vbatts/llama.cpp
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gguf-dump: right align element count

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brian khuu 2024-06-15 00:15:38 +10:00
parent 9310a02a7b
commit dfbf6e1458
1 changed files with 9 additions and 9 deletions
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18
gguf-py/scripts/gguf-dump.py
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@ -232,7 +232,7 @@ def dump_markdown_metadata(reader: GGUFReader, args: argparse.Namespace) -> None
markdown_content += f'There is {len(reader.fields)} key/value pair(s) in this file\n'
markdown_content += '\n'
kv_dump_table = []
kv_dump_table: list[dict[str, str | int]] = []
for n, field in enumerate(reader.fields.values(), 1):
if not field.types:
pretty_type = 'N/A'
@ -278,9 +278,9 @@ def dump_markdown_metadata(reader: GGUFReader, args: argparse.Namespace) -> None
if not args.no_tensors:
# Group tensors by their prefix and maintain order
tensor_prefix_order = []
tensor_name_to_key = {}
tensor_groups = {}
tensor_prefix_order: list[str] = []
tensor_name_to_key: dict[str, int] = {}
tensor_groups: dict[str, list[ReaderTensor]] = {}
total_elements = sum(tensor.n_elements for tensor in reader.tensors)
# Parsing Tensors Record
@ -320,7 +320,7 @@ def dump_markdown_metadata(reader: GGUFReader, args: argparse.Namespace) -> None
markdown_content += f"### <a name=\"{group.replace('.', '_')}\">{translate_tensor_name(group)} Tensor Group : {element_count_rounded_notation(group_elements)} Elements</a>\n\n"
# Precalculate pretty shape column sizing for visual consistency
prettify_dimension_max_widths = {}
prettify_dimension_max_widths: dict[int, int] = {}
for tensor in tensors:
for i, dimension_size in enumerate(list(tensor.shape) + [1] * (4 - len(tensor.shape))):
if i in prettify_dimension_max_widths:
@ -329,12 +329,12 @@ def dump_markdown_metadata(reader: GGUFReader, args: argparse.Namespace) -> None
prettify_dimension_max_widths[i] = len(str(dimension_size))
# Generate Tensor Layer Table Content
tensor_dump_table = []
tensor_dump_table: list[dict[str, str | int]] = []
for tensor in tensors:
human_friendly_name = translate_tensor_name(tensor.name.replace(".weight", ".(W)").replace(".bias", ".(B)"))
pretty_dimension = ' x '.join(f'{str(d):^{prettify_dimension_max_widths[i]}}' for i, d in enumerate(list(tensor.shape) + [1] * (4 - len(tensor.shape))))
element_count_est = f"({element_count_rounded_notation(tensor.n_elements):>4})"
element_count_string = f"{element_count_est:>6} {tensor.n_elements:^8}"
pretty_dimension = ' x '.join(f'{str(d):>{prettify_dimension_max_widths[i]}}' for i, d in enumerate(list(tensor.shape) + [1] * (4 - len(tensor.shape))))
element_count_est = f"({element_count_rounded_notation(tensor.n_elements):>5})"
element_count_string = f"{element_count_est} {tensor.n_elements:>8}"
type_name_string = f"{tensor.tensor_type.name}"
tensor_dump_table.append({"t_id":tensor_name_to_key[tensor.name], "layer_name":tensor.name, "human_layer_name":human_friendly_name, "element_count":element_count_string, "pretty_dimension":pretty_dimension, "tensor_type":type_name_string})