class_docstr: 实现了 **PaddlePaddle** 框架训练功能的基本 Driver。
  
  这个类被以下子类继承：
  
  1. :class:`~fastNLP.core.drivers.paddle_driver.PaddleSingleDriver`：实现了使用单卡和 ``cpu`` 训练的具体功能；
  2. :class:`~fastNLP.core.drivers.paddle_driver.PaddleFleetDriver`：实现了使用 ``fleet`` 分布式训练 API 进行集群式分布式训练的具体功能；
  
  .. warning::
  
      您不应当直接初始化该类，然后传入给 ``Trainer``，换句话说，您应当使用该类的子类 ``PaddleSingleDriver`` 和 ``PaddleDDPDriver``，而不是
      该类本身。
  
  .. note::
  
      您可以在使用 ``PaddleSingleDriver`` 和 ``PaddleFleetDriver`` 时使用 ``PaddleDriver`` 提供的接口。
  
  :param model: 训练时使用的 **PaddlePaddle** 模型
  :param fp16: 是否开启混合精度训练
  :param paddle_kwargs:
code: def worker_init_function(
      worker_id: int, rank: Optional[int] = None
  ) -> None:  # pragma: no cover
      # implementation notes: https://github.com/pytorch/pytorch/issues/5059#issuecomment-817392562
      global_rank = (
          rank
          if rank is not None
          else int(os.environ.get(FASTNLP_GLOBAL_RANK, 0))
      )
      # TODO gpu
      process_seed = (
          paddle.fluid.core.default_cpu_generator().initial_seed()
      )
      # back out the base seed so we can use all the bits
      base_seed = process_seed - worker_id
      ss = np.random.SeedSequence([base_seed, worker_id, global_rank])
      # use 128 bits (4 x 32-bit words)
      np.random.seed(ss.generate_state(4))
      # Spawn distinct SeedSequences for the PyTorch PRNG and the stdlib random module
      paddle_ss, stdlib_ss = ss.spawn(2)
      paddle.seed(paddle_ss.generate_state(1, dtype=np.uint64)[0])
      # use 128 bits expressed as an integer
      stdlib_seed = (
          stdlib_ss.generate_state(2, dtype=np.uint64).astype(object)
          * [1 << 64, 1]
      ).sum()
      random.seed(stdlib_seed)
  
imports: import os
  import random
  from typing import Union, Optional, Dict, Any
  from pathlib import Path
  from functools import partial
  from dataclasses import dataclass
  import numpy
  from .utils import _build_fp16_env, optimizer_state_to_device, DummyGradScaler
  from fastNLP.envs.imports import _NEED_IMPORT_PADDLE
  from fastNLP.core.drivers.driver import Driver
  from fastNLP.core.utils import apply_to_collection, paddle_move_data_to_device
  from fastNLP.core.utils.paddle_utils import _convert_data_device
  from fastNLP.envs import FASTNLP_MODEL_FILENAME, FASTNLP_CHECKPOINT_FILENAME, FASTNLP_GLOBAL_RANK, rank_zero_call
  from fastNLP.core.log import logger
  from fastNLP.core.dataloaders import OverfitDataLoader
  from fastNLP.core.samplers import ReproducibleBatchSampler, ReproducibleSampler, ReproduceBatchSampler, RandomSampler
label_desc: Use image node_id 18 for calling the PaddleDriver obj's underlying member method code with example usage: obj.worker_init_function(worker_id, rank) without return types