tf.contrib.framework.model_variable(*args, **kwargs) Gets an existing model variable with these parameters or creates a new one

tf.contrib.graph_editor.Transformer.__call__(sgv, dst_graph, dst_scope, src_scope='', reuse_dst_scope=False) Execute the transformation

tf.cholesky(input, name=None) Computes the Cholesky decomposition of one or more square matrices. The

tf.contrib.learn.monitors.GraphDump.set_estimator(estimator) A setter called automatically by the target estimator.

tf.contrib.distributions.Uniform.mean(name='mean') Mean.

tf.contrib.distributions.BernoulliWithSigmoidP.entropy(name='entropy') Shanon entropy in nats.

tf.contrib.layers.summarize_tensor(tensor, tag=None) Summarize a tensor using a suitable summary type. This

class tf.contrib.bayesflow.stochastic_tensor.QuantizedDistributionTensor QuantizedDistributionTensor is a

tf.transpose(a, perm=None, name='transpose') Transposes a. Permutes the dimensions according to perm

tf.contrib.learn.TensorFlowRNNRegressor.partial_fit(x, y) Incremental fit on a batch of samples. This