Class CUDAStream#
Defined in File CUDAStream.h
Page Contents
Class Documentation#
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class CUDAStream#
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Public Functions
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inline explicit CUDAStream(Stream stream)#
Construct a CUDAStream from a Stream.
This construction is checked, and will raise an error if the Stream is not, in fact, a CUDA stream.
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inline explicit CUDAStream(Unchecked, Stream stream)#
Construct a CUDAStream from a Stream with no error checking.
This constructor uses the “named” constructor idiom, and can be invoked as: CUDAStream(CUDAStream::UNCHECKED, stream)
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inline bool operator==(const CUDAStream &other) const noexcept#
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inline bool operator!=(const CUDAStream &other) const noexcept#
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inline operator cudaStream_t() const#
Implicit conversion to cudaStream_t.
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inline operator Stream() const#
Implicit conversion to Stream (a.k.a., forget that the stream is a CUDA stream).
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inline DeviceType device_type() const#
Used to avoid baking in device type explicitly to Python-side API.
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inline DeviceIndex device_index() const#
Get the CUDA device index that this stream is associated with.
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inline Device device() const#
Get the full Device that this stream is associated with.
The Device is guaranteed to be a CUDA device.
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inline StreamId id() const#
Return the stream ID corresponding to this particular stream.
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inline bool query() const#
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inline void synchronize() const#
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inline int priority() const#
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cudaStream_t stream() const#
Explicit conversion to cudaStream_t.
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inline Stream unwrap() const#
Explicit conversion to Stream.
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inline struct c10::StreamData3 pack3() const#
Reversibly pack a CUDAStream into a struct representation.
Previously the stream’s data was packed into a single int64_t, as it was assumed the fields would not require more than 64 bits of storage in total. See pytorch/pytorch#75854 for more information regarding newer platforms that may violate this assumption.
The CUDAStream can be unpacked using unpack().
Public Static Functions
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static inline CUDAStream unpack3(StreamId stream_id, DeviceIndex device_index, DeviceType device_type)#
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static inline std::tuple<int, int> priority_range()#
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inline explicit CUDAStream(Stream stream)#