/external/tensorflow/tensorflow/lite/toco/graph_transformations/ |
D | propagate_fixed_sizes.cc | 91 int rank_x = input_shape_x.dimensions_count(); in ComputeBinaryOperatorOutputSize() 92 int rank_y = input_shape_y.dimensions_count(); in ComputeBinaryOperatorOutputSize() 132 CHECK(input_shape.dimensions_count() == 4) in ProcessConvOperator() 134 << "\" is " << input_shape.dimensions_count() << "D."; in ProcessConvOperator() 142 CHECK_EQ(weights_shape.dimensions_count(), 4); in ProcessConvOperator() 153 CHECK_EQ(output_array.shape().dimensions_count(), 4); in ProcessConvOperator() 188 CHECK(specified_output_shape_array.shape().dimensions_count() == 1 && in ProcessTransposeConvOperator() 204 CHECK_EQ(weights_shape.dimensions_count(), 4) in ProcessTransposeConvOperator() 231 CHECK_EQ(input_shape.dimensions_count(), 4) in ProcessTransposeConvOperator() 261 CHECK_EQ(input_shape.dimensions_count(), 4); in ProcessDepthwiseConvOperator() [all …]
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D | resolve_tensorflow_matmul.cc | 92 int dimensions_count = lhs_array.shape().dimensions_count(); in Run() local 93 if (dimensions_count < 2) { in Run() 96 dimensions_count); in Run() 102 perm.reserve(dimensions_count); in Run() 103 for (int i = 0; i < dimensions_count; ++i) { in Run() 106 std::swap(perm[dimensions_count - 1], perm[dimensions_count - 2]); in Run()
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D | fuse_binary_into_preceding_affine.cc | 65 const int depth = bias_shape.dims(bias_shape.dimensions_count() - 1); in FuseAddOrSubParamsIntoPrecedingAffine() 67 if (operand_shape.dimensions_count() >= 1 && in FuseAddOrSubParamsIntoPrecedingAffine() 68 operand_shape.dims(operand_shape.dimensions_count() - 1) == in FuseAddOrSubParamsIntoPrecedingAffine() 69 bias_shape.dims(bias_shape.dimensions_count() - 1)) { in FuseAddOrSubParamsIntoPrecedingAffine() 71 } else if (operand_shape.dimensions_count() == 0 || in FuseAddOrSubParamsIntoPrecedingAffine() 72 operand_shape.dims(operand_shape.dimensions_count() - 1) == 1) { in FuseAddOrSubParamsIntoPrecedingAffine() 139 if (operand_shape.dimensions_count() >= 1 && in FuseMulOrDivParamsIntoPrecedingAffine() 140 operand_shape.dims(operand_shape.dimensions_count() - 1) == in FuseMulOrDivParamsIntoPrecedingAffine() 141 bias_shape.dims(bias_shape.dimensions_count() - 1)) { in FuseMulOrDivParamsIntoPrecedingAffine() 143 } else if (operand_shape.dimensions_count() == 0 || in FuseMulOrDivParamsIntoPrecedingAffine() [all …]
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D | resolve_constant_unary.cc | 56 std::vector<int> reduction_mask(input_shape.dimensions_count(), 1); in ReduceGeneric() 59 CHECK_LT(axis, input_shape.dimensions_count()); in ReduceGeneric() 64 std::vector<int> output_indices(input_shape.dimensions_count()); in ReduceGeneric() 69 for (int i = 0; i < input_shape.dimensions_count(); ++i) { in ReduceGeneric() 86 for (int i = 0; i < output_shape.dimensions_count(); ++i) { in ReduceGeneric() 211 const int output_dims_count = output_shape.dimensions_count(); in Run()
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D | unroll_batch_matmul.cc | 42 int rank = input_array.shape().dimensions_count(); in SliceInput() 94 const int32 dims = input_array.shape().dimensions_count(); in GetTransposePerm() 106 const int32 dims = input_shape.dimensions_count(); in GetTransposeShape() 169 const int dims_a = input_array_a.shape().dimensions_count(); in Run() 170 const int dims_b = input_array_b.shape().dimensions_count(); in Run()
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D | convert_squeeze_to_reshape.cc | 50 if (input_array.shape().dimensions_count() == 0) { in Run() 64 if (output_shape.dimensions_count() == 0) { in Run()
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D | convert_trivial_pack_to_reshape.cc | 48 if (input_array.shape().dimensions_count() == 0) { in Run() 65 const int shape_array_dims = 1 + input_array.shape().dimensions_count(); in Run()
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D | identify_nearest_upsample.cc | 122 if (const_array.shape().dimensions_count() != in Run() 123 nonconst_array.shape().dimensions_count()) { in Run() 160 for (; i < current_const_shape.dimensions_count() - 1; in Run() 174 for (; i < current_nonconst_shape.dimensions_count(); ++i) { in Run()
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D | resolve_constant_transpose.cc | 40 CHECK(input_shape.dimensions_count() == output_shape.dimensions_count()); in Transpose() 41 const int dim = input_shape.dimensions_count(); in Transpose()
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D | resolve_constant_binary.cc | 95 const int dims_count = output_shape.dimensions_count(); in EvaluateBinaryOperatorOnConstantInputs() 107 CHECK_EQ(input0_shape.dimensions_count(), input1_shape.dimensions_count()); in EvaluateBinaryOperatorOnConstantInputs() 108 CHECK_EQ(input0_shape.dimensions_count(), dims_count); in EvaluateBinaryOperatorOnConstantInputs()
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D | remove_trivial_binary.cc | 92 if (input_array_0.shape().dimensions_count() == in Run() 93 input_array_1.shape().dimensions_count() && in Run()
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D | shuffle_fc_weights.cc | 60 for (int i = 1; i < input_shape.dimensions_count() - 1; i++) { in Run() 92 if (weights_shape.dimensions_count() != 2) { in Run()
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D | move_binary_operator_before_reshape.cc | 29 int shape_end = shape.dimensions_count() - 1; in IsTailOfShape() 30 int tail_end = tail.dimensions_count() - 1; in IsTailOfShape()
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D | resolve_constant_concatenation.cc | 83 for (int i = 0; i < concatenated_array->shape().dimensions_count(); i++) { in ConcatenateTensorBuffers() 93 for (int i = concatenation_axis; i < array_shape.dimensions_count(); i++) { in ConcatenateTensorBuffers()
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D | remove_trivial_concatenation_input.cc | 49 input_array.has_shape() && input_array.shape().dimensions_count() == 0; in Run()
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D | unpartition_embedding_lookup.cc | 201 partition_array.shape().dimensions_count(); in Run() 220 merged_gather_op->input_rank = partition_array.shape().dimensions_count(); in Run()
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D | resolve_constant_shape_or_rank.cc | 59 output_buffer.data[0] = input_array.shape().dimensions_count(); in Run()
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D | fuse_binary_into_following_affine.cc | 81 CHECK_EQ(output_depth, bias_shape.dims(bias_shape.dimensions_count() - 1)); in FuseAddOrSubParamsIntoFollowingAffine() 96 weights_shape.dims(weights_shape.dimensions_count() - 1); in FuseAddOrSubParamsIntoFollowingAffine()
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D | resolve_strided_slice_attributes.cc | 82 int num_input_axes = input_array.shape().dimensions_count(); in Run()
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/external/tensorflow/tensorflow/lite/kernels/internal/ |
D | types.h | 158 explicit RuntimeShape(int dimensions_count) : size_(dimensions_count) { in RuntimeShape() argument 159 if (dimensions_count > kMaxSmallSize) { in RuntimeShape() 163 dims_pointer_ = new int32_t[dimensions_count]; in RuntimeShape() 175 RuntimeShape(int dimensions_count, const int32_t* dims_data) : size_(0) { in RuntimeShape() argument 176 ReplaceWith(dimensions_count, dims_data); in RuntimeShape() 237 inline void Resize(int dimensions_count) { in Resize() argument 245 size_ = dimensions_count; in Resize() 246 if (dimensions_count > kMaxSmallSize) { in Resize() 250 dims_pointer_ = new int32_t[dimensions_count]; in Resize() 255 inline void ReplaceWith(int dimensions_count, const int32_t* dims_data) { in ReplaceWith() argument [all …]
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/external/tensorflow/tensorflow/lite/micro/kernels/ceva/ |
D | types.h | 326 explicit RuntimeShape(int dimensions_count) : size_(dimensions_count) { 327 if (dimensions_count > kMaxSmallSize) { 331 dims_pointer_ = new int32_t[dimensions_count]; 343 RuntimeShape(int dimensions_count, const int32_t* dims_data) : size_(0) { 344 ReplaceWith(dimensions_count, dims_data); 400 inline void Resize(int dimensions_count) { 408 size_ = dimensions_count; 409 if (dimensions_count > kMaxSmallSize) { 413 dims_pointer_ = new int32_t[dimensions_count]; 418 inline void ReplaceWith(int dimensions_count, const int32_t* dims_data) { [all …]
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/external/tensorflow/tensorflow/lite/micro/ |
D | memory_helpers.cc | 148 const int dimensions_count = tflite::GetTensorShape(input).DimensionsCount(); in AllocateOutputDimensionsFromInput() local 149 for (int i = 0; i < dimensions_count; i++) { in AllocateOutputDimensionsFromInput() 160 for (int i = 0; i < dimensions_count; i++) { in AllocateOutputDimensionsFromInput()
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/external/tensorflow/tensorflow/lite/toco/ |
D | tooling_util.cc | 526 if (array_shape.dimensions_count() == 0) { in LogArray() 639 CHECK_GE(new_shape_size, shape->dimensions_count()); in ExtendShape() 640 const int size_increase = new_shape_size - shape->dimensions_count(); in ExtendShape() 647 CHECK_LE(new_shape_size, shape->dimensions_count()); in UnextendShape() 648 const int size_reduction = shape->dimensions_count() - new_shape_size; in UnextendShape() 676 for (int i = 0; i < shape.dimensions_count(); ++i) { in IsNonEmpty() 683 for (int i = 0; i < shape.dimensions_count(); ++i) { in CheckNonEmptyShapeDimensions() 695 if (shape1.dimensions_count() > shape0.dimensions_count()) { in ShapesAgreeUpToBroadcasting() 702 int longer_index = longer->dimensions_count() - 1; in ShapesAgreeUpToBroadcasting() 703 int shorter_index = shorter->dimensions_count() - 1; in ShapesAgreeUpToBroadcasting() [all …]
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D | tooling_util.h | 141 return ::tflite::RuntimeShape(shape.dimensions_count(), shape.dims().data()); 219 DCHECK_EQ(shape.dimensions_count(), indices.size()); 220 const int dims_count = shape.dimensions_count(); 234 const int dims_count = shape.dimensions_count();
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D | dump_graphviz.cc | 284 for (int dim = 0; dim < array_shape.dimensions_count(); dim++) { in GetArrayLabel() 286 if (dim + 1 < array_shape.dimensions_count()) { in GetArrayLabel() 300 if (array.shape().dimensions_count() > 0) { in GetArrayLabel() 309 if (array.shape().dimensions_count() > 0) { in GetArrayLabel()
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