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update model index and metafile (#1593)
* - * fix dev_scripts * update field name in readme * refactor format in readme
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,10 @@ | ||
| from .job_util import (filter_jobs, get_info_from_id, parse_job_list, | ||
| parse_job_list_from_file) | ||
| from .modelindex import (collate_metrics, dump_yaml_and_check_difference, | ||
| found_table, modelindex_to_dict) | ||
|
|
||
| __all__ = [ | ||
| 'modelindex_to_dict', 'found_table', 'dump_yaml_and_check_difference', | ||
| 'collate_metrics', 'parse_job_list', 'parse_job_list_from_file', | ||
| 'get_info_from_id', 'filter_jobs' | ||
| ] |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,88 @@ | ||
| import os.path as osp | ||
|
|
||
| import mmengine | ||
| from modelindex.models.Collection import Collection | ||
| from modelindex.models.Model import Model | ||
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| def dump_yaml_and_check_difference(obj, file): | ||
| """Dump object to a yaml file, and check if the file content is different | ||
| from the original. | ||
| Args: | ||
| obj (any): The python object to be dumped. | ||
| file (str): YAML filename to dump the object to. | ||
| Returns: | ||
| Bool: If the target YAML file is different from the original. | ||
| """ | ||
|
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| str_dump = mmengine.dump( | ||
| obj, None, file_format='yaml', sort_keys=True, | ||
| line_break='\n') # force use LF | ||
|
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| if osp.isfile(file): | ||
| file_exists = True | ||
| # print(f' exist {file}') | ||
| with open(file, 'r', encoding='utf-8') as f: | ||
| str_orig = f.read() | ||
| else: | ||
| file_exists = False | ||
| str_orig = None | ||
|
|
||
| if file_exists and str_orig == str_dump: | ||
| is_different = False | ||
| else: | ||
| is_different = True | ||
| print(f' update {file}') | ||
| with open(file, 'w', encoding='utf-8') as f: | ||
| f.write(str_dump) | ||
|
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| return is_different | ||
|
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| def collate_metrics(keys): | ||
| """Collect metrics from the first row of the table. | ||
| Args: | ||
| keys (List): Elements in the first row of the table. | ||
| Returns: | ||
| dict: A dict of metrics. | ||
| """ | ||
| used_metrics = dict() | ||
| for idx, key in enumerate(keys): | ||
| if key in ['Model', 'Dataset', 'Training Resources', 'Download']: | ||
| continue | ||
| used_metrics[key] = idx | ||
| return used_metrics | ||
|
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| def found_table(lines, i): | ||
| if i + 1 >= len(lines): | ||
| return False | ||
| if i - 2 < 0 or 'SKIP THIS TABLE' in lines[i - 2]: | ||
| return False | ||
| if lines[i][0] != '|': | ||
| return False | ||
|
|
||
| for c in ['| :', '|:', '|-']: | ||
| if c in lines[i + 1]: | ||
| return True | ||
| return False | ||
|
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|
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| def modelindex_to_dict(model): | ||
| if isinstance(model, Collection): | ||
| result = model.data | ||
| if model.metadata is not None: | ||
| result['Metadata'] = model.metadata.data | ||
| elif isinstance(model, Model): | ||
| result = model.data | ||
| if model.metadata is not None: | ||
| result['Metadata'] = model.metadata.data | ||
| if model.results is not None: | ||
| results_list = [] | ||
| for r in model.results: | ||
| results_list.append(r.data) | ||
| result['Results'] = results_list | ||
| return result |
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