| #pragma once | |
| #include <atomic> | |
| #include <condition_variable> | |
| #include <memory> | |
| #include <mutex> | |
| #include <queue> | |
| #include "caffe2/core/blob_stats.h" | |
| #include "caffe2/core/logging.h" | |
| #include "caffe2/core/stats.h" | |
| #include "caffe2/core/tensor.h" | |
| #include "caffe2/core/workspace.h" | |
| namespace caffe2 { | |
| // A thread-safe, bounded, blocking queue. | |
| // Modelled as a circular buffer. | |
| // Containing blobs are owned by the workspace. | |
| // On read, we swap out the underlying data for the blob passed in for blobs | |
| class CAFFE2_API BlobsQueue : public std::enable_shared_from_this<BlobsQueue> { | |
| public: | |
| BlobsQueue( | |
| Workspace* ws, | |
| const std::string& queueName, | |
| size_t capacity, | |
| size_t numBlobs, | |
| bool enforceUniqueName, | |
| const std::vector<std::string>& fieldNames = {}); | |
| ~BlobsQueue() { | |
| close(); | |
| } | |
| bool blockingRead( | |
| const std::vector<Blob*>& inputs, | |
| float timeout_secs = 0.0f); | |
| bool tryWrite(const std::vector<Blob*>& inputs); | |
| bool blockingWrite(const std::vector<Blob*>& inputs); | |
| void close(); | |
| size_t getNumBlobs() const { | |
| return numBlobs_; | |
| } | |
| private: | |
| bool canWrite(); | |
| void doWrite(const std::vector<Blob*>& inputs); | |
| std::atomic<bool> closing_{false}; | |
| size_t numBlobs_; | |
| std::mutex mutex_; // protects all variables in the class. | |
| std::condition_variable cv_; | |
| int64_t reader_{0}; | |
| int64_t writer_{0}; | |
| std::vector<std::vector<Blob*>> queue_; | |
| const std::string name_; | |
| struct QueueStats { | |
| CAFFE_STAT_CTOR(QueueStats); | |
| CAFFE_EXPORTED_STAT(queue_balance); | |
| CAFFE_EXPORTED_STAT(queue_dequeued_records); | |
| CAFFE_DETAILED_EXPORTED_STAT(queue_dequeued_bytes); | |
| CAFFE_AVG_EXPORTED_STAT(read_time_ns); | |
| CAFFE_AVG_EXPORTED_STAT(write_time_ns); | |
| } stats_; | |
| }; | |
| } // namespace caffe2 |