class_docstr: Basic transformation: 3x3, BN, AF, 3x3, BN.
class_docstr_tok: ["Basic","transformation",":","3x3",",","BN",",","AF",",","3x3",",","BN","."]
code: def __init__(self, w_in, w_out, stride, w_b=None, groups=1):
      err_str = (
          "Basic transform does not support w_b and groups options"
      )
      assert w_b is None and groups == 1, err_str
      super(BasicTransform, self).__init__()
      self.a = conv2d(w_in, w_out, 3, stride=stride)
      self.a_bn = norm2d(w_out)
      self.a_af = activation()
      self.b = conv2d(w_out, w_out, 3)
      self.b_bn = norm2d(w_out)
      self.b_bn.final_bn = True
  
imports: from pycls.core.config import cfg
  from pycls.models.blocks import activation, conv2d, conv2d_cx, gap2d, gap2d_cx, init_weights, linear, linear_cx, norm2d, norm2d_cx, pool2d, pool2d_cx
  from torch.nn import Module
label_desc: Use image node_id 1 to create a new BasicTransform object from inherited base classes: Module with example: obj = BasicTransform(w_in, w_out, stride, w_b, groups)