tf.contrib.bayesflow.stochastic_tensor.BernoulliTensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)

tf.contrib.distributions.Chi2.get_event_shape() Shape of a single sample from a single batch as a TensorShape. Same meaning as event_shape. May be only partially defined. Returns: event_shape: TensorShape, possibly unknown.

tf.contrib.distributions.Gamma.mode(name='mode') Mode. Additional documentation from Gamma: The mode of a gamma distribution is (alpha - 1) / beta when alpha > 1, and NaN otherwise. If self.allow_nan_stats is False, an exception will be raised rather than returning NaN.

tf.contrib.bayesflow.stochastic_tensor.TransformedDistributionTensor.value(name='value')

tf.contrib.distributions.Binomial.sample_n(n, seed=None, name='sample_n') Generate n samples. Args: n: Scalar Tensor of type int32 or int64, the number of observations to sample. seed: Python integer seed for RNG name: name to give to the op. Returns: samples: a Tensor with a prepended dimension (n,). Raises: TypeError: if n is not an integer type.

tf.Session.close() Closes this session. Calling this method frees all resources associated with the session. Raises: tf.errors.OpError: Or one of its subclasses if an error occurs while closing the TensorFlow session.

tf.contrib.distributions.MultivariateNormalFull.log_sigma_det(name='log_sigma_det') Log of determinant of covariance matrix.

tf.contrib.distributions.MultivariateNormalFull.param_shapes(cls, sample_shape, name='DistributionParamShapes') Shapes of parameters given the desired shape of a call to sample(). Subclasses should override static method _param_shapes. Args: sample_shape: Tensor or python list/tuple. Desired shape of a call to sample(). name: name to prepend ops with. Returns: dict of parameter name to Tensor shapes.

tf.contrib.graph_editor.SubGraphView.remap_outputs_make_unique() Remap the outputs so that all the tensors appears only once.

tf.contrib.framework.local_variable(initial_value, validate_shape=True, name=None) Create variable and add it to GraphKeys.LOCAL_VARIABLES collection. Args: initial_value: See variables.Variable.__init__. validate_shape: See variables.Variable.__init__. name: See variables.Variable.__init__. Returns: New variable.