Delete configs

configs/callbacks/csv_prediction_writer.yaml

@@ -1,4 +0,0 @@
-csv_prediction_writer:
-  _target_: deepscreen.utils.lightning.CSVPredictionWriter
-  output_dir: ${paths.output_dir}
-  write_interval: batch

configs/callbacks/default.yaml

@@ -1,5 +0,0 @@
-defaults:
-  - model_checkpoint
-  - early_stopping
-  - model_summary
-  - rich_progress_bar

configs/callbacks/early_stopping.yaml

@@ -1,17 +0,0 @@
-# https://pytorch-lightning.readthedocs.io/en/latest/api/pytorch_lightning.callbacks.EarlyStopping.html
-
-# Monitor a metric and stop training when it stops improving.
-# Look at the above link for more detailed information.
-early_stopping:
-  _target_: lightning.pytorch.callbacks.EarlyStopping
-  monitor: ${oc.select:callbacks.model_checkpoint.monitor,"val/loss"} # quantity to be monitored, must be specified!!!
-  min_delta: 0. # minimum change in the monitored quantity to qualify as an improvement
-  patience: 50 # number of checks with no improvement after which training will be stopped
-  verbose: False # verbosity mode
-  mode: ${callbacks.model_checkpoint.mode} # "max" means higher metric value is better, can be also "min"
-  strict: True # whether to crash the training if monitor is not found in the validation metrics
-  check_finite: True # when set True, stops training when the monitor becomes NaN or infinite
-  stopping_threshold: null # stop training immediately once the monitored quantity reaches this threshold
-  divergence_threshold: null # stop training as soon as the monitored quantity becomes worse than this threshold
-  check_on_train_epoch_end: False # whether to run early stopping at the end of the training epoch
-  log_rank_zero_only: False  # logs the status of the early stopping callback only for rank 0 process

configs/callbacks/inference.yaml

@@ -1,6 +0,0 @@
-defaults:
-  - model_summary
-  - rich_progress_bar
-
-model_summary:
-  max_depth: 2

configs/callbacks/model_checkpoint.yaml

@@ -1,19 +0,0 @@
-# https://pytorch-lightning.readthedocs.io/en/latest/api/pytorch_lightning.callbacks.ModelCheckpoint.html
-
-# Save the model periodically by monitoring a quantity.
-# Look at the above link for more detailed information.
-model_checkpoint:
-  _target_: lightning.pytorch.callbacks.ModelCheckpoint
-  dirpath: ${paths.output_dir} # directory to save the model file
-  filename: "checkpoints/epoch_{epoch:03d}" # checkpoint filename
-  monitor: ${eval:'"val/loss" if ${data.train_val_test_split}[1] else "train/loss"'} # name of the logged metric which determines when model is improving
-  verbose: False # verbosity mode
-  save_last: True # additionally always save an exact copy of the last checkpoint to a file last.ckpt
-  save_top_k: 1 # save k best models (determined by above metric)
-  mode: "min" # "max" means higher metric value is better, can be also "min"
-  auto_insert_metric_name: False # when True, the checkpoints filenames will contain the metric name
-  save_weights_only: False # if True, then only the model’s weights will be saved
-  every_n_train_steps: null # number of training steps between checkpoints
-  train_time_interval: null # checkpoints are monitored at the specified time interval
-  every_n_epochs: null # number of epochs between checkpoints
-  save_on_train_epoch_end: null # whether to run checkpointing at the end of the training epoch or the end of validation

configs/callbacks/model_summary.yaml

@@ -1,7 +0,0 @@
-# https://pytorch-lightning.readthedocs.io/en/latest/api/pytorch_lightning.callbacks.RichModelSummary.html
-
-# Generates a summary of all layers in a LightningModule with rich text formatting.
-# Look at the above link for more detailed information.
-model_summary:
-  _target_: lightning.pytorch.callbacks.RichModelSummary
-  max_depth: 2 # The maximum depth of layer nesting that the summary will include. `-1` for all modules `0` for none.

configs/callbacks/rich_progress_bar.yaml

@@ -1,6 +0,0 @@
-# https://pytorch-lightning.readthedocs.io/en/latest/api/pytorch_lightning.callbacks.RichProgressBar.html
-
-# Create a progress bar with rich text formatting.
-# Look at the above link for more detailed information.
-rich_progress_bar:
-  _target_: lightning.pytorch.callbacks.RichProgressBar

configs/data/collator/default.yaml

@@ -1,5 +0,0 @@
-_target_: deepscreen.data.utils.collator.collate_fn
-_partial_: true
-
-automatic_padding: false
-padding_value: 0.0

configs/data/collator/none.yaml

@@ -1,2 +0,0 @@
-_target_: deepscreen.utils.passthrough
-_partial_: true

configs/data/drug_featurizer/ecfp.yaml

@@ -1,6 +0,0 @@
-_target_: deepscreen.data.featurizers.fingerprint.smiles_to_fingerprint
-_partial_: true
-
-fingerprint: MorganFP
-nBits: 1024
-radius: 2

configs/data/drug_featurizer/fcs.yaml

@@ -1,4 +0,0 @@
-_target_: deepscreen.data.featurizers.fcs.drug_to_embedding
-_partial_: true
-
-max_sequence_length: 205

configs/data/drug_featurizer/graph.yaml

@@ -1,2 +0,0 @@
-_target_: deepscreen.data.featurizers.graph.smiles_to_graph
-_partial_: true

configs/data/drug_featurizer/label.yaml

@@ -1,15 +0,0 @@
-#_target_: deepscreen.data.featurizers.categorical.smiles_to_label
-#_partial_: true
-#
-#max_sequence_length: 100
-##in_channels: 63
-
-_target_: deepscreen.data.featurizers.categorical.sequence_to_label
-_partial_: true
-charset: ['#', '%', ')', '(', '+', '-', '.', '1', '0', '3', '2', '5', '4',
-          '7', '6', '9', '8', '=', 'A', 'C', 'B', 'E', 'D', 'G', 'F', 'I',
-          'H', 'K', 'M', 'L', 'O', 'N', 'P', 'S', 'R', 'U', 'T', 'W', 'V',
-          'Y', '[', 'Z', ']', '_', 'a', 'c', 'b', 'e', 'd', 'g', 'f', 'i',
-          'h', 'm', 'l', 'o', 'n', 's', 'r', 'u', 't', 'y']
-
-max_sequence_length: 100

configs/data/drug_featurizer/mol_features.yaml

@@ -1,4 +0,0 @@
-_target_: deepscreen.data.featurizers.graph.smiles_to_mol_features
-_partial_: true
-
-num_atom_feat: 34

configs/data/drug_featurizer/none.yaml

@@ -1,2 +0,0 @@
-_target_: deepscreen.utils.passthrough
-_partial_: true

configs/data/drug_featurizer/onehot.yaml

@@ -1,15 +0,0 @@
-#_target_: deepscreen.data.featurizers.categorical.smiles_to_onehot
-#_partial_: true
-#
-#max_sequence_length: 100
-##in_channels: 63
-
-_target_: deepscreen.data.featurizers.categorical.sequence_to_onehot
-_partial_: true
-charset: ['#', '%', ')', '(', '+', '-', '.', '1', '0', '3', '2', '5', '4',
-          '7', '6', '9', '8', '=', 'A', 'C', 'B', 'E', 'D', 'G', 'F', 'I',
-          'H', 'K', 'M', 'L', 'O', 'N', 'P', 'S', 'R', 'U', 'T', 'W', 'V',
-          'Y', '[', 'Z', ']', '_', 'a', 'c', 'b', 'e', 'd', 'g', 'f', 'i',
-          'h', 'm', 'l', 'o', 'n', 's', 'r', 'u', 't', 'y']
-
-max_sequence_length: 100

configs/data/drug_featurizer/tokenizer.yaml

@@ -1,6 +0,0 @@
-_target_: deepscreen.data.featurizers.token.sequence_to_token_ids
-_partial_: true
-
-tokenizer:
-  _target_: deepscreen.data.featurizers.token.SmilesTokenizer
-  vocab_file: resources/vocabs/smiles.txt

configs/data/dti.yaml.bak

@@ -1,21 +0,0 @@
-_target_: deepscreen.data.dti_datamodule.DTIdatamodule
-
-defaults:
-  - _self_
-  - split: null
-  - drug_featurizer: null
-  - protein_featurizer: null
-
-task: ${task.task}
-n_class: ${oc.select:task.task.n_class,null}
-
-data_dir: ${paths.data_dir}
-dataset_name: null
-
-batch_size: 16
-train_val_test_split: [0.7, 0.1, 0.2]
-
-num_workers: 0
-pin_memory: false
-
-train: ${train}

configs/data/dti_data.yaml

@@ -1,20 +0,0 @@
-_target_: deepscreen.data.dti.DTIDataModule
-
-defaults:
-  - split: null
-  - drug_featurizer: none  # ???
-  - protein_featurizer: none  # ???
-  - collator: default
-
-task: ${task.task}
-num_classes: ${task.num_classes}
-
-data_dir: ${paths.data_dir}
-data_file: null
-train_val_test_split: null
-
-batch_size: ???
-num_workers: 0
-pin_memory: false
-
-#train: ${train}

configs/data/protein_featurizer/fcs.yaml

@@ -1,4 +0,0 @@
-_target_: deepscreen.data.featurizers.fcs.protein_to_embedding
-_partial_: true
-
-max_sequence_length: 545

configs/data/protein_featurizer/label.yaml

@@ -1,12 +0,0 @@
-#_target_: deepscreen.data.featurizers.categorical.fasta_to_label
-#_partial_: true
-#
-#max_sequence_length: 1000
-##in_channels: 26
-
-_target_: deepscreen.data.featurizers.categorical.sequence_to_label
-_partial_: true
-charset: ['A', 'C', 'B', 'E', 'D', 'G', 'F', 'I', 'H', 'K', 'M', 'L', 'O',
-          'N', 'Q', 'P', 'S', 'R', 'U', 'T', 'W', 'V', 'Y', 'X', 'Z']
-
-max_sequence_length: 1000

configs/data/protein_featurizer/none.yaml

@@ -1,2 +0,0 @@
-_target_: deepscreen.utils.passthrough
-_partial_: true

configs/data/protein_featurizer/onehot.yaml

@@ -1,12 +0,0 @@
-#_target_: deepscreen.data.featurizers.categorical.fasta_to_onehot
-#_partial_: true
-#
-#max_sequence_length: 1000
-##in_channels: 26
-
-_target_: deepscreen.data.featurizers.categorical.sequence_to_onehot
-_partial_: true
-charset: ['A', 'C', 'B', 'E', 'D', 'G', 'F', 'I', 'H', 'K', 'M', 'L', 'O',
-          'N', 'Q', 'P', 'S', 'R', 'U', 'T', 'W', 'V', 'Y', 'X', 'Z']
-
-max_sequence_length: 1000

configs/data/protein_featurizer/tokenizer.yaml

@@ -1,6 +0,0 @@
-_target_: deepscreen.data.featurizers.token.sequence_to_token_ids
-_partial_: true
-
-tokenizer:
-  _target_: tape.TAPETokenizer.from_pretrained
-  vocab: iupac

configs/data/protein_featurizer/word2vec.yaml

@@ -1,6 +0,0 @@
-_target_: deepscreen.data.featurizers.word.protein_to_word_embedding
-_partial_: true
-
-model:
-  _target_: gensim.models.Word2Vec.load
-  fname: ${paths.resource_dir}/models/word2vec_30.model

configs/data/split/cold_drug.yaml

@@ -1,4 +0,0 @@
-_target_: deepscreen.data.utils.split.cold_start
-_partial_: true
-
-entity: drug

configs/data/split/cold_protein.yaml

@@ -1,4 +0,0 @@
-_target_: deepscreen.data.utils.split.cold_start
-_partial_: true
-
-entity: protein

configs/data/split/random.yaml

@@ -1,10 +0,0 @@
-#_target_: torch.utils.data.random_split
-#_partial_: true
-
-#generator:
-#  _target_: torch.Generator # will use global seed set by lightning.seed_everything or torch.manual_seed automatically
-
-_target_: deepscreen.data.utils.split.random_split
-_partial_: true
-
-seed: ${seed}

configs/data/transform/minmax.yaml

@@ -1,5 +0,0 @@
-_target_: deepscreen.data.utils.transform
-_partial_: true
-
-scaler:
-  _target_: sklearn.preprocessing.MinMaxScaler

configs/data/transform/none.yaml

@@ -1,2 +0,0 @@
-_target_: deepscreen.utils.passthrough
-_partial_: true

configs/debug/advanced.yaml

@@ -1,25 +0,0 @@
-# @package _global_
-
-# advanced debug mode that enables callbacks, loggers and gpu during debugging
-job_name: "debug"
-
-extras:
-  ignore_warnings: False
-  enforce_tags: False
-
-hydra:
-  job_logging:
-    root:
-      level: DEBUG
-  verbose: True
-
-trainer:
-  max_epochs: 1
-  accelerator: gpu
-  devices: 1
-  detect_anomaly: true
-  deterministic: false
-
-data:
-  num_workers: 0
-  pin_memory: False

configs/debug/default.yaml

@@ -1,35 +0,0 @@
-# @package _global_
-
-# default debugging setup, runs 1 full epoch
-# other debugging configs can inherit from this one
-
-# overwrite job name so debugging logs are stored in separate folder
-job_name: "debug"
-
-# disable callbacks and loggers during debugging
-callbacks: null
-logger: null
-
-extras:
-  ignore_warnings: False
-  enforce_tags: False
-
-# sets level of all command line loggers to 'DEBUG'
-# https://hydra.cc/docs/tutorials/basic/running_your_app/logging/
-hydra:
-  job_logging:
-    root:
-      level: DEBUG
-  # use this to also set hydra loggers to 'DEBUG'
-  verbose: True
-
-trainer:
-  max_epochs: 1
-  accelerator: cpu # debuggers don't like gpus
-  devices: 1 # debuggers don't like multiprocessing
-  detect_anomaly: true # raise exception if NaN or +/-inf is detected in any tensor
-  deterministic: false
-
-data:
-  num_workers: 0 # debuggers don't like multiprocessing
-  pin_memory: False # disable gpu memory pin

configs/debug/fdr.yaml

@@ -1,11 +0,0 @@
-# @package _global_
-
-# runs 1 train, 1 validation and 1 test step
-
-defaults:
-  - default
-
-trainer:
-  accelerator: gpu
-  fast_dev_run: true
-  detect_anomaly: true

configs/debug/fdr_advanced.yaml

@@ -1,11 +0,0 @@
-# @package _global_
-
-# runs 1 train, 1 validation and 1 test step
-
-defaults:
-  - advanced
-
-trainer:
-  accelerator: gpu
-  fast_dev_run: true
-  detect_anomaly: true

configs/debug/limit.yaml

@@ -1,12 +0,0 @@
-# @package _global_
-
-# uses only 1% of the training data and 5% of validation/test data
-
-defaults:
-  - default
-
-trainer:
-  max_epochs: 3
-  limit_train_batches: 0.01
-  limit_val_batches: 0.05
-  limit_test_batches: 0.05

configs/debug/overfit.yaml

@@ -1,13 +0,0 @@
-# @package _global_
-
-# overfits to 3 batches
-
-defaults:
-  - default
-
-trainer:
-  max_epochs: 20
-  overfit_batches: 3
-
-# model ckpt and early stopping need to be disabled during overfitting
-callbacks: null

configs/debug/profiler.yaml

@@ -1,12 +0,0 @@
-# @package _global_
-
-# runs with execution time profiling
-
-defaults:
-  - default
-
-trainer:
-  max_epochs: 1
-  profiler: "simple"
-  # profiler: "advanced"
-  # profiler: "pytorch"

configs/experiment/bindingdb.yaml

@@ -1,9 +0,0 @@
-# @package _global_
-defaults:
-  - dti_experiment
-  - override /task: binary
-
-data:
-  train_val_test_split: [dti_benchmark/random_split_update/bindingdb_train.csv,
-                         dti_benchmark/random_split_update/bindingdb_valid.csv,
-                         dti_benchmark/random_split_update/bindingdb_test.csv]

configs/experiment/chembl_random.yaml

@@ -1,9 +0,0 @@
-# @package _global_
-defaults:
-  - dti_experiment
-  - override /task: binary
-
-data:
-  train_val_test_split: [chembl_random_global_balance_1_train.csv,
-                         chembl_random_global_balance_1_valid.csv,
-                         chembl_random_global_balance_1_test.csv]

configs/experiment/chembl_rmfh_random.yaml

@@ -1,9 +0,0 @@
-# @package _global_
-defaults:
-  - dti_experiment
-  - override /task: binary
-
-data:
-  train_val_test_split: [chembl_rmFH_random_global_balance_1_train.csv,
-                         chembl_rmFH_random_global_balance_1_valid.csv,
-                         chembl_rmFH_random_global_balance_1_test.csv]

configs/experiment/davis.yaml

@@ -1,9 +0,0 @@
-# @package _global_
-defaults:
-  - dti_experiment
-  - override /task: binary
-
-data:
-  train_val_test_split: [dti_benchmark/random_split_update/davis_train.csv,
-                         dti_benchmark/random_split_update/davis_valid.csv,
-                         dti_benchmark/random_split_update/davis_test.csv]

configs/experiment/demo_bindingdb.yaml

@@ -1,9 +0,0 @@
-# @package _global_
-defaults:
-  - dti_experiment
-  - override /task: binary
-  - override /data/split: random
-
-data:
-  data_file: demo/binddb_ic50_demo.csv
-  train_val_test_split: [0.7, 0.1, 0.2]

configs/experiment/dti_experiment.yaml

@@ -1,19 +0,0 @@
-# @package _global_
-defaults:
-  - override /data: dti_data
-  - override /model: dti_model
-  - override /trainer: gpu
-
-seed: 12345
-
-trainer:
-  min_epochs: 1
-  max_epochs: 500
-  precision: 16-mixed
-
-callbacks:
-  early_stopping:
-    patience: 50
-
-data:
-  num_workers: 8

configs/experiment/example.yaml

@@ -1,35 +0,0 @@
-# @package _global_
-
-# to execute this experiment run:
-# python train.py experiment=example
-
-defaults:
-  - override /data: dti_data
-  - override /data/drug_featurizer: onehot
-  - override /data/protein_featurizer: onehot
-  - override /model: dti_model
-  - override /model/protein_encoder: cnn
-  - override /model/drug_encoder: cnn
-  - override /model/decoder: concat_mlp
-  - override /callbacks: default
-  - override /trainer: default
-
-# all parameters below will be merged with parameters from default configurations set above
-# this allows you to overwrite only specified parameters
-
-tags: ["dti"]
-
-seed: 12345
-
-data:
-  data_file: davis.csv
-  batch_size: 64
-
-model:
-  optimizer:
-    lr: 0.0001
-
-trainer:
-  min_epochs: 1
-  max_epochs: 100
-  accelerator: gpu

configs/experiment/ion_channels.yaml

@@ -1,9 +0,0 @@
-# @package _global_
-defaults:
-  - dti_experiment
-  - override /task: binary
-
-data:
-  train_val_test_split: [dti_benchmark/ChEMBL33/train/Ion_channels_train_data.csv,
-                         dti_benchmark/ChEMBL33/valid/Ion_channels_valid_data.csv,
-                         dti_benchmark/ChEMBL33/test/Ion_channels_both_unseen_test_data.csv]

configs/experiment/kiba.yaml

@@ -1,9 +0,0 @@
-# @package _global_
-defaults:
-  - dti_experiment
-  - /task: binary
-
-data:
-  train_val_test_split: [dti_benchmark/random_split_update/kiba_train.csv,
-                         dti_benchmark/random_split_update/kiba_valid.csv,
-                         dti_benchmark/random_split_update/kiba_test.csv]

configs/experiment/kinase.yaml

@@ -1,13 +0,0 @@
-# @package _global_
-defaults:
-  - dti_experiment
-  - override /task: binary
-
-data:
-  train_val_test_split:
-    - dti_benchmark/ChEMBL33/train/kinase_train_data.csv
-    - null
-    - null
-#                         dti_benchmark/ChEMBL33/valid/kinase_valid_data.csv,
-#                         dti_benchmark/ChEMBL33/test/kinase_both_unseen_test_data.csv
-

configs/experiment/membrane_receptors.yaml

@@ -1,13 +0,0 @@
-# @package _global_
-defaults:
-  - dti_experiment
-  - override /task: binary
-
-data:
-  train_val_test_split:
-    - dti_benchmark/ChEMBL33/train/Membrane_receptor_train_data.csv
-    - null
-    - null
-#                         dti_benchmark/ChEMBL33/valid/Membrane_receptor_valid_data.csv,
-#                         dti_benchmark/ChEMBL33/test/Membrane_receptor_drug_repo_test_data.csv
-