Direct Access to MLX Library

DirectMLXExample.java

import com.sun.jna.Library;
import com.sun.jna.Native;
import com.sun.jna.Pointer;
import com.sun.jna.Structure;
import com.sun.jna.ptr.PointerByReference;
import com.sun.jna.Memory;
import com.sun.jna.NativeLong;
import java.util.Arrays;

/**
 * Example of using JNA to interface directly with MLX library on Apple Silicon
 * without an intermediate C++ wrapper
 */
public class DirectMLXExample {

    /**
     * Direct MLX library interface definition
     * Note: This approach requires knowing the exact C++ mangled names and signatures
     */
    public interface MLXLibrary extends Library {
        // Load the MLX library directly
        MLXLibrary INSTANCE = Native.load("libmlx.dylib", MLXLibrary.class);
        
        // Example of directly accessing a C++ function with its mangled name
        // This is the mangled name for a specific constructor signature of mlx::core::array 
        // The exact mangled name will depend on your MLX version and compiler
        Pointer _ZN3mlx4core5arrayC1EPKfRKSt6vectorIiSaIiEENS0_5DtypeE(
            Pointer data,         // float* data
            Pointer shape_vector, // const std::vector<int>& shape
            int dtype             // mlx::core::Dtype dtype
        );
        
        // Function to create zeros array - mangled name for mlx::core::zeros
        Pointer _ZN3mlx4core5zerosERKSt6vectorIiSaIiEENS0_5DtypeE(
            Pointer shape_vector, // const std::vector<int>& shape
            int dtype             // mlx::core::Dtype dtype
        );
        
        // Addition operator - mangled name for operator+
        Pointer _ZNK3mlx4core5arrayplERKS1_(
            Pointer self,         // const mlx::core::array* self
            Pointer other         // const mlx::core::array& other
        );
        
        // Evaluation function - mangled name for mlx::core::eval
        void _ZN3mlx4core4evalERNS0_5arrayE(
            Pointer array         // mlx::core::array& array
        );
        
        // Function to get array data as host memory
        Pointer _ZNK3mlx4core5array7tohostIFaEEv(
            Pointer self          // const mlx::core::array* self
        );
        
        // Function to get array size
        int _ZNK3mlx4core5array4sizeEv(
            Pointer self          // const mlx::core::array* self
        );
    }
    
    // Simple std::vector<int> representation for JNA
    public static class StdVector extends Structure {
        public Pointer _M_start;  // Pointer to first element
        public Pointer _M_finish; // Pointer to one past last element
        public Pointer _M_end_of_storage; // Pointer to end of allocated storage
        
        public StdVector() {
            super();
        }
        
        @Override
        protected java.util.List<String> getFieldOrder() {
            return Arrays.asList("_M_start", "_M_finish", "_M_end_of_storage");
        }
        
        // Create a std::vector<int> with given values
        public static Pointer createIntVector(int[] values) {
            // Allocate memory for the vector structure
            StdVector vector = new StdVector();
            
            // Allocate memory for the vector data
            Memory data = new Memory(values.length * 4); // 4 bytes per int
            for (int i = 0; i < values.length; i++) {
                data.setInt(i * 4, values[i]);
            }
            
            // Set vector fields
            vector._M_start = data;
            vector._M_finish = data.share(values.length * 4);
            vector._M_end_of_storage = vector._M_finish;
            
            // Return pointer to the vector
            vector.write();
            return vector.getPointer();
        }
    }
    
    /**
     * Main method demonstrating direct MLX usage through JNA
     */
    public static void main(String[] args) {
        MLXLibrary lib = MLXLibrary.INSTANCE;
        
        try {
            // Create shape vector [2, 2]
            Pointer shapeVector = StdVector.createIntVector(new int[]{2, 2});
            
            // Create data for a 2x2 matrix
            float[] data = {1.0f, 2.0f, 3.0f, 4.0f};
            Memory dataMemory = new Memory(data.length * 4); // 4 bytes per float
            for (int i = 0; i < data.length; i++) {
                dataMemory.setFloat(i * 4, data[i]);
            }
            
            // Constants for MLX Dtype (0 = float32)
            final int MLX_FLOAT32 = 0;
            
            // Create MLX array directly
            Pointer array1 = lib._ZN3mlx4core5arrayC1EPKfRKSt6vectorIiSaIiEENS0_5DtypeE(
                dataMemory, shapeVector, MLX_FLOAT32);
                
            // Create another array with zeros
            Pointer array2 = lib._ZN3mlx4core5zerosERKSt6vectorIiSaIiEENS0_5DtypeE(
                shapeVector, MLX_FLOAT32);
                
            // Add the arrays
            Pointer sumArray = lib._ZNK3mlx4core5arrayplERKS1_(array1, array2);
            
            // Evaluate the result
            lib._ZN3mlx4core4evalERNS0_5arrayE(sumArray);
            
            System.out.println("Operation completed successfully");
            
            // Note: Memory management is extremely difficult with this approach
            // We would need proper destructors and memory cleanup which is complex
            // when working directly with C++ objects from JNA
            
        } catch (Exception e) {
            System.err.println("Error accessing MLX library directly: " + e.getMessage());
            e.printStackTrace();
        }
    }
}