tf.nn.rnn_cell.MultiRNNCell.__call__(inputs, state, scope=None) Run this multi-layer cell on inputs, starting from state.

tf.contrib.distributions.Gamma.alpha Shape parameter.

tf.contrib.distributions.Bernoulli.is_continuous

tf.contrib.bayesflow.stochastic_tensor.BinomialTensor.dtype

tf.sparse_merge(sp_ids, sp_values, vocab_size, name=None, already_sorted=False) Combines a batch of feature ids and values into

tf.contrib.bayesflow.stochastic_tensor.BernoulliWithSigmoidPTensor.clone(name=None, **dist_args)

tf.ifft(input, name=None) Compute the inverse 1-dimensional discrete Fourier Transform over the inner-most

tf.contrib.bayesflow.stochastic_tensor.DirichletTensor.clone(name=None, **dist_args)

tf.contrib.bayesflow.stochastic_tensor.MixtureTensor.clone(name=None, **dist_args)

tf.contrib.bayesflow.stochastic_tensor.SampleValue.declare_inputs(unused_stochastic_tensor, unused_inputs_dict)