Datasets:
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
< 1K
Tags:
Large Language Models
LLM Evaluation
Sequential Reasoning
Scaling Laws
Synthetic Benchmarks
Commonsense Reasoning
License:
| import string | |
| def generate_letter_number_list(): | |
| # spreadsheet style column names A-Z, AA-AB-ZZ, AAA-AAB-ZZZ, etc. | |
| result = [letter for letter in string.ascii_uppercase] | |
| for letter in string.ascii_uppercase: | |
| for letter2 in string.ascii_uppercase: | |
| result.append(f"{letter}{letter2}") | |
| return result | |
| class NameGenerator: | |
| def __init__(self, N, M): | |
| self.COLNAMES = generate_letter_number_list() | |
| self.Col = lambda x: self.COLNAMES[x] | |
| self.N = N | |
| self.M = M | |
| def get_name(self, cell): | |
| return f"{self.Col(cell[0])}{self.M - cell[1]}" | |
| if __name__ == "__main__": | |
| name_generator = NameGenerator() | |
| cell = (100, 200) | |
| print(name_generator.get_name(cell)) | |