Skip to main content

shim

Pytorch implementation of the tensor shim.

Classes​

PyTorchBackendTensorShim​

class PyTorchBackendTensorShim():

PyTorch backend shim/bridge for converting from/to PyTorch tensors.

Ancestors​

Variables​

Static methods​

clamp_params​

def clamp_params(    p: _TensorLike, prime_q: int, precision: int, num_workers: int,) ‑> bitfount.types._TensorLike:

Method for clipping params for secure sharing.

Constrains the parameters for secure sharing to be within the required range for secure sharing. Used only when steps_between_parameter_updates is 1.

Arguments

  • p: The tensor to be constrained.
  • prime_q: The prime use for secret aggregation.
  • precision: The precision used for secret aggregation.
  • num_workers: The number of workers taking part in the secure aggregation.

Returns The clamped parameters.

is_tensor​

def is_tensor(p: Any) ‑> bool:

See base class.

to_list​

def to_list(p: np.ndarray | _TensorLike) ‑> list[float]:

See base class.

to_numpy​

def to_numpy(t: _TensorLike | list[float]) ‑> numpy.ndarray:

See base class.

to_tensor​

def to_tensor(p: Sequence[Any], **kwargs: Any) ‑> bitfount.types._TensorLike:

See base class.