class_docstr: Module for the Conv-BN-ReLU tuple.
code: def __init__(
      self, c_in, c_out, kernel_size, stride, padding, dilation
  ):
      super(ConvBNReLU, self).__init__()
      self.conv = nn.Conv2d(
          c_in,
          c_out,
          kernel_size=kernel_size,
          stride=stride,
          padding=padding,
          dilation=dilation,
          bias=False,
      )
      self.bn = nn.BatchNorm2d(c_out)
      self.relu = nn.ReLU(inplace=True)
  
imports: import math
  import torch.utils.model_zoo
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.modules.batchnorm import _BatchNorm
  from .None import settings
label_desc: Use image node_id 1 to create a new ConvBNReLU object from inherited base classes: nn with example: obj = ConvBNReLU(c_in, c_out, kernel_size, stride, padding, dilation)