class_docstr: Group Normalization with 1 group. Input: tensor in shape [B, C, H, W]
class_docstr_tok: ["Group","Normalization","with","1","group",".","Input",":","tensor","in","shape","[","B",",","C",",","H",",","W","]"]
code: def __init__(self, num_channels, **kwargs):
      super().__init__(1, num_channels, **kwargs)
  
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 PoolFormerGroupNorm object from inherited base classes: nn with example: obj = PoolFormerGroupNorm(num_channels)