def entropy(self, name='entropy'):
    'The entropy of Gamma distribution(s).\n\n    This is defined to be\n\n    ```\n    entropy = alpha - log(beta) + log(Gamma(alpha))\n                 + (1-alpha)digamma(alpha)\n    ```\n\n    where digamma(alpha) is the digamma function.\n\n    Args:\n      name: The name to give this op.\n\n    Returns:\n      entropy: tensor of dtype `dtype`, the entropy.\n    '
    with ops.name_scope(self.name):
        with ops.name_scope(name, values=[self.alpha, self._beta]):
            alpha = self._alpha
            beta = self._beta
            return (((alpha - math_ops.log(beta)) + math_ops.lgamma(alpha)) + ((1 - alpha) * math_ops.digamma(alpha)))
The entropy of Gamma distribution(s).

This is defined to be

```
entropy = alpha - log(beta) + log(Gamma(alpha))
             + (1-alpha)digamma(alpha)
```

where digamma(alpha) is the digamma function.

Args:
  name: The name to give this op.

Returns:
  entropy: tensor of dtype `dtype`, the entropy.
def entropy(self, name='entropy'):
    'The entropy of Gamma distribution(s).\n\n    This is defined to be\n\n    ```\n    entropy = alpha - log(beta) + log(Gamma(alpha))\n                 + (1-alpha)digamma(alpha)\n    ```\n\n    where digamma(alpha) is the digamma function.\n\n    Args:\n      name: The name to give this op.\n\n    Returns:\n      entropy: tensor of dtype `dtype`, the entropy.\n    '
    with ops.name_scope(self.name):
        with ops.name_scope(name, values=[self.alpha, self._beta]):
            alpha = self._alpha
            beta = self._beta
            return (((alpha - math_ops.log(beta)) + math_ops.lgamma(alpha)) + ((1 - alpha) * math_ops.digamma(alpha)))