forked from mindspore-Ecosystem/mindspore
[MS][LITE] fullconnection matmul A B matrix const node bug
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b32c5c551e
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@ -23,6 +23,11 @@ using mindspore::lite::RET_OK;
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namespace mindspore::kernel {
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FullconnectionCPUKernel::~FullconnectionCPUKernel() {
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FreeBuf();
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return;
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}
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void FullconnectionCPUKernel::FreeBuf() {
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if (a_c8_ptr_ != nullptr) {
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free(a_c8_ptr_);
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a_c8_ptr_ = nullptr;
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@ -41,7 +46,11 @@ FullconnectionCPUKernel::~FullconnectionCPUKernel() {
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}
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}
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int FullconnectionCPUKernel::ReSize() { return RET_OK; }
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int FullconnectionCPUKernel::ReSize() {
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FreeBuf();
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Init();
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return RET_OK;
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}
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int FullconnectionCPUKernel::Init() {
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if (context_->infer_shape_interrupt_ && !context_->running_) {
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@ -75,16 +84,44 @@ int FullconnectionCPUKernel::Init() {
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return RET_MEMORY_FAILED;
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}
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memset(b_r8_ptr_, 0, fc_param_->col_8_ * fc_param_->deep_ * sizeof(float));
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RowMajor2Col8Major(reinterpret_cast<float *>(in_tensors_[1]->Data()), b_r8_ptr_, fc_param_->col_, fc_param_->deep_);
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c_r8x8_ptr_ = reinterpret_cast<float *>(malloc(fc_param_->row_8_ * fc_param_->col_8_ * sizeof(float)));
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if (c_r8x8_ptr_ == nullptr) {
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return RET_MEMORY_FAILED;
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}
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memset(c_r8x8_ptr_, 0, fc_param_->row_8_ * fc_param_->col_8_ * sizeof(float));
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fc_param_->a_const_ = false;
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fc_param_->b_const_ = false;
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InitMatrixA(reinterpret_cast<float *>(in_tensors_[0]->Data()), a_c8_ptr_);
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InitMatrixB(reinterpret_cast<float *>(in_tensors_[1]->Data()), b_r8_ptr_);
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return RET_OK;
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}
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void FullconnectionCPUKernel::InitMatrixA(float *src_ptr, float *dst_ptr) {
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if (fc_param_->a_const_ == true) {
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return;
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}
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if (src_ptr == nullptr) {
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return;
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}
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fc_param_->a_const_ = true;
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RowMajor2Col8Major(src_ptr, a_c8_ptr_, fc_param_->row_, fc_param_->deep_);
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return;
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}
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void FullconnectionCPUKernel::InitMatrixB(float *src_ptr, float *dst_ptr) {
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if (fc_param_->b_const_ == true) {
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return;
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}
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if (src_ptr == nullptr) {
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return;
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}
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fc_param_->b_const_ = true;
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RowMajor2Col8Major(src_ptr, dst_ptr, fc_param_->col_, fc_param_->deep_);
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return;
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}
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int FcFp32MatmulRun(int task_id, LiteParallelGroupEnv *penv, void *cdata) {
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auto fc = reinterpret_cast<FullconnectionCPUKernel *>(cdata);
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auto error_code = fc->DoMatmul(task_id);
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@ -115,9 +152,11 @@ int FullconnectionCPUKernel::Run() {
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return prepare_ret;
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}
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auto a_ptr = reinterpret_cast<float *>(in_tensors_.at(0)->Data());
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auto b_ptr = reinterpret_cast<float *>(in_tensors_.at(1)->Data());
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auto output_ptr = reinterpret_cast<float *>(out_tensors_.at(0)->Data());
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RowMajor2Col8Major(a_ptr, a_c8_ptr_, fc_param_->row_, fc_param_->deep_);
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InitMatrixA(a_ptr, a_c8_ptr_);
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InitMatrixB(b_ptr, b_r8_ptr_);
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LiteBackendParallelLaunch(FcFp32MatmulRun, this, thread_count_);
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@ -40,6 +40,11 @@ class FullconnectionCPUKernel : public FullconnectionBaseCPUKernel {
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public:
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int DoMatmul(int task_id);
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void FreeBuf();
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private:
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void InitMatrixA(float *src_ptr, float *dst_ptr);
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void InitMatrixB(float *src_ptr, float *dst_ptr);
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private:
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float *a_c8_ptr_;
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@ -78,6 +78,11 @@ int MatmulCPUKernel::Init() {
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}
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memset(c_r8x8_ptr_, 0, params_->row_8_ * params_->col_8_ * sizeof(float));
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params_->a_const_ = false;
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params_->b_const_ = false;
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InitMatrixA(reinterpret_cast<float *>(in_tensors_[0]->Data()), a_c8_ptr_);
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InitMatrixB(reinterpret_cast<float *>(in_tensors_[1]->Data()), b_r8_ptr_);
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if (in_tensors_.size() == 3) {
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bias_ptr_ = reinterpret_cast<float *>(malloc(params_->col_8_ * sizeof(float)));
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memset(bias_ptr_, 0, params_->col_8_ * sizeof(float));
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@ -89,6 +94,40 @@ int MatmulCPUKernel::Init() {
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return RET_OK;
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}
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void MatmulCPUKernel::InitMatrixA(float *src_ptr, float *dst_ptr) {
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if (params_->a_const_ == true) {
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return;
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}
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if (src_ptr == nullptr) {
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return;
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}
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params_->a_const_ = true;
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if (params_->a_transpose_) {
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RowMajor2Row8Major(src_ptr, dst_ptr, params_->deep_, params_->row_);
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} else {
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RowMajor2Col8Major(src_ptr, a_c8_ptr_, params_->row_, params_->deep_);
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}
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return;
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}
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void MatmulCPUKernel::InitMatrixB(float *src_ptr, float *dst_ptr) {
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if (params_->b_const_ == true) {
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return;
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}
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if (src_ptr == nullptr) {
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return;
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}
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params_->b_const_ = true;
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if (params_->b_transpose_) {
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RowMajor2Col8Major(src_ptr, dst_ptr, params_->col_, params_->deep_);
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} else {
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RowMajor2Row8Major(src_ptr, dst_ptr, params_->deep_, params_->col_);
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}
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return;
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}
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int MatmulCPUKernel::RunImpl(int task_id) {
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int cur_oc = MSMIN(thread_stride_, UP_DIV(params_->col_8_, 8) - task_id * thread_stride_);
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if (cur_oc <= 0) {
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@ -131,16 +170,10 @@ int MatmulCPUKernel::Run() {
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auto cur_a_ptr = a_ptr + i * a_stride;
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auto cur_b_ptr = b_ptr + i * b_stride;
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auto cur_c_ptr = c_ptr + i * c_stride;
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if (params_->a_transpose_) {
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RowMajor2Row8Major(cur_a_ptr, a_c8_ptr_, params_->deep_, params_->row_);
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} else {
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RowMajor2Col8Major(cur_a_ptr, a_c8_ptr_, params_->row_, params_->deep_);
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}
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if (params_->b_transpose_) {
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RowMajor2Col8Major(cur_b_ptr, b_r8_ptr_, params_->col_, params_->deep_);
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} else {
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RowMajor2Row8Major(cur_b_ptr, b_r8_ptr_, params_->deep_, params_->col_);
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}
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InitMatrixA(cur_a_ptr, a_c8_ptr_);
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InitMatrixB(cur_b_ptr, b_r8_ptr_);
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LiteBackendParallelLaunch(MatmulFloatRun, this, thread_count_);
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Row8x8Major2RowMajor(c_r8x8_ptr_, cur_c_ptr, params_->row_, params_->col_, params_->col_);
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}
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@ -35,6 +35,10 @@ class MatmulCPUKernel : public MatmulBaseCPUKernel {
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int Run() override;
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int RunImpl(int task_id);
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private:
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void InitMatrixA(float *src_ptr, float *dst_ptr);
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void InitMatrixB(float *src_ptr, float *dst_ptr);
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private:
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float *a_c8_ptr_;
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float *b_r8_ptr_;
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@ -33,6 +33,8 @@ typedef struct MatMulParameter {
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int batch;
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bool a_transpose_; /* false : row-major */
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bool b_transpose_; /* true : col-major */
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bool a_const_;
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bool b_const_;
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ActType act_type_;
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} MatMulParameter;
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