tf.SparseTensor.graph The Graph that contains the index, value, and shape tensors.

tf.contrib.distributions.InverseGamma.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.

tf.contrib.distributions.Mixture.log_cdf(value, name='log_cdf') Log cumulative distribution function. Given random variable X, the cumulative distribution function cdf is: log_cdf(x) := Log[ P[X <= x] ] Often, a numerical approximation can be used for log_cdf(x) that yields a more accurate answer than simply taking the logarithm of the cdf when x << -1. Args: value: float or double Tensor. name: The name to give this op. Returns: logcdf: a Tensor of shape sample_shape(x) + self.

tf.TFRecordReader.serialize_state(name=None) Produce a string tensor that encodes the state of a reader. Not all Readers support being serialized, so this can produce an Unimplemented error. Args: name: A name for the operation (optional). Returns: A string Tensor.

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

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

string tensorflow::TensorShape::DebugString() const For error messages.

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

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagTensor.input_dict

tf.contrib.distributions.Categorical.allow_nan_stats Python boolean describing behavior when a stat is undefined. Stats return +/- infinity when it makes sense. E.g., the variance of a Cauchy distribution is infinity. However, sometimes the statistic is undefined, e.g., if a distribution's pdf does not achieve a maximum within the support of the distribution, the mode is undefined. If the mean is undefined, then by definition the variance is undefined. E.g. the mean for Student's T for df = 1