| 21 | class HFUtilTest(unittest.TestCase): |
| 22 | |
| 23 | def setUp(self): |
| 24 | logger.info('SetUp') |
| 25 | self.api = HubApi() |
| 26 | response, _ = self.api.login(TEST_ACCESS_TOKEN1) |
| 27 | self.user = TEST_MODEL_ORG |
| 28 | print(self.user) |
| 29 | self.create_model_name = '%s/%s_%s' % (self.user, 'test_model_upload', |
| 30 | uuid.uuid4().hex) |
| 31 | logger.info('create %s' % self.create_model_name) |
| 32 | temporary_dir = tempfile.mkdtemp() |
| 33 | self.work_dir = temporary_dir |
| 34 | self.model_dir = os.path.join(temporary_dir, self.create_model_name) |
| 35 | self.repo_path = os.path.join(self.work_dir, 'repo_path') |
| 36 | self.test_folder = os.path.join(temporary_dir, 'test_folder') |
| 37 | self.test_file1 = os.path.join( |
| 38 | os.path.join(temporary_dir, 'test_folder', '1.json')) |
| 39 | self.test_file2 = os.path.join(os.path.join(temporary_dir, '2.json')) |
| 40 | os.makedirs(self.test_folder, exist_ok=True) |
| 41 | with open(self.test_file1, 'w') as f: |
| 42 | f.write('{}') |
| 43 | with open(self.test_file2, 'w') as f: |
| 44 | f.write('{}') |
| 45 | |
| 46 | self.pipeline_qa_context = r""" |
| 47 | Extractive Question Answering is the task of extracting an answer from a text given a question. An example |
| 48 | of a question answering dataset is the SQuAD dataset, which is entirely based on that task. If you would |
| 49 | like to fine-tune a model on a SQuAD task, you may leverage the |
| 50 | examples/pytorch/question-answering/run_squad.py script. |
| 51 | """ |
| 52 | self.pipeline_qa_question = 'What is a good example of a question answering dataset?' |
| 53 | |
| 54 | def tearDown(self): |
| 55 | logger.info('TearDown') |