code: def __init__(
      self,
      in_channels,
      out_channels,
      ksize,
      stride,
      pad,
      initialW=None,
      nobias=False,
      groups=1,
  ):
      W_shape = out_channels, int(in_channels / groups), ksize, ksize
      self.W = chx.array(
          np.random.normal(size=W_shape).astype(np.float32)
      )
      if nobias:
          self.b = None
      else:
          self.b = chx.array(
              np.random.normal(size=out_channels).astype(np.float32)
          )
      self.stride = stride
      self.pad = pad
  
imports: import numpy
  import chainerx
label_desc: Use image node_id 1 to create a new Convolution2D object from inherited base classes: object with example: obj = Convolution2D(in_channels, out_channels, ksize, stride, pad, initialW, nobias, groups)