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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 contextlib | |
| import importlib | |
| import io | |
| import unittest | |
| import transformers | |
| # Try to import everything from transformers to ensure every object can be loaded. | |
| from transformers import * # noqa F406 | |
| from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch | |
| from transformers.utils import ContextManagers, find_labels, is_flax_available, is_tf_available, is_torch_available | |
| if is_torch_available(): | |
| from transformers import BertForPreTraining, BertForQuestionAnswering, BertForSequenceClassification | |
| if is_tf_available(): | |
| from transformers import TFBertForPreTraining, TFBertForQuestionAnswering, TFBertForSequenceClassification | |
| if is_flax_available(): | |
| from transformers import FlaxBertForPreTraining, FlaxBertForQuestionAnswering, FlaxBertForSequenceClassification | |
| MODEL_ID = DUMMY_UNKNOWN_IDENTIFIER | |
| # An actual model hosted on huggingface.co | |
| REVISION_ID_DEFAULT = "main" | |
| # Default branch name | |
| REVISION_ID_ONE_SPECIFIC_COMMIT = "f2c752cfc5c0ab6f4bdec59acea69eefbee381c2" | |
| # One particular commit (not the top of `main`) | |
| REVISION_ID_INVALID = "aaaaaaa" | |
| # This commit does not exist, so we should 404. | |
| PINNED_SHA1 = "d9e9f15bc825e4b2c9249e9578f884bbcb5e3684" | |
| # Sha-1 of config.json on the top of `main`, for checking purposes | |
| PINNED_SHA256 = "4b243c475af8d0a7754e87d7d096c92e5199ec2fe168a2ee7998e3b8e9bcb1d3" | |
| # Sha-256 of pytorch_model.bin on the top of `main`, for checking purposes | |
| # Dummy contexts to test `ContextManagers` | |
| def context_en(): | |
| print("Welcome!") | |
| yield | |
| print("Bye!") | |
| def context_fr(): | |
| print("Bonjour!") | |
| yield | |
| print("Au revoir!") | |
| class TestImportMechanisms(unittest.TestCase): | |
| def test_module_spec_available(self): | |
| # If the spec is missing, importlib would not be able to import the module dynamically. | |
| assert transformers.__spec__ is not None | |
| assert importlib.util.find_spec("transformers") is not None | |
| class GenericUtilTests(unittest.TestCase): | |
| def test_context_managers_no_context(self, mock_stdout): | |
| with ContextManagers([]): | |
| print("Transformers are awesome!") | |
| # The print statement adds a new line at the end of the output | |
| self.assertEqual(mock_stdout.getvalue(), "Transformers are awesome!\n") | |
| def test_context_managers_one_context(self, mock_stdout): | |
| with ContextManagers([context_en()]): | |
| print("Transformers are awesome!") | |
| # The output should be wrapped with an English welcome and goodbye | |
| self.assertEqual(mock_stdout.getvalue(), "Welcome!\nTransformers are awesome!\nBye!\n") | |
| def test_context_managers_two_context(self, mock_stdout): | |
| with ContextManagers([context_fr(), context_en()]): | |
| print("Transformers are awesome!") | |
| # The output should be wrapped with an English and French welcome and goodbye | |
| self.assertEqual(mock_stdout.getvalue(), "Bonjour!\nWelcome!\nTransformers are awesome!\nBye!\nAu revoir!\n") | |
| def test_find_labels_pt(self): | |
| self.assertEqual(find_labels(BertForSequenceClassification), ["labels"]) | |
| self.assertEqual(find_labels(BertForPreTraining), ["labels", "next_sentence_label"]) | |
| self.assertEqual(find_labels(BertForQuestionAnswering), ["start_positions", "end_positions"]) | |
| # find_labels works regardless of the class name (it detects the framework through inheritance) | |
| class DummyModel(BertForSequenceClassification): | |
| pass | |
| self.assertEqual(find_labels(DummyModel), ["labels"]) | |
| def test_find_labels_tf(self): | |
| self.assertEqual(find_labels(TFBertForSequenceClassification), ["labels"]) | |
| self.assertEqual(find_labels(TFBertForPreTraining), ["labels", "next_sentence_label"]) | |
| self.assertEqual(find_labels(TFBertForQuestionAnswering), ["start_positions", "end_positions"]) | |
| # find_labels works regardless of the class name (it detects the framework through inheritance) | |
| class DummyModel(TFBertForSequenceClassification): | |
| pass | |
| self.assertEqual(find_labels(DummyModel), ["labels"]) | |
| def test_find_labels_flax(self): | |
| # Flax models don't have labels | |
| self.assertEqual(find_labels(FlaxBertForSequenceClassification), []) | |
| self.assertEqual(find_labels(FlaxBertForPreTraining), []) | |
| self.assertEqual(find_labels(FlaxBertForQuestionAnswering), []) | |
| # find_labels works regardless of the class name (it detects the framework through inheritance) | |
| class DummyModel(FlaxBertForSequenceClassification): | |
| pass | |
| self.assertEqual(find_labels(DummyModel), []) | |