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 """Enumerate dataset transformations.""" 16 from __future__ import absolute_import 17 from __future__ import division 18 from __future__ import print_function 19 20 import numpy as np 21 22 from tensorflow.python.data.ops import dataset_ops 23 from tensorflow.python.framework import dtypes 24 25 26 def enumerate_dataset(start=0): 27 """A transformation that enumerate the elements of a dataset. 28 29 It is Similar to python's `enumerate`. 30 For example: 31 32 ```python 33 # NOTE: The following examples use `{ ... }` to represent the 34 # contents of a dataset. 35 a = { 1, 2, 3 } 36 b = { (7, 8), (9, 10) } 37 38 # The nested structure of the `datasets` argument determines the 39 # structure of elements in the resulting dataset. 40 a.apply(tf.contrib.data.enumerate(start=5)) == { (5, 1), (6, 2), (7, 3) } 41 b.apply(tf.contrib.data.enumerate()) == { (0, (7, 8)), (1, (9, 10)) } 42 ``` 43 44 Args: 45 start: A `tf.int64` scalar `tf.Tensor`, representing the start 46 value for enumeration. 47 48 Returns: 49 A `Dataset` transformation function, which can be passed to 50 @{tf.data.Dataset.apply}. 51 """ 52 53 def _apply_fn(dataset): 54 max_value = np.iinfo(dtypes.int64.as_numpy_dtype).max 55 return dataset_ops.Dataset.zip((dataset_ops.Dataset.range(start, max_value), 56 dataset)) 57 58 return _apply_fn 59
