tf.contrib.distributions.DirichletMultinomial.allow_nan_stats Python boolean describing behavior when a stat is undefined. Stats return +/- infinity when it makes sense. E.g., the variance of a Cauchy distribution is infinity. However, sometimes the statistic is undefined, e.g., if a distribution's pdf does not achieve a maximum within the support of the distribution, the mode is undefined. If the mean is undefined, then by definition the variance is undefined. E.g. the mean for Student's T fo

tf.sparse_reshape(sp_input, shape, name=None) Reshapes a SparseTensor to represent values in a new dense shape. This operation has the same semantics as reshape on the represented dense tensor. The indices of non-empty values in sp_input are recomputed based on the new dense shape, and a new SparseTensor is returned containing the new indices and new shape. The order of non-empty values in sp_input is unchanged. If one component of shape is the special value -1, the size of that dimension is c

tf.contrib.learn.TensorFlowRNNClassifier.__repr__()

tf.contrib.bayesflow.stochastic_tensor.BetaTensor.clone(name=None, **dist_args)

tf.contrib.distributions.Dirichlet.entropy(name='entropy') Shanon entropy in nats.

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

class tf.errors.PermissionDeniedError Raised when the caller does not have permission to run an operation. For example, running the tf.WholeFileReader.read() operation could raise PermissionDeniedError if it receives the name of a file for which the user does not have the read file permission.

tf.contrib.learn.monitors.NanLoss.__init__(loss_tensor, every_n_steps=100, fail_on_nan_loss=True) Initializes NanLoss monitor. Args: loss_tensor: Tensor, the loss tensor. every_n_steps: int, run check every this many steps. fail_on_nan_loss: bool, whether to raise exception when loss is NaN.

int64 tensorflow::TensorShapeDim::size

tf.contrib.distributions.WishartFull.is_reparameterized