tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.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.distributions.Bernoulli.std(name='std') Standard deviation.

tf.contrib.distributions.MultivariateNormalDiag.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.contrib.bayesflow.stochastic_tensor.CategoricalTensor.input_dict

tf.contrib.distributions.Mixture.pdf(value, name='pdf') Probability density function. Args: value: float or double Tensor. name: The name to give this op. Returns: prob: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if not is_continuous.

tf.contrib.framework.get_variables_by_name(given_name, scope=None) Gets the list of variables that were given that name. Args: given_name: name given to the variable without any scope. scope: an optional scope for filtering the variables to return. Returns: a copied list of variables with the given name and scope.

tf.contrib.framework.get_local_variables(scope=None, suffix=None) Gets the list of model variables, filtered by scope and/or suffix. Args: scope: an optional scope for filtering the variables to return. suffix: an optional suffix for filtering the variables to return. Returns: a list of variables in collection with scope and suffix.

class tf.errors.AbortedError The operation was aborted, typically due to a concurrent action. For example, running a queue.enqueue() operation may raise AbortedError if a queue.close() operation previously ran.

tf.contrib.bayesflow.stochastic_tensor.InverseGammaWithSoftplusAlphaBetaTensor.graph

tf.contrib.distributions.MultivariateNormalFull.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.