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tfp.edward2.JointDistribution

Create a random variable for JointDistribution.

tfp.edward2.JointDistribution(
    *args,
    **kwargs
)

Defined in python/edward2/interceptor.py.

See JointDistribution for more details.

Returns:

RandomVariable.

Original Docstring for Distribution

Constructs the Distribution.

This is a private method for subclass use.

Args:

  • dtype: The type of the event samples. None implies no type-enforcement.
  • reparameterization_type: Instance of ReparameterizationType. If tfd.FULLY_REPARAMETERIZED, this Distribution can be reparameterized in terms of some standard distribution with a function whose Jacobian is constant for the support of the standard distribution. If tfd.NOT_REPARAMETERIZED, then no such reparameterization is available.
  • validate_args: Python bool, default False. When True distribution parameters are checked for validity despite possibly degrading runtime performance. When False invalid inputs may silently render incorrect outputs.
  • allow_nan_stats: Python bool, default True. When True, statistics (e.g., mean, mode, variance) use the value "NaN" to indicate the result is undefined. When False, an exception is raised if one or more of the statistic's batch members are undefined.
  • parameters: Python dict of parameters used to instantiate this Distribution.
  • graph_parents: Python list of graph prerequisites of this Distribution.
  • name: Python str name prefixed to Ops created by this class. Default: subclass name.

Raises:

  • ValueError: if any member of graph_parents is None or not a Tensor.