clipppy.stochastic.infinite

Module Contents

class clipppy.stochastic.infinite.InfiniteUniform(batch_shape=torch.Size(), event_shape=torch.Size(), validate_args=None)

A uniform distribution over all real numbers.

Sampling and log_prob always return zeros.

property arg_constraints(self)

Returns a dictionary from argument names to Constraint objects that should be satisfied by each argument of this distribution. Args that are not tensors need not appear in this dict.

log_prob(self, value)

Returns the log of the probability density/mass function evaluated at value.

Args:

value (Tensor):

rsample(self, 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.

support(self)

Returns a Constraint object representing this distribution’s support.

class clipppy.stochastic.infinite.SemiInfiniteUniform(batch_shape=torch.Size(), event_shape=torch.Size(), validate_args=None)

A uniform distribution over all real numbers.

Sampling and log_prob always return zeros.

log_prob(self, value)

Returns the log of the probability density/mass function evaluated at value.

Args:

value (Tensor):

support(self)

Returns a Constraint object representing this distribution’s support.