| """ |
| test module for the axolotl.utis.data module |
| """ |
| import unittest |
|
|
| from transformers import LlamaTokenizer |
|
|
| from axolotl.utils.data import encode_pretraining, md5 |
|
|
|
|
| class TestEncodePretraining(unittest.TestCase): |
| """ |
| test class for encode pretraining and md5 helper |
| """ |
|
|
| def setUp(self): |
| self.tokenizer = LlamaTokenizer.from_pretrained("huggyllama/llama-7b") |
| self.tokenizer.add_special_tokens( |
| { |
| "eos_token": "</s>", |
| "bos_token": "<s>", |
| "unk_token": "<unk>", |
| "pad_token": "<pad>", |
| } |
| ) |
| self.max_tokens = 15 |
|
|
| def test_encode_pretraining(self): |
| examples = { |
| "text": [ |
| "Hello, world!", |
| "Nice to meet you.", |
| "lorem ipsum dolor sit amet.", |
| "Nice to meet you again!.", |
| "hello, hello", |
| ] |
| } |
| result = encode_pretraining(self.tokenizer, self.max_tokens, examples["text"]) |
|
|
| self.assertEqual(len(result["input_ids"]), 3) |
|
|
| |
| self.assertEqual(len(result["input_ids"][0]), self.max_tokens) |
| self.assertEqual(len(result["attention_mask"][0]), self.max_tokens) |
|
|
| |
| |
| self.assertEqual(result["input_ids"][0][0], self.tokenizer.bos_token_id) |
| self.assertEqual(result["input_ids"][0][5], self.tokenizer.eos_token_id) |
| self.assertEqual(result["input_ids"][0][6], self.tokenizer.pad_token_id) |
| |
| self.assertEqual(result["input_ids"][0][7], self.tokenizer.bos_token_id) |
| self.assertEqual(result["input_ids"][0][13], self.tokenizer.eos_token_id) |
| self.assertEqual(result["input_ids"][0][14], self.tokenizer.pad_token_id) |
|
|
| def test_md5(self): |
| self.assertEqual(md5("hello world"), "5eb63bbbe01eeed093cb22bb8f5acdc3") |
| self.assertEqual( |
| md5("hello world", "utf-8"), "5eb63bbbe01eeed093cb22bb8f5acdc3" |
| ) |
|
|
|
|
| if __name__ == "__main__": |
| unittest.main() |
|
|
