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https://github.com/ggerganov/llama.cpp.git
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e236528e76
* gguf_hash.py: Add sha256 * gguf_hash.py: rename string UUIDv5 --> uuid * Apply suggestions from code review Co-authored-by: compilade <git@compilade.net> --------- Co-authored-by: compilade <git@compilade.net>
103 lines
3.6 KiB
Python
Executable File
103 lines
3.6 KiB
Python
Executable File
#!/usr/bin/env python3
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from __future__ import annotations
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import uuid
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import hashlib
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import logging
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import argparse
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import os
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import sys
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from pathlib import Path
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from tqdm import tqdm
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# Necessary to load the local gguf package
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if "NO_LOCAL_GGUF" not in os.environ and (Path(__file__).parent.parent.parent / 'gguf-py').exists():
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from gguf import GGUFReader # noqa: E402
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logger = logging.getLogger("gguf-hash")
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# UUID_NAMESPACE_LLAMA_CPP = uuid.uuid5(uuid.NAMESPACE_URL, 'en.wikipedia.org/wiki/Llama.cpp')
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UUID_NAMESPACE_LLAMA_CPP = uuid.UUID('ef001206-dadc-5f6d-a15f-3359e577d4e5')
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# For more information about what field.parts and field.data represent,
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# please see the comments in the modify_gguf.py example.
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def gguf_hash(reader: GGUFReader, filename: str, disable_progress_bar: bool, no_layer: bool) -> None:
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sha1 = hashlib.sha1()
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sha256 = hashlib.sha256()
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uuidv5_sha1 = hashlib.sha1()
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uuidv5_sha1.update(UUID_NAMESPACE_LLAMA_CPP.bytes)
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# Total Weight Calculation For Progress Bar
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total_weights = 0
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for n, tensor in enumerate(reader.tensors, 1):
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# We don't need these
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if tensor.name.endswith((".attention.masked_bias", ".attention.bias", ".rotary_emb.inv_freq")):
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continue
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# Calculate Tensor Volume
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sum_weights_in_tensor = 1
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for dim in tensor.shape:
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sum_weights_in_tensor *= dim
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total_weights += sum_weights_in_tensor
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# Hash Progress Bar
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bar = tqdm(desc="Hashing", total=total_weights, unit="weights", unit_scale=True, disable=disable_progress_bar)
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# Hashing Process
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for tensor in reader.tensors:
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# We don't need these
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if tensor.name.endswith((".attention.masked_bias", ".attention.bias", ".rotary_emb.inv_freq")):
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continue
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# Progressbar
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sum_weights_in_tensor = 1
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for dim in tensor.shape:
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sum_weights_in_tensor *= dim
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bar.update(sum_weights_in_tensor)
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if not no_layer:
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sha1_layer = hashlib.sha1()
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sha1_layer.update(tensor.data.data)
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print("sha1 {0} {1}:{2}".format(sha1_layer.hexdigest(), filename, tensor.name)) # noqa: NP100
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sha256_layer = hashlib.sha256()
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sha256_layer.update(tensor.data.data)
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print("sha256 {0} {1}:{2}".format(sha256_layer.hexdigest(), filename, tensor.name)) # noqa: NP100
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sha1.update(tensor.data.data)
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sha256.update(tensor.data.data)
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uuidv5_sha1.update(tensor.data.data)
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# Flush Hash Progress Bar
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bar.close()
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# Display Hash Output
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print("sha1 {0} {1}".format(sha1.hexdigest(), filename)) # noqa: NP100
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print("sha256 {0} {1}".format(sha256.hexdigest(), filename)) # noqa: NP100
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print("uuid {0} {1}".format(uuid.UUID(bytes=uuidv5_sha1.digest()[:16], version=5), filename)) # noqa: NP100
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def main() -> None:
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parser = argparse.ArgumentParser(description="Dump GGUF file metadata")
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parser.add_argument("model", type=str, help="GGUF format model filename")
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parser.add_argument("--no-layer", action="store_true", help="exclude per layer hash")
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parser.add_argument("--verbose", action="store_true", help="increase output verbosity")
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parser.add_argument("--progressbar", action="store_true", help="enable progressbar")
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args = parser.parse_args(None if len(sys.argv) > 1 else ["--help"])
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logging.basicConfig(level=logging.DEBUG if args.verbose else logging.INFO)
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reader = GGUFReader(args.model, 'r')
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gguf_hash(reader, args.model, not args.progressbar, args.no_layer)
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if __name__ == '__main__':
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main()
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