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| import unittest |
|
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| from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available |
| from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow |
|
|
|
|
| if is_flax_available(): |
| import jax |
|
|
| from transformers.models.auto.modeling_flax_auto import FlaxAutoModel |
| from transformers.models.bert.modeling_flax_bert import FlaxBertModel |
| from transformers.models.roberta.modeling_flax_roberta import FlaxRobertaModel |
|
|
|
|
| @require_flax |
| class FlaxAutoModelTest(unittest.TestCase): |
| @slow |
| def test_bert_from_pretrained(self): |
| for model_name in ["google-bert/bert-base-cased", "google-bert/bert-large-uncased"]: |
| with self.subTest(model_name): |
| config = AutoConfig.from_pretrained(model_name) |
| self.assertIsNotNone(config) |
| self.assertIsInstance(config, BertConfig) |
|
|
| model = FlaxAutoModel.from_pretrained(model_name) |
| self.assertIsNotNone(model) |
| self.assertIsInstance(model, FlaxBertModel) |
|
|
| @slow |
| def test_roberta_from_pretrained(self): |
| for model_name in ["FacebookAI/roberta-base", "FacebookAI/roberta-large"]: |
| with self.subTest(model_name): |
| config = AutoConfig.from_pretrained(model_name) |
| self.assertIsNotNone(config) |
| self.assertIsInstance(config, BertConfig) |
|
|
| model = FlaxAutoModel.from_pretrained(model_name) |
| self.assertIsNotNone(model) |
| self.assertIsInstance(model, FlaxRobertaModel) |
|
|
| @slow |
| def test_bert_jax_jit(self): |
| for model_name in ["google-bert/bert-base-cased", "google-bert/bert-large-uncased"]: |
| tokenizer = AutoTokenizer.from_pretrained(model_name) |
| model = FlaxBertModel.from_pretrained(model_name) |
| tokens = tokenizer("Do you support jax jitted function?", return_tensors=TensorType.JAX) |
|
|
| @jax.jit |
| def eval(**kwargs): |
| return model(**kwargs) |
|
|
| eval(**tokens).block_until_ready() |
|
|
| @slow |
| def test_roberta_jax_jit(self): |
| for model_name in ["FacebookAI/roberta-base", "FacebookAI/roberta-large"]: |
| tokenizer = AutoTokenizer.from_pretrained(model_name) |
| model = FlaxRobertaModel.from_pretrained(model_name) |
| tokens = tokenizer("Do you support jax jitted function?", return_tensors=TensorType.JAX) |
|
|
| @jax.jit |
| def eval(**kwargs): |
| return model(**kwargs) |
|
|
| eval(**tokens).block_until_ready() |
|
|
| def test_repo_not_found(self): |
| with self.assertRaisesRegex( |
| EnvironmentError, "bert-base is not a local folder and is not a valid model identifier" |
| ): |
| _ = FlaxAutoModel.from_pretrained("bert-base") |
|
|
| def test_revision_not_found(self): |
| with self.assertRaisesRegex( |
| EnvironmentError, r"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)" |
| ): |
| _ = FlaxAutoModel.from_pretrained(DUMMY_UNKNOWN_IDENTIFIER, revision="aaaaaa") |
|
|
| def test_model_file_not_found(self): |
| with self.assertRaisesRegex( |
| EnvironmentError, |
| "hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack", |
| ): |
| _ = FlaxAutoModel.from_pretrained("hf-internal-testing/config-no-model") |
|
|
| def test_model_from_pt_suggestion(self): |
| with self.assertRaisesRegex(EnvironmentError, "Use `from_pt=True` to load this model"): |
| _ = FlaxAutoModel.from_pretrained("hf-internal-testing/tiny-bert-pt-only") |
|
|