tf.contrib.learn.monitors.CaptureVariable.every_n_post_step(step, session) Callback after a step is finished or end()

tf.contrib.distributions.Bernoulli.validate_args Python boolean indicated possibly expensive checks are enabled.

tf.contrib.distributions.Poisson.event_shape(name='event_shape') Shape of a single sample from a single batch as a 1-D int32 Tensor

tf.IdentityReader.__init__(name=None) Create a IdentityReader. Args:

tf.contrib.distributions.Poisson.get_event_shape() Shape of a single sample from a single batch as a TensorShape

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

tf.sub(x, y, name=None) Returns x - y element-wise. NOTE: Sub supports broadcasting

tf.contrib.distributions.Chi2.dtype The DType of Tensors handled by this Distribution.

tf.contrib.learn.TensorFlowRNNRegressor.fit(x, y, steps=None, monitors=None, logdir=None) Neural network model from provided

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