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[Tokenization] Fix #5181 - make #5155 more explicit - move back the default logging level in tests to WARNING (#5252)

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* fix-5181

Padding to max sequence length while truncation to another length was wrong on slow tokenizers

* clean up and fix #5155

* fix XLM test

* Fix tests for Transfo-XL

* logging only above WARNING in tests

* switch slow tokenizers tests in @slow

* fix Marian truncation tokenization test

* style and quality

* make the test a lot faster by limiting the sequence length used in tests
This commit is contained in:
Thomas Wolf
2020-06-25 17:24:28 +02:00
committed by GitHub
parent e008d520bb
commit 27cf1d97f0
9 changed files with 134 additions and 75 deletions
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12
tests/test_modeling_auto.py
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@@ -14,7 +14,6 @@
# limitations under the License.
import logging
import unittest
from transformers import is_torch_available
@@ -67,7 +66,6 @@ if is_torch_available():
class AutoModelTest(unittest.TestCase):
@slow
def test_model_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
for model_name in BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
config = AutoConfig.from_pretrained(model_name)
self.assertIsNotNone(config)
@@ -82,7 +80,6 @@ class AutoModelTest(unittest.TestCase):
@slow
def test_model_for_pretraining_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
for model_name in BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
config = AutoConfig.from_pretrained(model_name)
self.assertIsNotNone(config)
@@ -98,7 +95,6 @@ class AutoModelTest(unittest.TestCase):
@slow
def test_lmhead_model_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
for model_name in BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
config = AutoConfig.from_pretrained(model_name)
self.assertIsNotNone(config)
@@ -111,7 +107,6 @@ class AutoModelTest(unittest.TestCase):
@slow
def test_model_for_causal_lm(self):
logging.basicConfig(level=logging.INFO)
for model_name in GPT2_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
config = AutoConfig.from_pretrained(model_name)
self.assertIsNotNone(config)
@@ -124,7 +119,6 @@ class AutoModelTest(unittest.TestCase):
@slow
def test_model_for_masked_lm(self):
logging.basicConfig(level=logging.INFO)
for model_name in BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
config = AutoConfig.from_pretrained(model_name)
self.assertIsNotNone(config)
@@ -137,7 +131,6 @@ class AutoModelTest(unittest.TestCase):
@slow
def test_model_for_encoder_decoder_lm(self):
logging.basicConfig(level=logging.INFO)
for model_name in T5_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
config = AutoConfig.from_pretrained(model_name)
self.assertIsNotNone(config)
@@ -150,7 +143,6 @@ class AutoModelTest(unittest.TestCase):
@slow
def test_sequence_classification_model_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
for model_name in BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
config = AutoConfig.from_pretrained(model_name)
self.assertIsNotNone(config)
@@ -165,7 +157,6 @@ class AutoModelTest(unittest.TestCase):
@slow
def test_question_answering_model_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
for model_name in BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
config = AutoConfig.from_pretrained(model_name)
self.assertIsNotNone(config)
@@ -178,7 +169,6 @@ class AutoModelTest(unittest.TestCase):
@slow
def test_token_classification_model_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
for model_name in BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
config = AutoConfig.from_pretrained(model_name)
self.assertIsNotNone(config)
@@ -190,14 +180,12 @@ class AutoModelTest(unittest.TestCase):
self.assertIsInstance(model, BertForTokenClassification)
def test_from_pretrained_identifier(self):
logging.basicConfig(level=logging.INFO)
model = AutoModelWithLMHead.from_pretrained(SMALL_MODEL_IDENTIFIER)
self.assertIsInstance(model, BertForMaskedLM)
self.assertEqual(model.num_parameters(), 14830)
self.assertEqual(model.num_parameters(only_trainable=True), 14830)
def test_from_identifier_from_model_type(self):
logging.basicConfig(level=logging.INFO)
model = AutoModelWithLMHead.from_pretrained(DUMMY_UNKWOWN_IDENTIFIER)
self.assertIsInstance(model, RobertaForMaskedLM)
self.assertEqual(model.num_parameters(), 14830)