tf.contrib.metrics.streaming_precision(*args, **kwargs) Computes the precision of the predictions with respect to the labels.

tf.contrib.graph_editor.detach_outputs(sgv, control_outputs=None) Detach the outputa of a subgraph view.

tf.contrib.learn.LinearRegressor.get_params(deep=True) Get parameters for this estimator. Args:

tf.contrib.bayesflow.stochastic_tensor.WishartCholeskyTensor.distribution

tf.contrib.distributions.Dirichlet.log_pdf(value, name='log_pdf') Log probability density function. Args:

tf.contrib.distributions.Exponential.log_pmf(value, name='log_pmf') Log probability mass function. Args:

tf.scalar_mul(scalar, x) Multiplies a scalar times a Tensor or IndexedSlices object.

class tf.contrib.learn.monitors.PrintTensor Prints given tensors every N steps. This is an EveryN

tf.contrib.distributions.Beta.mode(name='mode') Mode. Additional documentation from Beta:

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