code: def __init__(self, pool_size):
      super().__init__()
      self.pool = nn.AvgPool2d(
          pool_size,
          stride=1,
          padding=pool_size // 2,
          count_include_pad=False,
      )
  
imports: import collections.abc
  from typing import Optional, Tuple, Union
  import torch
  import torch.utils.checkpoint
  from torch import nn
  from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
  from ...activations import ACT2FN
  from ...modeling_outputs import BaseModelOutputWithNoAttention, ImageClassifierOutputWithNoAttention
  from ...modeling_utils import PreTrainedModel
  from ...utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, logging
  from .configuration_poolformer import PoolFormerConfig
label_desc: Use image node_id 1 to create a new PoolFormerPooling object from inherited base classes: nn with example: obj = PoolFormerPooling(pool_size)