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| import os |
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| from torch.utils import data |
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| from tests.e2e.envs.digit_completion import DigitCompletion |
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| if __name__ == "__main__": |
| simple_task = DigitCompletion(max_number=9, max_diff=9, max_num_in_response=9) |
| all_prompts = simple_task.get_all_prompts() |
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| train_data, test_data = data.random_split(all_prompts, lengths=[0.8, 0.2]) |
| train_data = list(train_data) |
| test_data = list(test_data) |
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| train_data = [[{"role": "user", "content": str(item)}] for item in train_data] |
| test_data = [[{"role": "user", "content": str(item)}] for item in test_data] |
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| print(f"Size of train: {len(train_data)}, size of test: {len(test_data)}") |
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| train_data = {"prompt": train_data} |
| test_data = {"prompt": test_data} |
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| model_folder = os.path.join(os.path.dirname(os.path.abspath(__file__))) |
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| import pandas as pd |
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| train_data_frame = pd.DataFrame(train_data) |
| test_data_frame = pd.DataFrame(test_data) |
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| train_data_frame.to_parquet(os.path.join(model_folder, "train.parquet")) |
| test_data_frame.to_parquet(os.path.join(model_folder, "test.parquet")) |
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