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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 unittest | |
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 | |
class FlaxAutoModelTest(unittest.TestCase): | |
def test_bert_from_pretrained(self): | |
for model_name in ["bert-base-cased", "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) | |
def test_roberta_from_pretrained(self): | |
for model_name in ["roberta-base", "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) | |
def test_bert_jax_jit(self): | |
for model_name in ["bert-base-cased", "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) | |
def eval(**kwargs): | |
return model(**kwargs) | |
eval(**tokens).block_until_ready() | |
def test_roberta_jax_jit(self): | |
for model_name in ["roberta-base", "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) | |
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") | |