tf.contrib.distributions.Uniform.range(name='range') b - a.

tf.contrib.bayesflow.stochastic_tensor.NormalWithSoftplusSigmaTensor.name

tf.contrib.rnn.GRUBlockCell.__init__(cell_size) Initialize the Block GRU cell. Args: cell_size: int, GRU cell size.

tf.contrib.learn.monitors.PrintTensor.every_n_post_step(step, session) Callback after a step is finished or end() is called. Args: step: int, the current value of the global step. session: Session object.

tf.neg(x, name=None) Computes numerical negative value element-wise. I.e., (y = -x). Args: x: A Tensor or SparseTensor. Must be one of the following types: half, float32, float64, int32, int64, complex64, complex128. name: A name for the operation (optional). Returns: A Tensor or SparseTensor, respectively. Has the same type as x.

tf.contrib.learn.monitors.SummarySaver.post_step(step, session)

tf.contrib.graph_editor.SubGraphView.remap_outputs_to_consumers() Remap the outputs to match the number of consumers.

tf.OpError.__str__()

tf.contrib.bayesflow.stochastic_tensor.BernoulliTensor.distribution

tf.contrib.bayesflow.stochastic_tensor.ExponentialTensor.loss(final_loss, name='Loss')