#!/usr/bin/env python3
"""
Export all SAM Audio components to ONNX format.

This script exports:
1. DACVAE encoder and decoder (audio codec)
2. T5 text encoder
3. DiT transformer (single-step for ODE solving)
4. Vision encoder (CLIP-based, for video-guided separation)
    python -m onnx_export.export_all --output-dir onnx_models --verify
"""

import os
import argparse
import subprocess
import sys


def run_export(module: str, args: list[str]) -> bool:
    """Run an export module with the given arguments."""
    cmd = [sys.executable, "-m", module] + args
    print(f"\n{'='*60}")
    print(f"Running: {' '.join(cmd)}")
    print(f"{'='*60}\n")
    
    result = subprocess.run(cmd, cwd=os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
    return result.returncode == 0


def main():
    parser = argparse.ArgumentParser(description="Export all SAM Audio components to ONNX")
    parser.add_argument(
        "--output-dir",
        type=str,
        default="onnx_models",
        help="Output directory for ONNX models",
    )
    parser.add_argument(
        "--model",
        type=str,
        default="facebook/sam-audio-small",
        help="SAM-Audio model ID (e.g., facebook/sam-audio-small, facebook/sam-audio-large, facebook/sam-audio-base-tv)",
    )
    parser.add_argument(
        "--verify",
        action="store_true",
        help="Verify ONNX output matches PyTorch",
    )
    parser.add_argument(
        "--skip-dacvae",
        action="store_true",
        help="Skip DACVAE export",
    )
    parser.add_argument(
        "--skip-t5",
        action="store_true",
        help="Skip T5 export",
    )
    parser.add_argument(
        "--skip-dit",
        action="store_true",
        help="Skip DiT export",
    )
    parser.add_argument(
        "--skip-vision",
        action="store_true",
        help="Skip Vision encoder export",
    )
    
    args = parser.parse_args()
    
    os.makedirs(args.output_dir, exist_ok=True)
    
    results = {}
    
    # Export DACVAE
    if not args.skip_dacvae:
        export_args = ["--output-dir", args.output_dir, "--model-id", args.model]
        if args.verify:
            export_args.append("--verify")
        results["DACVAE"] = run_export("onnx_export.export_dacvae", export_args)
    
    # Export T5
    if not args.skip_t5:
        export_args = ["--output-dir", args.output_dir, "--model-id", args.model]
        if args.verify:
            export_args.append("--verify")
        results["T5"] = run_export("onnx_export.export_t5", export_args)
    
    # Export DiT
    if not args.skip_dit:
        export_args = ["--output-dir", args.output_dir, "--model-id", args.model]
        if args.verify:
            export_args.append("--verify")
        results["DiT"] = run_export("onnx_export.export_dit", export_args)
    
    # Export Vision Encoder
    if not args.skip_vision:
        export_args = ["--output", args.output_dir, "--model", args.model]
        results["Vision"] = run_export("onnx_export.export_vision", export_args)
    
    # Print summary
    print(f"\n{'='*60}")
    print("Export Summary")
    print(f"{'='*60}")
    
    all_success = True
    for name, success in results.items():
        status = "✓" if success else "✗"
        print(f"  {status} {name}")
        if not success:
            all_success = False
    
    # List exported files
    print(f"\nExported files in {args.output_dir}:")
    for f in sorted(os.listdir(args.output_dir)):
        path = os.path.join(args.output_dir, f)
        if os.path.isfile(path):
            size_mb = os.path.getsize(path) / (1024 * 1024)
            print(f"  {f}: {size_mb:.1f} MB")
    
    if all_success:
        print("\n✓ All exports completed successfully!")
    else:
        print("\n✗ Some exports failed")
        sys.exit(1)


if __name__ == "__main__":
    main()