Delete Example_Loader.py

Example_Loader.py

@@ -1,141 +0,0 @@
-import torch
-import torch.nn as nn
-import json
-import random
-from collections import deque
-
-# ============ КЛАСС МОДЕЛИ (ДОЛЖЕН СОВПАДАТЬ) ============
-class AndreyBot(nn.Module):
-    def __init__(self, vocab_size=89, hidden_size=256, num_layers=2, embedding_dim=64):
-        super().__init__()
-        self.vocab_size = vocab_size
-        self.hidden_size = hidden_size
-        self.num_layers = num_layers
-        self.embedding_dim = embedding_dim
-        self.embedding = nn.Embedding(vocab_size, embedding_dim)
-        self.lstm = nn.LSTM(embedding_dim, hidden_size, batch_first=True, num_layers=num_layers, dropout=0.2)
-        self.fc = nn.Linear(hidden_size, vocab_size)
-        self.dropout = nn.Dropout(0.2)
-        
-    def forward(self, x):
-        if x.dim() == 1:
-            x = x.unsqueeze(0)
-        emb = self.embedding(x)
-        out, _ = self.lstm(emb)
-        out = self.dropout(out)
-        out = out[:, -1, :]
-        return self.fc(out)
-
-# ============ ЗАГРУЗЧИК ============
-class AndreyLoader:
-    def __init__(self, model_path='andrey_full.pt'):
-        print("🤖 Загрузка Андрея...")
-        
-        # Загружаем чекпоинт
-        checkpoint = torch.load(model_path, map_location='cpu')
-        
-        # Создаём модель
-        self.model = AndreyBot(
-            vocab_size=checkpoint['vocab_size'],
-            hidden_size=checkpoint['hidden_size'],
-            num_layers=checkpoint['num_layers'],
-            embedding_dim=checkpoint['embedding_dim']
-        )
-        self.model.load_state_dict(checkpoint['model_state_dict'])
-        self.model.eval()
-        
-        # Загружаем словари
-        self.word_to_idx = checkpoint['word_to_idx']
-        self.idx_to_word = {int(k): v for k, v in checkpoint['idx_to_word'].items()}
-        
-        # Параметры
-        self.vocab_size = checkpoint['vocab_size']
-        self.epoch = checkpoint['epoch']
-        
-        # Константы
-        self.PAD = 0
-        self.UNK = 1
-        
-        print(f"✅ Андрей загружен!")
-        print(f"   📚 Словарь: {self.vocab_size} слов")
-        print(f"   🧠 Обучен: {self.epoch} эпох")
-    
-    def tokenize(self, text):
-        """Текст → список токенов"""
-        words = text.lower().split()
-        return [self.word_to_idx.get(w, self.UNK) for w in words if w in self.word_to_idx]
-    
-    def detokenize(self, tokens):
-        """Токены → текст"""
-        words = []
-        for t in tokens:
-            if t not in [self.PAD, self.UNK]:
-                words.append(self.idx_to_word.get(t, '?'))
-        return ' '.join(words)
-    
-    def generate(self, question, temperature=0.85, max_length=12):
-        """Генерация ответа"""
-        tokens = self.tokenize(question)
-        
-        if not tokens:
-            return "..."
-        
-        current = tokens[0]
-        response_tokens = []
-        
-        with torch.no_grad():
-            for _ in range(max_length):
-                # Получаем логиты от модели
-                logits = self.model(torch.tensor([[current]]))
-                
-                # Применяем температуру
-                probs = torch.softmax(logits[0] / temperature, dim=-1)
-                
-                # Top-K выбор
-                top_k = min(5, self.vocab_size)
-                top_probs, top_idx = torch.topk(probs, top_k)
-                probs = top_probs / top_probs.sum()
-                current = top_idx[torch.multinomial(probs, 1)].item()
-                
-                # Пропускаем спецтокены
-                if current in [self.PAD, self.UNK]:
-                    continue
-                
-                response_tokens.append(current)
-                
-                # Останавливаемся при длине
-                if len(response_tokens) >= max_length - 2:
-                    break
-        
-        if not response_tokens:
-            return "..."
-        
-        return self.detokenize(response_tokens)
-    
-    def chat(self):
-        """Запуск чата"""
-        print("\n" + "="*50)
-        print("🤖 АНДРЕЙ")
-        print("   Скажи 'пока' для выхода")
-        print("="*50 + "\n")
-        
-        while True:
-            user = input("👤 Вы: ").strip().lower()
-            
-            if user in ['пока', 'выход', 'exit', 'quit']:
-                print("🤖 Андрей: Пока! 👋")
-                break
-            
-            if user == '':
-                continue
-            
-            answer = self.generate(user)
-            print(f"🤖 Андрей: {answer}\n")
-
-# ============ ЗАПУСК ============
-if __name__ == "__main__":
-    # Загружаем Андрея
-    andrey = AndreyLoader('andrey_full.pt')
-    
-    # Запускаем чат
-    andrey.chat()