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""" |
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Export all SAM Audio components to ONNX format. |
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This script exports: |
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1. DACVAE encoder and decoder (audio codec) |
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2. T5 text encoder |
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3. DiT transformer (single-step for ODE solving) |
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4. Vision encoder (CLIP-based, for video-guided separation) |
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python -m onnx_export.export_all --output-dir onnx_models --verify |
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""" |
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import os |
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import argparse |
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import subprocess |
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import sys |
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def run_export(module: str, args: list[str]) -> bool: |
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"""Run an export module with the given arguments.""" |
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cmd = [sys.executable, "-m", module] + args |
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print(f"\n{'='*60}") |
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print(f"Running: {' '.join(cmd)}") |
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print(f"{'='*60}\n") |
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result = subprocess.run(cmd, cwd=os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) |
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return result.returncode == 0 |
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def main(): |
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parser = argparse.ArgumentParser(description="Export all SAM Audio components to ONNX") |
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parser.add_argument( |
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"--output-dir", |
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type=str, |
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default="onnx_models", |
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help="Output directory for ONNX models", |
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) |
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parser.add_argument( |
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"--model", |
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type=str, |
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default="facebook/sam-audio-small", |
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help="SAM-Audio model ID (e.g., facebook/sam-audio-small, facebook/sam-audio-large, facebook/sam-audio-base-tv)", |
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) |
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parser.add_argument( |
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"--verify", |
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action="store_true", |
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help="Verify ONNX output matches PyTorch", |
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) |
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parser.add_argument( |
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"--skip-dacvae", |
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action="store_true", |
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help="Skip DACVAE export", |
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) |
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parser.add_argument( |
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"--skip-t5", |
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action="store_true", |
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help="Skip T5 export", |
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) |
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parser.add_argument( |
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"--skip-dit", |
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action="store_true", |
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help="Skip DiT export", |
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) |
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parser.add_argument( |
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"--skip-vision", |
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action="store_true", |
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help="Skip Vision encoder export", |
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) |
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args = parser.parse_args() |
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os.makedirs(args.output_dir, exist_ok=True) |
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results = {} |
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if not args.skip_dacvae: |
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export_args = ["--output-dir", args.output_dir, "--model-id", args.model] |
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if args.verify: |
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export_args.append("--verify") |
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results["DACVAE"] = run_export("onnx_export.export_dacvae", export_args) |
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if not args.skip_t5: |
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export_args = ["--output-dir", args.output_dir, "--model-id", args.model] |
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if args.verify: |
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export_args.append("--verify") |
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results["T5"] = run_export("onnx_export.export_t5", export_args) |
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if not args.skip_dit: |
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export_args = ["--output-dir", args.output_dir, "--model-id", args.model] |
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if args.verify: |
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export_args.append("--verify") |
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results["DiT"] = run_export("onnx_export.export_dit", export_args) |
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if not args.skip_vision: |
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export_args = ["--output", args.output_dir, "--model", args.model] |
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results["Vision"] = run_export("onnx_export.export_vision", export_args) |
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print(f"\n{'='*60}") |
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print("Export Summary") |
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print(f"{'='*60}") |
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all_success = True |
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for name, success in results.items(): |
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status = "✓" if success else "✗" |
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print(f" {status} {name}") |
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if not success: |
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all_success = False |
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print(f"\nExported files in {args.output_dir}:") |
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for f in sorted(os.listdir(args.output_dir)): |
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path = os.path.join(args.output_dir, f) |
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if os.path.isfile(path): |
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size_mb = os.path.getsize(path) / (1024 * 1024) |
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print(f" {f}: {size_mb:.1f} MB") |
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if all_success: |
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print("\n✓ All exports completed successfully!") |
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else: |
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print("\n✗ Some exports failed") |
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sys.exit(1) |
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if __name__ == "__main__": |
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main() |
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