1# Copyright 2017 The TensorFlow Authors. All Rights Reserved. 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================== 15"""Unique element dataset transformations.""" 16from __future__ import absolute_import 17from __future__ import division 18from __future__ import print_function 19 20from tensorflow.python.data.experimental.ops import unique as experimental_unique 21from tensorflow.python.util import deprecation 22 23 24@deprecation.deprecated(None, "Use `tf.data.experimental.unique()`.") 25def unique(): 26 """Creates a `Dataset` from another `Dataset`, discarding duplicates. 27 28 Use this transformation to produce a dataset that contains one instance of 29 each unique element in the input. For example: 30 31 ```python 32 dataset = tf.data.Dataset.from_tensor_slices([1, 37, 2, 37, 2, 1]) 33 34 # Using `unique()` will drop the duplicate elements. 35 dataset = dataset.apply(tf.contrib.data.unique()) # ==> { 1, 37, 2 } 36 ``` 37 38 Returns: 39 A `Dataset` transformation function, which can be passed to 40 `tf.data.Dataset.apply`. 41 """ 42 return experimental_unique.unique() 43