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import torch
import torch.nn as nn
import torch.nn.functional as F
import pickle

# SimpleClassifier ํด๋ž˜์Šค ์ •์˜
class SimpleClassifier(nn.Module):
    def __init__(self, input_size, num_classes):
        super(SimpleClassifier, self).__init__()
        self.fc1 = nn.Linear(input_size, 256)
        self.fc2 = nn.Linear(256, 128)
        self.fc3 = nn.Linear(128, num_classes)
        self.dropout = nn.Dropout(0.3)
        
    def forward(self, x):
        x = F.relu(self.fc1(x))
        x = self.dropout(x)
        x = F.relu(self.fc2(x))
        x = self.dropout(x)
        x = self.fc3(x)
        return x

# ๋ชจ๋ธ ํŒŒ์ผ ๋‹ค์‹œ ์ƒ์„ฑ
with open('semantic_model.pkl', 'rb') as f:
    data = pickle.load(f)

torch.save(data['model'].state_dict(), 'pytorch_model.bin')
print("๋ชจ๋ธ ํŒŒ์ผ ์žฌ์ƒ์„ฑ ์™„๋ฃŒ!")