class tf.contrib.bayesflow.stochastic_tensor.WishartFullTensor WishartFullTensor is a StochasticTensor backed by the distribution WishartFull.

tf.contrib.graph_editor.SubGraphView.__copy__() Create a copy of this subgraph. Note that this class is a "view", copying it only create another view and does not copy the underlying part of the tf.Graph. Returns: A new identical instance of the original subgraph view.

tf.parse_tensor(serialized, out_type, name=None) Transforms a serialized tensorflow.TensorProto proto into a Tensor. Args: serialized: A Tensor of type string. A scalar string containing a serialized TensorProto proto. out_type: A tf.DType. The type of the serialized tensor. The provided type must match the type of the serialized tensor and no implicit conversion will take place. name: A name for the operation (optional). Returns: A Tensor of type out_type. A Tensor of type out_type.

class tf.contrib.learn.LinearRegressor Linear regressor model. Train a linear regression model to predict target variable value given observation of feature values. Example: education = sparse_column_with_hash_bucket(column_name="education", hash_bucket_size=1000) occupation = sparse_column_with_hash_bucket(column_name="occupation", hash_bucket_size=1000) education_x_occupation = crossed_column(columns=[edu

tf.contrib.distributions.Normal.sigma Distribution parameter for standard deviation.

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagWithSoftplusStDevTensor.dtype

tf.contrib.distributions.TransformedDistribution.batch_shape(name='batch_shape') Shape of a single sample from a single event index as a 1-D Tensor. The product of the dimensions of the batch_shape is the number of independent distributions of this kind the instance represents. Args: name: name to give to the op Returns: batch_shape: Tensor.

tf.contrib.distributions.TransformedDistribution.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.bayesflow.stochastic_tensor.GammaTensor.dtype

tf.contrib.learn.monitors.StepCounter.every_n_post_step(step, session) Callback after a step is finished or end() is called. Args: step: int, the current value of the global step. session: Session object.