51 lines
2.1 KiB
Python
51 lines
2.1 KiB
Python
# 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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"""Resampling dataset transformations."""
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from tensorflow.python.util import deprecation
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from tensorflow.python.util.tf_export import tf_export
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@deprecation.deprecated(None, "Use `tf.data.Dataset.rejection_resample(...)`.")
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@tf_export("data.experimental.rejection_resample")
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def rejection_resample(class_func, target_dist, initial_dist=None, seed=None):
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"""A transformation that resamples a dataset to achieve a target distribution.
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**NOTE** Resampling is performed via rejection sampling; some fraction
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of the input values will be dropped.
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Args:
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class_func: A function mapping an element of the input dataset to a scalar
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`tf.int32` tensor. Values should be in `[0, num_classes)`.
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target_dist: A floating point type tensor, shaped `[num_classes]`.
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initial_dist: (Optional.) A floating point type tensor, shaped
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`[num_classes]`. If not provided, the true class distribution is
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estimated live in a streaming fashion.
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seed: (Optional.) Python integer seed for the resampler.
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Returns:
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A `Dataset` transformation function, which can be passed to
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`tf.data.Dataset.apply`.
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"""
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def _apply_fn(dataset):
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"""Function from `Dataset` to `Dataset` that applies the transformation."""
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return dataset.rejection_resample(
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class_func=class_func,
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target_dist=target_dist,
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initial_dist=initial_dist,
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seed=seed)
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return _apply_fn
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