taplib.utils Namespace Reference

Functions
def	ceildiv (a, b)
tuple[Sequence[int]|None, Sequence[int]|None]	validate_and_clean_sizes_strides (Sequence[int]|None sizes, Sequence[int]|None strides, bool allow_none=False, int|None expected_dims=None)
Sequence[int]	validate_tensor_dims (Sequence[int] tensor_dims, int|None expected_dims=None)
int	validate_offset (int offset, Sequence[int]|None tensor_dims)

Function Documentation

ceildiv()

def taplib.utils.ceildiv	(		a,
			b
	)

A helper function to calculate ceiling division without

Args:
    a (_type_): The dividend
    b (_type_): The devisor

Returns:
    _type_: The result

validate_and_clean_sizes_strides()

tuple[Sequence[int] | None, Sequence[int] | None] taplib.utils.validate_and_clean_sizes_strides	(	Sequence[int] | None	sizes,
		Sequence[int] | None	strides,
		bool	allow_none = False,
		int | None	expected_dims = None
	)

This is a helper function to validate sizes, strides and remove any
unused values from upper dimensions if possible.

Args:
    sizes (Sequence[int] | None): The transformation strides, or None
    strides (Sequence[int] | None): The transformation sizes, or None
    allow_none (bool, optional): Allow sizes and/or strides to be None. Defaults to False.
    expected_dims (int | None, optional): Number of dimensions expected for both sizes and strides. Defaults to None.

Raises:
    ValueError: Validate sizes and strides

Returns:
    tuple[Sequence[int] | None, Sequence[int] | None]: The 'cleaned' sizes and strides.

validate_offset()

int taplib.utils.validate_offset	(	int	offset,
		Sequence[int] | None	tensor_dims
	)

This is a helper function to validate an offset into the tensor.
It primarily checks to see if the offset is a valid index to the tensor.

Args:
    offset (int): The offset to check.
    tensor_dims (Sequence[int] | None): The dimensions of the tensor the offset corresponds to.

Raises:
    ValueError: Validate the offset.

Returns:
    int: The validated offset.

validate_tensor_dims()

Sequence[int] taplib.utils.validate_tensor_dims	(	Sequence[int]	tensor_dims,
		int | None	expected_dims = None
	)

This is a helper function used to validate dimensions of tensors, namely
be ensuring each dimension is > 0 and the dimensionality is as expected.

Args:
    tensor_dims (Sequence[int]): Tensor dimensions to check
    expected_dims (int | None, optional): Expected number of dimensions. Defaults to None.

Raises:
    ValueError: Validate the tensor dimensions

Returns:
    Sequence[int]: The validated tensor dimensions.