Spaces:
Runtime error
Runtime error
File size: 1,767 Bytes
2cdd41c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 |
import torch
from .resnetv1b import resnet34_v1b, resnet50_v1s, resnet101_v1s, resnet152_v1s
class ResNetBackbone(torch.nn.Module):
def __init__(self, backbone='resnet50', pretrained_base=True, dilated=True, **kwargs):
super(ResNetBackbone, self).__init__()
if backbone == 'resnet34':
pretrained = resnet34_v1b(pretrained=pretrained_base, dilated=dilated, **kwargs)
elif backbone == 'resnet50':
pretrained = resnet50_v1s(pretrained=pretrained_base, dilated=dilated, **kwargs)
elif backbone == 'resnet101':
pretrained = resnet101_v1s(pretrained=pretrained_base, dilated=dilated, **kwargs)
elif backbone == 'resnet152':
pretrained = resnet152_v1s(pretrained=pretrained_base, dilated=dilated, **kwargs)
else:
raise RuntimeError(f'unknown backbone: {backbone}')
self.conv1 = pretrained.conv1
self.bn1 = pretrained.bn1
self.relu = pretrained.relu
self.maxpool = pretrained.maxpool
self.layer1 = pretrained.layer1
self.layer2 = pretrained.layer2
self.layer3 = pretrained.layer3
self.layer4 = pretrained.layer4
def forward(self, x, additional_features=None):
x = self.conv1(x)
x = self.bn1(x)
x = self.relu(x)
if additional_features is not None:
x = x + torch.nn.functional.pad(additional_features,
[0, 0, 0, 0, 0, x.size(1) - additional_features.size(1)],
mode='constant', value=0)
x = self.maxpool(x)
c1 = self.layer1(x)
c2 = self.layer2(c1)
c3 = self.layer3(c2)
c4 = self.layer4(c3)
return c1, c2, c3, c4
|