Export symbols of hyperparams module together.

PiperOrigin-RevId: 309457250

official/modeling/hyperparams/__init__.py

+# Lint as: python3
+# Copyright 2020 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.
+# ==============================================================================
+"""Hyperparams package definition."""
+
+from official.modeling.hyperparams.base_config import *
+from official.modeling.hyperparams.params_dict import *

official/vision/image_classification/classifier_trainer.py

@@ -15,12 +15,7 @@
 # ==============================================================================
 """Runs an Image Classification model."""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
 import os
-
 import pprint
 from typing import Any, Tuple, Text, Optional, Mapping
 
@@ -29,8 +24,8 @@ from absl import flags
 from absl import logging
 import tensorflow as tf
 
+from official.modeling import hyperparams
 from official.modeling import performance
-from official.modeling.hyperparams import params_dict
 from official.utils import hyperparams_flags
 from official.utils.misc import distribution_utils
 from official.utils.misc import keras_utils
@@ -186,7 +181,7 @@ def _get_params_from_flags(flags_obj: flags.FlagValues):
 
   for param in overriding_configs:
     logging.info('Overriding params: %s', param)
-    params = params_dict.override_params_dict(params, param, is_strict=True)
+    params = hyperparams.override_params_dict(params, param, is_strict=True)
 
   params.validate()
   params.lock()
@@ -290,7 +285,7 @@ def serialize_config(params: base_configs.ExperimentConfig,
   params_save_path = os.path.join(model_dir, 'params.yaml')
   logging.info('Saving experiment configuration to %s', params_save_path)
   tf.io.gfile.makedirs(model_dir)
-  params_dict.save_params_dict_to_yaml(params, params_save_path)
+  hyperparams.save_params_dict_to_yaml(params, params_save_path)
 
 
 def train_and_eval(