/third_party/mindspore/mindspore/lite/test/ut/src/runtime/kernel/opencl/ |
D | stack_tests.cc | 36 std::vector<int> input_shapes[INPUT_NUM] = {{10}, {10}}; in TEST_F() local 45 TestMain({{input_shapes[0], input_datas[0], VAR}, {input_shapes[1], input_datas[1], VAR}}, in TEST_F() 53 std::vector<int> input_shapes[INPUT_NUM] = {{3, 4}, {3, 4}}; in TEST_F() local 64 TestMain({{input_shapes[0], input_datas[0], VAR}, {input_shapes[1], input_datas[1], VAR}}, in TEST_F() 72 std::vector<int> input_shapes[INPUT_NUM] = {{3, 4, 5}, {3, 4, 5}}; in TEST_F() local 83 …TestMain({{input_shapes[0], input_data1, VAR}, {input_shapes[1], input_data2, VAR}}, {output_shape… in TEST_F() 91 std::vector<int> input_shapes[INPUT_NUM] = {{3, 4, 5}, {3, 4, 5}}; in TEST_F() local 102 …TestMain({{input_shapes[0], input_data1, VAR}, {input_shapes[1], input_data2, VAR}}, {output_shape… in TEST_F() 110 std::vector<int> input_shapes[INPUT_NUM] = {{1, 96}, {1, 96}}; in TEST_F() local 121 …TestMain({{input_shapes[0], input_data1, VAR}, {input_shapes[1], input_data2, VAR}}, {output_shape… in TEST_F() [all …]
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/third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/gpu/arrays/ |
D | broadcast_to_gpu_kernel.h | 52 auto input_shapes = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0); in Init() local 54 is_null_input_ = CHECK_NULL_INPUT(input_shapes) || CHECK_NULL_INPUT(output_shapes); in Init() 60 if (input_shapes.size() > SHAPE_SIZE || output_shapes.size() > SHAPE_SIZE) { in Init() 64 if (output_shapes.size() < input_shapes.size()) { in Init() 68 size_t offset = output_shapes.size() - input_shapes.size(); in Init() 69 for (size_t i = 0; i < input_shapes.size(); i++) { in Init() 70 input_shape_[i + offset] = input_shapes[i]; in Init()
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D | unsorted_segment_min_gpu_kernel.h | 52 auto input_shapes = AnfAlgo::GetInputRealDeviceShapeIfExist(kernel_node, 0); in Init() local 56 …CHECK_NULL_INPUT(input_shapes) || CHECK_NULL_INPUT(segment_ids_shapes) || CHECK_NULL_INPUT(output_… in Init() 76 for (size_t i = 0; i < input_shapes.size(); i++) { in Init() 77 input_size_ *= input_shapes[i]; in Init() 90 outer_size_ = input_shapes[0]; in Init() 92 for (size_t i = 1; i < input_shapes.size(); i++) { in Init() 93 inner_size_ *= input_shapes[i]; in Init()
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D | unsorted_segment_max_gpu_kernel.h | 58 auto input_shapes = AnfAlgo::GetInputRealDeviceShapeIfExist(kernel_node, 0); in Init() local 62 …CHECK_NULL_INPUT(input_shapes) || CHECK_NULL_INPUT(segment_ids_shapes) || CHECK_NULL_INPUT(output_… in Init() 82 for (size_t i = 0; i < input_shapes.size(); i++) { in Init() 83 input_size_ *= input_shapes[i]; in Init() 96 outer_size_ = input_shapes[0]; in Init() 98 for (size_t i = 1; i < input_shapes.size(); i++) { in Init() 99 inner_size_ *= input_shapes[i]; in Init()
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D | topk_gpu_kernel.h | 87 auto input_shapes = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0); in Init() local 89 is_null_input_ = CHECK_NULL_INPUT(input_shapes) || CHECK_NULL_INPUT(output_shapes); in Init() 95 input_shape_size_ = input_shapes.size(); in Init() 96 for (size_t i = 0; i < input_shapes.size() - 1; i++) { in Init() 97 outer_size_ *= input_shapes[i]; in Init() 99 inner_size_ = input_shapes[input_shapes.size() - 1]; in Init()
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D | unsorted_segment_sum_gpu_kernel.h | 56 auto input_shapes = AnfAlgo::GetInputRealDeviceShapeIfExist(kernel_node, 0); in Init() local 59 …is_null_input_ = CHECK_NULL_INPUT(input_shapes) || CHECK_NULL_INPUT(ids_shapes) || CHECK_NULL_INPU… in Init() 74 for (size_t i = 0; i < input_shapes.size(); i++) { in Init() 76 input_dim0_ *= input_shapes[i]; in Init() 78 input_dim1_ *= input_shapes[i]; in Init()
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D | cast_gpu_kernel.h | 58 auto input_shapes = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0); in Init() local 60 is_null_input_ = CHECK_NULL_INPUT(input_shapes) || CHECK_NULL_INPUT(output_shapes); in Init() 67 for (size_t i = 0; i < input_shapes.size(); i++) { in Init() 68 input_size_ *= input_shapes[i]; in Init()
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/third_party/mindspore/mindspore/ccsrc/frontend/parallel/ops_info/ |
D | arithmetic_info.cc | 40 Shapes input_shapes; in InferExpendShape() local 44 input_shapes.push_back(input_a_shape); in InferExpendShape() 45 input_shapes.push_back(ExpendShape(input_a_shape, input_b_shape)); in InferExpendShape() 47 input_shapes.push_back(ExpendShape(input_b_shape, input_a_shape)); in InferExpendShape() 48 input_shapes.push_back(input_b_shape); in InferExpendShape() 50 input_shapes.push_back(input_a_shape); in InferExpendShape() 51 input_shapes.push_back(input_b_shape); in InferExpendShape() 53 return input_shapes; in InferExpendShape() 80 Shapes input_shapes = InferExpendShape(); in CheckStrategy() local 84 Shape input_a_shape = input_shapes.at(0); in CheckStrategy() [all …]
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/third_party/mindspore/mindspore/lite/micro/coder/opcoders/nnacl/fp32/ |
D | batchnorm_fp32_coder.cc | 30 std::vector<int> input_shapes = input_tensor_->shape(); in Init() local 31 if (input_shapes.empty()) { in Init() 34 int n_dim = static_cast<int>(input_shapes.size()); in Init() 35 bn_parameter->channel_ = input_shapes.at(n_dim - 1); in Init() 38 bn_parameter->unit_ *= input_shapes.at(i); in Init()
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/third_party/mindspore/mindspore/lite/test/st/scripts/ |
D | base_functions.sh | 128 … cfg_file_name line_info model_info spec_acc_limit model_name input_num input_shapes spec_threads \ 143 input_shapes=`echo ${model_info} | awk -F ';' '{print $3}'` 220 …elFile='${model_file}' --inDataFile='${input_files}' --inputShapes='${input_shapes}' --benchmarkDa… 221 …elFile='${model_file}' --inDataFile='${input_files}' --inputShapes='${input_shapes}' --benchmarkDa… 225 …elFile='${model_file}' --inDataFile='${input_files}' --inputShapes='${input_shapes}' --benchmarkDa… 226 …--modelFile=${model_file} --inDataFile=${input_files} --inputShapes=${input_shapes} --benchmarkDat… 246 …ataFile='${input_files}' --modelFile='${model_file}' --inputShapes='${input_shapes}' --enableFp16=… 247 …ataFile='${input_files}' --modelFile='${model_file}' --inputShapes='${input_shapes}' --enableFp16=… 251 …ataFile='${input_files}' --modelFile='${model_file}' --inputShapes='${input_shapes}' --warmUpLoopC… 252 …--inDataFile=${input_files} --modelFile=${model_file} --inputShapes=${input_shapes} --warmUpLoopCo…
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D | run_benchmark_x86.sh | 83 input_shapes=${line:length+1} 88 …els_path}'/input_output/input/'${model_name}'.ms.bin --inputShapes='${input_shapes}' --benchmarkDa… 89 …{models_path}/input_output/input/${model_name}.ms.bin --inputShapes=${input_shapes} --benchmarkDat… 99 …els_path}'/input_output/input/'${model_name}'.ms.bin --inputShapes='${input_shapes}' --benchmarkDa… 100 …{models_path}/input_output/input/${model_name}.ms.bin --inputShapes=${input_shapes} --benchmarkDat… 110 …els_path}'/input_output/input/'${model_name}'.ms.bin --inputShapes='${input_shapes}' --benchmarkDa… 111 …{models_path}/input_output/input/${model_name}.ms.bin --inputShapes=${input_shapes} --benchmarkDat…
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/third_party/mindspore/mindspore/lite/src/runtime/kernel/arm/int8/ |
D | batchnorm_int8.cc | 172 auto input_shapes = in_tensors_.at(0)->shape(); in Init() local 173 auto n_dim = input_shapes.size(); in Init() 175 batchnorm_param_->channel_ = input_shapes[n_dim - 1]; in Init() 178 batchnorm_param_->units_ *= input_shapes[i]; in Init() 205 auto input_shapes = in_tensors_.at(0)->shape(); in ReSize() local 207 for (size_t i = 0; i < input_shapes.size() - 1; i++) { in ReSize() 208 batchnorm_param_->unit_ *= input_shapes[i]; in ReSize()
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/third_party/mindspore/mindspore/ccsrc/backend/session/ |
D | single_kernel_graph.cc | 23 …ng &op_name, const std::vector<TypeId> &input_dtypes, const std::vector<ShapeVector> &input_shapes, in ConstructKernelGraphBasedOnSingleOp() argument 33 if (input_dtypes.size() != input_shapes.size()) { in ConstructKernelGraphBasedOnSingleOp() 38 auto tensor = std::make_shared<tensor::Tensor>(input_dtypes[i], input_shapes[i]); in ConstructKernelGraphBasedOnSingleOp()
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/third_party/mindspore/mindspore/lite/src/runtime/kernel/arm/fp32/ |
D | batchnorm_fp32.cc | 64 auto input_shapes = in_tensors_.at(0)->shape(); in FillParam() local 65 auto n_dim = input_shapes.size(); in FillParam() 68 param->channel_ = input_shapes[n_dim - 1]; in FillParam() 71 param->unit_ *= input_shapes[i]; in FillParam()
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/third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/host/ |
D | dynamic_broadcast_gradient_args_kernel.cc | 198 std::vector<std::vector<int64_t>> input_shapes(kInputNum); in Execute() local 199 input_shapes[0] = GetInputShape(cnode, 0); in Execute() 200 input_shapes[1] = GetInputShape(cnode, 1); in Execute() 201 auto grad_reduce_idx = CalculateOutput(input_shapes); in Execute() 203 auto r0_size = SetOutputValue(cnode, grad_reduce_idx, 0, input_shapes[0].size()); in Execute() 204 auto r1_size = SetOutputValue(cnode, grad_reduce_idx, 1, input_shapes[1].size()); in Execute()
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/third_party/mindspore/mindspore/lite/test/st/scripts/nnie/ |
D | run_benchmark_nnie.sh | 21 input_shapes=${model_info:${length}} 45 …h}'/'${model_name}'.ms --inDataFile='${input_files}' --inputShapes='${input_shapes}' --benchmarkDa… 46 …asepath}/${model_name}.ms --inDataFile=${input_files} --inputShapes=${input_shapes} --benchmarkDat…
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/third_party/mindspore/mindspore/lite/tools/optimizer/fisson/ |
D | node_out_shapes.cc | 30 std::vector<ShapeVector> input_shapes; in Run() local 44 input_shapes.push_back(shape); in Run() 69 Spliter::GetInstance()->UpdateNodeInputShapes(node_name, input_shapes); in Run()
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/third_party/ffmpeg/libavfilter/dnn/ |
D | dnn_backend_openvino.c | 279 input_shapes_t input_shapes; in init_model_ov() local 280 status = ie_network_get_input_shapes(ov_model->network, &input_shapes); in init_model_ov() 283 for (int i = 0; i < input_shapes.shape_num; i++) in init_model_ov() 284 input_shapes.shapes[i].shape.dims[0] = ctx->options.batch_size; in init_model_ov() 285 status = ie_network_reshape(ov_model->network, input_shapes); in init_model_ov() 286 ie_network_input_shapes_free(&input_shapes); in init_model_ov() 494 input_shapes_t input_shapes; in get_output_ov() local 497 status = ie_network_get_input_shapes(ov_model->network, &input_shapes); in get_output_ov() 498 input_shapes.shapes->shape.dims[2] = input_height; in get_output_ov() 499 input_shapes.shapes->shape.dims[3] = input_width; in get_output_ov() [all …]
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/third_party/mindspore/mindspore/lite/micro/coder/opcoders/nnacl/int8/ |
D | batchnorm_int8_coder.cc | 28 std::vector<int> input_shapes = input_tensor_->shape(); in Prepare() local 29 size_t n_dim = input_shapes.size(); in Prepare() 30 batchnorm_param_->channel_ = input_shapes[n_dim - 1]; in Prepare() 33 batchnorm_param_->units_ *= input_shapes[i]; in Prepare()
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/third_party/mindspore/mindspore/ccsrc/runtime/device/ |
D | launch_mul.cc | 32 std::vector<std::vector<int64_t>> input_shapes = {{shape}, {1}}; in ObtainMulKernelGraph() local 35 kMulOpName, input_dtypes, input_shapes, output_dtypes, output_shapes); in ObtainMulKernelGraph()
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/third_party/mindspore/mindspore/ccsrc/runtime/device/ascend/ |
D | ascend_launch_atomic_clean.cc | 86 std::vector<std::vector<int64_t>> input_shapes = {{static_cast<int64_t>(shape)}}; in ObtainAtomicCleanKernelGraph() local 89 kAtomicAddrCleanOpName, input_dtypes, input_shapes, output_dtypes, output_shapes); in ObtainAtomicCleanKernelGraph()
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D | ascend_launch_transdata.cc | 85 std::vector<std::vector<int64_t>> input_shapes = {{input_shape}}; in ObtainTransDataKernelGraph() local 88 kTransDataOpName, input_dtypes, input_shapes, output_dtypes, output_shapes); in ObtainTransDataKernelGraph()
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/third_party/mindspore/mindspore/lite/tools/optimizer/parallel/ |
D | spliter.cc | 139 …UpdateNodeInputShapes(const std::string &node_name, const std::vector<ShapeVector> &input_shapes) { in UpdateNodeInputShapes() argument 140 graph_node_input_shapes_[node_name] = (input_shapes); in UpdateNodeInputShapes()
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/third_party/mindspore/tests/ |
D | ops_common.py | 277 def gen_inputs(input_shapes, config): argument 279 if not input_shapes and add_fack_input: 281 return [convert(shp) for shp in input_shapes] 284 def gen_backward_inputs(input_shapes, output_shapes, config): argument 286 if not input_shapes and add_fack_input: 289 inputs = [convert(shp) for shp in input_shapes]
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/third_party/mindspore/mindspore/ops/_grad/ |
D | grad_array_ops.py | 324 def _concat_grad_uniform(input_shapes, input_nums): argument 328 if input_shapes[i - 1] != input_shapes[i]: 342 input_shapes = () 344 input_shapes = input_shapes + (shape_op(x[i]),) 345 is_uniform = _concat_grad_uniform(input_shapes, input_nums) 354 slice_out = P.Slice()(dout, out_offset[i], input_shapes[i]) 362 slice_out = P.Slice()(dout, out_offset[i], input_shapes[i])
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