Datasets:
Tasks:
Translation
Modalities:
Text
Formats:
json
Languages:
English
Size:
10K - 100K
Tags:
code
License:
| from random_data import generate_random_byte_array | |
| import json | |
| import os | |
| import random | |
| import base64 | |
| def base64_encode_byte_array(byte_array): | |
| return base64.b64encode(byte_array).decode('utf-8') | |
| def generate_dataset_item(seed): | |
| length = random.Random(seed + 1000).randint(0, 127) | |
| byte_array = generate_random_byte_array(length=length, seed=seed + 1001) | |
| input_formats = [ | |
| 'hex', | |
| 'json' | |
| ] | |
| input_format = random.Random(seed + 1002).choice(input_formats) | |
| names_hex = [ | |
| 'Hexadecimal', | |
| 'hexadecimal', | |
| 'hex', | |
| 'Hex', | |
| 'HEX', | |
| ] | |
| names_json = [ | |
| 'Json', | |
| 'json', | |
| 'JSON', | |
| ] | |
| name_input = None | |
| if input_format == 'hex': | |
| name_input = random.Random(seed + 1003).choice(names_hex) | |
| else: | |
| if input_format == 'json': | |
| name_input = random.Random(seed + 1004).choice(names_json) | |
| name_outputs = [ | |
| 'base64', | |
| 'Base64', | |
| 'BASE64', | |
| ] | |
| name_output = random.Random(seed + 1005).choice(name_outputs) | |
| instructions = [ | |
| f'Encode {name_input} to {name_output}', | |
| f'encode {name_input} to {name_output}', | |
| f'convert {name_input} to {name_output}', | |
| f'Convert {name_input} to {name_output}', | |
| f'Transform {name_input} to {name_output}', | |
| f'transform {name_input} to {name_output}', | |
| f'Change {name_input} to {name_output}', | |
| f'change {name_input} to {name_output}', | |
| f'{name_input} to {name_output}', | |
| f'{name_output} from {name_input}', | |
| ] | |
| instruction = random.Random(seed + 1006).choice(instructions) | |
| output = base64_encode_byte_array(byte_array) | |
| input = None | |
| if input_format == 'hex': | |
| input = byte_array.hex() | |
| else: | |
| if input_format == 'json': | |
| input = json.dumps(list(byte_array), separators=(',', ':')) | |
| dict = { | |
| 'instruction': instruction, | |
| 'input': input, | |
| 'output': output | |
| } | |
| return dict | |
| def generate_dataset(max_num_samples=1000, max_byte_size=1024*1024, seed_start=500000000): | |
| dataset = [] | |
| dataset_byte_size = 0 | |
| for i in range(max_num_samples): | |
| item = generate_dataset_item(seed_start + i) | |
| bytes = len(json.dumps(item)) | |
| if dataset_byte_size + bytes > max_byte_size: | |
| break | |
| dataset_byte_size += bytes | |
| dataset.append(item) | |
| return dataset | |
| dataset = generate_dataset( | |
| max_num_samples=50000, | |
| max_byte_size=1024*1024*20, | |
| ) | |
| # Save dataset to file | |
| filename = 'data.jsonl' | |
| with open(filename, 'w') as f: | |
| for item in dataset: | |
| f.write(json.dumps(item) + '\n') | |
| # Summary | |
| file_size = os.path.getsize(filename) | |
| print(f"Generated {len(dataset)} samples, saved to {filename}, file size: {file_size} bytes.") | |