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Searched refs:GetArray (Results 1 – 25 of 106) sorted by relevance

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/external/tensorflow/tensorflow/lite/toco/graph_transformations/
Dpropagate_array_data_types.cc30 model->GetArray(output).data_type = data_type; in SetDataTypeForAllOutputs()
45 model->GetArray(input).data_type == ArrayDataType::kNone) { in Run()
53 old_output_data_types[output] = model->GetArray(output).data_type; in Run()
85 const ArrayDataType data_type = model->GetArray(op->inputs[1]).data_type; in Run()
92 const ArrayDataType data_type = model->GetArray(op->inputs[0]).data_type; in Run()
99 const ArrayDataType data_type = model->GetArray(op->inputs[2]).data_type; in Run()
107 model->GetArray(op->outputs[0]).data_type = cast_op->dst_data_type; in Run()
114 model->GetArray(op->outputs[0]).data_type = argmax_op->output_data_type; in Run()
121 model->GetArray(op->outputs[0]).data_type = argmin_op->output_data_type; in Run()
134 data_type = model->GetArray(op->inputs[0]).data_type; in Run()
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Dpropagate_fixed_sizes.cc125 const auto& input_array = model->GetArray(op->inputs[0]); in ProcessConvOperator()
135 const auto& weights_array = model->GetArray(op->inputs[1]); in ProcessConvOperator()
143 auto& output_array = model->GetArray(op->outputs[0]); in ProcessConvOperator()
158 auto& im2col_array = model->GetArray(op->outputs[1]); in ProcessConvOperator()
177 model->GetArray(op->inputs[TransposeConvOperator::OUTPUT_SHAPE]); in ProcessTransposeConvOperator()
197 model->GetArray(op->inputs[TransposeConvOperator::WEIGHTS]); in ProcessTransposeConvOperator()
224 model->GetArray(op->inputs[TransposeConvOperator::DATA_INPUT]); in ProcessTransposeConvOperator()
240 auto& output_array = model->GetArray(op->outputs[0]); in ProcessTransposeConvOperator()
246 auto& im2col_array = model->GetArray(op->outputs[1]); in ProcessTransposeConvOperator()
254 const auto& input_array = model->GetArray(op->inputs[0]); in ProcessDepthwiseConvOperator()
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Dhardcode_min_max.cc33 auto& im2col_array = model->GetArray(op->outputs[1]); in HardcodeMinMaxForIm2colArray()
37 const auto& input_array = model->GetArray(op->inputs[0]); in HardcodeMinMaxForIm2colArray()
50 auto& output_array = model->GetArray(op->outputs[0]); in HardcodeMinMaxForL2Normalization()
54 const auto& input_array = model->GetArray(op->inputs[0]); in HardcodeMinMaxForL2Normalization()
67 auto& input = model->GetArray(op->inputs[0]); in HardcodeInputMinMaxFromOutput()
74 auto& output = model->GetArray(op->outputs[0]); in HardcodeInputMinMaxFromOutput()
76 const auto* minmax = model->GetArray(op->outputs[0]).minmax.get(); in HardcodeInputMinMaxFromOutput()
92 if (model->GetArray(input).minmax) { in HardcodeMinMaxForConcatenation()
94 const auto* minmax = model->GetArray(input).minmax.get(); in HardcodeMinMaxForConcatenation()
101 auto& output = model->GetArray(op->outputs[0]); in HardcodeMinMaxForConcatenation()
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Didentify_lstm_merge_inputs.cc60 int num_cell = model->GetArray(src_op->inputs[kInputToInputWeightsTensor]) in Run()
63 int num_input = model->GetArray(src_op->inputs[kInputToInputWeightsTensor]) in Run()
67 model->GetArray(src_op->inputs[kRecurrentToInputWeightsTensor]) in Run()
90 model->GetArray(src_op->inputs[kInputToInputWeightsTensor]), 0, 0); in Run()
93 model->GetArray(src_op->inputs[kInputToCellWeightsTensor]), num_cell, 0); in Run()
96 model->GetArray(src_op->inputs[kInputToForgetWeightsTensor]), in Run()
100 model->GetArray(src_op->inputs[kInputToOutputWeightsTensor]), in Run()
104 model->GetArray(src_op->inputs[kRecurrentToInputWeightsTensor]), 0, in Run()
108 model->GetArray(src_op->inputs[kRecurrentToCellWeightsTensor]), num_cell, in Run()
112 model->GetArray(src_op->inputs[kRecurrentToForgetWeightsTensor]), in Run()
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Dmerge_reshape_into_preceding_transpose.cc39 if (!model.GetArray(op->inputs[0]).has_shape() || in OperatorReady()
40 !model.GetArray(op->outputs[0]).has_shape()) { in OperatorReady()
45 if (!model.GetArray(op->inputs[1]).buffer) { in OperatorReady()
60 const auto& input_array = model.GetArray(op->inputs[0]); in ReshapeToTranspose()
61 const auto& output_array = model.GetArray(op->outputs[0]); in ReshapeToTranspose()
180 model->GetArray(transpose_op->inputs[1]) in Run()
186 model->GetArray(transpose_op->outputs[0]).clear_shape(); in Run()
Dmove_binary_operator_before_reshape.cc99 model->GetArray(binary_op->inputs[variable_input_idx]); in Run()
107 model->GetArray(binary_op->inputs[constant_input_idx]).shape(), in Run()
108 model->GetArray(binary_op->inputs[variable_input_idx]).shape())) { in Run()
127 const auto& reshape_input_array = model->GetArray(reshape_op->inputs[0]); in Run()
136 model->GetArray(binary_op->inputs[constant_input_idx]).shape(), in Run()
137 model->GetArray(reshape_op->outputs[0]).shape())) { in Run()
176 model->GetArray(binary_op->outputs[0]).clear_shape(); in Run()
Dfuse_binary_into_following_affine.cc45 const auto& weights = model->GetArray(following_op->inputs[1]); in FuseAddOrSubParamsIntoFollowingAffine()
46 auto& bias = model->GetArray(following_op->inputs[2]); in FuseAddOrSubParamsIntoFollowingAffine()
49 model->GetArray(add_or_sub_op->inputs[index_of_constant_input]); in FuseAddOrSubParamsIntoFollowingAffine()
125 auto& weights = model->GetArray(weights_name); in FuseMulOrDivParamsIntoFollowingAffine()
129 model->GetArray(mul_or_div_op->inputs[index_of_constant_input]); in FuseMulOrDivParamsIntoFollowingAffine()
203 model->GetArray(binary_op->inputs[index_of_constant_input]).shape(); in Run()
252 const auto& weights = model->GetArray(following_op->inputs[1]); in Run()
253 const auto& bias = model->GetArray(following_op->inputs[2]); in Run()
Dresolve_constant_binary.cc70 const auto& input0_array = model->GetArray(binary_op->inputs[0]); in EvaluateBinaryOperatorOnConstantInputs()
71 const auto& input1_array = model->GetArray(binary_op->inputs[1]); in EvaluateBinaryOperatorOnConstantInputs()
73 auto& output_array = model->GetArray(output_name); in EvaluateBinaryOperatorOnConstantInputs()
169 const auto inputs_data_type = model->GetArray(binary_op->inputs[0]).data_type; in EvaluateBinaryOperatorOnConstantInputs()
171 model->GetArray(binary_op->outputs[0]).data_type; in EvaluateBinaryOperatorOnConstantInputs()
214 const auto& input0_array = model->GetArray(binary_op->inputs[0]); in Run()
215 const auto& input1_array = model->GetArray(binary_op->inputs[1]); in Run()
221 auto& output_array = model->GetArray(binary_op->outputs[0]); in Run()
Dreorder_reshape_transpose.cc36 if (!model.GetArray(op->inputs[0]).has_shape() || in OperatorReady()
37 !model.GetArray(op->outputs[0]).has_shape()) { in OperatorReady()
42 if (!model.GetArray(op->inputs[1]).buffer) { in OperatorReady()
161 const auto& input_array = model->GetArray(input_name); in Run()
162 const auto& intermediate_array = model->GetArray(intermediate_name); in Run()
163 const auto& output_array = model->GetArray(output_name); in Run()
Dresolve_constant_pack.cc28 auto& output_array = model->GetArray(op.outputs[0]); in Pack()
41 const auto& input_array = model->GetArray(op.inputs[i]); in Pack()
65 auto& output_array = model->GetArray(op->outputs[0]); in Run()
86 axis += model->GetArray(op->inputs[0]).shape().dims().size(); in Run()
Dresolve_constant_fill.cc26 const auto& val_array = model->GetArray(op->inputs[1]); in ComputeFillArray()
27 auto& output_array = model->GetArray(op->outputs[0]); in ComputeFillArray()
58 auto& output_array = model->GetArray(op->outputs[0]); in Run()
69 const auto& val_array = model->GetArray(op->inputs[1]); in Run()
Didentify_lstm_split_inputs.cc56 if (!model->GetArray(curr_op->outputs[LstmCellOperator::ACTIV_OUTPUT]) in Run()
65 int num_input = model->GetArray(curr_op->inputs[LstmCellOperator::DATA_INPUT]) in Run()
71 model->GetArray(curr_op->outputs[LstmCellOperator::ACTIV_OUTPUT]) in Run()
88 model->GetArray(curr_op->inputs[LstmCellOperator::WEIGHTS_INPUT]); in Run()
136 model->GetArray(curr_op->inputs[LstmCellOperator::BIASES_INPUT]); in Run()
Dunroll_batch_matmul.cc39 const auto& input_array_a = model->GetArray(input_lhs); in UnrollBatchMatMul3D()
40 const auto& input_array_b = model->GetArray(input_rhs); in UnrollBatchMatMul3D()
125 const auto& input_array_a = model->GetArray(input_lhs); in UnrollBatchMatMulRecursion()
186 const auto& input_array = model->GetArray(input); in TransposeInput()
228 const auto& input_lhs_array = model->GetArray(input_lhs); in Run()
229 const auto& input_rhs_array = model->GetArray(input_rhs); in Run()
239 const auto& input_array_a = model->GetArray(input_lhs); in Run()
247 const auto& input_array_b = model->GetArray(input_rhs); in Run()
Dresolve_strided_slice_attributes.cc56 const auto& input_array = model->GetArray(op->inputs[0]); in Run()
62 auto& start_array = model->GetArray(op->inputs[1]); in Run()
69 auto& stop_array = model->GetArray(op->inputs[2]); in Run()
72 auto& stride_array = model->GetArray(op->inputs[3]); in Run()
Dconvert_squeeze_to_reshape.cc45 const auto& input_array = model->GetArray(squeeze_op->inputs[0]); in Run()
55 !model->GetArray(squeeze_op->outputs[0]).has_shape()) { in Run()
61 const auto& output_shape = model->GetArray(squeeze_op->outputs[0]).shape(); in Run()
Dfuse_binary_into_preceding_affine.cc39 auto& bias = model->GetArray(preceding_op->inputs[2]); in FuseAddOrSubParamsIntoPrecedingAffine()
42 model->GetArray(add_or_sub_op->inputs[index_of_constant_input]); in FuseAddOrSubParamsIntoPrecedingAffine()
105 auto& weights = model->GetArray(weights_name); in FuseMulOrDivParamsIntoPrecedingAffine()
107 auto& bias = model->GetArray(bias_name); in FuseMulOrDivParamsIntoPrecedingAffine()
110 model->GetArray(mul_or_div_op->inputs[index_of_constant_input]); in FuseMulOrDivParamsIntoPrecedingAffine()
282 const auto& weights = model->GetArray(weights_name); in Run()
283 const auto& bias = model->GetArray(bias_name); in Run()
Dresolve_constant_range.cc54 const auto& start_array = model->GetArray(op->inputs[0]); in Run()
59 const auto& limit_array = model->GetArray(op->inputs[1]); in Run()
64 const auto& delta_array = model->GetArray(op->inputs[2]); in Run()
78 auto& output_array = model->GetArray(op->outputs[0]); in Run()
Dconvert_trivial_tile_to_concat.cc34 const auto& input_array = model->GetArray(tile_op->inputs[0]); in Run()
35 const auto& multiples_array = model->GetArray(tile_op->inputs[1]); in Run()
36 const auto& output_array = model->GetArray(tile_op->outputs[0]); in Run()
Dquantize.cc84 auto& array = model->GetArray(array_name); in GetOrComputeMinMax()
188 auto& array = model->GetArray(input); in ChooseQuantizationForOperatorInput()
218 model->GetArray(op.inputs[activations_input_index]); in ChooseQuantizationForOperatorInput()
219 const auto& input_weights = model->GetArray(op.inputs[weights_input_index]); in ChooseQuantizationForOperatorInput()
344 auto& array = model->GetArray(output); in ChooseQuantizationForOperatorOutput()
351 *quantized_data_type = model->GetArray(op.inputs[0]).data_type; in ChooseQuantizationForOperatorOutput()
373 const auto& input_array = model->GetArray(op.inputs[data_input_index]); in ChooseQuantizationForOperatorOutput()
484 const auto& input_array = model->GetArray(input); in Run()
501 const auto& array = model->GetArray(input); in Run()
631 auto& output_array = model->GetArray(output); in Run()
Dresolve_batch_normalization.cc39 auto& mean_array = model->GetArray(bn_op->inputs[1]); in Run()
40 const auto& multiplier_array = model->GetArray(bn_op->inputs[2]); in Run()
41 const auto& offset_array = model->GetArray(bn_op->inputs[3]); in Run()
80 intermediate_array.data_type = model->GetArray(bn_op->inputs[0]).data_type; in Run()
Dremove_trivial_binary.cc86 const auto& input_array_0 = model->GetArray(binary_op->inputs[0]); in Run()
87 const auto& input_array_1 = model->GetArray(binary_op->inputs[1]); in Run()
106 model->GetArray(binary_op->inputs[index_of_constant_input]); in Run()
Ddequantize.cc56 auto* array = &model->GetArray(array_name); in ClearArrayQuantizationParams()
80 auto* array = &model->GetArray(array_name); in DequantizeArray()
196 auto& input_array = model->GetArray(op->inputs[0]); in Run()
205 auto& output_array = model->GetArray(op->outputs[0]); in Run()
Dremove_trivial_passthrough.cc45 const Array& from_array = model->GetArray(from); in Reroute()
80 if (!model->GetArray(passthru_op->inputs[i]).buffer) { in RemoveTrivialPassthroughOp()
121 model->GetArray(main_input_name).has_shape()) { in RemoveTrivialPassthroughOp()
/external/tensorflow/tensorflow/lite/toco/tflite/
Doperator.cc68 const Array& input_array = op_signature.model->GetArray(input_name); in GetVersion()
109 const Array& input_array = op_signature.model->GetArray(input_name); in GetVersion()
110 const Array& filter_array = op_signature.model->GetArray(filter_name); in GetVersion()
111 const Array& output_array = op_signature.model->GetArray(output_name); in GetVersion()
166 const Array& input_array = op_signature.model->GetArray(input_name); in GetVersion()
167 const Array& filter_array = op_signature.model->GetArray(filter_name); in GetVersion()
168 const Array& output_array = op_signature.model->GetArray(output_name); in GetVersion()
204 const Array& input_array = op_signature.model->GetArray(input_name); in GetVersion()
250 const Array& input_array = op_signature.model->GetArray(input_name); in GetVersion()
280 const Array& input_array = op_signature.model->GetArray(input_name); in GetVersion()
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/external/pdfium/fxbarcode/qrcode/
DBC_QRCoderMaskUtil.cpp40 uint8_t* array = matrix->GetArray(); in ApplyMaskPenaltyRule2()
59 uint8_t* array = matrix->GetArray(); in ApplyMaskPenaltyRule3()
111 uint8_t* array = matrix->GetArray(); in ApplyMaskPenaltyRule4()
179 uint8_t* array = matrix->GetArray(); in ApplyMaskPenaltyRule1Internal()

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