/external/tensorflow/tensorflow/core/kernels/ |
D | sparse_concat_op.cc | 77 const int input_rank = input_shape.dims(); in Compute() local 79 ? input_rank + concat_dim_attr_ in Compute() 81 OP_REQUIRES(context, concat_dim >= 0 && concat_dim < input_rank, in Compute() 83 -input_rank, ", ", input_rank, in Compute() 88 context, current_shape.dims() == input_rank, in Compute() 90 "Ranks of all input tensors must match: expected ", input_rank, in Compute() 92 for (int j = 0; j < input_rank; ++j) { in Compute() 112 gtl::InlinedVector<int64, 8> std_order(input_rank); in Compute() 116 concat_order.reserve(input_rank); in Compute() 118 for (int j = 0; j < input_rank; ++j) { in Compute()
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D | linalg_ops_common.cc | 118 int input_rank = -1; in AnalyzeInputs() local 122 input_rank = in.dims(); in AnalyzeInputs() 124 context, input_rank >= 2, in AnalyzeInputs() 126 " must have rank >= 2, got ", input_rank)); in AnalyzeInputs() 130 for (int dim = 0; dim < input_rank - 2; ++dim) { in AnalyzeInputs() 135 OP_REQUIRES(context, input_rank == in.dims(), in AnalyzeInputs() 138 for (int dim = 0; dim < input_rank - 2; ++dim) { in AnalyzeInputs() 146 const int row_dimension = input_rank - 2; in AnalyzeInputs() 147 const int col_dimension = input_rank - 1; in AnalyzeInputs()
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D | reshape_util.cc | 50 const int64 input_rank = input_shape_in.NumElements(); in Reshape() local 109 gtl::InlinedVector<int64, 8> input_strides(input_rank); in Reshape() 110 if (input_rank > 0) { in Reshape() 111 input_strides[input_rank - 1] = 1; in Reshape() 112 for (int d = input_rank - 2; d >= 0; --d) { in Reshape() 134 for (int j = 0; j < input_rank; ++j) { in Reshape()
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D | lu_op.cc | 71 int input_rank = input.dims(); in Compute() local 72 OP_REQUIRES(context, input_rank >= 2, in Compute() 74 "Input tensor must have rank >= 2, got ", input_rank)); in Compute() 81 for (int dim = 0; dim < input_rank - 2; ++dim) { in Compute() 84 const int64 num_rows = input.dim_size(input_rank - 2); in Compute() 85 const int64 num_cols = input.dim_size(input_rank - 1); in Compute()
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D | lu_op_gpu.cu.cc | 85 const int input_rank = input.dims(); in ComputeAsync() local 88 context, input_rank >= 2, in ComputeAsync() 89 errors::InvalidArgument("Input must have rank >= 2, got ", input_rank), in ComputeAsync() 92 const int64 num_rows = input.dim_size(input_rank - 2); in ComputeAsync() 93 const int64 num_cols = input.dim_size(input_rank - 1); in ComputeAsync() 102 for (int dim = 0; dim < input_rank - 2; ++dim) { in ComputeAsync()
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/external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
D | depthtospace_op.cc | 62 int input_rank = input_shape.size(); in Compile() local 65 OP_REQUIRES(ctx, kRequiredDims == input_rank, in Compile() 67 "; got: ", input_rank)); in Compile() 69 int feature_dim = GetTensorFeatureDimIndex(input_rank, data_format); in Compile() 70 int num_spatial_dims = GetTensorSpatialDims(input_rank, data_format); in Compile() 75 reshaped_shape.reserve(input_rank); in Compile() 76 transpose_order.reserve(input_rank); in Compile() 77 output_shape.reserve(input_rank); in Compile()
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D | spacetodepth_op.cc | 62 int input_rank = input_shape.size(); in Compile() local 65 OP_REQUIRES(ctx, kRequiredDims == input_rank, in Compile() 67 "; got ", input_rank)); in Compile() 69 int feature_dim = GetTensorFeatureDimIndex(input_rank, data_format); in Compile() 70 int num_spatial_dims = GetTensorSpatialDims(input_rank, data_format); in Compile() 75 reshaped_shape.reserve(input_rank); in Compile() 76 transpose_order.reserve(input_rank); in Compile() 77 output_shape.reserve(input_rank); in Compile()
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D | permute_op.cc | 50 int input_rank = input_tensor_shape.dims(); in Compile() local 51 OP_REQUIRES(ctx, input_rank == 1 || input_rank == 2, in Compile() 60 if (input_rank == 2) { in Compile() 77 if (input_rank == 2) { in Compile()
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D | batchtospace_op.cc | 28 const int input_rank = input_tensor_shape.dims(); in BatchToSpace() local 34 ctx, input_rank >= 1 + block_rank, in BatchToSpace() 36 " instead of ", input_rank)); in BatchToSpace() 70 std::vector<int64> reshaped_shape(input_rank + block_rank); in BatchToSpace() 105 std::vector<int64> reshaped_permuted_shape(input_rank); in BatchToSpace() 125 std::vector<int64> start_indices(input_rank, 0); in BatchToSpace() 127 std::vector<int64> strides(input_rank, 1); in BatchToSpace()
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D | spacetobatch_op.cc | 28 const int input_rank = input_tensor_shape.dims(); in SpaceToBatch() local 34 ctx, input_rank >= 1 + block_rank, in SpaceToBatch() 36 " instead of ", input_rank)); in SpaceToBatch() 89 std::vector<int64> reshaped_padded_shape(input_rank + block_rank); in SpaceToBatch() 136 std::vector<int64> output_shape(input_rank); in SpaceToBatch()
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/external/tensorflow/tensorflow/contrib/model_pruning/python/layers/ |
D | layers.py | 198 input_rank = inputs.get_shape().ndims 200 if input_rank == 3: 202 input_rank) 203 elif input_rank == 4: 205 elif input_rank == 5: 207 input_rank) 210 input_rank)
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/external/tensorflow/tensorflow/core/common_runtime/ |
D | eval_const_tensor.cc | 53 int input_rank = c->Rank(c->input(0)); in TryToInferTensorOutputFromInputShapes() local 54 Tensor t(node->output_type(0), TensorShape({input_rank})); in TryToInferTensorOutputFromInputShapes() 57 for (int i = 0; i < input_rank; i++) { in TryToInferTensorOutputFromInputShapes() 68 for (int i = 0; i < input_rank; i++) { in TryToInferTensorOutputFromInputShapes() 81 int32 input_rank = c->Rank(c->input(0)); in TryToInferTensorOutputFromInputShapes() local 83 t.flat<int32>()(0) = input_rank; in TryToInferTensorOutputFromInputShapes()
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/external/tensorflow/tensorflow/contrib/layers/python/layers/ |
D | feature_column_ops.py | 59 input_rank = tensor.get_shape().ndims 61 if input_rank is None and isinstance(tensor, sparse_tensor_py.SparseTensor): 63 input_rank = tensor.dense_shape.get_shape().as_list()[0] 65 if input_rank is None: 69 if output_rank > input_rank + 1: 75 column_name, input_rank, output_rank)) 76 elif output_rank == input_rank + 1: 88 elif output_rank < input_rank:
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D | layers.py | 1022 input_rank = inputs.get_shape().ndims 1024 if conv_dims is not None and conv_dims + 2 != input_rank: 1026 (conv_dims + 2, input_rank)) 1027 if input_rank == 3: 1029 elif input_rank == 4: 1031 elif input_rank == 5: 1035 input_rank) 2517 input_rank = inputs.get_shape().ndims 2518 if input_rank is None: 2520 if input_rank < 3: [all …]
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D | feature_column.py | 1652 input_rank = input_tensor.get_shape().ndims 1653 if input_rank is not None: 1654 if output_rank > input_rank + 1: 1659 input_rank, output_rank)) 1664 if output_rank == input_rank + 1: 1669 input_rank, output_rank)) 1671 if output_rank == input_rank:
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/external/tensorflow/tensorflow/core/ops/ |
D | array_ops.cc | 1490 const int32 input_rank = c->Rank(input); in __anon7c94107b2402() local 1491 if (batch_dim >= input_rank) { in __anon7c94107b2402() 1493 "batch_dim must be < input rank: ", batch_dim, " vs. ", input_rank); in __anon7c94107b2402() 1495 if (seq_dim >= input_rank) { in __anon7c94107b2402() 1497 "seq_dim must be < input rank: ", seq_dim, " vs. ", input_rank); in __anon7c94107b2402() 1808 const Tensor* paddings_t, int64 input_rank) { in MirrorPadKnown() argument 1810 std::vector<DimensionHandle> dims(input_rank); in MirrorPadKnown() 1811 for (int64 i = 0; i < input_rank; ++i) { in MirrorPadKnown() 1844 int64 input_rank = c->Value(pad_0); in __anon7c94107b2c02() local 1846 TF_RETURN_IF_ERROR(c->WithRank(c->input(0), input_rank, &input)); in __anon7c94107b2c02() [all …]
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D | math_ops.cc | 917 const int32 input_rank = c->Rank(input_shape); in ArgOpShape() local 918 if (input_rank <= 1) { in ArgOpShape() 928 std::vector<DimensionHandle> dims(input_rank - 1); in ArgOpShape() 944 int64 axis = dimension_val < 0 ? dimension_val + input_rank : dimension_val; in ArgOpShape() 945 if (axis < 0 || axis >= input_rank) { in ArgOpShape() 947 "Dimension (", dimension_val, ") must be in the range [", -input_rank, in ArgOpShape() 948 ", ", input_rank, "), where ", input_rank, in ArgOpShape() 954 for (int i = 0; i < input_rank; ++i) { in ArgOpShape()
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/external/tensorflow/tensorflow/core/framework/ |
D | shape_inference.cc | 984 int idx, int input_rank, DimensionHandle* out) { in MakeDimForScalarInputWithNegativeIndexing() argument 993 if (input_rank < 0) { in MakeDimForScalarInputWithNegativeIndexing() 996 } else if (val + input_rank < 0) { in MakeDimForScalarInputWithNegativeIndexing() 998 val, " must be in range [-", input_rank, in MakeDimForScalarInputWithNegativeIndexing() 999 ", ", input_rank, ")"); in MakeDimForScalarInputWithNegativeIndexing() 1001 val += input_rank; in MakeDimForScalarInputWithNegativeIndexing() 1003 } else if (input_rank >= 0 && val >= input_rank) { in MakeDimForScalarInputWithNegativeIndexing() 1005 val, " must be in range [-", input_rank, in MakeDimForScalarInputWithNegativeIndexing() 1006 ", ", input_rank, ")"); in MakeDimForScalarInputWithNegativeIndexing()
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D | common_shape_fns.cc | 1133 const int32 input_rank, in ReductionShapeHelper() argument 1138 if (reduction_index < -input_rank || reduction_index >= input_rank) { in ReductionShapeHelper() 1141 input_rank, " dimensions."); in ReductionShapeHelper() 1146 wrapped_index += input_rank; in ReductionShapeHelper() 1183 const int32 input_rank = c->Rank(input); in ReductionShape() local 1187 input_rank, &true_indices)); in ReductionShape() 1190 input_rank, &true_indices)); in ReductionShape() 1197 for (int i = 0; i < input_rank; ++i) { in ReductionShape()
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/external/tensorflow/tensorflow/lite/toco/graph_transformations/ |
D | unpartition_embedding_lookup.cc | 198 gather_params_permute_op->input_rank = in Run() 218 merged_gather_op->input_rank = partition_array.shape().dimensions_count(); in Run()
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D | propagate_fixed_sizes.cc | 572 int input_rank = input_shape.dimensions_count(); in ProcessTensorFlowReductionOperator() local 578 if (reduction_index < -input_rank || reduction_index >= input_rank) { in ProcessTensorFlowReductionOperator() 580 << " for input with " << input_rank << " dimensions"; in ProcessTensorFlowReductionOperator() 584 wrapped_index += input_rank; in ProcessTensorFlowReductionOperator() 591 for (int i = 0; i < input_rank; ++i) { in ProcessTensorFlowReductionOperator() 1396 op->input_rank = input_shape.dimensions_count(); in ProcessGatherOperator() 1397 QCHECK_LT(axis, op->input_rank); in ProcessGatherOperator()
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/external/tensorflow/tensorflow/compiler/xla/ |
D | shape_util.cc | 1302 int64 input_rank = input_shape.rank(); in AlignLayouts() local 1324 std::vector<int64> dimension_to_alignment_index(input_rank); in AlignLayouts() 1326 for (int64 i = 0, j = 0; i < input_rank || j < output_rank;) { in AlignLayouts() 1335 if (i == input_rank) { in AlignLayouts() 1352 alignment.push_back({input_rank, output_rank}); in AlignLayouts() 1361 for (int64 i = 0; i < input_rank;) { in AlignLayouts() 1378 if (i == input_rank) { in AlignLayouts()
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/external/tensorflow/tensorflow/python/ops/signal/ |
D | fft_ops.py | 95 input_rank = _array_ops.rank(input_tensor) 97 outer_dims = _math_ops.maximum(0, input_rank - fft_rank)
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/external/tensorflow/tensorflow/python/ops/ |
D | nn_ops.py | 2857 input_rank = array_ops.rank(logits) 2859 logits = _swap_axis(logits, dim_axis, math_ops.subtract(input_rank, 1)) 2865 output, dim_axis, math_ops.subtract(input_rank, 1), name=name) 3119 input_rank = array_ops.rank(precise_logits) 3134 precise_logits = _move_dim_to_end(precise_logits, axis, input_rank) 3135 labels = _move_dim_to_end(labels, axis, input_rank) 3151 [math_ops.subtract(input_rank, 1)])
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/external/tensorflow/tensorflow/cc/gradients/ |
D | math_grad.cc | 644 auto input_rank = Size(scope, input_shape); in ReducedShapeHelper() local 648 auto axes = Mod(scope, Add(scope, reduction_axes, input_rank), input_rank); in ReducedShapeHelper() 653 auto input_rank_range = Range(scope, zero, input_rank, one); in ReducedShapeHelper()
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