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Make norm layer as parameters in models.detection.backbone_utils.py #2081

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Apr 9, 2020
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Make norm layer as parameters in models.detection.backbone_utils.py #2081

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4 changes: 2 additions & 2 deletions torchvision/models/detection/backbone_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,10 +41,10 @@ def forward(self, x):
return x


def resnet_fpn_backbone(backbone_name, pretrained):
def resnet_fpn_backbone(backbone_name, pretrained, norm_layer=misc_nn_ops.FrozenBatchNorm2d):
backbone = resnet.__dict__[backbone_name](
pretrained=pretrained,
norm_layer=misc_nn_ops.FrozenBatchNorm2d)
norm_layer=norm_layer)
# freeze layers
for name, parameter in backbone.named_parameters():
if 'layer2' not in name and 'layer3' not in name and 'layer4' not in name:
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