class tf.contrib.distributions.BaseDistribution Simple abstract base class for probability distributions. Implementations of core distributions to be included in the distributions module should subclass Distribution. This base class may be useful to users that want to fulfill a simpler distribution contract.

tf.errors.AbortedError.__init__(node_def, op, message) Creates an AbortedError.

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

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

tf.contrib.distributions.Normal.validate_args Python boolean indicated possibly expensive checks are enabled.

tf.contrib.bayesflow.stochastic_tensor.LaplaceWithSoftplusScaleTensor.mean(name='mean')

tf.contrib.distributions.Exponential.log_prob(value, name='log_prob') Log probability density/mass function (depending on is_continuous). Args: value: float or double Tensor. name: The name to give this op. Returns: log_prob: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype.

A file abstraction for sequential writing. The implementation must provide buffering since callers may append small fragments at a time to the file. Member Details tensorflow::WritableFile::WritableFile() tensorflow::WritableFile::~WritableFile() virtual Status tensorflow::WritableFile::Append(const StringPiece &data)=0 virtual Status tensorflow::WritableFile::Close()=0 virtual Status tensorflow::WritableFile::Flush()=0 virtual Status tensorflow::WritableFile::Sync()=0

tf.contrib.distributions.Beta.a Shape parameter.

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