class_docstr: A lightweight buffer for maintaining lists.
  
  The TensorBuffer accumulates tensors of the given shape into a tensor (whose
  rank is one more than that of the given shape) via calls to `append`. The
  current value of the accumulated tensor can be extracted via the property
  `values`.
docstr: Returns the accumulated tensor.
docstr_tok: ["Returns","the","accumulated","tensor","."]
code: def values(self):
      """Returns the accumulated tensor."""
      begin_value = tf.zeros([self._rank + 1], dtype=tf.int32)
      value_size = tf.concat(
          [
              [self._current_size],
              tf.constant(-1, tf.int32, [self._rank]),
          ],
          0,
      )
      return tf.slice(self._buffer, begin_value, value_size)
  
imports: import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling the TensorBuffer obj's underlying member method code with example usage: obj.values() and returns: tf