| # Copyright 2017 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. | |
| # ============================================================================== | |
| """Hyperparameters for the object detection model in TF.learn. | |
| This file consolidates and documents the hyperparameters used by the model. | |
| """ | |
| from __future__ import absolute_import | |
| from __future__ import division | |
| from __future__ import print_function | |
| import tensorflow as tf | |
| def create_hparams(hparams_overrides=None): | |
| """Returns hyperparameters, including any flag value overrides. | |
| Args: | |
| hparams_overrides: Optional hparams overrides, represented as a | |
| string containing comma-separated hparam_name=value pairs. | |
| Returns: | |
| The hyperparameters as a tf.HParams object. | |
| """ | |
| hparams = tf.contrib.training.HParams( | |
| # Whether a fine tuning checkpoint (provided in the pipeline config) | |
| # should be loaded for training. | |
| load_pretrained=True) | |
| # Override any of the preceding hyperparameter values. | |
| if hparams_overrides: | |
| hparams = hparams.parse(hparams_overrides) | |
| return hparams | |