code: def test_renext_bottleneck():
      with pytest.raises(AssertionError):
          # Style must be in ['pytorch', 'caffe']
          BottleneckX(
              64, 64, groups=32, base_width=4, style="tensorflow"
          )
  
      # Test ResNeXt Bottleneck structure
      block = BottleneckX(
          64, 64, groups=32, base_width=4, stride=2, style="pytorch"
      )
      assert block.conv2.stride == (2, 2)
      assert block.conv2.groups == 32
      assert block.conv2.out_channels == 128
  
      # Test ResNeXt Bottleneck with DCN
      dcn = dict(type="DCN", deform_groups=1, fallback_on_stride=False)
      with pytest.raises(AssertionError):
          # conv_cfg must be None if dcn is not None
          BottleneckX(
              64,
              64,
              groups=32,
              base_width=4,
              dcn=dcn,
              conv_cfg=dict(type="Conv"),
          )
      BottleneckX(64, 64, dcn=dcn)
  
      # Test ResNeXt Bottleneck forward
      block = BottleneckX(64, 16, groups=32, base_width=4)
      x = torch.randn(1, 64, 56, 56)
      x_out = block(x)
      assert x_out.shape == torch.Size([1, 64, 56, 56])
  
      # Test ResNeXt Bottleneck forward with plugins
      plugins = [
          dict(
              cfg=dict(
                  type="GeneralizedAttention",
                  spatial_range=-1,
                  num_heads=8,
                  attention_type="0010",
                  kv_stride=2,
              ),
              stages=(False, False, True, True),
              position="after_conv2",
          )
      ]
      block = BottleneckX(
          64, 16, groups=32, base_width=4, plugins=plugins
      )
      x = torch.randn(1, 64, 56, 56)
      x_out = block(x)
      assert x_out.shape == torch.Size([1, 64, 56, 56])
  
imports: import pytest
  import torch
  from mmdet.models.backbones import ResNeXt
  from mmdet.models.backbones.resnext import Bottleneck
  from .utils import is_block
label_desc: Use image node_id 1 for calling a global function with example usage: test_renext_bottleneck() without return types