| | |
| | """ |
| | 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 = {} |
| | |
| | |
| | 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) |
| | |
| | |
| | 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) |
| | |
| | |
| | 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) |
| | |
| | |
| | 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(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 |
| | |
| | |
| | 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() |
| |
|