forked from huawei/mindspore2022
87 lines
2.9 KiB
C++
87 lines
2.9 KiB
C++
/**
|
|
* Copyright 2021 Huawei Technologies Co., Ltd
|
|
*
|
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
|
* you may not use this file except in compliance with the License.
|
|
* You may obtain a copy of the License at
|
|
*
|
|
* http://www.apache.org/licenses/LICENSE-2.0
|
|
*
|
|
* Unless required by applicable law or agreed to in writing, software
|
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
* See the License for the specific language governing permissions and
|
|
* limitations under the License.
|
|
*/
|
|
|
|
#include "runtime/device/launch_mul.h"
|
|
|
|
#include <vector>
|
|
#include <memory>
|
|
#include "abstract/utils.h"
|
|
#include "backend/session/single_kernel_graph.h"
|
|
#include "frontend/parallel/context.h"
|
|
|
|
namespace mindspore::device {
|
|
std::shared_ptr<session::KernelGraph> LaunchMul::ObtainMulKernelGraph() {
|
|
std::vector<TypeId> input_dtypes = {dtype_, dtype_};
|
|
std::vector<TypeId> output_dtypes = {dtype_};
|
|
// obtain input & output shapes
|
|
size_t dtype_size = abstract::TypeIdSize(dtype_);
|
|
if (dtype_size == 0) {
|
|
MS_LOG(EXCEPTION) << "Divide by zero.";
|
|
}
|
|
int64_t shape = SizeToLong(total_size_ / dtype_size);
|
|
std::vector<std::vector<int64_t>> input_shapes = {{shape}, {1}};
|
|
std::vector<std::vector<size_t>> output_shapes = {{static_cast<size_t>(shape)}};
|
|
auto mul_graph = session::SingleKernelGraph::ConstructKernelGraphBasedOnSingleOp(
|
|
kMulOpName, input_dtypes, input_shapes, output_dtypes, output_shapes);
|
|
MS_EXCEPTION_IF_NULL(mul_graph);
|
|
return mul_graph;
|
|
}
|
|
|
|
kernel::KernelMod *LaunchMul::ObtainLaunchMulKernelMod() {
|
|
if (mul_graph_ == nullptr) {
|
|
// construct mul kernel graph
|
|
mul_graph_ = ObtainMulKernelGraph();
|
|
MS_EXCEPTION_IF_NULL(mul_graph_);
|
|
// kernel select
|
|
KernelSelect(mul_graph_);
|
|
// kernel build
|
|
KernelBuild(mul_graph_);
|
|
}
|
|
// obtain kernel_mod
|
|
if (mul_graph_->execution_order().size() != 1) {
|
|
MS_LOG(ERROR) << "the execution order of the mul graph should have only one node";
|
|
}
|
|
return AnfAlgo::GetKernelMod(mul_graph_->execution_order()[0]);
|
|
}
|
|
|
|
void LaunchMul::ObtainMulInputsAddr() {
|
|
inputs_addr_.push_back(input1_addr_);
|
|
|
|
auto parallel_context = parallel::ParallelContext::GetInstance();
|
|
MS_EXCEPTION_IF_NULL(parallel_context);
|
|
auto device_num = parallel_context->device_num();
|
|
if (device_num == 0) {
|
|
MS_LOG(ERROR) << "device num can't be zero";
|
|
}
|
|
input2_value_ = 1.0f / device_num;
|
|
auto size = abstract::TypeIdSize(dtype_);
|
|
auto input_size = AlignSizeForLaunchKernel(size * 1);
|
|
// alloc memory
|
|
input2_addr_ = AllocDeviceMem(input_size);
|
|
CopyHostMemToDevice(size, input_size);
|
|
inputs_addr_.push_back(input2_addr_);
|
|
}
|
|
|
|
void LaunchMul::FreeInputDeviceMemory() {
|
|
input1_addr_ = nullptr;
|
|
if (input2_addr_ != nullptr) {
|
|
FreeDeviceMem(input2_addr_);
|
|
input2_addr_ = nullptr;
|
|
}
|
|
inputs_addr_.clear();
|
|
}
|
|
} // namespace mindspore::device
|