tf.TensorArray.read(index, name=None) Read the value at location index in the TensorArray. Args: index: 0-D. int32 tensor with the index to read from. name: A name for the operation (optional). Returns: The tensor at index index.

tf.TensorArray.pack(name=None) Return the values in the TensorArray as a packed Tensor. All of the values must have been written and their shapes must all match. Args: name: A name for the operation (optional). Returns: All the tensors in the TensorArray packed into one tensor.

tf.TensorArray.handle The reference to the TensorArray.

tf.TensorArray.grad(source, flow=None, name=None)

tf.TensorArray.gather(indices, name=None) Return selected values in the TensorArray as a packed Tensor. All of selected values must have been written and their shapes must all match. Args: indices: A 1-D Tensor taking values in [0, max_value). If the TensorArray is not dynamic, max_value=size(). name: A name for the operation (optional). Returns: The in the TensorArray selected by indices, packed into one tensor.

tf.TensorArray.flow The flow Tensor forcing ops leading to this TensorArray state.

tf.TensorArray.dtype The data type of this TensorArray.

tf.TensorArray.concat(name=None) Return the values in the TensorArray as a concatenated Tensor. All of the values must have been written, their ranks must match, and and their shapes must all match for all dimensions except the first. Args: name: A name for the operation (optional). Returns: All the tensors in the TensorArray concatenated into one tensor.

tf.TensorArray.close(name=None) Close the current TensorArray.

class tf.TensorArray Class wrapping dynamic-sized, per-time-step, write-once Tensor arrays. This class is meant to be used with dynamic iteration primitives such as while_loop and map_fn. It supports gradient back-propagation via special "flow" control flow dependencies.