tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalDiagPlusVDVTTensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)

tf.nn.rnn_cell.RNNCell.output_size Integer or TensorShape: size of outputs produced by this cell.

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

tf.image.transpose_image(image) Transpose an image by swapping the first and second dimension. See also transpose(). Args: image: 3-D tensor of shape [height, width, channels] Returns: A 3-D tensor of shape [width, height, channels] Raises: ValueError: if the shape of image not supported.

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

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

tf.train.shuffle_batch_join(tensors_list, batch_size, capacity, min_after_dequeue, seed=None, enqueue_many=False, shapes=None, allow_smaller_final_batch=False, shared_name=None, name=None) Create batches by randomly shuffling tensors. The tensors_list argument is a list of tuples of tensors, or a list of dictionaries of tensors. Each element in the list is treated similarly to the tensors argument of tf.train.shuffle_batch(). This version enqueues a different list of tensors in different threa

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

tf.contrib.bayesflow.stochastic_tensor.ExponentialTensor.dtype

tf.TextLineReader.reset(name=None) Restore a reader to its initial clean state. Args: name: A name for the operation (optional). Returns: The created Operation.