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

transformers/modeling_roberta.py

@@ -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)

transformers/tests/modeling_auto_test.py

@@ -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]:

transformers/tests/modeling_common_test.py

@@ -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]:

transformers/tests/modeling_encoder_decoder_test.py

@@ -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]:

transformers/tests/tokenization_auto_test.py

@@ -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]:

transformers/tests/tokenization_bert_test.py

@@ -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")
 

transformers/tests/tokenization_distilbert_test.py

@@ -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")
 

transformers/tests/tokenization_roberta_test.py

@@ -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")
 

transformers/tests/tokenization_utils_test.py

@@ -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]:

transformers/tests/tokenization_xlm_test.py

@@ -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")
 

transformers/tests/tokenization_xlnet_test.py

@@ -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")