class tf.contrib.distributions.MultivariateNormalDiagPlusVDVT The multivariate normal distribution on R^k. Every batch member of this distribution is defined by a mean and a lightweight covariance matrix C.

tf.contrib.distributions.StudentT.cdf(value, name='cdf') Cumulative distribution function. Given random variable X, the cumulative distribution function cdf is: cdf(x) := P[X <= x] Args: value: float or double Tensor. name: The name to give this op. Returns: cdf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype.

tf.contrib.bayesflow.stochastic_tensor.TransformedDistributionTensor.input_dict

class tf.python_io.TFRecordWriter A class to write records to a TFRecords file. This class implements __enter__ and __exit__, and can be used in with blocks like a normal file.

tf.contrib.distributions.InverseGamma.param_static_shapes(cls, sample_shape) param_shapes with static (i.e. TensorShape) shapes. Args: sample_shape: TensorShape or python list/tuple. Desired shape of a call to sample(). Returns: dict of parameter name to TensorShape. Raises: ValueError: if sample_shape is a TensorShape and is not fully defined.