Crate tch[−][src]
Modules
data | Dataset iterators. |
index | Indexing operations |
jit | JIT interface to run model trained/saved using PyTorch Python API. |
kind | The different kind of elements supported in Torch. |
nn | A small neural-network library based on Torch. |
vision | The |
Structs
CModule | A jit PyTorch module. |
COptimizer | |
NewAxis | |
NoGradGuard | A RAII guard that prevents gradient tracking until deallocated. |
Scalar | A single scalar value. |
Tensor | A tensor object. |
TrainableCModule | The trainable version of a jit PyTorch module. |
Enums
Cuda | Cuda related helper functions. |
Device | A torch device. |
IValue | Argument and output values for JIT models. |
Kind | The different kind of elements that a Tensor can hold. |
QEngine | Quantization engines |
Reduction | |
TchError | Main library error type. |
TensorIndexer |
Traits
IndexOp | |
Shape |
Functions
autocast | Runs a closure in mixed precision. |
get_num_interop_threads | Get the number of threads used by torch for inter-op parallelism. |
get_num_threads | Get the number of threads used by torch in parallel regions. |
manual_seed | Sets the random seed used by torch. |
maybe_init_cuda | |
no_grad | Runs a closure without keeping track of gradients. |
no_grad_guard | Disables gradient tracking, this will be enabled back when the returned value gets deallocated. |
set_num_interop_threads | Set the number of threads used by torch for inter-op parallelism. |
set_num_threads | Set the number of threads used by torch in parallel regions. |
with_grad | Runs a closure explicitly keeping track of gradients, this could be run within a no_grad closure for example. |