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https://github.com/saymrwulf/pytorch.git
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5ae3865112
Summary: (1) BlobsQueue is causing a gcc error (google search suggeste it was a bug, but we'll put the implementation in a separate cc file). (2) Preparing for cuda 9: update cub. (3) Prepare for cudnn 7: update cudnn rnn op. (4) Fix an MSVC issue Reviewed By: sf-wind, jerryzh168 Differential Revision: D5574352 fbshipit-source-id: 230820ce3ceaa32bee8323bdc509de352c93fcf2
67 lines
1.6 KiB
C++
67 lines
1.6 KiB
C++
#pragma once
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#include <atomic>
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#include <condition_variable>
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#include <memory>
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#include <mutex>
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#include <queue>
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#include "caffe2/core/blob_stats.h"
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#include "caffe2/core/logging.h"
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#include "caffe2/core/stats.h"
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#include "caffe2/core/tensor.h"
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#include "caffe2/core/workspace.h"
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namespace caffe2 {
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// A thread-safe, bounded, blocking queue.
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// Modelled as a circular buffer.
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// Containing blobs are owned by the workspace.
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// On read, we swap out the underlying data for the blob passed in for blobs
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class BlobsQueue : public std::enable_shared_from_this<BlobsQueue> {
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public:
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BlobsQueue(
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Workspace* ws,
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const std::string& queueName,
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size_t capacity,
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size_t numBlobs,
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bool enforceUniqueName,
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const std::vector<std::string>& fieldNames = {});
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~BlobsQueue() {
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close();
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}
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bool blockingRead(
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const std::vector<Blob*>& inputs,
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float timeout_secs = 0.0f);
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bool tryWrite(const std::vector<Blob*>& inputs);
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bool blockingWrite(const std::vector<Blob*>& inputs);
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void close();
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size_t getNumBlobs() const {
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return numBlobs_;
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}
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private:
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bool canWrite();
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void doWrite(const std::vector<Blob*>& inputs);
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std::atomic<bool> closing_{false};
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size_t numBlobs_;
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std::mutex mutex_; // protects all variables in the class.
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std::condition_variable cv_;
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int64_t reader_{0};
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int64_t writer_{0};
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std::vector<std::vector<Blob*>> queue_;
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struct QueueStats {
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CAFFE_STAT_CTOR(QueueStats);
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CAFFE_EXPORTED_STAT(queue_balance);
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CAFFE_EXPORTED_STAT(queue_dequeued_records);
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CAFFE_DETAILED_EXPORTED_STAT(queue_dequeued_bytes);
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} stats_;
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};
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} // namespace caffe2
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