Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.8/site-packages/tensorflow/_api/v2/compat/v1/ragged/__init__.py: 100%
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« prev ^ index » next coverage.py v7.4.0, created at 2024-01-03 07:57 +0000
« prev ^ index » next coverage.py v7.4.0, created at 2024-01-03 07:57 +0000
1# This file is MACHINE GENERATED! Do not edit.
2# Generated by: tensorflow/python/tools/api/generator/create_python_api.py script.
3"""Ragged Tensors.
5This package defines ops for manipulating ragged tensors (`tf.RaggedTensor`),
6which are tensors with non-uniform shapes. In particular, each `RaggedTensor`
7has one or more *ragged dimensions*, which are dimensions whose slices may have
8different lengths. For example, the inner (column) dimension of
9`rt=[[3, 1, 4, 1], [], [5, 9, 2], [6], []]` is ragged, since the column slices
10(`rt[0, :]`, ..., `rt[4, :]`) have different lengths. For a more detailed
11description of ragged tensors, see the `tf.RaggedTensor` class documentation
12and the [Ragged Tensor Guide](/guide/ragged_tensor).
15### Additional ops that support `RaggedTensor`
17Arguments that accept `RaggedTensor`s are marked in **bold**.
19* `tf.__operators__.eq`(**self**, **other**)
20* `tf.__operators__.ne`(**self**, **other**)
21* `tf.bitcast`(**input**, type, name=`None`)
22* `tf.bitwise.bitwise_and`(**x**, **y**, name=`None`)
23* `tf.bitwise.bitwise_or`(**x**, **y**, name=`None`)
24* `tf.bitwise.bitwise_xor`(**x**, **y**, name=`None`)
25* `tf.bitwise.invert`(**x**, name=`None`)
26* `tf.bitwise.left_shift`(**x**, **y**, name=`None`)
27* `tf.bitwise.right_shift`(**x**, **y**, name=`None`)
28* `tf.broadcast_to`(**input**, **shape**, name=`None`)
29* `tf.cast`(**x**, dtype, name=`None`)
30* `tf.clip_by_value`(**t**, clip_value_min, clip_value_max, name=`None`)
31* `tf.concat`(**values**, axis, name=`'concat'`)
32* `tf.debugging.assert_equal`(**x**, **y**, message=`None`, summarize=`None`, name=`None`)
33* `tf.debugging.assert_greater_equal`(**x**, **y**, message=`None`, summarize=`None`, name=`None`)
34* `tf.debugging.assert_greater`(**x**, **y**, message=`None`, summarize=`None`, name=`None`)
35* `tf.debugging.assert_less_equal`(**x**, **y**, message=`None`, summarize=`None`, name=`None`)
36* `tf.debugging.assert_less`(**x**, **y**, message=`None`, summarize=`None`, name=`None`)
37* `tf.debugging.assert_near`(**x**, **y**, rtol=`None`, atol=`None`, message=`None`, summarize=`None`, name=`None`)
38* `tf.debugging.assert_none_equal`(**x**, **y**, summarize=`None`, message=`None`, name=`None`)
39* `tf.debugging.check_numerics`(**tensor**, message, name=`None`)
40* `tf.dtypes.complex`(**real**, **imag**, name=`None`)
41* `tf.dtypes.saturate_cast`(**value**, dtype, name=`None`)
42* `tf.dynamic_partition`(**data**, **partitions**, num_partitions, name=`None`)
43* `tf.expand_dims`(**input**, axis, name=`None`)
44* `tf.gather_nd`(**params**, **indices**, batch_dims=`0`, name=`None`)
45* `tf.gather`(**params**, **indices**, validate_indices=`None`, axis=`None`, batch_dims=`0`, name=`None`)
46* `tf.image.adjust_brightness`(**image**, delta)
47* `tf.image.adjust_gamma`(**image**, gamma=`1`, gain=`1`)
48* `tf.image.convert_image_dtype`(**image**, dtype, saturate=`False`, name=`None`)
49* `tf.image.random_brightness`(**image**, max_delta, seed=`None`)
50* `tf.image.resize`(**images**, size, method=`'bilinear'`, preserve_aspect_ratio=`False`, antialias=`False`, name=`None`)
51* `tf.image.stateless_random_brightness`(**image**, max_delta, seed)
52* `tf.io.decode_base64`(**input**, name=`None`)
53* `tf.io.decode_compressed`(**bytes**, compression_type=`''`, name=`None`)
54* `tf.io.encode_base64`(**input**, pad=`False`, name=`None`)
55* `tf.linalg.matmul`(**a**, **b**, transpose_a=`False`, transpose_b=`False`, adjoint_a=`False`, adjoint_b=`False`, a_is_sparse=`False`, b_is_sparse=`False`, output_type=`None`, name=`None`)
56* `tf.math.abs`(**x**, name=`None`)
57* `tf.math.acos`(**x**, name=`None`)
58* `tf.math.acosh`(**x**, name=`None`)
59* `tf.math.add_n`(**inputs**, name=`None`)
60* `tf.math.add`(**x**, **y**, name=`None`)
61* `tf.math.angle`(**input**, name=`None`)
62* `tf.math.asin`(**x**, name=`None`)
63* `tf.math.asinh`(**x**, name=`None`)
64* `tf.math.atan2`(**y**, **x**, name=`None`)
65* `tf.math.atan`(**x**, name=`None`)
66* `tf.math.atanh`(**x**, name=`None`)
67* `tf.math.bessel_i0`(**x**, name=`None`)
68* `tf.math.bessel_i0e`(**x**, name=`None`)
69* `tf.math.bessel_i1`(**x**, name=`None`)
70* `tf.math.bessel_i1e`(**x**, name=`None`)
71* `tf.math.ceil`(**x**, name=`None`)
72* `tf.math.conj`(**x**, name=`None`)
73* `tf.math.cos`(**x**, name=`None`)
74* `tf.math.cosh`(**x**, name=`None`)
75* `tf.math.cumsum`(**x**, **axis**=`0`, **exclusive**=`False`, **reverse**=`False`, **name**=`None`)
76* `tf.math.digamma`(**x**, name=`None`)
77* `tf.math.divide_no_nan`(**x**, **y**, name=`None`)
78* `tf.math.divide`(**x**, **y**, name=`None`)
79* `tf.math.equal`(**x**, **y**, name=`None`)
80* `tf.math.erf`(**x**, name=`None`)
81* `tf.math.erfc`(**x**, name=`None`)
82* `tf.math.erfcinv`(**x**, name=`None`)
83* `tf.math.erfinv`(**x**, name=`None`)
84* `tf.math.exp`(**x**, name=`None`)
85* `tf.math.expm1`(**x**, name=`None`)
86* `tf.math.floor`(**x**, name=`None`)
87* `tf.math.floordiv`(**x**, **y**, name=`None`)
88* `tf.math.floormod`(**x**, **y**, name=`None`)
89* `tf.math.greater_equal`(**x**, **y**, name=`None`)
90* `tf.math.greater`(**x**, **y**, name=`None`)
91* `tf.math.imag`(**input**, name=`None`)
92* `tf.math.is_finite`(**x**, name=`None`)
93* `tf.math.is_inf`(**x**, name=`None`)
94* `tf.math.is_nan`(**x**, name=`None`)
95* `tf.math.less_equal`(**x**, **y**, name=`None`)
96* `tf.math.less`(**x**, **y**, name=`None`)
97* `tf.math.lgamma`(**x**, name=`None`)
98* `tf.math.log1p`(**x**, name=`None`)
99* `tf.math.log_sigmoid`(**x**, name=`None`)
100* `tf.math.log`(**x**, name=`None`)
101* `tf.math.logical_and`(**x**, **y**, name=`None`)
102* `tf.math.logical_not`(**x**, name=`None`)
103* `tf.math.logical_or`(**x**, **y**, name=`None`)
104* `tf.math.logical_xor`(**x**, **y**, name=`'LogicalXor'`)
105* `tf.math.maximum`(**x**, **y**, name=`None`)
106* `tf.math.minimum`(**x**, **y**, name=`None`)
107* `tf.math.multiply_no_nan`(**x**, **y**, name=`None`)
108* `tf.math.multiply`(**x**, **y**, name=`None`)
109* `tf.math.ndtri`(**x**, name=`None`)
110* `tf.math.negative`(**x**, name=`None`)
111* `tf.math.nextafter`(**x1**, x2, name=`None`)
112* `tf.math.not_equal`(**x**, **y**, name=`None`)
113* `tf.math.pow`(**x**, **y**, name=`None`)
114* `tf.math.real`(**input**, name=`None`)
115* `tf.math.reciprocal_no_nan`(**x**, name=`None`)
116* `tf.math.reciprocal`(**x**, name=`None`)
117* `tf.math.reduce_all`(**input_tensor**, axis=`None`, keepdims=`False`, name=`None`)
118* `tf.math.reduce_any`(**input_tensor**, axis=`None`, keepdims=`False`, name=`None`)
119* `tf.math.reduce_max`(**input_tensor**, axis=`None`, keepdims=`False`, name=`None`)
120* `tf.math.reduce_mean`(**input_tensor**, axis=`None`, keepdims=`False`, name=`None`)
121* `tf.math.reduce_min`(**input_tensor**, axis=`None`, keepdims=`False`, name=`None`)
122* `tf.math.reduce_prod`(**input_tensor**, axis=`None`, keepdims=`False`, name=`None`)
123* `tf.math.reduce_std`(**input_tensor**, axis=`None`, keepdims=`False`, name=`None`)
124* `tf.math.reduce_sum`(**input_tensor**, axis=`None`, keepdims=`False`, name=`None`)
125* `tf.math.reduce_variance`(**input_tensor**, axis=`None`, keepdims=`False`, name=`None`)
126* `tf.math.rint`(**x**, name=`None`)
127* `tf.math.round`(**x**, name=`None`)
128* `tf.math.rsqrt`(**x**, name=`None`)
129* `tf.math.scalar_mul`(**scalar**, **x**, name=`None`)
130* `tf.math.sigmoid`(**x**, name=`None`)
131* `tf.math.sign`(**x**, name=`None`)
132* `tf.math.sin`(**x**, name=`None`)
133* `tf.math.sinh`(**x**, name=`None`)
134* `tf.math.softplus`(**features**, name=`None`)
135* `tf.math.special.bessel_j0`(**x**, name=`None`)
136* `tf.math.special.bessel_j1`(**x**, name=`None`)
137* `tf.math.special.bessel_k0`(**x**, name=`None`)
138* `tf.math.special.bessel_k0e`(**x**, name=`None`)
139* `tf.math.special.bessel_k1`(**x**, name=`None`)
140* `tf.math.special.bessel_k1e`(**x**, name=`None`)
141* `tf.math.special.bessel_y0`(**x**, name=`None`)
142* `tf.math.special.bessel_y1`(**x**, name=`None`)
143* `tf.math.special.dawsn`(**x**, name=`None`)
144* `tf.math.special.expint`(**x**, name=`None`)
145* `tf.math.special.fresnel_cos`(**x**, name=`None`)
146* `tf.math.special.fresnel_sin`(**x**, name=`None`)
147* `tf.math.special.spence`(**x**, name=`None`)
148* `tf.math.sqrt`(**x**, name=`None`)
149* `tf.math.square`(**x**, name=`None`)
150* `tf.math.squared_difference`(**x**, **y**, name=`None`)
151* `tf.math.subtract`(**x**, **y**, name=`None`)
152* `tf.math.tan`(**x**, name=`None`)
153* `tf.math.tanh`(**x**, name=`None`)
154* `tf.math.truediv`(**x**, **y**, name=`None`)
155* `tf.math.unsorted_segment_max`(**data**, **segment_ids**, num_segments, name=`None`)
156* `tf.math.unsorted_segment_mean`(**data**, **segment_ids**, num_segments, name=`None`)
157* `tf.math.unsorted_segment_min`(**data**, **segment_ids**, num_segments, name=`None`)
158* `tf.math.unsorted_segment_prod`(**data**, **segment_ids**, num_segments, name=`None`)
159* `tf.math.unsorted_segment_sqrt_n`(**data**, **segment_ids**, num_segments, name=`None`)
160* `tf.math.unsorted_segment_sum`(**data**, **segment_ids**, num_segments, name=`None`)
161* `tf.math.xdivy`(**x**, **y**, name=`None`)
162* `tf.math.xlog1py`(**x**, **y**, name=`None`)
163* `tf.math.xlogy`(**x**, **y**, name=`None`)
164* `tf.math.zeta`(**x**, **q**, name=`None`)
165* `tf.nn.dropout`(**x**, rate, noise_shape=`None`, seed=`None`, name=`None`)
166* `tf.nn.elu`(**features**, name=`None`)
167* `tf.nn.experimental.stateless_dropout`(**x**, rate, seed, rng_alg=`None`, noise_shape=`None`, name=`None`)
168* `tf.nn.gelu`(**features**, approximate=`False`, name=`None`)
169* `tf.nn.leaky_relu`(**features**, alpha=`0.2`, name=`None`)
170* `tf.nn.relu6`(**features**, name=`None`)
171* `tf.nn.relu`(**features**, name=`None`)
172* `tf.nn.selu`(**features**, name=`None`)
173* `tf.nn.sigmoid_cross_entropy_with_logits`(**labels**=`None`, **logits**=`None`, name=`None`)
174* `tf.nn.silu`(**features**, beta=`1.0`)
175* `tf.nn.softmax`(**logits**, axis=`None`, name=`None`)
176* `tf.nn.softsign`(**features**, name=`None`)
177* `tf.one_hot`(**indices**, depth, on_value=`None`, off_value=`None`, axis=`None`, dtype=`None`, name=`None`)
178* `tf.ones_like`(**input**, dtype=`None`, name=`None`)
179* `tf.print`(***inputs**, **kwargs)
180* `tf.rank`(**input**, name=`None`)
181* `tf.realdiv`(**x**, **y**, name=`None`)
182* `tf.reshape`(**tensor**, **shape**, name=`None`)
183* `tf.reverse`(**tensor**, axis, name=`None`)
184* `tf.size`(**input**, out_type=`tf.int32`, name=`None`)
185* `tf.split`(**value**, num_or_size_splits, axis=`0`, num=`None`, name=`'split'`)
186* `tf.squeeze`(**input**, axis=`None`, name=`None`)
187* `tf.stack`(**values**, axis=`0`, name=`'stack'`)
188* `tf.strings.as_string`(**input**, precision=`-1`, scientific=`False`, shortest=`False`, width=`-1`, fill=`''`, name=`None`)
189* `tf.strings.format`(**template**, **inputs**, placeholder=`'{}'`, summarize=`3`, name=`None`)
190* `tf.strings.join`(**inputs**, separator=`''`, name=`None`)
191* `tf.strings.length`(**input**, unit=`'BYTE'`, name=`None`)
192* `tf.strings.lower`(**input**, encoding=`''`, name=`None`)
193* `tf.strings.reduce_join`(**inputs**, axis=`None`, keepdims=`False`, separator=`''`, name=`None`)
194* `tf.strings.regex_full_match`(**input**, pattern, name=`None`)
195* `tf.strings.regex_replace`(**input**, pattern, rewrite, replace_global=`True`, name=`None`)
196* `tf.strings.strip`(**input**, name=`None`)
197* `tf.strings.substr`(**input**, pos, len, unit=`'BYTE'`, name=`None`)
198* `tf.strings.to_hash_bucket_fast`(**input**, num_buckets, name=`None`)
199* `tf.strings.to_hash_bucket_strong`(**input**, num_buckets, key, name=`None`)
200* `tf.strings.to_hash_bucket`(**input**, num_buckets, name=`None`)
201* `tf.strings.to_number`(**input**, out_type=`tf.float32`, name=`None`)
202* `tf.strings.unicode_script`(**input**, name=`None`)
203* `tf.strings.unicode_transcode`(**input**, input_encoding, output_encoding, errors=`'replace'`, replacement_char=`65533`, replace_control_characters=`False`, name=`None`)
204* `tf.strings.upper`(**input**, encoding=`''`, name=`None`)
205* `tf.tile`(**input**, multiples, name=`None`)
206* `tf.truncatediv`(**x**, **y**, name=`None`)
207* `tf.truncatemod`(**x**, **y**, name=`None`)
208* `tf.where`(**condition**, **x**=`None`, **y**=`None`, name=`None`)
209* `tf.zeros_like`(**input**, dtype=`None`, name=`None`)n
210"""
212import sys as _sys
214from tensorflow.python.ops.ragged.ragged_array_ops import boolean_mask
215from tensorflow.python.ops.ragged.ragged_array_ops import cross
216from tensorflow.python.ops.ragged.ragged_array_ops import cross_hashed
217from tensorflow.python.ops.ragged.ragged_array_ops import stack_dynamic_partitions
218from tensorflow.python.ops.ragged.ragged_concat_ops import stack
219from tensorflow.python.ops.ragged.ragged_factory_ops import constant
220from tensorflow.python.ops.ragged.ragged_factory_ops import constant_value
221from tensorflow.python.ops.ragged.ragged_factory_ops import placeholder
222from tensorflow.python.ops.ragged.ragged_functional_ops import map_flat_values
223from tensorflow.python.ops.ragged.ragged_math_ops import range
224from tensorflow.python.ops.ragged.ragged_tensor_value import RaggedTensorValue
225from tensorflow.python.ops.ragged.segment_id_ops import row_splits_to_segment_ids
226from tensorflow.python.ops.ragged.segment_id_ops import segment_ids_to_row_splits