/
string_ops.py
148 lines (123 loc) · 5.07 KB
/
string_ops.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Operations for working with string Tensors.
See the @{$python/string_ops} guide.
@@string_to_hash_bucket_fast
@@string_to_hash_bucket_strong
@@string_to_hash_bucket
@@reduce_join
@@string_join
@@string_split
@@substr
@@as_string
@@encode_base64
@@decode_base64
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import sparse_tensor
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gen_string_ops
from tensorflow.python.ops import math_ops
# go/tf-wildcard-import
# pylint: disable=wildcard-import
from tensorflow.python.ops.gen_string_ops import *
from tensorflow.python.util import deprecation
# pylint: enable=wildcard-import
def string_split(source, delimiter=" "): # pylint: disable=invalid-name
"""Split elements of `source` based on `delimiter` into a `SparseTensor`.
Let N be the size of source (typically N will be the batch size). Split each
element of `source` based on `delimiter` and return a `SparseTensor`
containing the split tokens. Empty tokens are ignored.
If `delimiter` is an empty string, each element of the `source` is split
into individual strings, each containing one byte. (This includes splitting
multibyte sequences of UTF-8.) If delimiter contains multiple bytes, it is
treated as a set of delimiters with each considered a potential split point.
For example:
N = 2, source[0] is 'hello world' and source[1] is 'a b c', then the output
will be
st.indices = [0, 0;
0, 1;
1, 0;
1, 1;
1, 2]
st.shape = [2, 3]
st.values = ['hello', 'world', 'a', 'b', 'c']
Args:
source: `1-D` string `Tensor`, the strings to split.
delimiter: `0-D` string `Tensor`, the delimiter character, the string should
be length 0 or 1.
Raises:
ValueError: If delimiter is not a string.
Returns:
A `SparseTensor` of rank `2`, the strings split according to the delimiter.
The first column of the indices corresponds to the row in `source` and the
second column corresponds to the index of the split component in this row.
"""
delimiter = ops.convert_to_tensor(delimiter, dtype=dtypes.string)
source = ops.convert_to_tensor(source, dtype=dtypes.string)
# pylint: disable=protected-access
indices, values, shape = gen_string_ops._string_split(
source, delimiter=delimiter)
# pylint: enable=protected-access
indices.set_shape([None, 2])
values.set_shape([None])
shape.set_shape([2])
return sparse_tensor.SparseTensor(indices, values, shape)
def _reduce_join_reduction_dims(x, axis, reduction_indices):
"""Returns range(rank(x) - 1, 0, -1) if reduction_indices is None."""
# TODO(aselle): Remove this after deprecation
if reduction_indices is not None:
if axis is not None:
raise ValueError("Can't specify both 'axis' and 'reduction_indices'.")
axis = reduction_indices
if axis is not None:
return axis
else:
# Fast path: avoid creating Rank and Range ops if ndims is known.
if isinstance(x, ops.Tensor) and x.get_shape().ndims is not None:
return constant_op.constant(
np.arange(x.get_shape().ndims - 1, -1, -1), dtype=dtypes.int32)
# Otherwise, we rely on Range and Rank to do the right thing at run-time.
return math_ops.range(array_ops.rank(x) - 1, -1, -1)
def reduce_join(inputs, axis=None,
keep_dims=False,
separator="",
name=None,
reduction_indices=None):
reduction_indices = _reduce_join_reduction_dims(
inputs, axis, reduction_indices)
return gen_string_ops.reduce_join(
inputs=inputs,
reduction_indices=reduction_indices,
keep_dims=keep_dims,
separator=separator,
name=name)
reduce_join.__doc__ = deprecation.rewrite_argument_docstring(
gen_string_ops.reduce_join.__doc__, "reduction_indices", "axis")
ops.NotDifferentiable("StringToHashBucket")
ops.NotDifferentiable("StringToHashBucketFast")
ops.NotDifferentiable("StringToHashBucketStrong")
ops.NotDifferentiable("ReduceJoin")
ops.NotDifferentiable("StringJoin")
ops.NotDifferentiable("StringSplit")
ops.NotDifferentiable("AsString")
ops.NotDifferentiable("EncodeBase64")
ops.NotDifferentiable("DecodeBase64")