4、TORCH.CUDA

这个包增加了对 CUDA 张量类型的支持，它实现了与 CPU 张量相同的功能，但它们利用 GPU 进行计算。

它被延迟初始化，因此您可以随时导入它，并使用 is_available() 来确定您的系统是否支持 CUDA。CUDA 语义有更多关于使用 CUDA 的细节。

StreamContext	Context-manager that selects a given stream.
can_device_access_peer	Checks if peer access between two devices is possible.
current_blas_handle	Returns cublasHandle_t pointer to current cuBLAS handle
current_device	Returns the index of a currently selected device.
current_stream	Returns the currently selected Stream for a given device.
default_stream	Returns the default Stream for a given device.
device	Context-manager that changes the selected device.
device_count	Returns the number of GPUs available.
device_of	Context-manager that changes the current device to that of given object.
get_arch_list	Returns list CUDA architectures this library was compiled for.
get_device_capability	Gets the cuda capability of a device.
get_device_name	Gets the name of a device.
get_device_properties	Gets the properties of a device.
get_gencode_flags	Returns NVCC gencode flags this library was compiled with.
init	Initialize PyTorch’s CUDA state.
ipc_collect	Force collects GPU memory after it has been released by CUDA IPC.
is_available	Returns a bool indicating if CUDA is currently available.
is_initialized	Returns whether PyTorch’s CUDA state has been initialized.
set_device	Sets the current device.
set_stream	Sets the current stream.This is a wrapper API to set the stream.
stream	Wrapper around the Context-manager StreamContext that selects a given stream.
synchronize	Waits for all kernels in all streams on a CUDA device to complete.

Random Number Generator

get_rng_state	Returns the random number generator state of the specified GPU as a ByteTensor.
get_rng_state_all	Returns a list of ByteTensor representing the random number states of all devices.
set_rng_state	Sets the random number generator state of the specified GPU.
set_rng_state_all	Sets the random number generator state of all devices.
manual_seed	Sets the seed for generating random numbers for the current GPU.
manual_seed_all	Sets the seed for generating random numbers on all GPUs.
seed	Sets the seed for generating random numbers to a random number for the current GPU.
seed_all	Sets the seed for generating random numbers to a random number on all GPUs.
initial_seed	Returns the current random seed of the current GPU.

Communication collectives

comm.broadcast	Broadcasts a tensor to specified GPU devices.
comm.broadcast_coalesced	Broadcasts a sequence tensors to the specified GPUs.
comm.reduce_add	Sums tensors from multiple GPUs.
comm.scatter	Scatters tensor across multiple GPUs.
comm.gather	Gathers tensors from multiple GPU devices.

Streams and events

Stream	Wrapper around a CUDA stream.
Event	Wrapper around a CUDA event.

Memory management

empty_cache	Releases all unoccupied cached memory currently held by the caching allocator so that those can be used in other GPU application and visible in nvidia-smi.
list_gpu_processes	Returns a human-readable printout of the running processes and their GPU memory use for a given device.
memory_stats	Returns a dictionary of CUDA memory allocator statistics for a given device.
memory_summary	Returns a human-readable printout of the current memory allocator statistics for a given device.
memory_snapshot	Returns a snapshot of the CUDA memory allocator state across all devices.
memory_allocated	Returns the current GPU memory occupied by tensors in bytes for a given device.
max_memory_allocated	Returns the maximum GPU memory occupied by tensors in bytes for a given device.
reset_max_memory_allocated	Resets the starting point in tracking maximum GPU memory occupied by tensors for a given device.
memory_reserved	Returns the current GPU memory managed by the caching allocator in bytes for a given device.
max_memory_reserved	Returns the maximum GPU memory managed by the caching allocator in bytes for a given device.
set_per_process_memory_fraction	Set memory fraction for a process.
memory_cached	Deprecated; see memory_reserved().
max_memory_cached	Deprecated; see max_memory_reserved().
reset_max_memory_cached	Resets the starting point in tracking maximum GPU memory managed by the caching allocator for a given device.
reset_peak_memory_stats	Resets the “peak” stats tracked by the CUDA memory allocator.

NVIDIA Tools Extension (NVTX)

nvtx.mark	Describe an instantaneous event that occurred at some point.
nvtx.range_push	Pushes a range onto a stack of nested range span.
nvtx.range_pop	Pops a range off of a stack of nested range spans.