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

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.pdf(value, name='pdf') Probability density function.

tf.as_string(input, precision=None, scientific=None, shortest=None, width=None, fill=None, name=None) Converts each entry in the

tf.contrib.crf.crf_log_norm(inputs, sequence_lengths, transition_params) Computes the normalization for a CRF.

tf.contrib.bayesflow.stochastic_tensor.WishartFullTensor.input_dict

tf.contrib.learn.TensorFlowRNNRegressor.partial_fit(x, y) Incremental fit on a batch of samples. This

tf.contrib.distributions.Distribution.survival_function(value, name='survival_function') Survival function.

class tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma StudentT with df = floor(abs(df)) and sigma =

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalCholeskyTensor.name

tf.contrib.distributions.Gamma.prob(value, name='prob') Probability density/mass function (depending on is_continuous)