code: def _make_layer(
      self, block, planes, num_blocks, stride, stride_in_1x1
  ):
      strides = [stride] + [1] * (num_blocks - 1)
      layers = []
      for stride in strides:
          if block == Bottleneck:
              layers.append(
                  block(
                      self.in_planes,
                      planes,
                      stride,
                      stride_in_1x1,
                      self.groups,
                      self.base_width,
                  )
              )
          else:
              layers.append(
                  block(
                      self.in_planes,
                      planes,
                      stride,
                      self.groups,
                      self.base_width,
                  )
              )
          self.in_planes = planes * block.expansion
      return layers
  
file_path: tinygrad/extra/models/resnet.py
imports: import tinygrad.nn
  from tinygrad.tensor import Tensor
  from tinygrad.nn.state import torch_load
  from tinygrad.helpers import fetch, get_child
label_desc: Use image node_id 2 for calling the ResNet obj's underlying member method code with example usage: obj._make_layer(block, planes, num_blocks, stride, stride_in_1x1) and returns: layers