forked from mindspore-Ecosystem/mindspore
Add Size() and Capacity() in gpu queue.
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cc23f1d819
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@ -49,7 +49,7 @@ class DatasetInitKernel : public GpuKernel {
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std::vector<size_t> workspace_size_list_;
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// The capacity of buffer Q.
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size_t buffer_q_capacity_{2};
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size_t buffer_q_capacity_{1};
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};
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MS_REG_GPU_KERNEL(InitDataSetQueue, DatasetInitKernel)
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@ -22,7 +22,15 @@
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namespace mindspore {
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namespace device {
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GpuQueue::GpuQueue(void *addr, const std::vector<size_t> &shape, const size_t &capacity)
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: buffer_(addr), head_(0), tail_(0), shape_(shape), len_(0), capacity_(capacity), stream_(0), node_info_(nullptr) {
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: buffer_(addr),
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head_(0),
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tail_(0),
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shape_(shape),
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len_(0),
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size_(0),
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capacity_(capacity),
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stream_(0),
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node_info_(nullptr) {
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CHECK_CUDA_RET_WITH_ERROR(cudaStreamCreate(&stream_), "Cuda Create Stream Failed");
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node_info_ = std::make_unique<NodeInfo[]>(capacity);
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for (auto item : shape) {
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@ -52,6 +60,7 @@ BlockQueueStatus_T GpuQueue::Push(const std::vector<DataItemGpu> &data) {
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CHECK_CUDA_RET_WITH_ERROR(cudaEventCreate(&(*(node_info_[tail_].event_))), "Cuda Create Event Failed");
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node_info_[tail_].data_ = data;
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tail_ = (tail_ + 1) % (capacity_);
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++size_;
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return SUCCESS;
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}
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@ -69,6 +78,7 @@ BlockQueueStatus_T GpuQueue::Front(void **addr, size_t *len) const {
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BlockQueueStatus_T GpuQueue::Pop() {
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head_ = (head_ + 1) % (capacity_);
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--size_;
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return SUCCESS;
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}
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@ -44,13 +44,15 @@ class GpuQueue {
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void RegisterRelease(const std::function<void(void *)> &func) { host_release_ = func; }
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inline bool IsEmpty() const { return head_ == tail_; }
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inline bool IsFull() const { return head_ == ((tail_ + 1) % (capacity_)); }
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inline bool IsEmpty() const { return size_ == 0; }
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inline bool IsFull() const { return size_ == capacity_; }
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BlockQueueStatus_T Push(const std::vector<DataItemGpu> &data);
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BlockQueueStatus_T Front(void **ptr, size_t *len) const;
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BlockQueueStatus_T Pop();
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bool Destroy();
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size_t Size() { return size_; }
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size_t Capacity() { return capacity_; }
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private:
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struct NodeInfo {
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@ -63,6 +65,7 @@ class GpuQueue {
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size_t tail_;
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std::vector<size_t> shape_;
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size_t len_;
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size_t size_;
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size_t capacity_;
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cudaStream_t stream_;
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std::unique_ptr<NodeInfo[]> node_info_;
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@ -83,6 +86,8 @@ class BlockingQueue {
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BlockQueueStatus_T Front(void **ptr, size_t *len);
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BlockQueueStatus_T Pop();
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bool Destroy();
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size_t Size() { return queue_->Size(); }
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size_t Capacity() { return queue_->Capacity(); }
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private:
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std::mutex mutex_;
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@ -187,5 +187,39 @@ bool GpuBufferMgr::CloseNotify() {
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}
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void GpuBufferMgr::CloseConfirm() { sema.Signal(); }
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size_t GpuBufferMgr::Size(unsigned int handle) {
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if (handle == HandleMgr::INVALID_HANDLE) {
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MS_LOG(ERROR) << "handle is invalid";
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return 0;
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}
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return handle_queue_map_.at(handle)->Size();
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}
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size_t GpuBufferMgr::Size(unsigned int device_id, const std::string &channel_name) {
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std::string name = std::to_string(device_id) + std::string("_") + channel_name;
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if (!name_queue_map_.count(name)) {
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MS_LOG(ERROR) << "Queue not exist " << name;
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return 0;
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}
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return name_queue_map_.at(name)->Size();
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}
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size_t GpuBufferMgr::Capacity(unsigned int handle) {
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if (handle == HandleMgr::INVALID_HANDLE) {
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MS_LOG(ERROR) << "handle is invalid";
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return 0;
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}
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return handle_queue_map_.at(handle)->Capacity();
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}
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size_t GpuBufferMgr::Capacity(unsigned int device_id, const std::string &channel_name) {
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std::string name = std::to_string(device_id) + std::string("_") + channel_name;
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if (!name_queue_map_.count(name)) {
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MS_LOG(ERROR) << "Queue not exist " << name;
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return 0;
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}
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return name_queue_map_.at(name)->Capacity();
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}
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} // namespace device
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} // namespace mindspore
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@ -111,6 +111,14 @@ class GpuBufferMgr {
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// call for dataset send thread
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EXPORT void CloseConfirm();
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EXPORT size_t Size(unsigned int handle);
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EXPORT size_t Size(unsigned int device_id, const std::string &channel_name);
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EXPORT size_t Capacity(unsigned int handle);
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EXPORT size_t Capacity(unsigned int device_id, const std::string &channel_name);
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private:
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void set_device() const;
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