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 tensorflow.python.util import deprecation 17from tensorflow.python.util.tf_export import tf_export 18 19 20@deprecation.deprecated(None, "Use `tf.data.Dataset.unique(...)") 21@tf_export("data.experimental.unique") 22def unique(): 23 """Creates a `Dataset` from another `Dataset`, discarding duplicates. 24 25 Use this transformation to produce a dataset that contains one instance of 26 each unique element in the input. For example: 27 28 ```python 29 dataset = tf.data.Dataset.from_tensor_slices([1, 37, 2, 37, 2, 1]) 30 31 # Using `unique()` will drop the duplicate elements. 32 dataset = dataset.apply(tf.data.experimental.unique()) # ==> { 1, 37, 2 } 33 ``` 34 35 Returns: 36 A `Dataset` transformation function, which can be passed to 37 `tf.data.Dataset.apply`. 38 """ 39 40 def _apply_fn(dataset): 41 return dataset.unique() 42 43 return _apply_fn 44