tf.sparse_tensor_dense_matmul(sp_a, b, adjoint_a=False, adjoint_b=False, name=None) Multiply SparseTensor (of rank 2) "A" by dense

tf.contrib.distributions.Uniform.std(name='std') Standard deviation.

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

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

tf.contrib.distributions.DirichletMultinomial.log_cdf(value, name='log_cdf') Log cumulative distribution function.

tf.contrib.training.NextQueuedSequenceBatch.total_length The lengths of the original (non-truncated) unrolled examples.

tf.contrib.learn.monitors.RunHookAdapterForMonitors.after_run(run_context, run_values)

tf.contrib.distributions.MultivariateNormalDiag.parameters Dictionary of parameters used by this Distribution.

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

tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.std(name='std') Standard deviation.