tf.contrib.bayesflow.stochastic_tensor.BernoulliWithSigmoidPTensor.value_type

tf.contrib.distributions.Distribution.pdf(value, name='pdf') Probability density function. Args:

tf.contrib.learn.monitors.CaptureVariable.epoch_begin(epoch) Begin epoch. Args:

tf.contrib.distributions.Laplace.sample(sample_shape=(), seed=None, name='sample') Generate samples of the specified shape.

tf.contrib.distributions.MultivariateNormalCholesky.log_pdf(value, name='log_pdf') Log probability density function.

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

tf.contrib.distributions.Categorical.get_batch_shape() Shape of a single sample from a single event index as a TensorShape

tf.matrix_diag(diagonal, name=None) Returns a batched diagonal tensor with a given batched diagonal values.

tf.contrib.learn.monitors.StopAtStep.run_on_all_workers

tf.edit_distance(hypothesis, truth, normalize=True, name='edit_distance') Computes the Levenshtein distance between sequences