| import os | |
| import glob | |
| import pandas as pd | |
| # Directory containing the CSV files | |
| csv_dir = 'runs_jsons/loss_epoch' | |
| # Find all CSV files in the directory | |
| csv_files = glob.glob(os.path.join(csv_dir, '*.csv')) | |
| total_time = 0.0 | |
| for csv_file in csv_files: | |
| df = pd.read_csv(csv_file) | |
| # Assuming the time column is named 'time' or similar | |
| # Adjust the column name if needed | |
| time_col = None | |
| for col in df.columns: | |
| if 'time' in col.lower(): | |
| time_col = col | |
| break | |
| # print(df.columns) | |
| if time_col is None: | |
| continue # Skip if no time column found | |
| first_time = df[time_col].iloc[0] | |
| last_time = df[time_col].iloc[-1] | |
| total_time += (last_time - first_time) | |
| print(f"Cumulative time spent: {total_time} seconds") | |
| hours = 1/3600 | |
| days = hours / 24 | |
| print(f"Cumulative time spent: {total_time * hours} hours") | |
| print(f"Cumulative time spent: {total_time * days} days") |