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44 lines
1.6 KiB
44 lines
1.6 KiB
# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Hyperparameters for the object detection model in TF.learn.
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This file consolidates and documents the hyperparameters used by the model.
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"""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import tensorflow as tf
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def create_hparams(hparams_overrides=None):
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"""Returns hyperparameters, including any flag value overrides.
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Args:
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hparams_overrides: Optional hparams overrides, represented as a
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string containing comma-separated hparam_name=value pairs.
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Returns:
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The hyperparameters as a tf.HParams object.
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"""
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hparams = tf.contrib.training.HParams(
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# Whether a fine tuning checkpoint (provided in the pipeline config)
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# should be loaded for training.
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load_pretrained=True)
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# Override any of the preceding hyperparameter values.
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if hparams_overrides:
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hparams = hparams.parse(hparams_overrides)
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return hparams
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