0c8d3c9830
* Add C-Eval HTML report * Fix C-Eval workflow pr trigger path * Fix C-Eval workflow typos * Add permissions to C-Eval workflow * Fix C-Eval workflow typo * Add pandas dependency * Fix C-Eval workflow typo
94 lines
3.2 KiB
Python
94 lines
3.2 KiB
Python
#
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# Copyright 2016 The BigDL Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import os
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import pdb
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import sys
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import csv
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import json
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import datetime
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import pandas as pd
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if __name__ == '__main__':
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result_path = sys.argv[1]
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output_path = sys.argv[2]
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column_size = [25, 15, 10, 18, 15, 10, 10, 10]
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pad_string = lambda x, l: [i.ljust(j) for i, j in zip(x, l)]
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column_names = ["Model Name", "Precision", "STEM", "Social Science", "Humanities", "Other", "Hard", "Average"]
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print(f'\nDumping results for C-Eval score:\n')
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print(' '.join(pad_string(column_names, column_size)))
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print()
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file_lst = os.listdir(result_path)
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file_lst = [f'{result_path}/{i}' for i in file_lst]
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organized_dict = {} # {'Qwen-7B': {'sym_int4': [], 'mixed_fp4': }}
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for file in file_lst:
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# Read the JSON file
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with open(file, 'r') as file:
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data = json.load(file)
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result_lst = [data['Model Name'], data['Precision']]
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result_lst += data['Results']
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# store in the organized dictionary
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try:
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organized_dict[data['Model Name']][data['Precision']] = result_lst
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except:
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organized_dict[data['Model Name']] = {}
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organized_dict[data['Model Name']][data['Precision']] = result_lst
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# define the print precision order
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model_order = ['chatglm2-6b', 'chinese-llama2-7b', 'Qwen-7B-Chat']
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precision_order = ['sym_int4', 'fp8_e5m2']
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# print the results
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for model_name in organized_dict.keys():
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for precision in precision_order:
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try:
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# print the result
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print(' '.join(pad_string(organized_dict[model_name][precision], column_size)))
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except KeyError:
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pass
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# separate between models
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print()
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# initialize the csv file
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current_date = datetime.datetime.now().strftime("%Y-%m-%d")
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file_name = f'results_{current_date}.csv'
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file_name = os.path.join(output_path, file_name) if output_path else file_name
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print('Writing to', file_name)
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with open(file_name, mode='w', newline='') as csv_file:
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writer = csv.writer(csv_file)
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headers = ["Model Name", "Precision", 'STEM', 'Social Science', 'Humanities', 'Other', 'Hard', 'Average']
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writer.writerow(headers)
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# print the results
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for model_name in model_order:
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for precision in precision_order:
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try:
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# write the result to the csv row
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writer.writerow(organized_dict[model_name][precision])
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except KeyError:
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writer.writerow([model_name, precision]+[pd.NA for i in range(len(headers[2:]))])
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