log_prob(value)
  Scores the sample by inverting the transform(s) and computing
  the score using the score of the base distribution and the log
  abs det jacobian.

rsample(sample_shape=torch.Size([]))
  Generates a sample_shape shaped reparameterized sample or
  sample_shape shaped batch of reparameterized samples if the
  distribution parameters are batched. Samples first from base
  distribution and applies *transform()* for every transform in
  the list.

sample(sample_shape=torch.Size([]))
  Generates a sample_shape shaped sample or sample_shape shaped
  batch of samples if the distribution parameters are batched.
  Samples first from base distribution and applies *transform()*
  for every transform in the list.

property support
Uniform
class torch.distributions.uniform.Uniform(low, high, validate_args=None)
Bases: "Distribution"
Generates uniformly distributed random samples from the half-open
   interval "[low, high)".