code: def _pad_tensors_to_max_len(model_cfg, tensor, max_length):
      pad_token_id = (
          model_cfg.pad_token_id
          if model_cfg.pad_token_id
          else model_cfg.eos_token_id
      )
      if pad_token_id is None:
          raise ValueError(
              f"Make sure that either `config.pad_token_id` or `config.eos_token_id` "
              f"is defined if tensor has to be padded to `max_length`={max_length}"
          )
  
      padded_tensor = pad_token_id * torch.ones(
          (tensor.shape[0], max_length),
          dtype=tensor.dtype,
          device=tensor.device,
      )
      padded_tensor[:, : tensor.shape[-1]] = tensor
      return padded_tensor
  
imports: import os
  import warnings
  from typing import Any, Dict, Iterable, List, Optional, Type, Union
  import torch
  from pytorch_lightning import Callback
  from pytorch_lightning.utilities import rank_zero_info
  from torch import Tensor
  from torch.nn import Module
  from flash.core.data.io.input import DataKeys, ServeInput
  from flash.core.data.io.input_transform import InputTransform
  from flash.core.data.io.output import Output
  from flash.core.data.io.output_transform import OutputTransform
  from flash.core.model import Task
  from flash.core.registry import ExternalRegistry, FlashRegistry
  from flash.core.serve import Composition
  from flash.core.utilities.imports import _TOPIC_TEXT_AVAILABLE, requires
  from flash.core.utilities.providers import _HUGGINGFACE
  from flash.core.utilities.types import INPUT_TRANSFORM_TYPE, LOSS_FN_TYPE, LR_SCHEDULER_TYPE, METRICS_TYPE, OPTIMIZER_TYPE
  from flash.text.input import TextDeserializer
  from flash.text.ort_callback import ORTCallback
  from flash.text.seq2seq.core.collate import TextSeq2SeqCollate
label_desc: Use image node_id 1 for calling a global function with example usage: _pad_tensors_to_max_len(model_cfg, tensor, max_length) and returns: padded_tensor