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| import csv | |
| import json | |
| # Given mapping | |
| mapping = { | |
| "humaneval": "humaneval-python", | |
| "multiple-lua": "lua", | |
| "multiple-java": "java", | |
| "multiple-jl": "julia", | |
| "multiple-cpp": "cpp", | |
| "multiple-rs": "rust", | |
| "multiple-rkt": "racket", | |
| "multiple-php": "php", | |
| "multiple-r": "r", | |
| "multiple-js": "javascript", | |
| "multiple-d": "d", | |
| "multiple-swift": "swift" | |
| } | |
| BASE_PATH = "/fsx/loubna/projects/bigcode-models-leaderboard" | |
| # JSON Data (replace this with your actual loaded JSON) | |
| json_path = f"/fsx/loubna/projects/bigcode-models-leaderboard/community_results/m-a-p_OpenCodeInterpreter-DS-33B_Anitaliu98/m-a-p_OpenCodeInterpreter-DS-33B_Anitaliu98.json" | |
| with open(json_path, "r") as f: | |
| json_data = json.load(f) | |
| parsed_data = json_data['results'] | |
| # Create a dictionary with column names as keys and empty values | |
| csv_columns = ["Models", "Size (B)", "Throughput (tokens/s)", "Seq_length", "#Languages", "humaneval-python", "java", "javascript", "cpp", "php", "julia", "d", "lua", "r", "racket", "rust", "swift", "Throughput (tokens/s) bs=50", "Peak Memory (MB)"] | |
| row_data = {col: '' for col in csv_columns} | |
| # Fill the dictionary with data from the JSON | |
| for item in parsed_data: | |
| csv_col = mapping.get(item['task']) | |
| if csv_col: | |
| row_data[csv_col] = round(item['pass@1'] * 100, 2) | |
| # Set model name under the 'Models' column | |
| row_data['Models'] = json_data['meta']['model'] | |
| # Write to CSV | |
| csv_file = f"{BASE_PATH}/data/raw_scores.csv" | |
| with open(csv_file, 'a', newline='') as csvfile: | |
| writer = csv.DictWriter(csvfile, fieldnames=row_data.keys()) | |
| writer.writerow(row_data) | |
| # print last 3 rows in csv | |
| with open(csv_file, 'r') as f: | |
| lines = f.readlines() | |
| for line in lines[-3:]: | |
| print(line) | |