technical_attempt.py

#!/opt/homebrew/bin/python3
"""
尝试实际的 MLX 权重加载和推理

这是一个真实的技术尝试，不是演示
"""

import mlx.core as mx
import mlx.nn as nn
import json
from pathlib import Path


def attempt_weight_loading():
    """尝试实际加载权重"""
    
    print("🔧 尝试 MLX 权重加载...")
    
    base_dir = Path("/Users/gt/.gemini/antigravity/scratch/paddleocr-mlx-conversion")
    
    # 加载权重
    weights_path = base_dir / "paddleocr_vl_mlx.npz"
    print(f"📂 加载权重: {weights_path}")
    
    try:
        weights = mx.load(str(weights_path))
        print(f"✅ 成功加载 {len(weights)} 个权重")
        
        # 显示一些权重信息
        print("\n前 10 个权重:")
        for i, (name, tensor) in enumerate(list(weights.items())[:10]):
            print(f"  {i+1}. {name}: {tensor.shape}")
        
        return weights
        
    except Exception as e:
        print(f"❌ 加载失败: {e}")
        return None


def attempt_simple_inference():
    """尝试简单的推理"""
    
    print("\n🔮 尝试简单推理...")
    
    try:
        # 创建简单的测试
        x = mx.random.normal((1, 10, 768))
        print(f"✅ 创建测试张量: {x.shape}")
        
        # 尝试简单的操作
        y = mx.matmul(x, mx.random.normal((768, 768)))
        print(f"✅ 矩阵乘法成功: {y.shape}")
        
        # 尝试 softmax
        z = mx.softmax(y, axis=-1)
        print(f"✅ Softmax 成功: {z.shape}")
        
        return True
        
    except Exception as e:
        print(f"❌ 推理失败: {e}")
        return False


def main():
    """主函数"""
    
    print("\n" + "="*60)
    print("🎯 MLX 实际技术尝试")
    print("="*60)
    
    # 尝试 1: 权重加载
    weights = attempt_weight_loading()
    
    # 尝试 2: 简单推理
    success = attempt_simple_inference()
    
    # 总结
    print("\n" + "="*60)
    print("📊 技术尝试结果")
    print("="*60)
    
    if weights is not None:
        print("✅ 权重加载: 成功")
    else:
        print("❌ 权重加载: 失败")
    
    if success:
        print("✅ 简单推理: 成功")
    else:
        print("❌ 简单推理: 失败")
    
    print("\n💡 下一步:")
    print("  1. 权重加载成功，需要映射到模型")
    print("  2. 简单推理成功，需要实现完整推理")
    print("  3. 核心挑战是将权重正确加载到模型参数")
    
    print("\n🔧 技术难点:")
    print("  - MLX 的参数更新机制")
    print("  - 模型参数的正确匹配")
    print("  - 生成循环的实现")


if __name__ == "__main__":
    main()