pose_format.torch.masked.tensor module

Classes:

MaskedTensor(tensor[, mask])

Container for a PyTorch tensor, providing utility functions for tensor masking.

class pose_format.torch.masked.tensor.MaskedTensor(tensor, mask=None)[source]

Bases: object

Container for a PyTorch tensor, providing utility functions for tensor masking.

Parameters:

tensor (torch.Tensor) – Tensor data.
mask (torch.Tensor, optional) – A boolean mask tensor of the same shape as tensor. If specified, elements of tensor corresponding to True values in the mask are considered valid. Defaults to a tensor of all True values.

Methods:

`arithmetic`(action, other)	Helper method to perform arithmetic operations on tensors.
`cuda`([device, non_blocking])	Moves tensor to the GPU.
`div`(other[, in_place, update_mask])	Performs element-wise division with another tensor.
`fix_nan`()	Replaces any NaN values in the tensor with zeros.
`matmul`(matrix)	Perform matrix multiplication.
`permute`(dims)	Permute dimensions of tensor.
`pow_`(exponent)	Raises tensor to power of a given exponent in-place.
`rename`(*names)	Rename tensor's dimensions.
`reshape`(shape)	Reshape tensor to given shape.
`size`(*args)	Get size of tensor for specified dimensions.
`split`(split_size_or_sections[, dim])	Split tensor into multiple tensors.
`squeeze`(dim)	Squeeze tensor along chosen dimension.
`sum`(dim)	Sums along a specified dimension.
`to`(device)	Moves tensor to a custom device.
`transpose`(dim0, dim1)	Transposes tensor along two dimensions.
`zero_filled`()	Get tensor with masked values set to zero.

arithmetic(action, other)[source]

Helper method to perform arithmetic operations on tensors.

Parameters:

action (str) – The arithmetic operation to be performed.
other (Union[MaskedTensor`, torch.Tensor, float, int]) – The second operand.

Returns:

New MaskedTensor after the operation.

Return type:

MaskedTensor

cuda(device=None, non_blocking=False)[source]

Moves tensor to the GPU.

Parameters:

device (str or torch.device, optional) – The target CUDA device.
non_blocking (bool, optional) – Whether to perform an operation asynchronously. Default is False.

Returns:

Tensor on CUDA device.

Return type:

MaskedTensor

div(other, in_place=False, update_mask=True)[source]

Performs element-wise division with another tensor.

Parameters:

other (MaskedTensor) – The tensor to divide with.
in_place (bool, optional) – If True, performs the operation in-place. Default is False.
update_mask (bool, optional) – If True, updates the mask after division. Default is True.

Returns:

Resultant tensor after division.

Return type:

MaskedTensor

fix_nan()[source]

Replaces any NaN values in the tensor with zeros.

Returns:: Tensor with NaN values replaced by zeros.
Return type:: MaskedTensor

matmul(matrix)[source]

Perform matrix multiplication.

Parameters:: matrix (torch.Tensor) – matrix to multiply with.
Returns:: New masked tensor after multiplication.
Return type:: MaskedTensor

permute(dims)[source]

Permute dimensions of tensor.

Parameters:: dims (tuple) – Desired ordering of dimensions.
Returns:: Permuted masked tensor.
Return type:: MaskedTensor

pow_(exponent)[source]

Raises tensor to power of a given exponent in-place.

Parameters:: exponent (float) – The exponent value.
Returns:: Masked tensor raised to a given exponent.
Return type:: MaskedTensor

rename(*names)[source]

Rename tensor’s dimensions.

Parameters:: names (tuple) – Desired names for each dimension.
Returns:: Renamed masked tensor.
Return type:: MaskedTensor

reshape(shape)[source]

Reshape tensor to given shape.

Parameters:: shape (tuple) – Desired shape.
Returns:: Reshaped tensor.
Return type:: MaskedTensor

size(*args)[source]

Get size of tensor for specified dimensions.

Returns:: Size of tensor.
Return type:: torch.Size

split(split_size_or_sections, dim=0)[source]

Split tensor into multiple tensors.

Parameters:

split_size_or_sections (int or tuple) – Size or sections to split tensor.
dim (int, optional) – Dimension along which to split tensor. Default is 0.

Returns:

List of split tensors.

Return type:

list[MaskedTensor]

squeeze(dim)[source]

Squeeze tensor along chosen dimension.

Parameters:: dim (int) – Dimension to squeeze.
Returns:: Squeezed masked tensor.
Return type:: MaskedTensor

sum(dim)[source]

Sums along a specified dimension.

Parameters:: dim (int) – dimension to sum over.
Returns:: Summed tensor along the specified dimension.
Return type:: MaskedTensor

to(device)[source]

Moves tensor to a custom device.

Parameters:: device (str or torch.device) – The target device.
Returns:: Tensor on the other device.
Return type:: MaskedTensor

transpose(dim0, dim1)[source]

Transposes tensor along two dimensions.

Parameters:

dim0 (int) – Two dimensions to which to transpose.
dim1 (int) – Two dimensions to which to transpose.

Returns:

Transposed masked tensor.

Return type:

MaskedTensor

zero_filled()[source]

Get tensor with masked values set to zero.

Returns:: Tensor with masked values set to zero.
Return type:: torch.Tensor