mindspore-ci-bot
4 years ago
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Gitee
commit
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "backend/kernel_compiler/gpu/nn/ctclossv2_gpu_kernel.h"
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namespace mindspore {
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namespace kernel {
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MS_REG_GPU_KERNEL_ONE(CTCLossV2,
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KernelAttr()
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.AddInputAttr(kNumberTypeFloat32)
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.AddInputAttr(kNumberTypeInt32)
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.AddInputAttr(kNumberTypeInt32)
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.AddInputAttr(kNumberTypeInt32)
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.AddOutputAttr(kNumberTypeFloat32)
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.AddOutputAttr(kNumberTypeFloat32),
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CtcLossV2GpuKernel, float)
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} // namespace kernel
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} // namespace mindspore
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@ -1,192 +0,0 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_NN_CTCLOSS_GPU_KERNEL_H_
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#define MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_NN_CTCLOSS_GPU_KERNEL_H_
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#include <cuda_runtime_api.h>
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#include <vector>
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#include "backend/kernel_compiler/gpu/gpu_kernel.h"
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#include "backend/kernel_compiler/gpu/gpu_kernel_factory.h"
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#include "runtime/device/gpu/gpu_memory_allocator.h"
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namespace mindspore {
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namespace kernel {
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template <typename T>
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class CtcLossV2GpuKernel : public GpuKernel {
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public:
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CtcLossV2GpuKernel()
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: cudnn_handle_(nullptr),
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probs_desc_(nullptr),
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ctcloss_desc_(nullptr),
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label_size_(0),
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input_lengths_size_(0),
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label_lengths_size_(0) {}
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~CtcLossV2GpuKernel() override { DestroyResource(); }
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const std::vector<size_t> &GetInputSizeList() const override { return input_size_list_; }
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const std::vector<size_t> &GetOutputSizeList() const override { return output_size_list_; }
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const std::vector<size_t> &GetWorkspaceSizeList() const override { return workspace_size_list_; }
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bool Launch(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &,
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const std::vector<AddressPtr> &outputs, void *stream_ptr) override {
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float *probs = GetDeviceAddress<float>(inputs, 0);
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float *costs = GetDeviceAddress<float>(outputs, 0);
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float *grads = GetDeviceAddress<float>(outputs, 1);
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// Copy labels/input_lengths/label_length to host as cudnn7.x.x requires
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int *labels_host = nullptr;
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int *no_blank_labels_host = nullptr;
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void *input_lengths_host = nullptr;
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void *label_lengths_host = nullptr;
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cudaStream_t stream = reinterpret_cast<cudaStream_t>(stream_ptr);
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AllocHostMem(&labels_host, &no_blank_labels_host, &input_lengths_host, &label_lengths_host, inputs);
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CopyToHostSync(labels_host, no_blank_labels_host, input_lengths_host, label_lengths_host, inputs, stream);
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size_t workspace_size = 0;
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CHECK_CUDNN_RET_WITH_EXCEPT(
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cudnnGetCTCLossWorkspaceSize(
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cudnn_handle_, probs_desc_, probs_desc_, reinterpret_cast<int *>(no_blank_labels_host),
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reinterpret_cast<int *>(label_lengths_host), reinterpret_cast<int *>(input_lengths_host),
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CUDNN_CTC_LOSS_ALGO_DETERMINISTIC, ctcloss_desc_, &workspace_size),
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"cudnnGetCTCLossWorkspaceSize failed.");
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void *workspace = device::gpu::GPUMemoryAllocator::GetInstance().AllocTensorMem(workspace_size);
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if (workspace == nullptr) {
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MS_LOG(EXCEPTION) << "Failed to alloc workspace, size: " << workspace_size;
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}
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CHECK_CUDNN_RET_WITH_EXCEPT(
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cudnnCTCLoss(cudnn_handle_, probs_desc_, probs, reinterpret_cast<int *>(no_blank_labels_host),
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reinterpret_cast<int *>(label_lengths_host), reinterpret_cast<int *>(input_lengths_host), costs,
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probs_desc_, grads, CUDNN_CTC_LOSS_ALGO_DETERMINISTIC, ctcloss_desc_, workspace, workspace_size),
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"cudnnCtcLoss failed.");
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CHECK_CUDA_RET_WITH_EXCEPT(cudaStreamSynchronize(stream), "cudaStreamSynchronize failed.");
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device::gpu::GPUMemoryAllocator::GetInstance().FreeTensorMem(workspace);
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FreeHostMem(labels_host, no_blank_labels_host, input_lengths_host, label_lengths_host);
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return true;
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}
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bool Init(const CNodePtr &kernel_node) override {
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InitResource();
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auto probs_shape = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0);
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if (probs_shape.size() != 3) {
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MS_LOG(EXCEPTION) << "probs dims: " << probs_shape.size() << " not support.";
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}
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probs_dims_[0] = probs_shape[0];
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probs_dims_[1] = probs_shape[1];
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probs_dims_[2] = probs_shape[2];
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auto labels_dims = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 1);
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if (labels_dims.size() != 1 && labels_dims.size() != 2) {
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MS_LOG(EXCEPTION) << "labels dims: " << labels_dims.size() << " not support.";
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}
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label_size_ = sizeof(int);
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for (auto i : labels_dims) {
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label_size_ *= i;
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}
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auto input_length_dims = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 2);
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input_lengths_size_ = input_length_dims[0] * sizeof(int);
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auto label_length_dims = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 3);
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label_lengths_size_ = label_length_dims[0] * sizeof(int);
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CHECK_CUDNN_RET_WITH_EXCEPT(
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cudnnSetTensorNdDescriptorEx(probs_desc_, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, 3, probs_dims_),
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"cudnnSetTensorNdDescriptorEx failed.");
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CHECK_CUDNN_RET_WITH_EXCEPT(cudnnSetCTCLossDescriptorEx(ctcloss_desc_, CUDNN_DATA_FLOAT,
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CUDNN_LOSS_NORMALIZATION_SOFTMAX, CUDNN_PROPAGATE_NAN),
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"cudnnSetCTCLossDescriptorEx failed.");
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InitSizeLists();
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return true;
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}
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protected:
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void InitResource() override {
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cudnn_handle_ = device::gpu::GPUDeviceManager::GetInstance().GetCudnnHandle();
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CHECK_CUDNN_RET_WITH_EXCEPT(cudnnCreateTensorDescriptor(&probs_desc_), "cudnnCreateTensorDescriptor failed.");
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CHECK_CUDNN_RET_WITH_EXCEPT(cudnnCreateCTCLossDescriptor(&ctcloss_desc_), "cudnnCreateCTCLossDescriptor failed.");
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}
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void InitSizeLists() override {
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input_size_list_.push_back(probs_dims_[0] * probs_dims_[1] * probs_dims_[2] * sizeof(float));
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input_size_list_.push_back(label_size_);
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input_size_list_.push_back(input_lengths_size_);
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input_size_list_.push_back(label_lengths_size_);
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output_size_list_.push_back(probs_dims_[1] * sizeof(float));
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output_size_list_.push_back(probs_dims_[0] * probs_dims_[1] * probs_dims_[2] * sizeof(float));
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}
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private:
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void DestroyResource() noexcept {
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CHECK_CUDNN_RET_WITH_ERROR(cudnnDestroyCTCLossDescriptor(ctcloss_desc_), "cudnnDestroyCTCLossDescriptor failed.");
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CHECK_CUDNN_RET_WITH_ERROR(cudnnDestroyTensorDescriptor(probs_desc_), "cudnnDestroyTensorDescriptor failed.");
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}
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void AllocHostMem(int **labels_host, int **no_blank_labels_host, void **input_lengths_host, void **label_lengths_host,
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const std::vector<AddressPtr> &inputs) {
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CHECK_CUDA_RET_WITH_EXCEPT(cudaMallocHost(labels_host, inputs[1]->size), "cudaMallocHost failed.");
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CHECK_CUDA_RET_WITH_EXCEPT(cudaMallocHost(no_blank_labels_host, inputs[1]->size), "cudaMallocHost failed.");
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CHECK_CUDA_RET_WITH_EXCEPT(cudaMallocHost(input_lengths_host, inputs[2]->size), "cudaMallocHost failed.");
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CHECK_CUDA_RET_WITH_EXCEPT(cudaMallocHost(label_lengths_host, inputs[3]->size), "cudaMallocHost failed.");
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}
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void FreeHostMem(int *labels_host, int *no_blank_labels_host, void *input_lengths_host, void *label_lengths_host) {
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CHECK_CUDA_RET_WITH_EXCEPT(cudaFreeHost(label_lengths_host), "cudaFreeHost failed.");
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CHECK_CUDA_RET_WITH_EXCEPT(cudaFreeHost(input_lengths_host), "cudaFreeHost failed.");
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CHECK_CUDA_RET_WITH_EXCEPT(cudaFreeHost(labels_host), "cudaFreeHost failed.");
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CHECK_CUDA_RET_WITH_EXCEPT(cudaFreeHost(no_blank_labels_host), "cudaFreeHost failed.");
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}
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void CopyToHostSync(int *labels_host, int *no_blank_labels_host, void *input_lengths_host, void *label_lengths_host,
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const std::vector<AddressPtr> &inputs, cudaStream_t stream) {
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CHECK_CUDA_RET_WITH_EXCEPT(cudaStreamSynchronize(stream), "cudaStreamSynchronize failed.");
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CHECK_CUDA_RET_WITH_EXCEPT(
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cudaMemcpyAsync(labels_host, inputs[1]->addr, inputs[1]->size, cudaMemcpyDeviceToHost, stream),
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"cudaMemcpyAsync failed.");
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CHECK_CUDA_RET_WITH_EXCEPT(
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cudaMemcpyAsync(input_lengths_host, inputs[2]->addr, inputs[2]->size, cudaMemcpyDeviceToHost, stream),
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"cudaMemcpyAsync failed.");
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CHECK_CUDA_RET_WITH_EXCEPT(
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cudaMemcpyAsync(label_lengths_host, inputs[3]->addr, inputs[3]->size, cudaMemcpyDeviceToHost, stream),
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"cudaMemcpyAsync failed.");
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CHECK_CUDA_RET_WITH_EXCEPT(cudaStreamSynchronize(stream), "cudaStreamSynchronize failed.");
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// remove blank element
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size_t j = 0;
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for (size_t i = 0; i < inputs[1]->size / sizeof(int); i++) {
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if (labels_host[i] != 0) {
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no_blank_labels_host[j] = labels_host[i];
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j++;
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}
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}
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}
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std::vector<size_t> input_size_list_;
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std::vector<size_t> output_size_list_;
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std::vector<size_t> workspace_size_list_;
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cudnnHandle_t cudnn_handle_;
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cudnnTensorDescriptor_t probs_desc_;
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cudnnCTCLossDescriptor_t ctcloss_desc_;
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int probs_dims_[3] = {0};
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int label_size_;
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int input_lengths_size_;
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int label_lengths_size_;
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};
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} // namespace kernel
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} // namespace mindspore
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#endif // MINDSPORE_CCSRC_BACKEND_KERNEL_COMPILER_GPU_NN_CTCLOSS_GPU_KERNEL_H_
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