tf.contrib.distributions.WishartCholesky.sample(sample_shape=(), seed=None, name='sample') Generate samples of the specified shape. Note that a call to sample() without arguments will generate a single sample. Args: sample_shape: 0D or 1D int32 Tensor. Shape of the generated samples. seed: Python integer seed for RNG name: name to give to the op. Returns: samples: a Tensor with prepended dimensions sample_shape.

tf.contrib.bayesflow.stochastic_tensor.WishartCholeskyTensor.value_type

tf.ReaderBase.__init__(reader_ref, supports_serialize=False) Creates a new ReaderBase. Args: reader_ref: The operation that implements the reader. supports_serialize: True if the reader implementation can serialize its state.

tf.ReaderBase.reset(name=None) Restore a reader to its initial clean state. Args: name: A name for the operation (optional). Returns: The created Operation.

tf.contrib.learn.monitors.PrintTensor.begin(max_steps=None) Called at the beginning of training. When called, the default graph is the one we are executing. Args: max_steps: int, the maximum global step this training will run until. Raises: ValueError: if we've already begun a run.

tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.is_continuous

tf.contrib.graph_editor.SubGraphView.output_index(t) Find the output index corresponding to given output tensor t. Args: t: the output tensor of this subgraph view. Returns: The index in the self.outputs list. Raises: Error: if t in not an output tensor.

tf.contrib.distributions.MultivariateNormalDiag.get_batch_shape() Shape of a single sample from a single event index as a TensorShape. Same meaning as batch_shape. May be only partially defined. Returns: batch_shape: TensorShape, possibly unknown.

tf.contrib.distributions.Laplace.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.bayesflow.stochastic_tensor.QuantizedDistributionTensor.distribution