tf.contrib.bayesflow.stochastic_tensor.UniformTensor.graph

tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.pmf(value, name='pmf') Probability mass function. Args: value: float or double Tensor. name: The name to give this op. Returns: pmf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if is_continuous.

tf.contrib.distributions.LaplaceWithSoftplusScale.name Name prepended to all ops created by this Distribution.

tf.contrib.learn.DNNClassifier.export(export_dir, input_fn=None, input_feature_key=None, use_deprecated_input_fn=True, signature_fn=None, default_batch_size=1, exports_to_keep=None) See BaseEstimator.export.

tf.contrib.distributions.Normal.is_continuous

tf.TFRecordReader.reader_ref Op that implements the reader.

tf.contrib.distributions.WishartFull.scale_operator_pd Wishart distribution scale matrix as an OperatorPD.

tf.contrib.distributions.WishartFull.pmf(value, name='pmf') Probability mass function. Args: value: float or double Tensor. name: The name to give this op. Returns: pmf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if is_continuous.

tf.contrib.distributions.MultivariateNormalCholesky.pmf(value, name='pmf') Probability mass function. Args: value: float or double Tensor. name: The name to give this op. Returns: pmf: a Tensor of shape sample_shape(x) + self.batch_shape with values of type self.dtype. Raises: TypeError: if is_continuous.

tf.contrib.distributions.Beta.variance(name='variance') Variance.