tf.contrib.distributions.WishartCholesky.event_shape(name='event_shape') Shape of a single sample from a single batch as a 1-D int32 Tensor. Args: name: name to give to the op Returns: event_shape: Tensor.

tf.contrib.distributions.Chi2.pmf(value, name='pmf') Probability mass function. Args: value: float or double Tensor. name: The name to give this op. Returns: pmf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if is_continuous.

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalFullTensor.clone(name=None, **dist_args)

tf.contrib.learn.LinearRegressor.__repr__()

tf.contrib.learn.monitors.ExportMonitor.run_on_all_workers

tf.contrib.bayesflow.stochastic_tensor.TransformedDistributionTensor.graph

tf.contrib.graph_editor.reroute_a2b(sgv0, sgv1) Re-route the inputs and outputs of sgv0 to sgv1 (see _reroute).

tf.nn.rnn_cell.EmbeddingWrapper.state_size

tf.ReaderBase.supports_serialize Whether the Reader implementation can serialize its state.

class tf.contrib.distributions.Binomial Binomial distribution. This distribution is parameterized by a vector p of probabilities and n, the total counts.