class_docstr: Container for the resnet test model
class_docstr_tok: ["Container","for","the","resnet","test","model"]
docstr: strided
code: def module_s2(self, nfm):
      """
      strided
      """
      module = [BatchNorm(), Activation(Rectlin())]
      mainpath = [
          Conv(**self.conv_params(1, nfm, stride=2)),
          Conv(**self.conv_params(3, nfm)),
          Conv(
              **self.conv_params(
                  1, nfm * 4, relu=False, batch_norm=False
              )
          ),
      ]
      sidepath = [
          Conv(
              **self.conv_params(
                  1, nfm * 4, stride=2, relu=False, batch_norm=False
              )
          )
      ]
      module.append(MergeSum([sidepath, mainpath]))
      return module
  
imports: import numpy
  import pytest
  from builtins import zip
  from neon import NervanaObject
  from neon.initializers import Gaussian, Constant, Kaiming
  from neon.layers import GeneralizedCost, Affine, Activation, Dropout
  from neon.layers import Conv, Pooling, Sequential, MergeMultistream
  from neon.layers import MergeSum, SkipNode, BatchNorm, MergeBroadcast, GeneralizedCostMask
  from neon.layers import BranchNode, Multicost, SingleOutputTree, LSTM
  from neon.layers.container import Broadcast
  from neon.models import Model
  from neon.transforms import Rectlin, CrossEntropyBinary, Softmax, Tanh
  from neon.transforms import Logistic, CrossEntropyMulti
label_desc: Use image node_id 4 for calling the ResnetModel obj's underlying member method code with example usage: obj.module_s2(nfm) and returns: module