code: def __init__(
      self,
      inplanes,
      outplanes,
      kernel_size,
      stride,
      padding,
      dilation,
      relu=True,
  ):
      super(_ConvBatchNormReluBlock, self).__init__()
      self.add_module(
          "cov",
          nn.Conv2d(
              in_channels=inplanes,
              out_channels=outplanes,
              kernel_size=kernel_size,
              stride=stride,
              padding=padding,
              dilation=dilation,
              bias=False,
          ),
      )
      self.add_module(
          "bn",
          nn.BatchNorm2d(
              num_features=outplanes, momentum=0.999, affine=True
          ),
      )
      if relu:
          self.add_module("relu", nn.ReLU())
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from .None import seg_resnet
  from .None import seg_resnext
label_desc: Use image node_id 1 to create a new _ConvBatchNormReluBlock object from inherited base classes: nn with example: obj = _ConvBatchNormReluBlock(inplanes, outplanes, kernel_size, stride, padding, dilation, relu)