code: def pad_date_tensors(date_tensors, name=None):
      """Pads the innermost dimension of `DateTensor`s to a common shape.
  
      Given a list of `DateTensor`s of shapes `batch_shape_i + [n_i]`, pads the
      innermost dimension of each corresponding ordinal tensor to
      `batch_shape_i + [max(n_i)]`. For each ordinal tensor `t`, the padding is done
      with values `t[..., -1]`.
  
      ### Example
      ```python
      x = [(2020, 1, 1), (2021, 2, 2)]
      y = [(2019, 5, 5), (2028, 10, 21), (2028, 11, 10)]
      pad_date_tensors([x, y])
      # Expected: [DateTensor: [(2020, 1, 1), (2021, 2, 2), (2021, 2, 2)],
      #            DateTensor: [(2019, 5, 5), (2028, 10, 21), (2028, 11, 10)]]
      ```
  
      Args:
        date_tensors: a list of tensors of shapes `batch_shape_i + [n_i]`.
        name: Python string. The name to give to the ops created by this class.
          Default value: `None` which maps to the default name `pad_date_tensors`.
      Returns:
        A list of `DateTensor`s of shape `batch_shape_i + [max(n_i)]`.
      """
      name = name or "pad_date_tensors"
      with tf.name_scope(name):
          ordinals = [
              date_tensor.convert_to_date_tensor(t).ordinal()
              for t in date_tensors
          ]
          padded_tensors = pad_tensors(ordinals)
          return [date_tensor.from_ordinals(p) for p in padded_tensors]
  
imports: import tensorflow.compat.v2
  from tf_quant_finance.datetime import date_tensor
label_desc: Use image node_id 2 for calling a global function with example usage: pad_date_tensors(date_tensors, name) and returns: unknown