Add resnet_config.py.

Remove callback_test.py as it uses private TF symbol callback_test

PiperOrigin-RevId: 302990143

official/vision/image_classification/resnet/resnet_config.py

@@ -0,0 +1,61 @@
+# 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.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]
+
+
+@dataclasses.dataclass
+class ResNetModelConfig(base_configs.ModelConfig):
+  """Configuration for the ResNet model."""
+  name: str = 'ResNet'
+  num_classes: int = 1000
+  model_params: Mapping[str, Any] = 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))