tf.contrib.bayesflow.stochastic_tensor.BetaTensor.name

tf.contrib.distributions.BaseDistribution.sample_n(n, seed=None, name='sample') 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.

class tf.contrib.learn.monitors.StopAtStep Monitor to request stop at a specified step.

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

tf.contrib.distributions.Chi2WithAbsDf.parameters Dictionary of parameters used by this Distribution.

tf.contrib.bayesflow.stochastic_tensor.BaseStochasticTensor.name

tf.contrib.distributions.Normal.mu Distribution parameter for the mean.

tf.contrib.distributions.DirichletMultinomial.mode(name='mode') Mode.

tf.contrib.distributions.StudentT.name Name prepended to all ops created by this Distribution.

tf.errors.PermissionDeniedError.__init__(node_def, op, message) Creates a PermissionDeniedError.