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!14479 fix rpnt_pdr model 

From: @zoloft
Reviewed-by: 
Signed-off-by:
This commit is contained in:
mindspore-ci-bot 2021-04-02 14:32:40 +08:00 committed by Gitee
parent 8634675e2d c64f05bc06
commit ece2f27889
11 changed files with 47 additions and 33 deletions
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2
mindspore/lite/micro/coder/generator/component/common_component.cc
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@ -232,7 +232,7 @@ void CodeFreeResourceImplement(std::ofstream &ofs, const std::unique_ptr<CoderCo
for (const auto &item : ctx->tensors_map()) { for (const auto &item : ctx->tensors_map()) {
Tensor *tensor = item.first; Tensor *tensor = item.first;
std::string name = item.second; std::string name = item.second;
if (tensor->data_c() != nullptr && tensor->category() != Tensor::Category::CONST_TENSOR) { if (tensor->data_c() != nullptr && !(CheckConstantTensor(tensor))) {
ofs << name << ", "; ofs << name << ", ";
num++; num++;
} }

10
mindspore/lite/micro/coder/generator/component/weight_component.cc
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@ -43,7 +43,7 @@ void CodeModelParamsState(std::ofstream &ofs, const std::map<std::string, Tensor
for (auto &item : weights) { for (auto &item : weights) {
std::string name = item.first; std::string name = item.first;
Tensor *tensor = item.second; Tensor *tensor = item.second;
if (tensor->category() == Tensor::Category::CONST_TENSOR) { if (CheckConstantTensor(tensor)) {
if (tensor->data_c() == nullptr) { if (tensor->data_c() == nullptr) {
continue; continue;
} }
@ -56,7 +56,7 @@ void CodeModelParamsData(std::ofstream &ofs, const std::map<std::string, Tensor
for (auto &item : weights) { for (auto &item : weights) {
std::string name = item.first; std::string name = item.first;
Tensor *tensor = item.second; Tensor *tensor = item.second;
if (tensor->category() == Tensor::Category::CONST_TENSOR) { if (CheckConstantTensor(tensor)) {
if (tensor->data_c() == nullptr) { if (tensor->data_c() == nullptr) {
continue; continue;
} }
@ -78,7 +78,7 @@ void CodeModelParamsForNet(std::ofstream &hofs, std::ofstream &cofs, const std::
if (tensor->data_c() == nullptr) { if (tensor->data_c() == nullptr) {
continue; continue;
} }
if (tensor->category() == Tensor::Category::CONST_TENSOR) { if (CheckConstantTensor(tensor)) {
hofs << "extern " << GetTensorDataType(tensor->data_type()) << name << "[];\n"; hofs << "extern " << GetTensorDataType(tensor->data_type()) << name << "[];\n";
cofs << GetTensorDataType(tensor->data_type()) << name << "[" << tensor->ElementsNum() << "];\n"; cofs << GetTensorDataType(tensor->data_type()) << name << "[" << tensor->ElementsNum() << "];\n";
} else if (tensor->category() == Tensor::Category::VAR) { } else if (tensor->category() == Tensor::Category::VAR) {
@ -114,7 +114,7 @@ void CodeWeightInitFunc(std::ofstream &ofs, const std::unique_ptr<CoderContext>
for (const auto &item : ctx->saved_weights()) { for (const auto &item : ctx->saved_weights()) {
std::string name = item.first; std::string name = item.first;
Tensor *tensor = item.second; Tensor *tensor = item.second;
if (tensor->category() != Tensor::Category::CONST_TENSOR) { if (!CheckConstantTensor(tensor)) {
continue; continue;
} }
std::map<Tensor *, std::string> ctx_tensor_map = ctx->tensors_map(); std::map<Tensor *, std::string> ctx_tensor_map = ctx->tensors_map();
@ -152,7 +152,7 @@ void SaveDataToNet(const std::map<std::string, Tensor *> &saved_weights, const s
for (auto &item : saved_weights) { for (auto &item : saved_weights) {
std::string name = item.first; std::string name = item.first;
Tensor *tensor = item.second; Tensor *tensor = item.second;
if (tensor->category() == Tensor::Category::CONST_TENSOR && tensor->data_c() != nullptr) { if ((CheckConstantTensor(tensor)) && tensor->data_c() != nullptr) {
net.write(reinterpret_cast<const char *>(tensor->data_c()), tensor->Size()); net.write(reinterpret_cast<const char *>(tensor->data_c()), tensor->Size());
} }
} }

30
mindspore/lite/micro/coder/opcoders/nnacl/fp32/arithmetic_fp32_coder.cc
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@ -265,15 +265,7 @@ void ArithmeticFP32Coder::ComputeInOutStrides() {
} }
} }
int ArithmeticFP32Coder::DoCode(CoderContext *const context) { void ArithmeticFP32Coder::CollectFilesForFnc(CoderContext *const context) {
ComputeInOutStrides();
int element_num = output_tensor_->ElementsNum();
MS_CHECK_TRUE(thread_num_ > 0, "thread_num_ <= 0");
int stride = UP_DIV(element_num, thread_num_);
int count = MSMIN(stride, element_num - stride * kDefaultTaskId);
MS_CHECK_TRUE(!arithmetic_run_.empty(), "arithmetic_run function is nullptr!");
NNaclFp32Serializer code;
/** /**
* for nnacl's operator combine all arithmetic to nnalc/arithmetic.c * for nnacl's operator combine all arithmetic to nnalc/arithmetic.c
* this solution is not suitable for micro, for the size of package. * this solution is not suitable for micro, for the size of package.
@ -312,18 +304,34 @@ int ArithmeticFP32Coder::DoCode(CoderContext *const context) {
{ {
"add_relu_fp32.c", "add_relu_fp32.c",
}); });
} else if (arithmetic_run_ == "ElementDivRelu6" || arithmetic_run_ == "ElementDivRelu" ||
arithmetic_run_ == "ElementDiv") {
Collect(context,
{
"nnacl/fp32/div_fp32.h",
},
{
"div_fp32.c",
});
} else { } else {
Collect(context, Collect(context,
{ {
"nnacl/arithmetic_common.h",
"nnacl/fp32/arithmetic_fp32.h", "nnacl/fp32/arithmetic_fp32.h",
}, },
{ {
"arithmetic_common.c",
"arithmetic_fp32.c", "arithmetic_fp32.c",
}); });
} }
}
int ArithmeticFP32Coder::DoCode(CoderContext *const context) {
ComputeInOutStrides();
int element_num = output_tensor_->ElementsNum();
MS_CHECK_TRUE(thread_num_ > 0, "thread_num_ is less than zero");
int stride = UP_DIV(element_num, thread_num_);
int count = MSMIN(stride, element_num - stride * kDefaultTaskId);
MS_CHECK_TRUE(!arithmetic_run_.empty(), "arithmetic_run function is nullptr!");
NNaclFp32Serializer code;
if (arithmetic_parameter_->broadcasting_) { if (arithmetic_parameter_->broadcasting_) {
stride = UP_DIV(outside_, thread_num_); stride = UP_DIV(outside_, thread_num_);
out_count_ = MSMIN(stride, outside_ - stride * kDefaultTaskId); out_count_ = MSMIN(stride, outside_ - stride * kDefaultTaskId);

2
mindspore/lite/micro/coder/opcoders/nnacl/fp32/arithmetic_fp32_coder.h
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@ -85,6 +85,8 @@ class ArithmeticFP32Coder final : public OperatorCoder {
int BroadcastRun(const std::string &input0, const std::string &input1, const std::string &output, int dim, int BroadcastRun(const std::string &input0, const std::string &input1, const std::string &output, int dim,
int out_count, int out_thread_stride, NNaclFp32Serializer *const code); int out_count, int out_thread_stride, NNaclFp32Serializer *const code);
void CollectFilesForFnc(CoderContext *const context);
int break_pos_{0}; int break_pos_{0};
int outside_{0}; int outside_{0};

5
mindspore/lite/micro/coder/opcoders/nnacl/fp32/arithmetic_self_fp32_coder.cc
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@ -69,11 +69,10 @@ int ArithmeticSelfFP32Coder::DoCode(CoderContext *const context) {
Collect(context, Collect(context,
{ {
"nnacl/arithmetic_common.h", "nnacl/fp32/arithmetic_self_fp32.h",
"nnacl/fp32/arithmetic_self.h",
}, },
{ {
"nnacl/fp32/arithmetic_self.c", "arithmetic_self_fp32.c",
}); });
NNaclFp32Serializer code; NNaclFp32Serializer code;
code.CodeFunction(arithmetic_self_run_, input_tensor_, output_tensor_, size); code.CodeFunction(arithmetic_self_run_, input_tensor_, output_tensor_, size);

6
mindspore/lite/micro/coder/opcoders/nnacl/fp32/concat_fp32_coder.cc
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@ -37,10 +37,10 @@ int ConcatFP32Coder::ReSize() {
int ConcatFP32Coder::DoCode(CoderContext *const context) { int ConcatFP32Coder::DoCode(CoderContext *const context) {
Collect(context, Collect(context,
{ {
"nnacl/fp32/concat.h", "nnacl/base/concat_base.h",
}, },
{ {
"nnacl/fp32/concat.c", "concat_base.c",
}); });
size_t input_num = input_tensors_.size(); size_t input_num = input_tensors_.size();
@ -74,7 +74,7 @@ int ConcatFP32Coder::DoCode(CoderContext *const context) {
code << "};\n"; code << "};\n";
code.CodeFunction("Concat", "inputs_addr", input_num, axis_, "inputs_output_shape", output_tensor_->shape().size(), code.CodeFunction("Concat", "inputs_addr", input_num, axis_, "inputs_output_shape", output_tensor_->shape().size(),
output_tensor_, 0, thread_num_); output_tensor_, 0, thread_num_, sizeof(float));
context->AppendCode(code.str()); context->AppendCode(code.str());
return RET_OK; return RET_OK;
} }

2
mindspore/lite/micro/coder/opcoders/nnacl/fp32/exp_fp32_coder.cc
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@ -50,7 +50,7 @@ int ExpFP32Coder::DoCode(CoderContext *ctx) {
}); });
nnacl::NNaclFp32Serializer code; nnacl::NNaclFp32Serializer code;
code.CodeStruct("exp_parameter", *exp_parameter_); code.CodeStruct("exp_parameter", *exp_parameter_);
code.CodeFunction("Exp", input_tensor_, "(ExpParameter *)&exp_parameter", kDefaultTaskId); code.CodeFunction("Exp", input_tensor_, output_tensor_, "(ExpParameter *)&exp_parameter", kDefaultTaskId);
ctx->AppendCode(code.str()); ctx->AppendCode(code.str());
return RET_OK; return RET_OK;
} }

7
mindspore/lite/micro/coder/opcoders/nnacl/fp32/power_fp32_coder.cc
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@ -38,7 +38,7 @@ int PowerFP32Coder::DoCode(CoderContext *const context) {
std::string exp_addr; std::string exp_addr;
bool broadcast = true; bool broadcast = true;
if (input_tensors_.size() == 2) { if (input_tensors_.size() == 2) {
exp_addr = allocator_->GetRuntimeAddr(filter_tensor); exp_addr = allocator_->GetRuntimeAddr(filter_tensor, true);
broadcast = !(input_tensor_->shape() == filter_tensor->shape()); broadcast = !(input_tensor_->shape() == filter_tensor->shape());
} }
std::string cur_exp_str; std::string cur_exp_str;
@ -50,10 +50,11 @@ int PowerFP32Coder::DoCode(CoderContext *const context) {
// generate code .h .c // generate code .h .c
Collect(context, Collect(context,
{ {
"nnacl/power.h", "nnacl/power_parameter.h",
"nnacl/fp32/power_fp32.h",
}, },
{ {
"power.c", "power_fp32.c",
}); });
NNaclFp32Serializer code; NNaclFp32Serializer code;
code.CodeFunction("Power", input_tensor_, cur_exp_str, output_tensor_, len, scale_, shift_, broadcast); code.CodeFunction("Power", input_tensor_, cur_exp_str, output_tensor_, len, scale_, shift_, broadcast);

6
mindspore/lite/micro/coder/utils/coder_utils.cc
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@ -24,6 +24,10 @@
#include "coder/allocator/allocator.h" #include "coder/allocator/allocator.h"
namespace mindspore::lite::micro { namespace mindspore::lite::micro {
bool CheckConstantTensor(const Tensor *const tensor) {
return tensor->category() == Tensor::Category::CONST_TENSOR || tensor->category() == Tensor::Category::CONST_SCALAR;
}
template <typename T> template <typename T>
void TensorDataToFile(const lite::Tensor *tensor, std::ofstream &ofs) { void TensorDataToFile(const lite::Tensor *tensor, std::ofstream &ofs) {
const int NUM = 45; const int NUM = 45;
@ -79,7 +83,7 @@ std::string TensorsToString(const std::vector<Tensor *> &tensors, const std::str
MemoryAllocator *allocator = MemoryAllocator::GetInstance(); MemoryAllocator *allocator = MemoryAllocator::GetInstance();
std::string info; std::string info;
for (const auto &tensor : tensors) { for (const auto &tensor : tensors) {
if (tensor->category() == Tensor::Category::CONST_TENSOR) { if (CheckConstantTensor(tensor)) {
continue; continue;
} }
info += " {\n"; info += " {\n";

2
mindspore/lite/micro/coder/utils/coder_utils.h
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@ -30,6 +30,8 @@ namespace mindspore::lite::micro {
constexpr int kWeightPrecision = 9; constexpr int kWeightPrecision = 9;
bool CheckConstantTensor(const Tensor *const tensor);
std::vector<std::string> AddDumpDataInfo(const std::vector<std::string> &blocks, std::vector<std::string> AddDumpDataInfo(const std::vector<std::string> &blocks,
const std::vector<std::unique_ptr<OperatorCoder>> &opcoders); const std::vector<std::unique_ptr<OperatorCoder>> &opcoders);

8
mindspore/lite/micro/example/mobilenetv2/mobilenetv2.sh
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@ -93,11 +93,9 @@ gen_mobile() {
local CODEGEN_FILE="${CODEGEN_FILE_NAME}.tar.gz" local CODEGEN_FILE="${CODEGEN_FILE_NAME}.tar.gz"
local CODEGEN_LITE_DOWNLOAD_URL="https://ms-release.obs.cn-north-4.myhuaweicloud.com/${VERSION_STR}/MindSpore/lite/release/linux/${CODEGEN_FILE}" local CODEGEN_LITE_DOWNLOAD_URL="https://ms-release.obs.cn-north-4.myhuaweicloud.com/${VERSION_STR}/MindSpore/lite/release/linux/${CODEGEN_FILE}"
# if [ ! -e ${BASEPATH}/build/${CODEGEN_FILE} ]; then if [ ! -e ${BASEPATH}/build/${CODEGEN_FILE} ]; then
# wget -c -O ${BASEPATH}/build/${CODEGEN_FILE} --no-check-certificate ${CODEGEN_LITE_DOWNLOAD_URL} wget -c -O ${BASEPATH}/build/${CODEGEN_FILE} --no-check-certificate ${CODEGEN_LITE_DOWNLOAD_URL}
# fi fi
cp ${OUTPUT_DIR}/${CODEGEN_FILE} ${BASEPATH}/build || exit 1
tar xzvf ${BASEPATH}/build/${CODEGEN_FILE} -C ${BASEPATH}/build/ || exit 1 tar xzvf ${BASEPATH}/build/${CODEGEN_FILE} -C ${BASEPATH}/build/ || exit 1
rm ${BASEPATH}/build/${CODEGEN_FILE} || exit 1 rm ${BASEPATH}/build/${CODEGEN_FILE} || exit 1