class_docstr: Basic transformation: [3x3 conv, BN, Relu] x2.
class_docstr_tok: ["Basic","transformation",":","[","3x3","conv",",","BN",",","Relu","]","x2","."]
code: def forward(self, x):
      for layer in self.children():
          x = layer(x)
      return x
  
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, SE
  from torch.nn import Module
label_desc: Use image node_id 2 for calling the BasicTransform obj's underlying member method code with example usage: obj.forward(x) and returns: x