 field to_numpy range place i32 field from_numpy empty range to_numpy a field range from_numpy field range place field f64 from_numpy to_numpy range f32 from_numpy to_numpy empty i32 ones field from_numpy to_numpy place f32 field lazy_grad compute_loss range f32 field grad lazy_grad range f32 field grad lazy_grad range place f32 field ker place f32 field ker f32 field ker f32 field ker i32 ker field place f32 field ker run run place field place field range test place field range test field range test field range test field range test Array2D m range n place inc Array2D inc2 f32 field grad lazy_grad m range n inc Array2D grad lazy_grad m range n range Array1D lazy_grad n Array1D lazy_grad range Solver run_hook TestPortery TestStatic i32 place field func i32 place field func i32 range field func i32 place field func i32 place field func i32 range field func i32 place field field func range field func f32 _test_pow_f f64 _test_pow_f i32 _test_pow_i _test_pow_i i64 sync func sync func sync func sync field func sync func sync field func sync field func print field sync func sync func list field func zip range range field func list field func zip range list field func zip range field func func MyClass f32 field init fill to_numpy range f32 field init fill to_numpy range f32 field fill to_numpy range int field to_numpy gen range gen f32 field range f32 field reset init append gen to_numpy int modf field f64 foo to_numpy f32 field init fill to_numpy range reduce field fill reduce_tmp to_numpy i32 _test_reduction_single _test_reduction_single u32 _test_reduction_single f32 _test_reduction_single i64 u64 _test_reduction_single _test_reduction_single f64 ones place set_b f32 field set_a range init list is_integral range zip i32 f32 _test_binary_func_ret environ list keys upper str f32 field range set_logging_level init Vector np_func astype init to_numpy Vector np_func astype init to_numpy to_numpy Vector array init Vector array init place place f32 field fill_range field range fill_struct field range clear place sync inc i32 field serial_z get_counters init_xy get_kernel_stats to_numpy range clear sync arange field from_numpy scatter get_counters get_kernel_stats to_numpy range arange f32 field from_numpy compute_mean_of_boundary_edges i32 field i32 field dense place i field dense int place field i i32 test_sort_for_dtype f32 pointer i activate dense place sync pointer field foo i deactivate place deactivate i32 f32 field pointer i func clear place f32 field pointer i func set10 range clear copy_from_temp place ij f32 field pointer clear_temp copy_to_temp fill2 fill to_numpy range clear j fetch_length i32 dynamic func analyze_pattern SparseMatrixBuilder f32 field solve build SparseSolver factorize fill range SparseMatrixBuilder fill range build SparseMatrixBuilder fill build SparseMatrixBuilder fill range build SparseMatrixBuilder fill range build SparseMatrixBuilder fill range build SparseMatrixBuilder transpose build fill range SparseMatrixBuilder fill range build SparseMatrixBuilder fill build SparseMatrixBuilder fill range build Vector sync test to_numpy range i32 activate place task sync field range SparseMatrixBuilder f32 field build fill range SparseMatrixBuilder f32 field build fill array range SparseMatrixBuilder f32 field build fill array range sqrt f32 field func f32 field func range range range i32 place field static i32 place field fill field range i32 field func i32 field func place run place f32 field lazy_grad range place f32 field lazy_grad range place f32 field lazy_grad range i32 place field range test_linear range i32 place field range i32 place field range i32 place field range i32 fill field i32 place fill field fill place i32 field fill range place i32 field fill range place i32 fill place i32 field fill range place i32 field fill range place i32 field fill range place i32 field fill range place func3 func1 field func2 place pointer field ijk int place field place field init count append place i32 field iterate range _test_nested _test_nested _test_nested _test_nested place i32 field accumulate range _test_1d _test_1d place i32 field accumulate range _test_2d _test_2d forward field f64 print field range run wrapped field run i32 range field func place f32 field place f32 field place f32 field place f32 field place f32 field i32 place field i32 field i32 field i32 field i32 field fill field append sum range _test_dimensionality range get_max_num_indices i32 place field dense j place i32 field k i dense j place i32 field k i materialize dense j place i32 field k i dense j place f32 field i get_rel_eps get_rel_eps get_rel_eps get backward ones f32 field apply tensor numpy range backward ones f32 field apply device tensor numpy range load inc field store is_available to numpy range append backward ones apply cpu tensor range ones tensor sum apply ones tensor sum apply to_torch ones from_torch f32 field tensor range from_torch zeros to_torch field from_torch to_torch field range to_torch from_torch f32 field get_num_compiled_functions is_available f32 field to_torch from_torch f32 field range to_torch from_torch f32 field range test_torch zeros place f32 field pointer i init place f32 field pointer i init range f32 field func f32 field f32 field f32 field func f32 field func f32 field func f32 field func f32 field f32 field func f32 field f32 field f32 field f32 field func field func _test_type_assign_argument _test_type_assign_argument range field func _test_type_operator _test_type_operator range field func _test_type_field _test_type_field is_signed field func _test_overflow _test_overflow to_numpy field run i32 ndarray format default_fp print field arch fill range wrapped i32 field func laplace range | taichi-dev/taichi | 3,795 |
taikiinoue45/RIAD | ['anomaly detection'] | ['Reconstruction by Inpainting for Visual Anomaly Detection'] | riad/run.py riad/models/unet.py riad/utils/early_stopping.py riad/criterions/msgms.py riad/criterions/ssim.py riad/metrics/__init__.py riad/models/__init__.py riad/runner/runner.py riad/utils/__init__.py riad/criterions/__init__.py riad/metrics/auroc.py riad/utils/utils.py riad/datasets/mvtec.py riad/runner/base_runner.py riad/datasets/__init__.py riad/runner/__init__.py main MSGMSLoss SSIMLoss MVTecDataset compute_auroc upconv2x2 UNetUpBlock UNet UNetDownBlock conv BaseRunner Runner EarlyStopping denormalize savefig mean_smoothing start_run log_params log_artifacts getcwd set_experiment params Runner log_param experiment_name set_tracking_uri run plot xlabel roc_curve close ylabel tight_layout savefig legend max roc_auc_score len ones to device set_title denormalize close colorbar imshow toggle_label ImageGrid zip tick_params enumerate array | taikiinoue45/RIAD | 3,796 |
tailintalent/causal | ['time series'] | ['Discovering Nonlinear Relations with Minimum Predictive Information Regularization'] | estimators/entropy_estimators.py estimators/entropy_test.py settings/global_param.py causality/util_causality.py util.py datasets/prepare_dataset.py estimators/setup.py estimators/Gaussian_estimators.py causality/causality_unified_exp.py settings/filepath.py causality/models.py record_data norm format_list get_args normalize_tensor make_dir plot_matrices sort_two_lists new_dict Early_Stopping train_test_split get_conditional_MI get_mutual_information plot_comparison MPIR elastic_Net get_model get_causal_influence get_Granger_linear_reg append_sig_to_tensor MLP_noise Variational_Entropy get_prfs get_MIs partition parse_filename get_AUCs get_ROC_AUC plot_examples flatten_matrix get_PR_AUC get_shapes plot_clusters process_time_series get_A_matrix get_synthetic_data centropydc corexcd midd centropycd column flatten mi ctc zip2 micd tc ctccd centropy corexd to_np_array shuffle_test entropyfromprobs discretize cmidd entropyd tcd elog ctcdc cmi midc entropy centropyd kldiv hist corexdc vectorize avgdigamma ctcd corex get_MI_from_cov get_MI_from_cov_np get_entropy_Gaussian get_cov_np get_MI_Gaussian get_noise_entropy get_entropy_Gaussian_list get_entropy_from_cov get_cov set_bad add_subplot xticks max yticks show set_title matshow canvas savefig append ceil expand_dims set_canvas binary range Inf format astype tight_layout close isinf float suptitle xlabel print min isnan any figure array len append zip print format dirname makedirs clamp isinstance int list view choice set device to range len update deepcopy deepcopy run_line_magic ndarray std isinstance view concatenate tuple reshape min mean shape stack append max range cat append cat view format print plot_matrices mi zeros get_shapes range index_select get_shapes zeros to range cmi mean TimeSeriesSplit ElasticNetCV zeros get_shapes fit concatenate flatten mean take to_np_array zeros get_shapes range LinearRegression log predict fit MLP_noise Loss_with_uncertainty Model_with_uncertainty get_criterion model model_dict squeeze plot_matrices to_np_array get_shapes range cat get_model format get_loss get_AUCs mean permute_dim flush deepcopy print kldiv zeros train any plot_matrices prfs flatten nanmean flatten_matrix to_np_array append range roc_auc_score len len nanmean precision_recall_curve flatten_matrix to_np_array append range auc format_list format print get_ROC_AUC get_PR_AUC any pi log2 mi device is_cuda view shape to_np_array to sum range size e float expand_tensor int get_entropy_Gaussian isinstance zeros std len list isinstance size set shape array range show xlabel KMeans min axvline ylabel mean title hist figure numpy max fit_predict show subplot plot concatenate size title figure range int float eval split append size range int list isinstance shape range len normalize_tensor view size mean shape stack cuda append std range len exponential randn plot_matrices choice lognormal zeros cuda Tensor enumerate randn model rand abs cuda list view FloatTensor plot_matrices shape to_np_array legend append sum range cat observational_model plot size choice sqrt stack enumerate int multivariate_normal get_A_matrix isinstance print process_time_series to_Variable repeat figure zeros numpy cKDTree digamma to_np_array log len entropy to_np_array flatten cKDTree zip2 flatten cKDTree zip2 cKDTree log to_np_array len to_np_array flatten flatten flatten entropyd discretize tuple get dict get list entropy print tuple set flatten dict keys range len flatten flatten flatten sort shuffle measure append range cKDTree query_ball_point range len data isinstance cpu numpy is_cuda append ndarray isinstance view print reshape tolist append Tensor array T concatenate flatten shape mean dot int det log transpose matmul flatten shape mean cat det e pi log2 float int log2 det get_cov diag eye append get_entropy_Gaussian get_cov e pi log2 stack append float sum range | tailintalent/causal | 3,797 |
taimurhassan/TST | ['instance segmentation', 'semantic segmentation'] | ['Trainable Structure Tensors for Autonomous Baggage Threat Detection Under Extreme Occlusion'] | codebase/cli_interface.py codebase/__main__.py codebase/models/segnet.py codebase/predict.py codebase/models/unet.py utils/structure_tensor_get.py codebase/models/model.py codebase/models/model_utils.py codebase/data_utils/data_loader.py trainer.py codebase/models/fcn.py codebase/models/resnet50.py codebase/models/_pspnet_2.py codebase/models/vgg16.py codebase/metrics.py codebase/models/pspnet.py codebase/models/basic_models.py codebase/models/config.py codebase/train.py codebase/data_utils/visualize_dataset.py codebase/data_utils/augmentation.py codebase/models/mobilenet.py train_action verify_dataset_action visualize_dataset_action evaluate_model_action predict_action main get_iou predict_multiple evaluate model_from_checkpoint_path predict train loss customLoss find_latest_checkpoint main _load_augmentation _try_n_times _augment_seg augment_seg get_segmentation_array get_image_array get_pairs_from_paths image_segmentation_generator DataLoaderError ImageSegmentationGen verify_segmentation_dataset _get_colored_segmentation_image visualize_segmentation_dataset_one visualize_segmentation_dataset vanilla_encoder fcn_32_mobilenet fcn_8_mobilenet fcn_8_vgg fcn_32_resnet50 fcn_32 fcn_8 fcn_32_vgg fcn_8_resnet50 crop get_mobilenet_encoder _depthwise_conv_block relu6 _conv_block Model resize_image get_segmentation_model transfer_weights pspnet_50 vgg_pspnet resnet50_pspnet pspnet pspnet_101 pool_block _pspnet one_side_pad identity_block conv_block get_resnet50_encoder vgg_segnet _segnet segnet mobilenet_segnet segnet_decoder resnet50_segnet unet_mini _unet resnet50_unet mobilenet_unet unet vgg_unet get_vgg_encoder residual_conv short_convolution_branch BN empty_branch ResNet residual_short interp_block residual_empty build_pyramid_pooling_module Interp _build_pspnet remove_center_line set_white_roc structureTensor scale_feature set_defaults add_argument add_parser set_defaults add_argument add_parser set_defaults add_argument add_parser set_defaults add_argument add_parser set_defaults add_argument add_parser train_action verify_dataset_action visualize_dataset_action evaluate_model_action func predict_action ArgumentParser parse_args add_subparsers maximum zeros float sum range read find_latest_checkpoint print loads load_weights string_types imwrite isinstance input_height get_image_array model_from_checkpoint_path output_height input_width n_classes output_width resize zeros imread argmax range string_types join str basename isinstance glob model_from_checkpoint_path tqdm append predict enumerate sum list print model_from_checkpoint_path get_pairs_from_paths output_height n_classes flatten tqdm mean output_width zip zeros argmax get_segmentation_array range predict mean sum glob list max str input_height find_latest_checkpoint print output_height input_width n_classes fit_generator save_weights load_weights ImageSegmentationGen output_width verify_segmentation_dataset range compile Sequential get_arr_int augment_segmentation_maps _load_augmentation SegmentationMapOnImage augment_image to_deterministic append listdir splitext string_types rollaxis isinstance astype float32 resize imread string_types isinstance reshape astype resize zeros imread range str format print get_pairs_from_paths tqdm imread max get_image_array shuffle get_pairs_from_paths cycle augment_seg append imread next get_segmentation_array range augment_seg range zeros_like print _get_colored_segmentation_image waitKey get_pairs_from_paths imshow imread print _get_colored_segmentation_image waitKey get_pairs_from_paths choice imshow imread append Input range abs output_shape encoder crop get_segmentation_model encoder get_segmentation_model fcn_8 fcn_32 fcn_8 fcn_32 fcn_8 fcn_32 int int get_file _depthwise_conv_block _conv_block load_weights Input list layers print tqdm zip get_weights set_weights Model input_shape MethodType output_shape resize_image resize_image get_segmentation_model append encoder pool_block _pspnet _pspnet _pspnet _build_pspnet _build_pspnet str add str add conv_block get_file one_side_pad load_weights identity_block Input range encoder segnet_decoder get_segmentation_model _segnet _segnet _segnet _segnet Input get_segmentation_model concatenate encoder get_segmentation_model concatenate _unet _unet _unet _unet get_file Input load_weights str str residual_conv short_convolution_branch residual_conv empty_branch residual_empty residual_short print range print exit tuple interp_block ResNet Input build_pyramid_pooling_module get_segmentation_model fit all sort where mean shape all where exp arange convolve float64 transpose astype apply_along_axis shape sum | taimurhassan/TST | 3,798 |
taimurhassan/cancer | ['scene parsing', 'whole slide images', 'semantic segmentation'] | ['A Dilated Residual Hierarchically Fashioned Segmentation Framework for Extracting Gleason Tissues and Grading Prostate Cancer from Whole Slide Images'] | codebase/cli_interface.py codebase/__main__.py codebase/models/net.py codebase/models/segnet.py codebase/predict.py codebase/models/unet.py codebase/models/model.py codebase/models/model_utils.py codebase/data_utils/data_loader.py codebase/models/net2.py trainer.py codebase/models/fcn.py codebase/models/_pspnet_2.py codebase/train2.py codebase/models/vgg16.py codebase/metrics.py codebase/models/pspnet.py codebase/models/basic_models.py codebase/models/all_models.py salient.py codebase/models/net_models.py codebase/models/drn_encoder.py codebase/models/config.py codebase/train.py codebase/data_utils/visualize_dataset.py codebase/data_utils/augmentation.py codebase/models/mobilenet.py resize_image train_action verify_dataset_action visualize_dataset_action evaluate_model_action predict_action main get_iou predict_multiple evaluate model_from_checkpoint_path predict train_maml customLoss find_latest_checkpoint np_to_tensor loss_function hLoss compute_loss copy_model train train loss customLoss find_latest_checkpoint main _load_augmentation _try_n_times _augment_seg augment_seg get_segmentation_array get_image_array get_pairs_from_paths image_segmentation_generator DataLoaderError ImageSegmentationGen verify_segmentation_dataset _get_colored_segmentation_image visualize_segmentation_dataset_one visualize_segmentation_dataset vanilla_encoder one_side_pad get_drn_encoder residual_block dcn fcn_32_mobilenet fcn_8_mobilenet fcn_8_vgg fcn_32_resnet50 fcn_32 fcn_8 fcn_32_vgg fcn_8_resnet50 crop get_mobilenet_encoder _depthwise_conv_block relu6 _conv_block Model resize_image get_segmentation_model transfer_weights vgg_net net_101 decoder get_segmentor net_50 drn_net net encoder net get_segmentor decoder net_encoder pspnet_50 vgg_pspnet resnet50_pspnet pspnet pspnet_101 pool_block _pspnet vgg_segnet _segnet segnet mobilenet_segnet drn_segnet segnet_decoder unet_mini _unet resnet50_unet mobilenet_unet unet vgg_unet get_vgg_encoder residual_conv short_convolution_branch BN empty_branch ResNet residual_short interp_block residual_empty build_pyramid_pooling_module Interp _build_pspnet set_defaults add_argument add_parser set_defaults add_argument add_parser set_defaults add_argument add_parser set_defaults add_argument add_parser set_defaults add_argument add_parser train_action verify_dataset_action visualize_dataset_action evaluate_model_action func predict_action ArgumentParser parse_args add_subparsers maximum zeros float sum range read find_latest_checkpoint print loads load_weights string_types imwrite isinstance input_height get_image_array model_from_checkpoint_path output_height input_width n_classes output_width resize zeros imread argmax range string_types join str basename isinstance glob model_from_checkpoint_path tqdm append predict enumerate sum list print model_from_checkpoint_path get_pairs_from_paths output_height n_classes flatten tqdm mean output_width zip zeros argmax get_segmentation_array range predict Variable loss_fn model mean sum glob list max string_types str input_height isinstance print find_latest_checkpoint output_height input_width n_classes fit_generator save_weights load_weights ImageSegmentationGen output_width verify_segmentation_dataset range compile get_weights resnet50_segnet set_weights list model Variable print Adam gradient apply_gradients trainable_weights zip range categorical_crossentropy Sequential get_arr_int augment_segmentation_maps _load_augmentation SegmentationMapOnImage augment_image to_deterministic append listdir splitext string_types rollaxis isinstance astype float32 resize imread string_types isinstance reshape astype resize zeros imread range str format print get_pairs_from_paths tqdm imread max get_image_array shuffle get_pairs_from_paths cycle augment_seg append imread next get_segmentation_array range augment_seg range zeros_like print _get_colored_segmentation_image waitKey get_pairs_from_paths imshow imread print _get_colored_segmentation_image waitKey get_pairs_from_paths choice imshow imread append Input range str add str add get_file dcn one_side_pad load_weights residual_block Input abs output_shape encoder crop get_segmentation_model encoder get_segmentation_model fcn_8 fcn_32 fcn_8 fcn_32 fcn_8 fcn_32 int int get_file _depthwise_conv_block _conv_block load_weights Input list layers print tqdm zip get_weights set_weights Model input_shape MethodType output_shape encoder decoder get_segmentation_model get_segmentor get_segmentor get_segmentor _build_net _build_net print resize_image append len Input add add append Input range resize_image resize_image get_segmentation_model append encoder pool_block _pspnet _pspnet _pspnet _build_pspnet _build_pspnet range encoder segnet_decoder get_segmentation_model _segnet _segnet _segnet _segnet Input get_segmentation_model concatenate encoder get_segmentation_model concatenate _unet _unet _unet _unet get_file Input load_weights str str residual_conv short_convolution_branch residual_conv empty_branch residual_empty residual_short print range print exit tuple interp_block ResNet Input build_pyramid_pooling_module get_segmentation_model | taimurhassan/cancer | 3,799 |
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