gguf-dump.py: add --markdown dump output
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brian khuu
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7b2f4a7d19
commit
f13e94ca1d
1 changed files with 126 additions and 1 deletions
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@ -101,25 +101,150 @@ def dump_metadata_json(reader: GGUFReader, args: argparse.Namespace) -> None:
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json.dump(result, sys.stdout)
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def element_count_rounded_notation(count: int) -> str:
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if count > 1e15 :
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# Quadrillion
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scaled_amount = count * 1e-15
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scale_suffix = "Q"
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elif count > 1e12 :
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# Trillions
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scaled_amount = count * 1e-12
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scale_suffix = "T"
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elif count > 1e9 :
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# Billions
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scaled_amount = count * 1e-9
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scale_suffix = "B"
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elif count > 1e6 :
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# Millions
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scaled_amount = count * 1e-6
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scale_suffix = "M"
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elif count > 1e3 :
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# Thousands
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scaled_amount = count * 1e-3
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scale_suffix = "K"
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else:
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# Under Thousands
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scaled_amount = count
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scale_suffix = ""
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return f"{'~' if count > 1e3 else ''}{round(scaled_amount)}{scale_suffix}"
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def translate_tensor_name(name):
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import re
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words = re.split(r"[._]", name)
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abbreviation_dictionary = {
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'ffn' : 'Feed Forward',
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'attn' : 'Attention',
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'blk' : 'Block',
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'norm' : 'Normalization',
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'embd' : 'Embedding',
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}
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expanded_words = []
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for word in words:
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word_norm = word.strip().lower()
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if word_norm in abbreviation_dictionary:
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expanded_words.append(abbreviation_dictionary[word_norm])
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else:
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expanded_words.append(word.title())
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return ' '.join(expanded_words)
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def dump_markdown_metadata(reader: GGUFReader, args: argparse.Namespace) -> None:
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host_endian, file_endian = get_file_host_endian(reader)
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print(f'# {args.model} - GGUF Internal File Dump') # noqa: NP100
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print(f'* Endian: {file_endian} endian') # noqa: NP100
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print('') # noqa: NP100
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print('## Key Value Metadata Store') # noqa: NP100
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print(f'There is {len(reader.fields)} key/value pair(s) in this file') # noqa: NP100
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print('') # noqa: NP100
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print('| POS | TYPE | Elements | Key | Value |') # noqa: NP100
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print('|-----|------------|----------|----------------------------------------|--------------------------------------------------------------------------------|') # noqa: NP100
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for n, field in enumerate(reader.fields.values(), 1):
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if not field.types:
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pretty_type = 'N/A'
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elif field.types[0] == GGUFValueType.ARRAY:
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nest_count = len(field.types) - 1
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pretty_type = '[' * nest_count + str(field.types[-1].name) + ']' * nest_count
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else:
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pretty_type = str(field.types[-1].name)
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if len(field.types) == 1:
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curr_type = field.types[0]
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if curr_type == GGUFValueType.STRING:
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value = repr(str(bytes(field.parts[-1]), encoding='utf-8')[:60])
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elif field.types[0] in reader.gguf_scalar_to_np:
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value = field.parts[-1][0]
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print(f'| {n:3} | {pretty_type:10} | {len(field.data):8} | {field.name:38} | {value:<78} |') # noqa: NP100
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print("\n") # noqa: NP100
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if not args.no_tensors:
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# Group tensors by their prefix and maintain order
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tensor_prefix_order = []
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tensor_groups = {}
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total_elements = sum(tensor.n_elements for tensor in reader.tensors)
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for tensor in reader.tensors:
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tensor_name = tensor.name.replace(".weight", "")
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tensor_components = tensor_name.split('.')
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tensor_prefix = tensor_components[0]
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if tensor_prefix == 'blk':
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tensor_prefix = f"{tensor_components[0]}.{tensor_components[1]}"
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if tensor_prefix not in tensor_groups:
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tensor_groups[tensor_prefix] = []
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tensor_prefix_order.append(tensor_prefix)
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tensor_groups[tensor_prefix].append(tensor)
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# Generate Markdown metadata
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for group in tensor_prefix_order:
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tensors = tensor_groups[group]
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group_elements = sum(tensor.n_elements for tensor in tensors)
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group_percentage = group_elements / total_elements * 100
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print(f"## {translate_tensor_name(group)} Tensor Group : {element_count_rounded_notation(group_elements)} Elements") # noqa: NP100
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print("| Tensor Name | Human Friendly Name | Elements | Shape | Type |") # noqa: NP100
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print("|----------------------|-------------------------------------|----------------|---------------------------------|------|") # noqa: NP100
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for tensor in tensors:
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tensor_name = tensor.name.replace(".weight", "")
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human_friendly_name = translate_tensor_name(tensor.name.replace(".weight", ""))
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prettydims = ' x '.join('{0:^5}'.format(d) for d in list(tensor.shape) + [1] * (4 - len(tensor.shape)))
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print(f"| {tensor_name:20} | {human_friendly_name:35} | ({element_count_rounded_notation(tensor.n_elements):>4}) {tensor.n_elements:7} | [{prettydims:29}] | {tensor.tensor_type.name:4} |") # noqa: NP100
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print("") # noqa: NP100
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print(f"- Total elements in {group}: ({element_count_rounded_notation(group_elements):>4}) {group_elements}") # noqa: NP100
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print(f"- Percentage of total elements: {group_percentage:.2f}%") # noqa: NP100
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print("\n") # 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-tensors", action="store_true", help="Don't dump tensor metadata")
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parser.add_argument("--json", action="store_true", help="Produce JSON output")
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parser.add_argument("--json-array", action="store_true", help="Include full array values in JSON output (long)")
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parser.add_argument("--markdown", action="store_true", help="Produce markdown output")
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parser.add_argument("--verbose", action="store_true", help="increase output verbosity")
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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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if not args.json:
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if not args.json and not args.markdown:
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logger.info(f'* Loading: {args.model}')
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reader = GGUFReader(args.model, 'r')
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if args.json:
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dump_metadata_json(reader, args)
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elif args.markdown:
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dump_markdown_metadata(reader, args)
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else:
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dump_metadata(reader, args)
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