torch.backends
torch.backends controls the behavior of various backends that
PyTorch supports.
These backends include:


"torch.backends.cuda"


"torch.backends.cudnn"


"torch.backends.mps"


"torch.backends.mkl"


"torch.backends.mkldnn"


"torch.backends.openmp"


"torch.backends.opt_einsum"


"torch.backends.xeon"


torch.backends.cuda
torch.backends.cuda.is_built()
Returns whether PyTorch is built with CUDA support.  Note that this
   doesn't necessarily mean CUDA is available; just that if this
   PyTorch binary were run a machine with working CUDA drivers and
   devices, we would be able to use it.
torch.backends.cuda.matmul.allow_tf32
A "bool" that controls whether TensorFloat-32 tensor cores may be
   used in matrix multiplications on Ampere or newer GPUs. See
   TensorFloat-32(TF32) on Ampere devices.
torch.backends.cuda.matmul.allow_fp16_reduced_precision_reduction
A "bool" that controls whether reduced precision reductions (e.g.,