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# torch.nn.functional.log_softmax

torch.nn.functional.log_softmax(input, dim=None, _stacklevel=3, dtype=None)

  Applies a softmax followed by a logarithm.

  While mathematically equivalent to log(softmax(x)), doing these two operations separately is slower and numerically unstable. This function uses an alternative formulation to compute the output and gradient correctly.

  See `LogSoftmax` for more details.

  Parameters:

    - input (Tensor) – input

    - dim (int) – A dimension along which log_softmax will be computed.

    - dtype (`torch.dtype`, optional) – the desired data type of returned tensor. If specified, the input tensor is cast to `dtype` before the operation is performed. This is useful for preventing data type overflows. Default: None.

  Return type:

    Tensor

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