tf.contrib.bayesflow.stochastic_tensor.WishartCholeskyTensor.dtype

tf.contrib.framework.create_global_step(graph=None) Create global step tensor in graph. Args:

tf.nn.rnn_cell.BasicLSTMCell.zero_state(batch_size, dtype) Return zero-filled state tensor(s). Args:

tf.contrib.learn.monitors.PrintTensor.epoch_end(epoch) End epoch. Args:

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

tf.contrib.learn.monitors.SummarySaver.every_n_step_begin(step)

tf.contrib.bayesflow.stochastic_tensor.ExponentialTensor.distribution

tf.contrib.bayesflow.stochastic_tensor.MeanValue.popped_above(unused_value_type)

tf.nn.rnn_cell.LSTMStateTuple.__new__(_cls, c, h) Create new instance of LSTMStateTuple(c, h)

tf.contrib.distributions.Exponential.param_static_shapes(cls, sample_shape) param_shapes with static (i.e. TensorShape) shapes