aicomp_demo / src /models /shufflenetv2.py
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import torch
import torch.nn as nn
from torchvision.models import shufflenet_v2_x1_0
class ShuffleNetV2Classifier(nn.Module):
def __init__(self, num_classes=5, pretrained=True):
super().__init__()
self.backbone = shufflenet_v2_x1_0(pretrained=pretrained)
in_features = self.backbone.fc.in_features
self.backbone.fc = nn.Linear(in_features, num_classes)
def forward(self, x):
return self.backbone(x)