17bdb1a60b
* LLM: add whisper models into nightly test * small fix * small fix * add more whisper models * test all cases * test specific cases * collect the csv * store the resut * to html * small fix * small test * test all cases * modify whisper_csv_to_html
50 lines
1.7 KiB
Python
50 lines
1.7 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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# Python program to concat CSVs
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import os
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import sys
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import argparse
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import pandas as pd
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from datetime import date
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def main():
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parser = argparse.ArgumentParser(description="concat .csv files")
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parser.add_argument("-i", "--input_path", type=str, dest="input_path",
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help="The directory which stores the original CSV files", default="./")
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parser.add_argument("-o", "--output_path", type=str, dest="output_path",
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help="The directory which stores the concated CSV file", default="./")
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args = parser.parse_args()
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csv_files = []
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for file_name in os.listdir(args.input_path):
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file_path = os.path.join(args.input_path, file_name)
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if os.path.isfile(file_path) and file_name.endswith(".csv"):
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csv_files.append(file_path)
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csv_files.sort()
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merged_df = pd.concat([pd.read_csv(file) for file in csv_files], ignore_index=True)
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merged_df.reset_index(drop=True, inplace=True)
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today = date.today()
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csv_name = f'whisper-{today}.csv'
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output_file_path = os.path.join(args.output_path, csv_name)
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merged_df.to_csv(output_file_path)
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if __name__ == "__main__":
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sys.exit(main())
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