/external/tensorflow/tensorflow/python/ops/ragged/ |
D | ragged_batch_gather_with_default_op.py | 121 params_shape = array_ops.shape(params) 123 params_shape[:num_batch_dimensions], 125 params_shape[num_batch_dimensions + 1:params.shape.ndims] 127 upper_bounds = params_shape[num_batch_dimensions] 150 params_shape = ragged_tensor_shape.RaggedTensorDynamicShape.from_tensor( 157 if params_shape.num_inner_dimensions == 0: 158 pad_dims = params_shape.partitioned_dim_sizes[:-1] + ( 159 array_ops.ones_like(params_shape.partitioned_dim_sizes[-1]),) 164 params_shape.partitioned_dim_sizes, 165 array_ops.concat([params_shape.inner_dim_sizes[:-1], [1]], axis=0)) [all …]
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/external/tensorflow/tensorflow/core/kernels/ |
D | scatter_nd_op.cc | 271 TensorShape params_shape; in DoCompute() local 278 params_shape = params.shape(); in DoCompute() 281 params_shape = params.shape(); in DoCompute() 287 params_shape = c->input(0).shape(); in DoCompute() 288 if (!c->forward_input_to_output_with_shape(0, 0, params_shape, in DoCompute() 292 OP_REQUIRES_OK(c, c->allocate_output(0, params_shape, ¶ms_ptr)); in DoCompute() 304 c, indices, updates, params_shape, ¶ms, false /*allocate*/)); in DoCompute() 518 Status ValidateUpdateShape(const TensorShape& params_shape, in ValidateUpdateShape() argument 530 ", params_shape: ", params_shape.DebugString(), in ValidateUpdateShape() 535 if (params_shape.dims() < slice_dim + (updates.dims() - batch_dim)) { in ValidateUpdateShape() [all …]
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D | gather_nd_op.cc | 123 const TensorShape& params_shape(params.shape()); in DoGatherNd() local 124 Index total_nd = params_shape.dims(); in DoGatherNd() 131 slice_size_big *= params_shape.dim_size(i); in DoGatherNd() 132 result_shape.AddDim(params_shape.dim_size(i)); in DoGatherNd() 147 if (params_shape.num_elements() == 0) { in DoGatherNd() 151 params_shape.DebugString()); in DoGatherNd()
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D | cudnn_rnn_ops.cc | 1802 const TensorShape& params_shape, in AllocateOutputs() argument 1821 context->allocate_output(3, params_shape, params_backprop)); in AllocateOutputs()
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/external/tensorflow/tensorflow/contrib/layers/python/layers/ |
D | normalization.py | 117 params_shape = inputs_shape[reduction_axis:reduction_axis + 1] 118 if not params_shape.is_fully_defined(): 120 inputs.name, params_shape)) 133 shape=params_shape, 146 shape=params_shape, 324 params_shape = [channels] 337 shape=params_shape, 350 shape=params_shape,
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D | layers.py | 287 params_shape = inputs_shape[-1:] 289 params_shape = inputs_shape[1:2] 290 if not params_shape.is_fully_defined(): 292 (inputs.name, params_shape)) 311 shape=params_shape, 318 beta = array_ops.constant(0.0, dtype=variable_dtype, shape=params_shape) 327 shape=params_shape, 334 gamma = array_ops.constant(1.0, dtype=variable_dtype, shape=params_shape) 350 shape=params_shape, 361 shape=params_shape, [all …]
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D | embedding_ops.py | 848 params_shape = array_ops.shape(params[0]) 855 params_shape, [1], [-1])
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/external/tensorflow/tensorflow/python/kernel_tests/ |
D | gather_op_test.py | 342 params_shape=[2, 3, 4, 5, 6, 7], 350 params_shape=[2, 3, 4, 5, 6, 7], 358 params_shape=[2, 3, 4, 5, 6, 7], 366 params_shape=[2, 3, 4, 5, 6, 7], 374 params_shape=[2, 3, 4, 5, 6, 7], 382 params_shape=[2, 3, 4, 5, 6, 7], 390 params_shape=[2, 3, 4, 5, 6, 7], 398 params_shape=[2, 3, 4, 5, 6, 7], 407 def testBatchDimsMatchesPythonBatching(self, params_shape, indices_shape, argument 411 params_size = np.prod(params_shape) [all …]
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D | resource_variable_ops_test.py | 1169 params_shape=[2, 3, 4, 5, 6, 7], 1176 params_shape=[2, 3, 4, 5, 6, 7], 1183 params_shape=[2, 3, 4, 5, 6, 7], 1190 params_shape=[2, 3, 4, 5, 6, 7], 1197 params_shape=[2, 3, 4, 5, 6, 7], 1205 def testGatherWithBatchDimsMatchesTensor(self, params_shape, indices_shape, argument 1209 params_size = np.prod(params_shape) 1210 params = np.reshape(np.arange(params_size, dtype=np.int32), params_shape) 1216 indices = indices % params_shape[batch_dims]
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D | embedding_ops_test.py | 552 for params_shape in (12,), (6, 3): 553 params = np.random.randn(*params_shape) 573 for params_shape in (12,), (6, 3), (6, 2, 3): 576 params = 2 * np.ones(params_shape)
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/external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
D | gather_op.cc | 206 TensorShape params_shape = context->InputShape(0); in Compile() local 208 OP_REQUIRES(context, TensorShapeUtils::IsVectorOrHigher(params_shape), in Compile() 215 context, num_index_dims <= params_shape.dims(), in Compile() 219 params_shape.dims())); in Compile() 225 OP_REQUIRES_OK(context, XlaGather(params, params_shape, indices, in Compile()
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/external/tensorflow/tensorflow/core/ops/ |
D | cudnn_rnn_ops.cc | 225 auto params_shape = c->input(3); in __anon3a5366b80602() local 229 c->set_output(3, params_shape); in __anon3a5366b80602() 262 auto params_shape = c->input(3); in __anon3a5366b80702() local 266 c->set_output(3, params_shape); in __anon3a5366b80702() 301 auto params_shape = c->input(3); in __anon3a5366b80802() local 305 c->set_output(3, params_shape); in __anon3a5366b80802()
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D | array_ops.cc | 1118 ShapeHandle params_shape; in __anondb9326b21802() local 1119 TF_RETURN_IF_ERROR(c->WithRankAtLeast(c->input(0), 1, ¶ms_shape)); in __anondb9326b21802() 1129 if (c->RankKnown(params_shape) && c->RankKnown(indices_shape)) { in __anondb9326b21802() 1130 c->set_output(0, c->UnknownShapeOfRank(c->Rank(params_shape) + in __anondb9326b21802() 1149 params_shape, axis < 0 ? -axis : axis + 1, &unused)); in __anondb9326b21802() 1153 c->Subshape(params_shape, 0, axis, ¶ms_outer_subshape)); in __anondb9326b21802() 1166 c->Subshape(params_shape, axis + 1, ¶ms_inner_subshape)); in __anondb9326b21802()
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/external/tensorflow/tensorflow/python/ops/ |
D | array_grad.py | 402 params_shape = array_ops.shape(params, out_type=ops.dtypes.int64) 403 params_shape = math_ops.cast(params_shape, dtypes.int32) 408 values_shape = array_ops.concat([size, params_shape[1:]], 0) 411 return [ops.IndexedSlices(values, indices, params_shape), None] 425 params_shape = array_ops.shape(params, out_type=ops.dtypes.int64) 426 params_shape = math_ops.cast(params_shape, dtypes.int32) 436 params_tail_shape = params_shape.cpu()[1:] 438 params_tail_shape = params_shape[1:] 442 return [ops.IndexedSlices(values, indices, params_shape), None, None] 444 outer_shape = params_shape[:axis] [all …]
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D | embedding_ops.py | 230 params_shape = array_ops.shape(params[0]) 231 element_shape_d = params_shape[1:]
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D | resource_variable_ops.py | 1514 params_shape = variable_shape(handle) 1516 values_shape = array_ops.concat([size, params_shape[1:]], 0) 1519 return (ops.IndexedSlices(values, indices, params_shape), None)
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D | array_ops.py | 3493 params_shape = shape(params) 3498 casted_params_shape = gen_math_ops.cast(params_shape, indices_dtype) 3511 outer_shape = params_shape[batch_dims + 1:] 3512 flat_inner_shape = gen_math_ops.prod(params_shape[:batch_dims + 1], [0],
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/external/tensorflow/tensorflow/contrib/gan/python/features/python/ |
D | virtual_batchnorm_impl.py | 209 params_shape = self._reference_batch.shape[axis] 235 shape=(params_shape,), 242 shape=(params_shape,),
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/external/tensorflow/tensorflow/python/ops/distributions/ |
D | categorical.py | 54 params_shape = array_ops.shape(params)[:-1] 55 event *= array_ops.ones(params_shape, dtype=event.dtype)
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/external/tensorflow/tensorflow/lite/kernels/internal/reference/ |
D | reference_ops.h | 2973 inline void GatherNd(const RuntimeShape& params_shape, in GatherNd() argument 2984 const int params_dims = params_shape.DimensionsCount(); in GatherNd() 2989 slice_size *= params_shape.Dims(i); in GatherNd() 2992 int remain_flat_size = params_shape.FlatSize(); in GatherNd() 2995 dims_to_count[i] = remain_flat_size / params_shape.Dims(i); in GatherNd()
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