code: def __init__(
      self,
      in_channels,
      out_channels,
      kernel_size=1,
      stride=1,
      padding=0,
  ):
      super(ConvBnRelu, self).__init__()
      self.in_channels = in_channels
      self.out_channels = out_channels
      self.conv_bn_relu = nn.Sequential(
          nn.Conv2d(
              in_channels,
              out_channels,
              kernel_size,
              stride,
              padding,
              bias=False,
          ),
          nn.BatchNorm2d(out_channels),
          nn.ReLU(inplace=True),
      )
      self.reset_parameters()
  
file_path: nni/examples/nas/legacy/nasbench101/base_ops.py
imports: import math
  import torch.nn
label_desc: Use image node_id 1 to create a new ConvBnRelu object from inherited base classes: nn with example: obj = ConvBnRelu(in_channels, out_channels, kernel_size, stride, padding)