tf.contrib.learn.monitors.EveryN.every_n_step_begin(step) Callback before every n'th step begins. Args: step: int, the current value of the global step. Returns: A list of tensors that will be evaluated at this step.

tf.contrib.distributions.LaplaceWithSoftplusScale.mean(name='mean') Mean.

Status tensorflow::Env::IsDirectory(const string &fname) Returns whether the given path is a directory or not. Typical return codes (not guaranteed exhaustive): OK - The path exists and is a directory. FAILED_PRECONDITION - The path exists and is not a directory. NOT_FOUND - The path entry does not exist. PERMISSION_DENIED - Insufficient permissions. UNIMPLEMENTED - The file factory doesn't support directories.

TTypes<T>::ConstMatrix tensorflow::Tensor::matrix() const

class tf.contrib.bayesflow.stochastic_tensor.BetaTensor BetaTensor is a StochasticTensor backed by the distribution Beta.

tf.contrib.learn.monitors.NanLoss.run_on_all_workers

tf.contrib.bayesflow.stochastic_tensor.Chi2WithAbsDfTensor.input_dict

tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.dtype The DType of Tensors handled by this Distribution.

tf.contrib.distributions.InverseGamma.mean(name='mean') Mean. Additional documentation from InverseGamma: The mean of an inverse gamma distribution is beta / (alpha - 1), when alpha > 1, and NaN otherwise. If self.allow_nan_stats is False, an exception will be raised rather than returning NaN

tf.contrib.distributions.Binomial.is_reparameterized