input.
  \digamma(x) = \frac{d}{dx} \ln\left(\Gamma\left(x\right)\right)
  = \frac{\Gamma'(x)}{\Gamma(x)}

Parameters:
      input (Tensor) -- the tensor to compute the digamma
      function on
Keyword Arguments:
      out (Tensor, optional) -- the output tensor.
Note:
 This function is similar to SciPy's *scipy.special.digamma*.

Note:
 From PyTorch 1.8 onwards, the digamma function returns *-Inf* for
 *0*. Previously it returned *NaN* for *0*.

Example:
  >>> a = torch.tensor([1, 0.5])
  >>> torch.special.digamma(a)
  tensor([-0.5772, -1.9635])

torch.special.entr(input, *, out=None) -> Tensor
Computes the entropy on "input" (as defined below), elementwise.
  \begin{align} \text{entr(x)} = \begin{cases}     -x * \ln(x)  &
  x > 0 \\     0 &  x = 0.0 \\     -\infty & x < 0 \end{cases}
  \end{align}

Parameters:
      input (Tensor) -- the input tensor.
Keyword Arguments: