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Disallow scalar parameters in Dirichlet and Categorical #11589

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Disallow scalar parameters in Dirichlet and Categorical #11589

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59f8a07
Check correct shape for Dirichlet parameters
neerajprad Sep 12, 2018
b72c37d
address comments
neerajprad Sep 12, 2018
45e314d
address comments
neerajprad Sep 12, 2018
2cb3003
raise error early.
neerajprad Sep 13, 2018
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4 changes: 4 additions & 0 deletions torch/distributions/categorical.py
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Expand Up @@ -45,8 +45,12 @@ def __init__(self, probs=None, logits=None, validate_args=None):
if (probs is None) == (logits is None):
raise ValueError("Either `probs` or `logits` must be specified, but not both.")
if probs is not None:
if probs.dim() < 1:
raise ValueError("`probs` parameter must be at least one-dimensional.")
self.probs = probs / probs.sum(-1, keepdim=True)
else:
if logits.dim() < 1:
raise ValueError("`logits` parameter must be at least one-dimensional.")
self.logits = logits - logits.logsumexp(dim=-1, keepdim=True)
self._param = self.probs if probs is not None else self.logits
self._num_events = self._param.size()[-1]
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4 changes: 3 additions & 1 deletion torch/distributions/dirichlet.py
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Expand Up @@ -54,7 +54,9 @@ class Dirichlet(ExponentialFamily):
has_rsample = True

def __init__(self, concentration, validate_args=None):
self.concentration, = broadcast_all(concentration)
if concentration.dim() < 1:
raise ValueError("`concentration` parameter must be at least one-dimensional.")
self.concentration = concentration
batch_shape, event_shape = concentration.shape[:-1], concentration.shape[-1:]
super(Dirichlet, self).__init__(batch_shape, event_shape, validate_args=validate_args)

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