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| # Copyright 2020 The HuggingFace Team. All rights reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| import tempfile | |
| import unittest | |
| import numpy as np | |
| from huggingface_hub import HfFolder, delete_repo | |
| from requests.exceptions import HTTPError | |
| from transformers import BertConfig, is_flax_available | |
| from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax | |
| if is_flax_available(): | |
| import os | |
| from flax.core.frozen_dict import unfreeze | |
| from flax.traverse_util import flatten_dict | |
| from transformers import FlaxBertModel | |
| os.environ["XLA_PYTHON_CLIENT_MEM_FRACTION"] = "0.12" # assumed parallelism: 8 | |
| class FlaxModelPushToHubTester(unittest.TestCase): | |
| def setUpClass(cls): | |
| cls._token = TOKEN | |
| HfFolder.save_token(TOKEN) | |
| def tearDownClass(cls): | |
| try: | |
| delete_repo(token=cls._token, repo_id="test-model-flax") | |
| except HTTPError: | |
| pass | |
| try: | |
| delete_repo(token=cls._token, repo_id="valid_org/test-model-flax-org") | |
| except HTTPError: | |
| pass | |
| def test_push_to_hub(self): | |
| config = BertConfig( | |
| vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37 | |
| ) | |
| model = FlaxBertModel(config) | |
| model.push_to_hub("test-model-flax", use_auth_token=self._token) | |
| new_model = FlaxBertModel.from_pretrained(f"{USER}/test-model-flax") | |
| base_params = flatten_dict(unfreeze(model.params)) | |
| new_params = flatten_dict(unfreeze(new_model.params)) | |
| for key in base_params.keys(): | |
| max_diff = (base_params[key] - new_params[key]).sum().item() | |
| self.assertLessEqual(max_diff, 1e-3, msg=f"{key} not identical") | |
| # Reset repo | |
| delete_repo(token=self._token, repo_id="test-model-flax") | |
| # Push to hub via save_pretrained | |
| with tempfile.TemporaryDirectory() as tmp_dir: | |
| model.save_pretrained(tmp_dir, repo_id="test-model-flax", push_to_hub=True, use_auth_token=self._token) | |
| new_model = FlaxBertModel.from_pretrained(f"{USER}/test-model-flax") | |
| base_params = flatten_dict(unfreeze(model.params)) | |
| new_params = flatten_dict(unfreeze(new_model.params)) | |
| for key in base_params.keys(): | |
| max_diff = (base_params[key] - new_params[key]).sum().item() | |
| self.assertLessEqual(max_diff, 1e-3, msg=f"{key} not identical") | |
| def test_push_to_hub_in_organization(self): | |
| config = BertConfig( | |
| vocab_size=99, hidden_size=32, num_hidden_layers=5, num_attention_heads=4, intermediate_size=37 | |
| ) | |
| model = FlaxBertModel(config) | |
| model.push_to_hub("valid_org/test-model-flax-org", use_auth_token=self._token) | |
| new_model = FlaxBertModel.from_pretrained("valid_org/test-model-flax-org") | |
| base_params = flatten_dict(unfreeze(model.params)) | |
| new_params = flatten_dict(unfreeze(new_model.params)) | |
| for key in base_params.keys(): | |
| max_diff = (base_params[key] - new_params[key]).sum().item() | |
| self.assertLessEqual(max_diff, 1e-3, msg=f"{key} not identical") | |
| # Reset repo | |
| delete_repo(token=self._token, repo_id="valid_org/test-model-flax-org") | |
| # Push to hub via save_pretrained | |
| with tempfile.TemporaryDirectory() as tmp_dir: | |
| model.save_pretrained( | |
| tmp_dir, repo_id="valid_org/test-model-flax-org", push_to_hub=True, use_auth_token=self._token | |
| ) | |
| new_model = FlaxBertModel.from_pretrained("valid_org/test-model-flax-org") | |
| base_params = flatten_dict(unfreeze(model.params)) | |
| new_params = flatten_dict(unfreeze(new_model.params)) | |
| for key in base_params.keys(): | |
| max_diff = (base_params[key] - new_params[key]).sum().item() | |
| self.assertLessEqual(max_diff, 1e-3, msg=f"{key} not identical") | |
| def check_models_equal(model1, model2): | |
| models_are_equal = True | |
| flat_params_1 = flatten_dict(model1.params) | |
| flat_params_2 = flatten_dict(model2.params) | |
| for key in flat_params_1.keys(): | |
| if np.sum(np.abs(flat_params_1[key] - flat_params_2[key])) > 1e-4: | |
| models_are_equal = False | |
| return models_are_equal | |
| class FlaxModelUtilsTest(unittest.TestCase): | |
| def test_model_from_pretrained_subfolder(self): | |
| config = BertConfig.from_pretrained("hf-internal-testing/tiny-bert-flax-only") | |
| model = FlaxBertModel(config) | |
| subfolder = "bert" | |
| with tempfile.TemporaryDirectory() as tmp_dir: | |
| model.save_pretrained(os.path.join(tmp_dir, subfolder)) | |
| with self.assertRaises(OSError): | |
| _ = FlaxBertModel.from_pretrained(tmp_dir) | |
| model_loaded = FlaxBertModel.from_pretrained(tmp_dir, subfolder=subfolder) | |
| self.assertTrue(check_models_equal(model, model_loaded)) | |
| def test_model_from_pretrained_subfolder_sharded(self): | |
| config = BertConfig.from_pretrained("hf-internal-testing/tiny-bert-flax-only") | |
| model = FlaxBertModel(config) | |
| subfolder = "bert" | |
| with tempfile.TemporaryDirectory() as tmp_dir: | |
| model.save_pretrained(os.path.join(tmp_dir, subfolder), max_shard_size="10KB") | |
| with self.assertRaises(OSError): | |
| _ = FlaxBertModel.from_pretrained(tmp_dir) | |
| model_loaded = FlaxBertModel.from_pretrained(tmp_dir, subfolder=subfolder) | |
| self.assertTrue(check_models_equal(model, model_loaded)) | |
| def test_model_from_pretrained_hub_subfolder(self): | |
| subfolder = "bert" | |
| model_id = "hf-internal-testing/tiny-random-bert-subfolder" | |
| with self.assertRaises(OSError): | |
| _ = FlaxBertModel.from_pretrained(model_id) | |
| model = FlaxBertModel.from_pretrained(model_id, subfolder=subfolder) | |
| self.assertIsNotNone(model) | |
| def test_model_from_pretrained_hub_subfolder_sharded(self): | |
| subfolder = "bert" | |
| model_id = "hf-internal-testing/tiny-random-bert-sharded-subfolder" | |
| with self.assertRaises(OSError): | |
| _ = FlaxBertModel.from_pretrained(model_id) | |
| model = FlaxBertModel.from_pretrained(model_id, subfolder=subfolder) | |
| self.assertIsNotNone(model) | |