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Searched refs:input_rank (Results 1 – 25 of 49) sorted by relevance

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/external/tensorflow/tensorflow/core/kernels/
Dsparse_concat_op.cc77 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()
Dsparse_split_op.cc51 const int64 input_rank = input_shape.vec<int64>().size(); in Compute() local
52 const int64 axis = (axis_input < 0) ? input_rank + axis_input : axis_input; in Compute()
55 context, axis >= 0 && axis < input_rank, in Compute()
56 errors::InvalidArgument("Input axis should be in range [", -input_rank, in Compute()
57 ", ", input_rank, "), got ", axis_input)); in Compute()
Dreshape_util.cc44 const int64 input_rank = input_shape.dims(); in operator ()() local
47 gtl::InlinedVector<int64, 8> input_strides(input_rank); in operator ()()
48 if (input_rank > 0) { in operator ()()
49 input_strides[input_rank - 1] = 1; in operator ()()
50 for (int d = input_rank - 2; d >= 0; --d) { in operator ()()
66 for (int j = 0; j < input_rank; ++j) { in operator ()()
/external/tensorflow/tensorflow/compiler/tf2xla/kernels/
Dmatrix_diag_ops.cc125 const int input_rank = input_shape.dims(); in SetMatrixDiag() local
127 padding_config = xla::MakeNoPaddingConfig(input_rank - 1); in SetMatrixDiag()
158 std::vector<int64> broadcast_dimensions(input_rank - 1); in SetMatrixDiag()
191 broadcast_dimensions.back() = input_rank - 1; // Column-wise. in SetMatrixDiag()
193 broadcast_dimensions.back() = input_rank - 2; // Row-wise. in SetMatrixDiag()
199 broadcast_dimensions.back() = input_rank - 2; // Row-wise. in SetMatrixDiag()
202 broadcast_dimensions.back() = input_rank - 1; // Column-wise. in SetMatrixDiag()
210 padding_config.mutable_dimensions(input_rank - 2) in SetMatrixDiag()
212 padding_config.mutable_dimensions(input_rank - 2) in SetMatrixDiag()
358 const int input_rank = input_shape.dims(); in Compile() local
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Ddepthtospace_op.cc62 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()
Dspacetodepth_op.cc62 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()
Dbatchtospace_op.cc28 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()
Dspacetobatch_op.cc28 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()
Dquantize_and_dequantize_op.cc81 int64 input_rank = input_shape.dims(); in Compile() local
82 OP_REQUIRES(ctx, input_rank >= 1, in Compile()
86 ctx, axis_ >= 0 && axis_ < input_rank, in Compile()
88 dimensions_to_reduce.reserve(input_rank - 1); in Compile()
89 for (int64 i = 0; i < input_rank; ++i) { in Compile()
Ddata_format_ops.cc109 int input_rank = input_tensor_shape.dims(); in Compile() local
110 OP_REQUIRES(ctx, input_rank == 1 || input_rank == 2, in Compile()
121 if (input_rank == 2) { in Compile()
/external/tensorflow/tensorflow/core/kernels/linalg/
Dlinalg_ops_common.cc120 int input_rank = -1; in AnalyzeInputs() local
124 input_rank = in.dims(); in AnalyzeInputs()
126 context, input_rank >= 2, in AnalyzeInputs()
128 " must have rank >= 2, got ", input_rank)); in AnalyzeInputs()
132 for (int dim = 0; dim < input_rank - 2; ++dim) { in AnalyzeInputs()
137 OP_REQUIRES(context, input_rank == in.dims(), in AnalyzeInputs()
140 for (int dim = 0; dim < input_rank - 2; ++dim) { in AnalyzeInputs()
148 const int row_dimension = input_rank - 2; in AnalyzeInputs()
149 const int col_dimension = input_rank - 1; in AnalyzeInputs()
Dlu_op.cc71 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()
Dlu_op_gpu.cu.cc87 const int input_rank = input.dims(); in ComputeAsync() local
90 context, input_rank >= 2, in ComputeAsync()
91 errors::InvalidArgument("Input must have rank >= 2, got ", input_rank), in ComputeAsync()
94 const int64 num_rows = input.dim_size(input_rank - 2); in ComputeAsync()
95 const int64 num_cols = input.dim_size(input_rank - 1); in ComputeAsync()
104 for (int dim = 0; dim < input_rank - 2; ++dim) { in ComputeAsync()
Dmatrix_set_diag_op.cc90 const int input_rank = input_shape.dims(); in Compute() local
103 const Eigen::Index num_rows = input_shape.dim_size(input_rank - 2); in Compute()
104 const Eigen::Index num_cols = input_shape.dim_size(input_rank - 1); in Compute()
129 (diag_shape.dim_size(input_rank - 2) == num_diags), in Compute()
/external/tensorflow/tensorflow/compiler/mlir/tosa/transforms/
Dlegalize_common.cc90 int32_t input_rank = input_type.getShape().size(); in convertPackOp() local
91 if (axis < 0) axis += input_rank; in convertPackOp()
143 if (axis < 0) axis += input_rank; in convertPackOp()
269 int64_t input_rank = input_shape.size(); in convertUnpackOp() local
274 if (axis < 0) axis += input_rank; in convertUnpackOp()
285 SmallVector<int64_t, 2> a1_transpose_shape(input_rank); in convertUnpackOp()
288 for (int i = 0; i < input_rank; i++) { in convertUnpackOp()
296 for (int i = 0; i < input_rank; i++) { in convertUnpackOp()
577 auto input_rank = input_type.getShape().size(); in convertConcatV2Op() local
579 if (axis < 0) axis += input_rank; in convertConcatV2Op()
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/external/tensorflow/tensorflow/core/common_runtime/
Deval_const_tensor.cc57 int input_rank = c->Rank(c->input(0)); in TryToInferTensorOutputFromInputShapes() local
58 Tensor t(node->output_type(0), TensorShape({input_rank})); in TryToInferTensorOutputFromInputShapes()
61 for (int i = 0; i < input_rank; i++) { in TryToInferTensorOutputFromInputShapes()
72 for (int i = 0; i < input_rank; i++) { in TryToInferTensorOutputFromInputShapes()
85 int32 input_rank = c->Rank(c->input(0)); in TryToInferTensorOutputFromInputShapes() local
87 t.flat<int32>()(0) = input_rank; in TryToInferTensorOutputFromInputShapes()
/external/tensorflow/tensorflow/core/framework/
Dcommon_shape_fns.cc1290 const int32 input_rank = c->Rank(input_shape); in MatrixDiagPartV2Shape() local
1291 const int32 num_rows = c->Value(c->Dim(input_shape, input_rank - 2)); in MatrixDiagPartV2Shape()
1292 const int32 num_cols = c->Value(c->Dim(input_shape, input_rank - 1)); in MatrixDiagPartV2Shape()
1309 dims.reserve(input_rank - 2); in MatrixDiagPartV2Shape()
1310 for (int i = 0; i < input_rank - 2; ++i) { in MatrixDiagPartV2Shape()
1348 const int32 input_rank = c->Rank(input_shape); in MatrixDiagV2Shape() local
1350 const int32 num_diags = c->Value(c->Dim(input_shape, input_rank - 2)); in MatrixDiagV2Shape()
1351 const int32 other_dim = c->Value(c->Dim(input_shape, input_rank - 1)); in MatrixDiagV2Shape()
1358 ", d_upper = ", upper_diag_index, " ", input_rank, " ", other_dim); in MatrixDiagV2Shape()
1377 const int32 max_diag_len = c->Value(c->Dim(input_shape, input_rank - 1)); in MatrixDiagV2Shape()
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Dshape_inference.cc957 int idx, int input_rank, DimensionHandle* out) { in MakeDimForScalarInputWithNegativeIndexing() argument
966 if (input_rank < 0) { in MakeDimForScalarInputWithNegativeIndexing()
969 } else if (val + input_rank < 0) { in MakeDimForScalarInputWithNegativeIndexing()
971 val, " must be in range [-", input_rank, in MakeDimForScalarInputWithNegativeIndexing()
972 ", ", input_rank, ")"); in MakeDimForScalarInputWithNegativeIndexing()
974 val += input_rank; in MakeDimForScalarInputWithNegativeIndexing()
976 } else if (input_rank >= 0 && val >= input_rank) { in MakeDimForScalarInputWithNegativeIndexing()
978 val, " must be in range [-", input_rank, in MakeDimForScalarInputWithNegativeIndexing()
979 ", ", input_rank, ")"); in MakeDimForScalarInputWithNegativeIndexing()
/external/tensorflow/tensorflow/core/ops/
Darray_ops.cc1472 int64 input_rank = c->Rank(input); in UniqueIdxShapeFn() local
1473 if (axis < -input_rank || axis >= input_rank) { in UniqueIdxShapeFn()
1475 -input_rank, ", ", input_rank, ")"); in UniqueIdxShapeFn()
1478 axis += input_rank; in UniqueIdxShapeFn()
1629 const int32 input_rank = c->Rank(input); in __anon42d741192402() local
1630 if (batch_dim >= input_rank) { in __anon42d741192402()
1632 "batch_dim must be < input rank: ", batch_dim, " vs. ", input_rank); in __anon42d741192402()
1634 if (seq_dim >= input_rank) { in __anon42d741192402()
1636 "seq_dim must be < input rank: ", seq_dim, " vs. ", input_rank); in __anon42d741192402()
1963 const Tensor* paddings_t, int64 input_rank) { in MirrorPadKnown() argument
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Dmath_ops.cc1054 const int32 input_rank = c->Rank(input_shape); in ArgOpShape() local
1055 if (input_rank <= 1) { in ArgOpShape()
1065 std::vector<DimensionHandle> dims(input_rank - 1); in ArgOpShape()
1081 int64 axis = dimension_val < 0 ? dimension_val + input_rank : dimension_val; in ArgOpShape()
1082 if (axis < 0 || axis >= input_rank) { in ArgOpShape()
1084 "Dimension (", dimension_val, ") must be in the range [", -input_rank, in ArgOpShape()
1085 ", ", input_rank, "), where ", input_rank, in ArgOpShape()
1091 for (int i = 0; i < input_rank; ++i) { in ArgOpShape()
/external/tensorflow/tensorflow/compiler/mlir/tensorflow/transforms/
Dlower_tf.cc838 int64_t input_rank = input_type.getRank(); in matchAndRewrite() local
840 int64_t remaining_rank = input_rank - 1 - block_rank; in matchAndRewrite()
863 RankedTensorType::get({input_rank, 2}, rewriter.getIntegerType(64)); in matchAndRewrite()
902 RankedTensorType::get({input_rank}, rewriter.getIntegerType(64)); in matchAndRewrite()
913 RankedTensorType::get({input_rank}, rewriter.getIntegerType(64)), in matchAndRewrite()
923 input_rank, RankedTensorType::get({1}, rewriter.getIntegerType(64))); in matchAndRewrite()
966 for (int64_t i = 1 + block_rank; i < input_rank; ++i) { in matchAndRewrite()
986 for (int64_t i = 1 + block_rank; i < input_rank; ++i) { in matchAndRewrite()
1002 for (int64_t i = 1 + block_rank; i < input_rank; ++i) { in matchAndRewrite()
1040 const int input_rank = input_ty.getRank(); in matchAndRewrite() local
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/external/libtextclassifier/native/tensorflow_models/seq_flow_lite/tflite_ops/
Dlayer_norm.cc234 const int input_rank = input->dims->size; in DefaultLayerNormFloat() local
235 const int num_features = input->dims->data[input_rank - 1]; in DefaultLayerNormFloat()
262 const int input_rank = input->dims->size; in DefaultLayerNorm() local
263 const int num_features = input->dims->data[input_rank - 1]; in DefaultLayerNorm()
/external/tensorflow/tensorflow/lite/toco/graph_transformations/
Dunpartition_embedding_lookup.cc200 gather_params_permute_op->input_rank = in Run()
220 merged_gather_op->input_rank = partition_array.shape().dimensions_count(); in Run()
/external/tensorflow/tensorflow/compiler/xla/
Dshape_util.cc1460 int64 input_rank = input_shape.rank(); in AlignLayouts() local
1482 std::vector<int64> dimension_to_alignment_index(input_rank); in AlignLayouts()
1484 for (int64 i = 0, j = 0; i < input_rank || j < output_rank;) { in AlignLayouts()
1493 if (i == input_rank) { in AlignLayouts()
1510 alignment.push_back({input_rank, output_rank}); in AlignLayouts()
1519 for (int64 i = 0; i < input_rank;) { in AlignLayouts()
1536 if (i == input_rank) { in AlignLayouts()
/external/tensorflow/tensorflow/compiler/mlir/xla/transforms/
Dlegalize_tf.cc991 int64_t input_rank = input_ty.getRank(); in CanBeTranslatedToDynamicSlice() local
997 for (int64_t i = 0; i < input_rank; ++i) { in CanBeTranslatedToDynamicSlice()
1021 int64_t input_rank = input_ty.getRank(); in TFSliceSizes2HLOSliceSizes() local
1025 for (int64_t i = 0; i < input_rank; ++i) { in TFSliceSizes2HLOSliceSizes()
2921 int64_t input_rank = input_type.getRank(); in matchAndRewrite() local
2923 if (dim_index < 0) dim_index += input_rank; in matchAndRewrite()
2941 SmallVector<int64_t, 4> begin_indices(input_rank, 0); in matchAndRewrite()
2943 SmallVector<int64_t, 4> strides(input_rank, 1); in matchAndRewrite()
3037 int64_t input_rank = input_type.getRank(); in matchAndRewrite() local
3039 if (dim_index < 0) dim_index += input_rank; in matchAndRewrite()
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