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| # Lint as: python3 | |
| # Copyright 2019 The TensorFlow Authors. All Rights Reserved. | |
| # | |
| # 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 | |
| # | |
| # http://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. | |
| # ============================================================================== | |
| """Configuration definitions for ResNet losses, learning rates, and optimizers.""" | |
| from __future__ import absolute_import | |
| from __future__ import division | |
| from __future__ import print_function | |
| from typing import Any, Mapping | |
| import dataclasses | |
| from official.modeling.hyperparams import base_config | |
| from official.vision.image_classification.configs import base_configs | |
| _RESNET_LR_SCHEDULE = [ # (multiplier, epoch to start) tuples | |
| (1.0, 5), (0.1, 30), (0.01, 60), (0.001, 80) | |
| ] | |
| _RESNET_LR_BOUNDARIES = list(p[1] for p in _RESNET_LR_SCHEDULE[1:]) | |
| _RESNET_LR_MULTIPLIERS = list(p[0] for p in _RESNET_LR_SCHEDULE) | |
| _RESNET_LR_WARMUP_EPOCHS = _RESNET_LR_SCHEDULE[0][1] | |
| class ResNetModelConfig(base_configs.ModelConfig): | |
| """Configuration for the ResNet model.""" | |
| name: str = 'ResNet' | |
| num_classes: int = 1000 | |
| model_params: base_config.Config = dataclasses.field( | |
| default_factory=lambda: { | |
| 'num_classes': 1000, | |
| 'batch_size': None, | |
| 'use_l2_regularizer': True, | |
| 'rescale_inputs': False, | |
| }) | |
| loss: base_configs.LossConfig = base_configs.LossConfig( | |
| name='sparse_categorical_crossentropy') | |
| optimizer: base_configs.OptimizerConfig = base_configs.OptimizerConfig( | |
| name='momentum', | |
| decay=0.9, | |
| epsilon=0.001, | |
| momentum=0.9, | |
| moving_average_decay=None) | |
| learning_rate: base_configs.LearningRateConfig = ( | |
| base_configs.LearningRateConfig( | |
| name='piecewise_constant_with_warmup', | |
| examples_per_epoch=1281167, | |
| warmup_epochs=_RESNET_LR_WARMUP_EPOCHS, | |
| boundaries=_RESNET_LR_BOUNDARIES, | |
| multipliers=_RESNET_LR_MULTIPLIERS)) | |