/external/tensorflow/tensorflow/contrib/lite/toco/graph_transformations/ |
H A D | resolve_reorder_axes.cc | 34 Array* input_array, Array* output_array) { 36 CHECK(!output_array->buffer); 39 reordered_data.resize(RequiredBufferSizeForShape(output_array->shape())); 42 Shape output_shape = output_array->shape(); 50 input_array->copy_shape(output_array->shape()); 62 auto& output_array = model->GetArray(output_array_name); local 67 if (!output_array.has_shape()) { 74 &input_array, &output_array); 78 &input_array, &output_array); 83 input_array.copy_shape(output_array 33 ReorderAxes(AxesOrder input_axes_order, AxesOrder output_axes_order, Array* input_array, Array* output_array) argument [all...] |
H A D | resolve_constant_stack.cc | 28 auto& output_array = model->GetArray(op.outputs[0]); local 29 CHECK(output_array.data_type == Type); 33 output_array.GetMutableBuffer<Type>().data; 34 output_data.resize(RequiredBufferSizeForShape(output_array.shape())); 62 auto& output_array = model->GetArray(op->outputs[0]); local 63 if (output_array.data_type == ArrayDataType::kNone) { 68 if (!output_array.has_shape()) { 80 CHECK(!output_array.buffer); 81 switch (output_array.data_type) {
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H A D | resolve_constant_shape_or_rank.cc | 31 auto& output_array = model->GetArray(op->outputs[0]); local 32 if (output_array.data_type == ArrayDataType::kNone) { 43 if (!output_array.has_shape()) { 49 CHECK(!output_array.buffer); 50 auto& output_buffer = output_array.GetMutableBuffer<ArrayDataType::kInt32>(); 59 output_array.mutable_shape()->ReplaceDims(
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H A D | resolve_constant_strided_slice.cc | 62 Array* output_array) { 69 CHECK(output_array->data_type == Type); 82 output_array->GetMutableBuffer<Type>().data; 83 output_data.resize(RequiredBufferSizeForShape(output_array->shape())); 138 auto& output_array = model->GetArray(op->outputs[0]); local 139 if (output_array.data_type == ArrayDataType::kNone) { 144 if (!output_array.has_shape()) { 165 CHECK(!output_array.buffer); 166 switch (output_array.data_type) { 168 StridedSlice<ArrayDataType::kFloat>(*op, input_array, &output_array); 61 StridedSlice(StridedSliceOperator const& op, Array const& input_array, Array* output_array) argument [all...] |
H A D | remove_trivial_slice.cc | 37 const auto& output_array = model.GetArray(op.outputs[0]); local 38 if (input_array.has_shape() && output_array.has_shape()) { 39 if (input_array.shape() == output_array.shape()) {
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H A D | resolve_constant_fill.cc | 27 auto& output_array = model->GetArray(op->outputs[0]); local 30 CHECK(output_array.data_type == Type); 34 output_array.GetMutableBuffer<Type>().data; 35 data.resize(RequiredBufferSizeForShape(output_array.shape())); 55 auto& output_array = model->GetArray(op->outputs[0]); local 56 if (output_array.data_type == ArrayDataType::kNone) { 61 if (!output_array.has_shape()) { 77 switch (output_array.data_type) {
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H A D | resolve_multiply_by_zero.cc | 61 auto& output_array = model->GetArray(output_array_name); local 64 if (!output_array.has_shape()) { 92 CHECK(constant_input_array.data_type == output_array.data_type); 93 switch (output_array.data_type) { 101 FillArrayWithZeros<ArrayDataType::kFloat>(&output_array); 110 FillArrayWithZeros<ArrayDataType::kUint8>(&output_array); 119 FillArrayWithZeros<ArrayDataType::kInt32>(&output_array); 128 FillArrayWithZeros<ArrayDataType::kInt64>(&output_array);
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H A D | remove_trivial_quantized_activation_func.cc | 36 const auto& output_array = model->GetArray(op->outputs[0]); local 37 if (!output_array.quantization_params) { 40 if (output_array.data_type != ArrayDataType::kUint8) { 43 const auto& quantization_params = output_array.GetQuantizationParams();
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H A D | remove_trivial_reshape.cc | 38 const auto& output_array = model.GetArray(op.outputs[0]); local 39 if (input_array.has_shape() && output_array.has_shape()) { 41 ShapesAgreeUpToExtending(input_array.shape(), output_array.shape())) { 49 if (input_array.shape().dims() == output_array.shape().dims()) {
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H A D | resolve_constant_fake_quant.cc | 48 auto& output_array = model->GetArray(fakequant_op->outputs[0]); local 50 output_array.data_type = ArrayDataType::kFloat; 51 CHECK(!output_array.buffer); 53 output_array.GetOrCreateMinMax() = *fakequant_op->minmax; 54 auto& output_buffer = output_array.GetMutableBuffer<ArrayDataType::kFloat>();
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H A D | resolve_constant_transpose.cc | 30 const std::vector<int>& perm, Array* output_array) { 35 const Shape& output_shape = output_array->shape(); 37 output_array->GetMutableBuffer<Type>().data; 114 auto& output_array = model->GetArray(op->outputs[0]); local 115 if (output_array.data_type == ArrayDataType::kNone) { 119 if (!output_array.has_shape()) { 132 output_array.GetOrCreateMinMax() = input_array.GetMinMax(); 143 CHECK(!output_array.buffer); 144 switch (output_array.data_type) { 147 &output_array); 29 Transpose(Model* model, const Array& input_array, const std::vector<int>& perm, Array* output_array) argument [all...] |
H A D | drop_fake_quant.cc | 40 const auto& output_array = model->GetArray(fakequant_op->outputs[0]); local 41 if (!output_array.minmax) {
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H A D | hardcode_min_max.cc | 50 auto& output_array = model->GetArray(op->outputs[0]); local 51 if (output_array.minmax) { 59 CHECK(!output_array.minmax); 60 auto& output_minmax = output_array.GetOrCreateMinMax(); 130 auto& output_array = model->GetArray(op->outputs[0]); local 131 if (output_array.minmax) { 139 CHECK(!output_array.minmax); 140 auto& output_minmax = output_array.GetOrCreateMinMax(); 147 auto& output_array = model->GetArray(op->outputs[0]); local 148 if (output_array 166 auto& output_array = model->GetArray(op->outputs[0]); local [all...] |
H A D | convert_trivial_transpose_to_reshape.cc | 32 const auto& output_array = model->GetArray(transpose_op->outputs[0]); local 33 if (!output_array.has_shape()) { 40 std::vector<int> const& dims = output_array.shape().dims();
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H A D | propagate_fixed_sizes.cc | 66 Array* output_array) { 74 std::vector<int>* dims_out = output_array->mutable_shape()->mutable_dims(); 102 CHECK(output_array->has_shape()); 164 auto& output_array = model->GetArray(op->outputs[0]); local 170 output_array.mutable_shape(), 172 CHECK_EQ(output_array.shape().dimensions_count(), 4); 176 const auto& output_shape = output_array.shape(); 280 auto& output_array = model->GetArray(op->outputs[0]); local 281 if (output_array.has_shape()) { 301 *(output_array 64 ComputeBinaryOperatorOutputSize(const Shape& input_shape_x, const Shape& input_shape_y, Array* output_array) argument 331 auto& output_array = model->GetArray(op->outputs[0]); local 337 auto& output_array = model->GetArray(op->outputs[0]); local 406 auto& output_array = model->GetArray(output_name); local 423 auto& output_array = model->GetArray(output_name); local 446 auto& output_array = model->GetArray(op->outputs[0]); local 468 auto& output_array = model->GetArray(op->outputs[0]); local 524 auto& output_array = model->GetArray(op->outputs[0]); local 564 auto& output_array = model->GetArray(op->outputs[0]); local 638 auto& output_array = model->GetArray(op->outputs[0]); local 955 auto& output_array = model->GetArray(op->outputs[0]); local 1034 auto& output_array = model->GetArray(op->outputs[0]); local 1051 auto& output_array = model->GetArray(op->outputs[0]); local 1072 auto& output_array = model->GetArray(op->outputs[0]); local 1093 auto& output_array = model->GetArray(op->outputs[0]); local 1134 auto& output_array = model->GetArray(op->outputs[0]); local [all...] |
H A D | resolve_constant_range.cc | 55 auto& output_array = model->GetArray(op->outputs[0]); local 56 if (output_array.data_type == ArrayDataType::kNone) { 79 auto& buffer = output_array.GetMutableBuffer<ArrayDataType::kInt32>(); 85 CHECK_EQ(buffer.data.size(), output_array.shape().dims()[0]);
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H A D | remove_unused_op.cc | 58 for (const string& output_array : model->flags.output_arrays()) { 59 if (output == output_array) {
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H A D | resolve_constant_binary.cc | 73 auto& output_array = model->GetArray(output_name); local 76 CHECK(output_array.data_type == OutputDataType); 83 CHECK(!output_array.buffer); 90 const Shape& output_shape = output_array.shape(); 91 auto& output_data = output_array.GetMutableBuffer<OutputDataType>().data; 218 auto& output_array = model->GetArray(binary_op->outputs[0]); local 220 if (!output_array.has_shape()) {
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H A D | dequantize.cc | 136 for (const string& output_array : model->flags.output_arrays()) { 137 if (array_name == output_array) { 202 auto& output_array = model->GetArray(op->outputs[0]); local 203 output_array.data_type = ArrayDataType::kFloat; 204 output_array.quantization_params = nullptr;
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/external/libjpeg-turbo/ |
H A D | jutils.c | 95 JSAMPARRAY output_array, int dest_row, 99 * to output_array[dest_row++]; these areas may overlap for duplication. 108 output_array += dest_row; 112 outptr = *output_array++; 94 jcopy_sample_rows(JSAMPARRAY input_array, int source_row, JSAMPARRAY output_array, int dest_row, int num_rows, JDIMENSION num_cols) argument
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/external/tensorflow/tensorflow/contrib/lite/toco/ |
H A D | tooling_util.cc | 647 for (const string& output_array : model_flags.output_arrays()) { 648 QCHECK_NE(input_array.name(), output_array) 649 << "The array " << output_array 690 for (const string& output_array : model_flags.output_arrays()) { 691 QCHECK(IsAsciiPrintable(output_array)) 693 << output_array << ". Pass --allow_nonascii_arrays to allow that. " 695 << DumpAscii(output_array); 707 for (const string& output_array : model.flags.output_arrays()) { 708 CHECK(model.HasArray(output_array)) 709 << "Output array not found: " << output_array; 1331 auto& output_array = model->GetArray(output); local 1485 const auto& output_array = model.GetArray(op->outputs[0]); local 1506 const auto& output_array = model.GetArray(op->outputs[0]); local 1514 const auto& output_array = model.GetArray(op->outputs[0]); local 1527 const auto& output_array = model.GetArray(op->outputs[0]); local 1540 const auto& output_array = model.GetArray(op->outputs[0]); local 1551 const auto& output_array = model.GetArray(op->outputs[0]); local 1561 const auto& output_array = model.GetArray(op->outputs[0]); local 1573 const auto& output_array = model.GetArray(op->outputs[0]); local [all...] |
/external/tensorflow/tensorflow/core/kernels/ |
H A D | requantize.cc | 68 auto output_array = output->flat<T2>(); 73 output_array.data());
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H A D | quantize_down_and_shrink_range.cc | 75 auto output_array = output->flat<T2>(); 79 output_array.data());
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/external/tensorflow/tensorflow/compiler/xla/service/llvm_ir/ |
H A D | ops.cc | 41 ElementGenerator update_array_generator, const IrArray& output_array, 44 const Shape& output_shape = output_array.GetShape(); 73 output_array.EmitWriteArrayElement(output_index, update_data, ir_builder); 88 const IrArray& output_array, tensorflow::StringPiece name, 96 Shape output_shape = output_array.GetShape(); 108 output_array, /*launch_dimensions=*/nullptr, name, ir_builder); 39 EmitDynamicUpdateSliceInPlaceImpl( const Shape& update_shape, const ElementGenerator& start_indices_generator, ElementGenerator update_array_generator, const IrArray& output_array, const gpu::LaunchDimensions* launch_dimensions, tensorflow::StringPiece name, llvm::IRBuilder<>* ir_builder) argument 86 EmitDynamicUpdateSliceInPlace( tensorflow::gtl::ArraySlice<IrArray> operand_arrays, const IrArray& output_array, tensorflow::StringPiece name, llvm::IRBuilder<>* ir_builder) argument
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/external/tensorflow/tensorflow/contrib/training/python/training/ |
H A D | resample.py | 58 output_array, num_writes = control_flow_ops.while_loop( 63 output_array.concat,
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