sam-audio-small-onnx / export_all.py
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#!/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()