tf.contrib.bayesflow.stochastic_tensor.UniformTensor.dtype

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalCholeskyTensor.entropy(name='entropy')

tf.contrib.layers.batch_norm(*args, **kwargs) Adds a Batch Normalization layer from http://arxiv.org/abs/1502.03167. "Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift" Sergey Ioffe, Christian Szegedy Can be used as a normalizer function for conv2d and fully_connected. Note: When is_training is True the moving_mean and moving_variance need to be updated, by default the update_ops are placed in tf.GraphKeys.UPDATE_OPS so they need to be added as a depe

tf.contrib.rnn.LSTMBlockCell.output_size

tf.contrib.learn.DNNClassifier.evaluate(x=None, y=None, input_fn=None, feed_fn=None, batch_size=None, steps=None, metrics=None, name=None) See evaluable.Evaluable.

tf.contrib.rnn.LSTMBlockCell.state_size

tf.contrib.rnn.LSTMBlockCell.__call__(x, states_prev, scope=None) Long short-term memory cell (LSTM).

tf.contrib.bayesflow.stochastic_tensor.BinomialTensor.entropy(name='entropy')

tf.contrib.distributions.WishartFull.log_normalizing_constant(name='log_normalizing_constant') Computes the log normalizing constant, log(Z).

tf.errors.UnauthenticatedError.__init__(node_def, op, message) Creates an UnauthenticatedError.