tf.contrib.distributions.Beta.__init__()

tf.contrib.distributions.Beta.__init__(a, b, validate_args=False, allow_nan_stats=True, name='Beta')

Initialize a batch of Beta distributions.

Args:

• a: Positive floating point tensor with shape broadcastable to [N1,..., Nm] m >= 0. Defines this as a batch of N1 x ... x Nm different Beta distributions. This also defines the dtype of the distribution.
• b: Positive floating point tensor with shape broadcastable to [N1,..., Nm] m >= 0. Defines this as a batch of N1 x ... x Nm different Beta distributions.
• validate_args: Boolean, default False. Whether to assert valid values for parameters a, b, and x in prob and log_prob. If False and inputs are invalid, correct behavior is not guaranteed.
• allow_nan_stats: Boolean, default True. If False, raise an exception if a statistic (e.g. mean/mode/etc...) is undefined for any batch member. If True, batch members with valid parameters leading to undefined statistics will return NaN for this statistic.

• name: The name to prefix Ops created by this distribution class.

• Examples:

# Define 1-batch.
dist = Beta(1.1, 2.0)

# Define a 2-batch.
dist = Beta([1.0, 2.0], [4.0, 5.0])