concat_softmax

ConcatSoftmax

Bases: torch.nn.Module

Applies softmax to the concatenation of a list of tensors.

Source code in pytorch_adapt\layers\concat_softmax.py

class ConcatSoftmax(torch.nn.Module):
    """
    Applies softmax to the concatenation of a list of tensors.
    """

    def __init__(self, dim: int = 1):
        """
        Arguments:
            dim: a dimension along which softmax will be computed
        """
        super().__init__()
        self.dim = dim

    def forward(self, *x: torch.Tensor):
        """
        Arguments:
            *x: A sequence of tensors to be concatenated
        """
        all_logits = torch.cat(x, dim=self.dim)
        return torch.nn.functional.softmax(all_logits, dim=self.dim)

    def extra_repr(self):
        """"""
        return c_f.extra_repr(self, ["dim"])

__init__(dim=1)

Parameters:

Name	Type	Description	Default
dim	int	a dimension along which softmax will be computed	1

Source code in pytorch_adapt\layers\concat_softmax.py

def __init__(self, dim: int = 1):
    """
    Arguments:
        dim: a dimension along which softmax will be computed
    """
    super().__init__()
    self.dim = dim

forward(*x)

Parameters:

Name	Type	Description	Default
*x	torch.Tensor	A sequence of tensors to be concatenated	()

Source code in pytorch_adapt\layers\concat_softmax.py

def forward(self, *x: torch.Tensor):
    """
    Arguments:
        *x: A sequence of tensors to be concatenated
    """
    all_logits = torch.cat(x, dim=self.dim)
    return torch.nn.functional.softmax(all_logits, dim=self.dim)