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fix tests - flagged as slow all the tests downloading from AWS

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This commit is contained in:
thomwolf 2019-11-04 16:03:36 +01:00
parent f02805da6f
commit b340a910ed
11 changed files with 21 additions and 7 deletions
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2
transformers/modeling_roberta.py
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@ -173,7 +173,7 @@ class RobertaModel(BertModel):
return self.embeddings.word_embeddings
def set_input_embeddings(self, value):
self.embeddings.word_emebddings = value
self.embeddings.word_embeddings = value
@add_start_docstrings("""RoBERTa Model with a `language modeling` head on top. """,
ROBERTA_START_DOCSTRING, ROBERTA_INPUTS_DOCSTRING)

4
transformers/tests/modeling_auto_test.py
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@ -38,6 +38,7 @@ else:
class AutoModelTest(unittest.TestCase):
@pytest.mark.slow
def test_model_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
for model_name in list(BERT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
@ -52,6 +53,7 @@ class AutoModelTest(unittest.TestCase):
for value in loading_info.values():
self.assertEqual(len(value), 0)
@pytest.mark.slow
def test_lmhead_model_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
for model_name in list(BERT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
@ -64,6 +66,7 @@ class AutoModelTest(unittest.TestCase):
self.assertIsNotNone(model)
self.assertIsInstance(model, BertForMaskedLM)
@pytest.mark.slow
def test_sequence_classification_model_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
for model_name in list(BERT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
@ -76,6 +79,7 @@ class AutoModelTest(unittest.TestCase):
self.assertIsNotNone(model)
self.assertIsInstance(model, BertForSequenceClassification)
@pytest.mark.slow
def test_question_answering_model_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
for model_name in list(BERT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:

8
transformers/tests/modeling_common_test.py
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@ -429,12 +429,6 @@ class CommonTestCases:
list(hidden_states[0].shape[-2:]),
[self.model_tester.seq_length, self.model_tester.hidden_size])
def test_debug(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
model_embed = model.resize_token_embeddings(config.vocab_size + 10)
def test_resize_tokens_embeddings(self):
original_config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
if not self.test_resize_embeddings:
@ -703,6 +697,7 @@ class CommonTestCases:
config_and_inputs = self.prepare_config_and_inputs()
self.create_and_check_presents(*config_and_inputs)
@pytest.mark.slow
def run_slow_tests(self):
self.create_and_check_model_from_pretrained()
@ -776,6 +771,7 @@ def floats_tensor(shape, scale=1.0, rng=None, name=None):
class ModelUtilsTest(unittest.TestCase):
@pytest.mark.slow
def test_model_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
for model_name in list(BERT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:

1
transformers/tests/modeling_encoder_decoder_test.py
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@ -27,6 +27,7 @@ else:
class EncoderDecoderModelTest(unittest.TestCase):
@pytest.mark.slow
def test_model2model_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
for model_name in list(BERT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:

1
transformers/tests/tokenization_auto_test.py
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@ -26,6 +26,7 @@ from transformers import BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, GPT2_PRETRAINED_CON
class AutoTokenizerTest(unittest.TestCase):
@pytest.mark.slow
def test_tokenizer_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
for model_name in list(BERT_PRETRAINED_CONFIG_ARCHIVE_MAP.keys())[:1]:

2
transformers/tests/tokenization_bert_test.py
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@ -16,6 +16,7 @@ from __future__ import absolute_import, division, print_function, unicode_litera
import os
import unittest
import pytest
from io import open
from transformers.tokenization_bert import (BasicTokenizer,
@ -125,6 +126,7 @@ class BertTokenizationTest(CommonTestCases.CommonTokenizerTester):
self.assertFalse(_is_punctuation(u"A"))
self.assertFalse(_is_punctuation(u" "))
@pytest.mark.slow
def test_sequence_builders(self):
tokenizer = self.tokenizer_class.from_pretrained("bert-base-uncased")

2
transformers/tests/tokenization_distilbert_test.py
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@ -16,6 +16,7 @@ from __future__ import absolute_import, division, print_function, unicode_litera
import os
import unittest
import pytest
from io import open
from transformers.tokenization_distilbert import (DistilBertTokenizer)
@ -30,6 +31,7 @@ class DistilBertTokenizationTest(BertTokenizationTest):
def get_tokenizer(self, **kwargs):
return DistilBertTokenizer.from_pretrained(self.tmpdirname, **kwargs)
@pytest.mark.slow
def test_sequence_builders(self):
tokenizer = DistilBertTokenizer.from_pretrained("distilbert-base-uncased")

2
transformers/tests/tokenization_roberta_test.py
View File

@ -17,6 +17,7 @@ from __future__ import absolute_import, division, print_function, unicode_litera
import os
import json
import unittest
import pytest
from io import open
from transformers.tokenization_roberta import RobertaTokenizer, VOCAB_FILES_NAMES
@ -78,6 +79,7 @@ class RobertaTokenizationTest(CommonTestCases.CommonTokenizerTester):
[0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]
)
@pytest.mark.slow
def test_sequence_builders(self):
tokenizer = RobertaTokenizer.from_pretrained("roberta-base")

2
transformers/tests/tokenization_utils_test.py
View File

@ -18,11 +18,13 @@ from __future__ import print_function
import unittest
import six
import pytest
from transformers import PreTrainedTokenizer
from transformers.tokenization_gpt2 import GPT2Tokenizer
class TokenizerUtilsTest(unittest.TestCase):
@pytest.mark.slow
def check_tokenizer_from_pretrained(self, tokenizer_class):
s3_models = list(tokenizer_class.max_model_input_sizes.keys())
for model_name in s3_models[:1]:

2
transformers/tests/tokenization_xlm_test.py
View File

@ -17,6 +17,7 @@ from __future__ import absolute_import, division, print_function, unicode_litera
import os
import unittest
import json
import pytest
from transformers.tokenization_xlm import XLMTokenizer, VOCAB_FILES_NAMES
@ -66,6 +67,7 @@ class XLMTokenizationTest(CommonTestCases.CommonTokenizerTester):
self.assertListEqual(
tokenizer.convert_tokens_to_ids(input_tokens), input_bpe_tokens)
@pytest.mark.slow
def test_sequence_builders(self):
tokenizer = XLMTokenizer.from_pretrained("xlm-mlm-en-2048")

2
transformers/tests/tokenization_xlnet_test.py
View File

@ -16,6 +16,7 @@ from __future__ import absolute_import, division, print_function, unicode_litera
import os
import unittest
import pytest
from transformers.tokenization_xlnet import (XLNetTokenizer, SPIECE_UNDERLINE)
@ -89,6 +90,7 @@ class XLNetTokenizationTest(CommonTestCases.CommonTokenizerTester):
u'9', u'2', u'0', u'0', u'0', u',', SPIECE_UNDERLINE + u'and', SPIECE_UNDERLINE + u'this',
SPIECE_UNDERLINE + u'is', SPIECE_UNDERLINE + u'f', u'al', u'se', u'.'])
@pytest.mark.slow
def test_sequence_builders(self):
tokenizer = XLNetTokenizer.from_pretrained("xlnet-base-cased")