Crate tch

Modules

• data
  Dataset iterators.
• display
• 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.
• utils
• vision
  The vision module groups functions and models related to computer vision.

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. Note that it is important to bind this to a name like “guard” and not to “” as these two would have different semantics. See https://internals.rust-lang.org/t/pre-rfc-must-bind/12658/46 for more details.
• 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.