code: def _make_layer(self, ni, nf, blocks, stride, sa, **kwargs):
      return nn.Sequential(
          *[
              self.block(
                  self.expansion,
                  ni if i == 0 else nf,
                  nf,
                  stride=stride if i == 0 else 1,
                  sa=sa and i == (blocks - 1),
                  act_cls=self.act_cls,
                  ndim=self.ndim,
                  ks=self.ks,
                  **kwargs,
              )
              for i in range(blocks)
          ]
      )
  
imports: from __future__ import annotations
  from ...torch_basics import *
label_desc: Use image node_id 3 for calling the XResNet obj's underlying member method code with example usage: obj._make_layer(ni, nf, blocks, stride, sa) and returns: nn