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pr to master #8

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m7grui4p8 wants to merge 201 commits from p69201753/mindspore:cpu-kernel-reuse-1 into master
pull from: p69201753/mindspore:cpu-kernel-reuse-1
merge into: OSSInnovation:master
Conversation 0 Commits 201 Files Changed 306 +13 -12
5 changed files with 13 additions and 12 deletions
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Showing only changes of commit 6807c98696 - Show all commits

11
mindspore/lite/tools/converter/parser/onnx/onnx_model_parser.cc
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@ -171,10 +171,12 @@ STATUS OnnxModelParser::SetGraphOutputTensor(const onnx::GraphProto &onnx_graph,
return RET_OK;
}
void OnnxModelParser::ParseOnnxGemmNode(const onnx::GraphProto &onnx_graph, const onnx::NodeProto &onnx_node,
schema::MetaGraphT *graph, TensorCache *tensor_cache) {
void OnnxModelParser::ParseOnnxGemmNode(const onnx::GraphProto &onnx_graph,
const onnx::NodeProto &onnx_node, schema::MetaGraphT *graph,
TensorCache *tensor_cache, const QuantType &quant_type) {
std::unique_ptr<schema::CNodeT> dst_op_1 = std::make_unique<schema::CNodeT>();
dst_op_1->name = "Gemm_MatMul_" + onnx_node.output(0);
dst_op_1->quantType = quant_type;
ParseOnnxNodeAttr(onnx_graph, onnx_node, "MatMul", dst_op_1.get());
auto matmul_output_id = "Gemm_MatMul_" + onnx_node.output(0);
std::vector<string> matmul_inputs{onnx_node.input(0), onnx_node.input(1)};
@ -185,6 +187,7 @@ void OnnxModelParser::ParseOnnxGemmNode(const onnx::GraphProto &onnx_graph, cons
std::unique_ptr<schema::CNodeT> dst_op_2 = std::make_unique<schema::CNodeT>();
dst_op_2->name = "Gemm_BiasAdd_" + onnx_node.output(0);
dst_op_2->quantType = quant_type;
ParseOnnxNodeAttr(onnx_graph, onnx_node, "BiasAdd", dst_op_2.get());
std::vector<string> biasadd_inputs{matmul_output_id, onnx_node.input(2)};
std::vector<string> biasadd_outputs{onnx_node.output(0)};
@ -343,8 +346,6 @@ void OnnxModelParser::SetOpQuantParams(const onnx::GraphProto &onnx_graph, const
}
if (findQuantParams == needQuantParams) {
dst_op->quantType = schema::QuantType_AwareTraining;
} else {
dst_op->quantType = schema::QuantType_QUANT_NONE;
}
}
@ -520,7 +521,7 @@ schema::MetaGraphT *OnnxModelParser::ParseToFb(const std::string &modelFile, con
}
if (onnx_node.op_type() == "Gemm") {
if (status == RET_OK) {
ParseOnnxGemmNode(onnx_graph, onnx_node, dst_graph.get(), &tensor_cache);
ParseOnnxGemmNode(onnx_graph, onnx_node, dst_graph.get(), &tensor_cache, quantType);
}
continue;
} else if (onnx_node.op_type() == "Int8GivenIntTensorFill" || onnx_node.op_type() == "Int8GivenTensorFill") {

2
mindspore/lite/tools/converter/parser/onnx/onnx_model_parser.h
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@ -65,7 +65,7 @@ class OnnxModelParser : public ModelParser {
const QuantType &quantType);
void ParseOnnxGemmNode(const onnx::GraphProto &onnx_graph, const onnx::NodeProto &onnx_node,
schema::MetaGraphT *graph, TensorCache *tensor_cache);
schema::MetaGraphT *graph, TensorCache *tensor_cache, const QuantType &quant_type);
STATUS ParseOnnxGivenFillNode(const onnx::NodeProto &onnx_node, TensorCache *tensor_cache);

7
mindspore/lite/tools/converter/parser/tflite/tflite_model_parser.cc
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@ -47,14 +47,11 @@ std::unique_ptr<tflite::ModelT> TfliteModelParser::ReadTfliteModel(const char *m
STATUS TfliteModelParser::CopyConstTensorData(const std::vector<std::unique_ptr<tflite::BufferT>> &tflite_model_buffer,
const tflite::TensorT *tflite_tensor, schema::TensorT *tensor) {
auto count = 1;
std::for_each(tflite_tensor->shape.begin(), tflite_tensor->shape.end(), [&](int32_t sha) { count *= sha; });
auto data_size = count * GetDataTypeSize(TypeId(tensor->dataType));
auto buffer_idx = tflite_tensor->buffer;
if (!tflite_model_buffer[buffer_idx]->data.empty()) {
auto data_size = tflite_model_buffer[buffer_idx]->data.size();
tensor->data.resize(data_size);
if (memcpy_s(tensor->data.data(), tensor->data.size(), tflite_model_buffer[buffer_idx]->data.data(),
tflite_model_buffer[buffer_idx]->data.size())) {
if (memcpy_s(tensor->data.data(), data_size, tflite_model_buffer[buffer_idx]->data.data(), data_size) != EOK) {
MS_LOG(ERROR) << "memcpy tensor data failed";
return RET_MEMORY_FAILED;
}

3
mindspore/lite/tools/converter/parser/tflite/tflite_util.cc
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@ -119,6 +119,9 @@ std::map<tflite::BuiltinOperator, std::string> tfMsOpTypeMap{
{tflite::BuiltinOperator_CUSTOM, "Custom"},
{tflite::BuiltinOperator_MIRROR_PAD, "MirrorPad"},
{tflite::BuiltinOperator_NEG, "Neg"},
{tflite::BuiltinOperator_HASHTABLE_LOOKUP, "HashtableLookup"},
{tflite::BuiltinOperator_LSH_PROJECTION, "LshProjection"},
{tflite::BuiltinOperator_SKIP_GRAM, "SKipGram"},
};
std::map<tflite::ActivationFunctionType, schema::ActivationType> tfMsActivationFunctionMap{

2
mindspore/lite/tools/optimizer/fusion/conv_biasadd_fusion.cc
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@ -117,7 +117,7 @@ int GenConvNewBias(const FuncGraphPtr &func_graph, const CNodePtr &conv_node, co
}
} else {
if (EOK != memcpy_s(add_bias_data, kernel_nums * sizeof(float), add_weight_data, kernel_nums * sizeof(float))) {
MS_LOG(ERROR) << "memset_s conv_bias_data failed";
MS_LOG(ERROR) << "memcpy_s conv_bias_data failed";
delete[] add_bias_data;
return lite::RET_MEMORY_FAILED;
}