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

tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.is_reparameterized

StringPiece tensorflow::Tensor::tensor_data() const Returns a StringPiece mapping the current tensor's buffer. The returned StringPiece may point to memory location on devices that the CPU cannot address directly. NOTE: The underlying tensor buffer is refcounted, so the lifetime of the contents mapped by the StringPiece matches the lifetime of the buffer; callers should arrange to make sure the buffer does not get destroyed while the StringPiece is still used. REQUIRES: DataTypeCanUseMemcpy(dt

tf.contrib.bayesflow.stochastic_tensor.BinomialTensor.name

tf.contrib.learn.monitors.SummarySaver.end(session=None)

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

tf.contrib.distributions.Mixture.event_shape(name='event_shape') Shape of a single sample from a single batch as a 1-D int32 Tensor. Args: name: name to give to the op Returns: event_shape: Tensor.

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

tf.contrib.learn.monitors.BaseMonitor.__init__()

tf.contrib.bayesflow.stochastic_tensor.Chi2WithAbsDfTensor.clone(name=None, **dist_args)