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tfp.edward2.DirichletMultinomial

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Create a random variable for DirichletMultinomial.

Aliases:

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

See DirichletMultinomial for more details.

Returns:

RandomVariable.

Original Docstring for Distribution

Initialize a batch of DirichletMultinomial distributions.

Args:

total_count: Non-negative integer-valued tensor, whose dtype is the same as concentration. The shape is broadcastable to [N1,..., Nm] with m >= 0. Defines this as a batch of N1 x ... x Nm different Dirichlet multinomial distributions. Its components should be equal to integer values. concentration: Positive floating point tensor with shape broadcastable to [N1,..., Nm, K] m >= 0. Defines this as a batch of N1 x ... x Nm different K class Dirichlet multinomial distributions. 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, 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.
  • name: Python str name prefixed to Ops created by this class.