tf.ceil(x, name=None) Returns element-wise smallest integer in not less than x. Args: x: A Tensor. Must be one of the following types: half, float32, float64. name: A name for the operation (optional). Returns: A Tensor. Has the same type as x.

tf.random_crop(value, size, seed=None, name=None) Randomly crops a tensor to a given size. Slices a shape size portion out of value at a uniformly chosen offset. Requires value.shape >= size. If a dimension should not be cropped, pass the full size of that dimension. For example, RGB images can be cropped with size = [crop_height, crop_width, 3]. Args: value: Input tensor to crop. size: 1-D tensor with size the rank of value. seed: Python integer. Used to create a random seed. See set_ra

tf.contrib.learn.DNNRegressor.__repr__()

tf.TextLineReader.num_work_units_completed(name=None) Returns the number of work units this reader has finished processing. Args: name: A name for the operation (optional). Returns: An int64 Tensor.

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

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

tf.contrib.learn.monitors.CaptureVariable.set_estimator(estimator) A setter called automatically by the target estimator. If the estimator is locked, this method does nothing. Args: estimator: the estimator that this monitor monitors. Raises: ValueError: if the estimator is None.

tf.contrib.framework.is_tensor(x) Check for tensor types. Check whether an object is a tensor. Equivalent to isinstance(x, [tf.Tensor, tf.SparseTensor, tf.Variable]). Args: x: An python object to check. Returns: True if x is a tensor, False if not.

tf.contrib.distributions.Categorical.get_event_shape() Shape of a single sample from a single batch as a TensorShape. Same meaning as event_shape. May be only partially defined. Returns: event_shape: TensorShape, possibly unknown.

tf.nn.rnn_cell.BasicLSTMCell.state_size