# Copyright 2022 Google LLC | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# https://www.apache.org/licenses/LICENSE-2.0 | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
# ============================================================================== | |
model.name = 'film_net' | |
film_net.pyramid_levels = 7 | |
film_net.fusion_pyramid_levels = 5 | |
film_net.specialized_levels = 3 | |
film_net.sub_levels = 4 | |
film_net.flow_convs = | |
film_net.flow_filters = | |
film_net.filters = 64 | |
training.learning_rate = 0.0001 | |
training.learning_rate_decay_steps = 750000 | |
training.learning_rate_decay_rate = 0.464158 | |
training.learning_rate_staircase = True | |
training.num_steps = 3000000 | |
# in the sweep | |
training_dataset.file = 'gs://xcloud-shared/fitsumreda/frame_interpolation/datasets/vimeo_interp_train.tfrecord@200' | |
training_dataset.batch_size = 8 | |
training_dataset.crop_size = 256 | |
eval_datasets.batch_size = 1 | |
eval_datasets.max_examples = -1 | |
# eval_datasets.files = ['gs://xcloud-shared/fitsumreda/frame_interpolation/datasets/vimeo_interp_test.tfrecord@3', | |
# 'gs://xcloud-shared/fitsumreda/frame_interpolation/datasets/middlebury_other.tfrecord@3', | |
# 'gs://xcloud-shared/fitsumreda/frame_interpolation/datasets/UCF101_interp_test.tfrecord@2', | |
# 'gs://xcloud-shared/fitsumreda/frame_interpolation/datasets/xiph_2K.tfrecord@2', | |
# 'gs://xcloud-shared/fitsumreda/frame_interpolation/datasets/xiph_4K.tfrecord@2'] | |
# eval_datasets.names = ['vimeo90K', 'middlebury', 'ucf101', 'xiph2K', 'xiph4K'] | |
eval_datasets.files = | |
eval_datasets.names = | |
# Training augmentation (in addition to random crop) | |
data_augmentation.names = | |
# Loss functions | |
training_losses.loss_names = | |
training_losses.loss_weights = | |
test_losses.loss_names = | |
test_losses.loss_weights = | |