mirror of
https://github.com/invoke-ai/InvokeAI
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51 lines
1.5 KiB
Python
Executable File
51 lines
1.5 KiB
Python
Executable File
#!/usr/bin/env python
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"""
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Read a checkpoint/safetensors file and write out a template .json file containing
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its metadata for use in fast model probing.
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"""
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import sys
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import argparse
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import json
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from pathlib import Path
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from invokeai.backend.model_management.models.base import read_checkpoint_meta, ModelType
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parser = argparse.ArgumentParser(description="Create a .json template from checkpoint/safetensors model")
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parser.add_argument(type=Path, help="Path to the input checkpoint/safetensors file")
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parser.add_argument("--template", "--out", type=Path, help="Path to the output .json file")
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parser.add_argument("--base-type",
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type=str,
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choices=['sd-1','sd-2','sdxl'],
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help="Base type of the model",
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)
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parser.add_argument("--model-type",
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type=str,
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choices=[x.value for x in ModelType],
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help="Base type of the model",
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)
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opt = parser.parse_args()
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ckpt = read_checkpoint_meta(opt.checkpoint)
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while "state_dict" in ckpt:
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ckpt = ckpt["state_dict"]
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tmpl = {}
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for key, tensor in ckpt.items():
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tmpl[key] = list(tensor.shape)
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meta = {
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'base_type': opt.base_type,
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'model_type': opt.model_type,
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'template': tmpl
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}
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try:
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with open(opt.template, "w") as f:
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json.dump(meta, f)
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print(f"Template written out as {opt.template}")
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except Exception as e:
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print(f"An exception occurred while writing template: {str(e)}")
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