mirror of
https://github.com/google-deepmind/deepmind-research.git
synced 2026-05-09 20:51:03 +08:00
Clara Huiyi Hu
98 lines
3.6 KiB
Python
98 lines
3.6 KiB
Python
# Copyright 2020 DeepMind Technologies Limited.
|
|
#
|
|
#
|
|
# 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.
|
|
"""Tests for BYOL's main training loop."""
|
|
|
|
from absl import flags
|
|
from absl.testing import absltest
|
|
import tensorflow_datasets as tfds
|
|
|
|
from byol import byol_experiment
|
|
from byol import eval_experiment
|
|
from byol import main_loop
|
|
from byol.configs import byol as byol_config
|
|
from byol.configs import eval as eval_config
|
|
|
|
|
|
FLAGS = flags.FLAGS
|
|
|
|
|
|
class MainLoopTest(absltest.TestCase):
|
|
|
|
def test_pretrain(self):
|
|
config = byol_config.get_config(num_epochs=40, batch_size=4)
|
|
temp_dir = self.create_tempdir().full_path
|
|
|
|
# Override some config fields to make test lighter.
|
|
config['network_config']['encoder_class'] = 'TinyResNet'
|
|
config['network_config']['projector_hidden_size'] = 256
|
|
config['network_config']['predictor_hidden_size'] = 256
|
|
config['checkpointing_config']['checkpoint_dir'] = temp_dir
|
|
config['evaluation_config']['batch_size'] = 16
|
|
config['max_steps'] = 16
|
|
|
|
with tfds.testing.mock_data(num_examples=64):
|
|
experiment_class = byol_experiment.ByolExperiment
|
|
main_loop.train_loop(experiment_class, config)
|
|
main_loop.eval_loop(experiment_class, config)
|
|
|
|
def test_linear_eval(self):
|
|
config = eval_config.get_config(checkpoint_to_evaluate=None, batch_size=4)
|
|
temp_dir = self.create_tempdir().full_path
|
|
|
|
# Override some config fields to make test lighter.
|
|
config['network_config']['encoder_class'] = 'TinyResNet'
|
|
config['allow_train_from_scratch'] = True
|
|
config['checkpointing_config']['checkpoint_dir'] = temp_dir
|
|
config['evaluation_config']['batch_size'] = 16
|
|
config['max_steps'] = 16
|
|
|
|
with tfds.testing.mock_data(num_examples=64):
|
|
experiment_class = eval_experiment.EvalExperiment
|
|
main_loop.train_loop(experiment_class, config)
|
|
main_loop.eval_loop(experiment_class, config)
|
|
|
|
def test_pipeline(self):
|
|
b_config = byol_config.get_config(num_epochs=40, batch_size=4)
|
|
temp_dir = self.create_tempdir().full_path
|
|
|
|
# Override some config fields to make test lighter.
|
|
b_config['network_config']['encoder_class'] = 'TinyResNet'
|
|
b_config['network_config']['projector_hidden_size'] = 256
|
|
b_config['network_config']['predictor_hidden_size'] = 256
|
|
b_config['checkpointing_config']['checkpoint_dir'] = temp_dir
|
|
b_config['evaluation_config']['batch_size'] = 16
|
|
b_config['max_steps'] = 16
|
|
|
|
with tfds.testing.mock_data(num_examples=64):
|
|
main_loop.train_loop(byol_experiment.ByolExperiment, b_config)
|
|
|
|
e_config = eval_config.get_config(
|
|
checkpoint_to_evaluate=f'{temp_dir}/pretrain.pkl',
|
|
batch_size=4)
|
|
|
|
# Override some config fields to make test lighter.
|
|
e_config['network_config']['encoder_class'] = 'TinyResNet'
|
|
e_config['allow_train_from_scratch'] = True
|
|
e_config['checkpointing_config']['checkpoint_dir'] = temp_dir
|
|
e_config['evaluation_config']['batch_size'] = 16
|
|
e_config['max_steps'] = 16
|
|
|
|
with tfds.testing.mock_data(num_examples=64):
|
|
main_loop.train_loop(eval_experiment.EvalExperiment, e_config)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
absltest.main()
|