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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. 

4 

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). 

13 

14 

15### Additional ops that support `RaggedTensor` 

16 

17Arguments that accept `RaggedTensor`s are marked in **bold**. 

18 

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""" 

211 

212import sys as _sys 

213 

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_functional_ops import map_flat_values 

221from tensorflow.python.ops.ragged.ragged_math_ops import range 

222from tensorflow.python.ops.ragged.segment_id_ops import row_splits_to_segment_ids 

223from tensorflow.python.ops.ragged.segment_id_ops import segment_ids_to_row_splits