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Tensor operations with mask for PyTorch.

Project description

torchmasked

Tensor operations with mask for PyTorch.

Sometimes you need to perform operations on tensors with the masked elements been ignored, for example:

>>> input = torch.tensor([1., 2., 3.])
>>> result = torch.sum(input)
>>> print(result)

tensor(6.)

>>> mask = torch.tensor([1, 1, 0]).byte()
>>> masked_result = torchmasked.masked_sum(input, mask)
>>> print(masked_result)

tensor(3.)  # element input[2] is masked and ignored

Then this package could be helpful.

 

Installation

From source:

pip install git+https://github.com/Renovamen/torchmasked.git --upgrade

# or

python setup.py install

 

Supported Operations

  • max (masked version of torch.max)
  • min (torch.min)
  • sum (torch.sum)
  • mean (torch.mean)
  • softmax (torch.nn.functional.softmax and torch.nn.Softmax)

 

License

MIT

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