将slowfast中resnet50替换为resnext50
时间: 2023-12-09 08:37:26 浏览: 43
在SlowFast模型中将ResNet-50替换为ResNeXt-50是可行的。以下是一种可能的实现方法:
1. 首先,导入所需的库和模型:
```python
import torch
import torchvision.models as models
from torchvision.models.resnet import Bottleneck
# 导入SlowFast模型
from slowfast.models.video_model_builder import SlowFast
```
2. 定义ResNeXt-50模型:
```python
class ResNeXt(models.ResNet):
def __init__(self, block, layers, num_classes=1000, zero_init_residual=False,
groups=32, width_per_group=4, replace_stride_with_dilation=None,
norm_layer=None):
super(ResNeXt, self).__init__(block, layers, num_classes, zero_init_residual,
groups, width_per_group, replace_stride_with_dilation,
norm_layer)
def _forward_impl(self, x):
# 前向传播逻辑
x = self.conv1(x)
x = self.bn1(x)
x = self.relu(x)
x = self.maxpool(x)
x = self.layer1(x)
x = self.layer2(x)
x = self.layer3(x)
x = self.layer4(x)
x = self.avgpool(x)
x = torch.flatten(x, 1)
x = self.fc(x)
return x
def _resnext(arch, block, layers, pretrained, progress, **kwargs):
model = ResNeXt(block, layers, **kwargs)
if pretrained:
state_dict = torch.load(pretrained)
model.load_state_dict(state_dict)
return model
def resnext50(pretrained=False, progress=True, **kwargs):
return _resnext('resnext50', Bottleneck, [3, 4, 6, 3], pretrained, progress,
**kwargs)
```
3. 替换SlowFast模型中的ResNet-50为ResNeXt-50:
```python
slowfast = SlowFast(resnet_depth=50, num_classes=400)
# 加载预训练的ResNeXt-50模型
resnext = resnext50(pretrained=True)
# 替换SlowFast模型中的ResNet-50为ResNeXt-50
slowfast.s1_net = resnext
```
现在,SlowFast模型中的ResNet-50已被成功替换为ResNeXt-50。你可以继续使用slowfast进行训练或推理。