| @@ -31,9 +31,7 @@ using mindspore::lite::RET_ERROR; | |||
| using mindspore::schema::PrimitiveType_MatMul; | |||
| namespace mindspore::kernel { | |||
| MatmulCPUKernel::~MatmulCPUKernel() { FreeTmpBuffer(); } | |||
| void MatmulCPUKernel::FreeTmpBuffer() { | |||
| MatmulCPUKernel::~MatmulCPUKernel() { | |||
| if (a_pack_ptr_ != nullptr) { | |||
| free(a_pack_ptr_); | |||
| a_pack_ptr_ = nullptr; | |||
| @@ -48,6 +46,17 @@ void MatmulCPUKernel::FreeTmpBuffer() { | |||
| } | |||
| } | |||
| void MatmulCPUKernel::FreeTmpBuffer() { | |||
| if (a_pack_ptr_ != nullptr) { | |||
| params_->a_const_ ? free(a_pack_ptr_) : context_->allocator->Free(a_pack_ptr_); | |||
| a_pack_ptr_ = nullptr; | |||
| } | |||
| if (b_pack_ptr_ != nullptr) { | |||
| params_->b_const_ ? free(b_pack_ptr_) : context_->allocator->Free(b_pack_ptr_); | |||
| b_pack_ptr_ = nullptr; | |||
| } | |||
| } | |||
| int MatmulCPUKernel::MallocMatrixABuffer() { | |||
| auto a_shape = in_tensors_[0]->shape(); | |||
| int batch = 1; | |||
| @@ -66,20 +75,28 @@ int MatmulCPUKernel::MallocMatrixABuffer() { | |||
| params_->row_12_ = UP_ROUND(params_->row_, C12NUM); | |||
| #if defined(ENABLE_ARM32) || defined(ENABLE_X86_64_SSE) | |||
| a_pack_ptr_ = reinterpret_cast<float *>(malloc(params_->batch * params_->row_4_ * params_->deep_ * sizeof(float))); | |||
| if (params_->a_const_) { | |||
| a_pack_ptr_ = reinterpret_cast<float *>(malloc(params_->batch * params_->row_4_ * params_->deep_ * sizeof(float))); | |||
| } else { | |||
| a_pack_ptr_ = reinterpret_cast<float *>( | |||
| context_->allocator->Malloc(params_->batch * params_->row_4_ * params_->deep_ * sizeof(float))); | |||
| } | |||
| if (a_pack_ptr_ == nullptr) { | |||
| FreeTmpBuffer(); | |||
| return RET_MEMORY_FAILED; | |||
| } | |||
| memset(a_pack_ptr_, 0, params_->row_4_ * params_->deep_ * sizeof(float)); | |||
| #else | |||
| int row_tmp = is_vector_a_ ? 1 : params_->row_12_; | |||
| a_pack_ptr_ = reinterpret_cast<float *>(malloc(params_->batch * row_tmp * params_->deep_ * sizeof(float))); | |||
| if (params_->a_const_) { | |||
| a_pack_ptr_ = reinterpret_cast<float *>(malloc(params_->batch * row_tmp * params_->deep_ * sizeof(float))); | |||
| } else { | |||
| a_pack_ptr_ = | |||
| reinterpret_cast<float *>(context_->allocator->Malloc(params_->batch * row_tmp * params_->deep_ * sizeof(float))); | |||
| } | |||
| if (a_pack_ptr_ == nullptr) { | |||
| FreeTmpBuffer(); | |||
| return RET_MEMORY_FAILED; | |||
| } | |||
| memset(a_pack_ptr_, 0, params_->batch * row_tmp * params_->deep_ * sizeof(float)); | |||
| #endif | |||
| return RET_OK; | |||
| } | |||
| @@ -99,12 +116,16 @@ int MatmulCPUKernel::MallocMatrixBBuffer() { | |||
| params_->deep_ = params_->b_transpose_ ? b_shape[b_shape.size() - 1] : b_shape[b_shape.size() - 2]; | |||
| int col_tmp = is_vector_a_ ? params_->col_ : params_->col_8_; | |||
| b_pack_ptr_ = reinterpret_cast<float *>(malloc(params_->batch * col_tmp * params_->deep_ * sizeof(float))); | |||
| if (params_->b_const_) { | |||
| b_pack_ptr_ = reinterpret_cast<float *>(malloc(params_->batch * col_tmp * params_->deep_ * sizeof(float))); | |||
| } else { | |||
| b_pack_ptr_ = | |||
| reinterpret_cast<float *>(context_->allocator->Malloc(params_->batch * col_tmp * params_->deep_ * sizeof(float))); | |||
| } | |||
| if (b_pack_ptr_ == nullptr) { | |||
| FreeTmpBuffer(); | |||
| return RET_MEMORY_FAILED; | |||
| } | |||
| memset(b_pack_ptr_, 0, params_->batch * col_tmp * params_->deep_ * sizeof(float)); | |||
| thread_count_ = MSMIN(thread_count_, UP_DIV(params_->col_8_, 8)); | |||
| thread_stride_ = UP_DIV(UP_DIV(params_->col_8_, 8), thread_count_); | |||
| @@ -112,59 +133,33 @@ int MatmulCPUKernel::MallocMatrixBBuffer() { | |||
| } | |||
| int MatmulCPUKernel::InitBias() { | |||
| auto b_shape = in_tensors_[1]->shape(); | |||
| auto c_shape = out_tensors_[0]->shape(); | |||
| params_->col_ = params_->b_const_ | |||
| ? (params_->b_transpose_ ? b_shape[b_shape.size() - 2] : b_shape[b_shape.size() - 1]) | |||
| : (c_shape[c_shape.size() - 1]); | |||
| params_->col_8_ = UP_ROUND(params_->col_, 8); | |||
| auto col_tmp = is_vector_a_ ? params_->col_ : params_->col_8_; | |||
| bias_ptr_ = reinterpret_cast<float *>(malloc(col_tmp * sizeof(float))); | |||
| if (bias_ptr_ == nullptr) { | |||
| FreeTmpBuffer(); | |||
| return RET_MEMORY_FAILED; | |||
| } | |||
| memset(bias_ptr_, 0, col_tmp * sizeof(float)); | |||
| if (in_tensors_.size() == 3) { | |||
| auto c_shape = out_tensors_[0]->shape(); | |||
| auto bias_shape = in_tensors_[1]->shape(); | |||
| if (bias_shape[bias_shape.size() - 1] != c_shape[c_shape.size() - 1]) { | |||
| MS_LOG(ERROR) << "The bias'dimension is not equal with colum"; | |||
| FreeTmpBuffer(); | |||
| return RET_INPUT_TENSOR_ERROR; | |||
| } | |||
| auto col = c_shape[c_shape.size() - 1]; | |||
| auto col_8 = UP_ROUND(col, 8); | |||
| auto col_tmp = is_vector_a_ ? col : col_8; | |||
| bias_ptr_ = reinterpret_cast<float *>(malloc(col_tmp * sizeof(float))); | |||
| if (bias_ptr_ == nullptr) { | |||
| FreeTmpBuffer(); | |||
| return RET_MEMORY_FAILED; | |||
| } | |||
| memcpy(bias_ptr_, in_tensors_[2]->data_c(), in_tensors_[2]->ElementsNum() * sizeof(float)); | |||
| } | |||
| return RET_OK; | |||
| } | |||
| int MatmulCPUKernel::ReSize() { | |||
| if (params_->a_const_ == false || params_->a_init_shape_ == false) { | |||
| if (a_pack_ptr_ != nullptr) { | |||
| free(a_pack_ptr_); | |||
| a_pack_ptr_ = nullptr; | |||
| } | |||
| auto ret = MallocMatrixABuffer(); | |||
| if (!params_->b_const_) { | |||
| auto ret = InitBias(); | |||
| if (ret != RET_OK) { | |||
| MS_LOG(ERROR) << "Matmul fp32 malloc matrix a buffer failed"; | |||
| MS_LOG(ERROR) << "Matmul fp32 init bias failed"; | |||
| return RET_ERROR; | |||
| } | |||
| } | |||
| if (params_->b_const_ == false || params_->b_init_shape_ == false) { | |||
| if (b_pack_ptr_ != nullptr) { | |||
| free(b_pack_ptr_); | |||
| b_pack_ptr_ = nullptr; | |||
| } | |||
| auto ret = MallocMatrixBBuffer(); | |||
| if (ret != RET_OK) { | |||
| MS_LOG(ERROR) << "Matmul fp32 malloc matrix b buffer failed"; | |||
| return RET_ERROR; | |||
| } | |||
| } | |||
| if (bias_ptr_ != nullptr) { | |||
| free(bias_ptr_); | |||
| bias_ptr_ = nullptr; | |||
| } | |||
| auto ret = InitBias(); | |||
| if (ret != RET_OK) { | |||
| MS_LOG(ERROR) << "Matmul fp32 init bias failed"; | |||
| return RET_ERROR; | |||
| } | |||
| return RET_OK; | |||
| } | |||
| @@ -222,40 +217,31 @@ void MatmulCPUKernel::InitMatrixB(float *src_ptr, float *dst_ptr) { | |||
| } | |||
| int MatmulCPUKernel::Init() { | |||
| params_->a_init_shape_ = (in_tensors_[0]->shape().size() != 0); | |||
| params_->b_init_shape_ = (in_tensors_[1]->shape().size() != 0); | |||
| if (params_->a_init_shape_ == true) { | |||
| params_->a_const_ = (in_tensors_[0]->data_c() != nullptr); | |||
| params_->b_const_ = (in_tensors_[1]->data_c() != nullptr); | |||
| if (params_->a_const_) { | |||
| auto ret = MallocMatrixABuffer(); | |||
| if (ret != RET_OK) { | |||
| MS_LOG(ERROR) << "Matmul fp32 malloc matrix a buffer failed"; | |||
| MS_LOG(ERROR) << "Matmul fp32 malloc matrix A buffer failed"; | |||
| return RET_ERROR; | |||
| } | |||
| InitMatrixA(reinterpret_cast<float *>(in_tensors_[0]->data_c()), a_pack_ptr_); | |||
| a_ptr_ = a_pack_ptr_; | |||
| } | |||
| if (params_->b_init_shape_ == true) { | |||
| if (params_->b_const_) { | |||
| auto ret = MallocMatrixBBuffer(); | |||
| if (ret != RET_OK) { | |||
| MS_LOG(ERROR) << "Matmul fp32 malloc matrix b buffer failed"; | |||
| MS_LOG(ERROR) << "Matmul fp32 malloc matrix B buffer failed"; | |||
| return RET_ERROR; | |||
| } | |||
| } | |||
| params_->a_const_ = (in_tensors_[0]->data_c() != nullptr); | |||
| params_->b_const_ = (in_tensors_[1]->data_c() != nullptr); | |||
| if (params_->a_const_ == true) { | |||
| InitMatrixA(reinterpret_cast<float *>(in_tensors_[0]->data_c()), a_pack_ptr_); | |||
| a_ptr_ = a_pack_ptr_; | |||
| } | |||
| if (params_->b_const_ == true) { | |||
| InitMatrixB(reinterpret_cast<float *>(in_tensors_[1]->data_c()), b_pack_ptr_); | |||
| b_ptr_ = b_pack_ptr_; | |||
| } | |||
| if (!InferShapeDone()) { | |||
| return RET_OK; | |||
| } | |||
| auto ret = InitBias(); | |||
| if (ret != RET_OK) { | |||
| MS_LOG(ERROR) << "Matmul fp32 init bias failed"; | |||
| return RET_ERROR; | |||
| // init bias | |||
| ret = InitBias(); | |||
| if (ret != RET_OK) { | |||
| MS_LOG(ERROR) << "Matmul fp32 init bias failed"; | |||
| return RET_ERROR; | |||
| } | |||
| } | |||
| return RET_OK; | |||
| } | |||
| @@ -291,7 +277,16 @@ int MatmulCPUKernel::Run() { | |||
| auto b_src = reinterpret_cast<float *>(in_tensors_[1]->data_c()); | |||
| auto c_src = reinterpret_cast<float *>(out_tensors_[0]->data_c()); | |||
| if (params_->a_const_ == false || is_train()) { | |||
| if (!params_->a_const_ || is_train()) { | |||
| if (a_pack_ptr_ != nullptr) { | |||
| params_->a_const_ ? free(a_pack_ptr_) : context_->allocator->Free(a_pack_ptr_); | |||
| a_pack_ptr_ = nullptr; | |||
| } | |||
| auto ret = MallocMatrixABuffer(); | |||
| if (ret != RET_OK) { | |||
| MS_LOG(ERROR) << "Matmul fp32 malloc matrix a buffer failed"; | |||
| return RET_ERROR; | |||
| } | |||
| if (is_vector_a_) { | |||
| a_ptr_ = a_src; | |||
| } else { | |||
| @@ -299,7 +294,16 @@ int MatmulCPUKernel::Run() { | |||
| a_ptr_ = a_pack_ptr_; | |||
| } | |||
| } | |||
| if (params_->b_const_ == false || is_train()) { | |||
| if (!params_->b_const_ || is_train()) { | |||
| if (b_pack_ptr_ != nullptr) { | |||
| params_->b_const_ ? free(b_pack_ptr_) : context_->allocator->Free(b_pack_ptr_); | |||
| b_pack_ptr_ = nullptr; | |||
| } | |||
| auto ret = MallocMatrixBBuffer(); | |||
| if (ret != RET_OK) { | |||
| MS_LOG(ERROR) << "Matmul fp32 malloc matrix b buffer failed"; | |||
| return RET_ERROR; | |||
| } | |||
| if (is_vector_a_ && params_->b_transpose_) { | |||
| b_ptr_ = b_src; | |||
| } else { | |||
| @@ -318,7 +322,20 @@ int MatmulCPUKernel::Run() { | |||
| cur_b_ptr_ = b_ptr_ + i * params_->deep_ * params_->col_8_; | |||
| cur_c_ptr_ = c_src + i * params_->row_ * params_->col_; | |||
| } | |||
| ParallelLaunch(this->context_->thread_pool_, MatmulFloatRun, this, thread_count_); | |||
| auto ret = ParallelLaunch(this->context_->thread_pool_, MatmulFloatRun, this, thread_count_); | |||
| if (ret != RET_OK) { | |||
| MS_LOG(ERROR) << "Matmul fp32 run function MatmulFloatRun failed"; | |||
| FreeTmpBuffer(); | |||
| return RET_ERROR; | |||
| } | |||
| } | |||
| if (!params_->a_const_ || is_train()) { | |||
| context_->allocator->Free(a_pack_ptr_); | |||
| a_pack_ptr_ = nullptr; | |||
| } | |||
| if (!params_->b_const_ || is_train()) { | |||
| context_->allocator->Free(b_pack_ptr_); | |||
| b_pack_ptr_ = nullptr; | |||
| } | |||
| return RET_OK; | |||
| } | |||
| @@ -326,10 +343,10 @@ int MatmulCPUKernel::Run() { | |||
| void MatmulCPUKernel::eval() { | |||
| // Copy weights after training | |||
| LiteKernel::eval(); | |||
| if (params_->a_const_ == true) { | |||
| if (params_->a_const_) { | |||
| InitMatrixA(reinterpret_cast<float *>(in_tensors_[0]->MutableData()), a_pack_ptr_); | |||
| } | |||
| if (params_->b_const_ == true) { | |||
| if (params_->b_const_) { | |||
| InitMatrixB(reinterpret_cast<float *>(in_tensors_[1]->MutableData()), b_pack_ptr_); | |||
| } | |||
| } | |||