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from clip.clip import load | |
import torch.nn as nn | |
class CLIPViTL14Model(nn.Module): | |
def __init__(self, num_classes=1): | |
super(CLIPViTL14Model, self).__init__() | |
self.model, self.preprocess = load("ViT-L/14", device="cpu") | |
self.fc = nn.Linear(768, num_classes) | |
def forward(self, x, return_feature=False): | |
features = self.model.encode_image(x) | |
if return_feature: | |
return features | |
return self.fc(features) |