code: def _cat_and_pad(tensors, pad_token_id):
      output = (
          tensors[0]
          .new(
              sum([t.shape[0] for t in tensors]),
              max([t.shape[1] for t in tensors]),
          )
          .fill_(pad_token_id)
      )
      ind = 0
      for t in tensors:
          output[ind : ind + t.shape[0], : t.shape[1]] = t
          ind += t.shape[0]
      return output
  
imports: import copy
  from dataclasses import dataclass
  from typing import Callable, List, Optional, Tuple, Union
  import torch
  from torch import nn
  from ...configuration_utils import PretrainedConfig
  from ...generation import BeamSearchScorer, GenerationConfig, LogitsProcessorList, StoppingCriteriaList
  from ...modeling_outputs import ModelOutput
  from ...modeling_utils import PreTrainedModel
  from ...utils import add_start_docstrings_to_model_forward, logging, replace_return_docstrings
  from .configuration_rag import RagConfig
  from .retrieval_rag import RagRetriever
label_desc: Use image node_id 10 for calling the RagSequenceForGeneration obj's underlying member method code with example usage: obj._cat_and_pad(tensors, pad_token_id) and returns: output