Fabio
c36510c21e
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86 lines
4.1 KiB
Python
86 lines
4.1 KiB
Python
#!/usr/bin/env python3
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"""Package Ming's model, tokenizer and native CAMPPlus speaker weights in one GGUF."""
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import argparse
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from pathlib import Path
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import re
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import shutil
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import subprocess
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import tempfile
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import numpy as np
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import onnx
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from onnx import numpy_helper
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from safetensors.numpy import save_file
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def campplus_weights(path):
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model = onnx.load(path)
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constants = {item.name: numpy_helper.to_array(item) for item in model.graph.initializer}
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for node in model.graph.node:
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if node.op_type == "Identity" and node.input[0] in constants:
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constants[node.output[0]] = constants[node.input[0]]
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elif node.op_type == "Constant":
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for attr in node.attribute:
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if attr.name == "value":
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constants[node.output[0]] = numpy_helper.to_array(attr.t)
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weights = {}
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for node in model.graph.node:
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if node.op_type not in ("Conv", "BatchNormalization"):
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continue
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name = re.sub(r"/(layer\d+)/\1\.(\d+)", r"/\1/\2", node.name)
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name = re.sub(r"/shortcut/shortcut\.(\d+)", r"/shortcut/\1", name)
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prefix = "speaker_encoder." + name.rsplit("/", 1)[0].strip("/").replace("/", ".")
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suffixes = ("weight", "bias") if node.op_type == "Conv" else (
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"weight", "bias", "running_mean", "running_var")
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if len(node.input) not in ((2, 3) if node.op_type == "Conv" else (5,)):
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raise ValueError(f"Unsupported parameter count: {node.name}")
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for source, suffix in zip(node.input[1:], suffixes):
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value = constants[source]
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if value.dtype != np.float32:
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raise ValueError(f"CAMPPlus parameter {source} must be float32, got {value.dtype}")
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target = prefix + "." + suffix
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if target in weights:
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raise ValueError(f"Duplicate CAMPPlus parameter: {target}")
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weights[target] = np.ascontiguousarray(value)
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if node.op_type == "BatchNormalization":
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attrs = {attr.name: onnx.helper.get_attribute_value(attr) for attr in node.attribute}
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if abs(attrs.get("epsilon", 1e-5) - 1e-5) > 1e-10 or attrs.get("training_mode", 0):
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raise ValueError(f"Unsupported CAMPPlus batch normalization: {node.name}")
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if weights["speaker_encoder.xvector.dense.linear.weight"].shape != (192, 1024, 1):
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raise ValueError("Ming requires the published 192-dimensional CAMPPlus encoder")
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return weights
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def main():
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument("--source", type=Path, required=True, help="Published Ming checkpoint directory")
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parser.add_argument("--output", type=Path, required=True, help="Output GGUF file")
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parser.add_argument("--type", choices=("orig", "q8_0"), default="orig")
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parser.add_argument("--converter", type=Path, default=Path("build/debug/bin/audiocpp_gguf"))
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parser.add_argument("--overwrite", action="store_true")
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args = parser.parse_args()
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if args.output.exists() and not args.overwrite:
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raise FileExistsError(args.output)
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source = args.source.resolve()
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weights = campplus_weights(source / "campplus.onnx")
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args.output.parent.mkdir(parents=True, exist_ok=True)
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spec = Path(__file__).resolve().parents[2] / "model_specs/ming3_tts.json"
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with tempfile.TemporaryDirectory(prefix=".ming-convert-", dir=args.output.parent) as temporary:
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root = Path(temporary)
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for name in ("config.json", "tokenizer.json", "tokenizer_config.json"):
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shutil.copyfile(source / name, root / name)
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speaker = root / "speaker.safetensors"
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save_file(weights, speaker)
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command = [str(args.converter.resolve()), "--input", str(source / "model.safetensors"),
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"--input", f"speaker={speaker}", "--root", str(root), "--model-spec", str(spec),
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"--type", args.type, "--output", str(args.output.resolve()),
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"--keep-type", "speaker.*=f32", "--keep-type", "stop_head*=bf16"]
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if args.overwrite:
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command.append("--overwrite")
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subprocess.run(command, check=True)
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if __name__ == "__main__":
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main()
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