class tf.VarLenFeature Configuration for parsing a variable-length input feature. Fields: dtype: Data type of input.

TTypes< T, NDIMS >::UnalignedConstTensor tensorflow::Tensor::unaligned_shaped(gtl::ArraySlice< int64 > new_sizes) const

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

class tf.contrib.distributions.Categorical Categorical distribution. The categorical distribution is parameterized by the log-probabilities of a set of classes.

tf.contrib.bayesflow.stochastic_tensor.InverseGammaTensor.entropy(name='entropy')

class tf.errors.UnimplementedError Raised when an operation has not been implemented. Some operations may raise this error when passed otherwise-valid arguments that it does not currently support. For example, running the tf.nn.max_pool() operation would raise this error if pooling was requested on the batch dimension, because this is not yet supported.

virtual Status tensorflow::Session::Close(const RunOptions &run_options)

tf.contrib.bayesflow.stochastic_tensor.SampleAndReshapeValue.stop_gradient

tf.contrib.bayesflow.stochastic_tensor.PoissonTensor.entropy(name='entropy')

tf.contrib.distributions.Distribution.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.