I rebuilt resnet101  code:
self.layer3 = self._make_layer(block, norm_layer, 256, layers[2],
                                       inplace, stride=1,
                                       bn_eps=bn_eps, bn_momentum=bn_momentum)
self.layer4 = self._make_layer(block, norm_layer, 512, layers[3],
                                       inplace, stride=1,
                                       bn_eps=bn_eps, bn_momentum=bn_momentum)

pytorch code:

self.layer3 = self._make_layer(block, planes[2], layers[2], stride=2, groups=groups, 
                          norm_layer=norm_layer)
self.layer4 = self._make_layer(block, planes[3], layers[3], stride=2, groups=groups, 
                          norm_layer=norm_layer)

note : my code  stride = 1, I want to downsample the input image by 1/8，or  set dilation = 3 in nn.conv2d().  Can I still use pretrained weight?
thanks!!!