Remove datasets requirement (#14795)

src/transformers/testing_utils.py

@@ -31,7 +31,6 @@ from transformers import logging as transformers_logging
 
 from .deepspeed import is_deepspeed_available
 from .file_utils import (
-    is_datasets_available,
     is_detectron2_available,
     is_faiss_available,
     is_flax_available,
@@ -513,15 +512,6 @@ def require_torch_tf32(test_case):
         return test_case
 
 
-def require_datasets(test_case):
-    """Decorator marking a test that requires datasets."""
-
-    if not is_datasets_available():
-        return unittest.skip("test requires `datasets`")(test_case)
-    else:
-        return test_case
-
-
 def require_detectron2(test_case):
     """Decorator marking a test that requires detectron2."""
     if not is_detectron2_available():

tests/test_modeling_flax_wav2vec2.py

@@ -23,7 +23,6 @@ from transformers import Wav2Vec2Config, is_flax_available
 from transformers.testing_utils import (
     is_librosa_available,
     is_pyctcdecode_available,
-    require_datasets,
     require_flax,
     require_librosa,
     require_pyctcdecode,
@@ -367,7 +366,6 @@ class FlaxWav2Vec2UtilsTest(unittest.TestCase):
 
 
 @require_flax
-@require_datasets
 @require_soundfile
 @slow
 class FlaxWav2Vec2ModelIntegrationTest(unittest.TestCase):

tests/test_modeling_hubert.py

@@ -22,7 +22,7 @@ import pytest
 
 from tests.test_modeling_common import floats_tensor, ids_tensor, random_attention_mask
 from transformers import HubertConfig, is_torch_available
-from transformers.testing_utils import require_datasets, require_soundfile, require_torch, slow, torch_device
+from transformers.testing_utils import require_soundfile, require_torch, slow, torch_device
 
 from .test_configuration_common import ConfigTester
 from .test_modeling_common import ModelTesterMixin, _config_zero_init
@@ -606,7 +606,6 @@ class HubertUtilsTest(unittest.TestCase):
 
 
 @require_torch
-@require_datasets
 @require_soundfile
 @slow
 class HubertModelIntegrationTest(unittest.TestCase):

tests/test_modeling_sew.py

@@ -22,7 +22,7 @@ import pytest
 
 from tests.test_modeling_common import floats_tensor, ids_tensor, random_attention_mask
 from transformers import SEWConfig, is_torch_available
-from transformers.testing_utils import require_datasets, require_soundfile, require_torch, slow, torch_device
+from transformers.testing_utils import require_soundfile, require_torch, slow, torch_device
 
 from .test_configuration_common import ConfigTester
 from .test_modeling_common import ModelTesterMixin, _config_zero_init
@@ -462,7 +462,6 @@ class SEWUtilsTest(unittest.TestCase):
 
 
 @require_torch
-@require_datasets
 @require_soundfile
 @slow
 class SEWModelIntegrationTest(unittest.TestCase):

tests/test_modeling_sew_d.py

@@ -22,7 +22,7 @@ import pytest
 
 from tests.test_modeling_common import floats_tensor, ids_tensor, random_attention_mask
 from transformers import SEWDConfig, is_torch_available
-from transformers.testing_utils import require_datasets, require_soundfile, require_torch, slow, torch_device
+from transformers.testing_utils import require_soundfile, require_torch, slow, torch_device
 
 from .test_configuration_common import ConfigTester
 from .test_modeling_common import ModelTesterMixin, _config_zero_init
@@ -475,7 +475,6 @@ class SEWDUtilsTest(unittest.TestCase):
 
 
 @require_torch
-@require_datasets
 @require_soundfile
 @slow
 class SEWDModelIntegrationTest(unittest.TestCase):

tests/test_modeling_tf_hubert.py

@@ -23,7 +23,7 @@ import numpy as np
 import pytest
 
 from transformers import is_tf_available
-from transformers.testing_utils import require_datasets, require_soundfile, require_tf, slow
+from transformers.testing_utils import require_soundfile, require_tf, slow
 
 from .test_configuration_common import ConfigTester
 from .test_modeling_tf_common import TFModelTesterMixin, ids_tensor
@@ -473,7 +473,6 @@ class TFHubertUtilsTest(unittest.TestCase):
 
 @require_tf
 @slow
-@require_datasets
 @require_soundfile
 class TFHubertModelIntegrationTest(unittest.TestCase):
     def _load_datasamples(self, num_samples):

tests/test_modeling_tf_wav2vec2.py

@@ -25,7 +25,7 @@ from datasets import load_dataset
 
 from transformers import Wav2Vec2Config, is_tf_available
 from transformers.file_utils import is_librosa_available, is_pyctcdecode_available
-from transformers.testing_utils import require_datasets, require_librosa, require_pyctcdecode, require_tf, slow
+from transformers.testing_utils import require_librosa, require_pyctcdecode, require_tf, slow
 
 from .test_configuration_common import ConfigTester
 from .test_modeling_tf_common import TFModelTesterMixin, ids_tensor
@@ -483,7 +483,6 @@ class TFWav2Vec2UtilsTest(unittest.TestCase):
 
 @require_tf
 @slow
-@require_datasets
 class TFWav2Vec2ModelIntegrationTest(unittest.TestCase):
     def _load_datasamples(self, num_samples):
         from datasets import load_dataset

tests/test_modeling_unispeech.py

@@ -23,7 +23,7 @@ from datasets import load_dataset
 
 from tests.test_modeling_common import floats_tensor, ids_tensor, random_attention_mask
 from transformers import UniSpeechConfig, is_torch_available
-from transformers.testing_utils import require_datasets, require_soundfile, require_torch, slow, torch_device
+from transformers.testing_utils import require_soundfile, require_torch, slow, torch_device
 
 from .test_configuration_common import ConfigTester
 from .test_modeling_common import ModelTesterMixin, _config_zero_init
@@ -525,7 +525,6 @@ class UniSpeechRobustModelTest(ModelTesterMixin, unittest.TestCase):
 
 
 @require_torch
-@require_datasets
 @require_soundfile
 @slow
 class UniSpeechModelIntegrationTest(unittest.TestCase):

tests/test_modeling_unispeech_sat.py

@@ -23,7 +23,7 @@ from datasets import load_dataset
 
 from tests.test_modeling_common import floats_tensor, ids_tensor, random_attention_mask
 from transformers import UniSpeechSatConfig, is_torch_available
-from transformers.testing_utils import require_datasets, require_soundfile, require_torch, slow, torch_device
+from transformers.testing_utils import require_soundfile, require_torch, slow, torch_device
 
 from .test_configuration_common import ConfigTester
 from .test_modeling_common import ModelTesterMixin, _config_zero_init
@@ -783,7 +783,6 @@ class UniSpeechSatRobustModelTest(ModelTesterMixin, unittest.TestCase):
 
 
 @require_torch
-@require_datasets
 @require_soundfile
 @slow
 class UniSpeechSatModelIntegrationTest(unittest.TestCase):

tests/test_modeling_wav2vec2.py

@@ -26,7 +26,6 @@ from transformers.testing_utils import (
     is_pt_flax_cross_test,
     is_pyctcdecode_available,
     is_torchaudio_available,
-    require_datasets,
     require_pyctcdecode,
     require_soundfile,
     require_torch,
@@ -1060,7 +1059,6 @@ class Wav2Vec2UtilsTest(unittest.TestCase):
 
 
 @require_torch
-@require_datasets
 @require_soundfile
 @slow
 class Wav2Vec2ModelIntegrationTest(unittest.TestCase):

tests/test_pipelines_audio_classification.py

@@ -21,7 +21,6 @@ from transformers.pipelines import AudioClassificationPipeline, pipeline
 from transformers.testing_utils import (
     is_pipeline_test,
     nested_simplify,
-    require_datasets,
     require_tf,
     require_torch,
     require_torchaudio,
@@ -65,7 +64,6 @@ class AudioClassificationPipelineTests(unittest.TestCase, metaclass=PipelineTest
 
         self.run_torchaudio(audio_classifier)
 
-    @require_datasets
     @require_torchaudio
     def run_torchaudio(self, audio_classifier):
         import datasets
@@ -101,7 +99,6 @@ class AudioClassificationPipelineTests(unittest.TestCase, metaclass=PipelineTest
         )
 
     @require_torch
-    @require_datasets
     @slow
     def test_large_model_pt(self):
         import datasets

tests/test_pipelines_automatic_speech_recognition.py

@@ -26,14 +26,7 @@ from transformers import (
     Wav2Vec2ForCTC,
 )
 from transformers.pipelines import AutomaticSpeechRecognitionPipeline, pipeline
-from transformers.testing_utils import (
+from transformers.testing_utils import is_pipeline_test, require_tf, require_torch, require_torchaudio, slow
-    is_pipeline_test,
-    require_datasets,
-    require_tf,
-    require_torch,
-    require_torchaudio,
-    slow,
-)
 
 from .test_pipelines_common import ANY, PipelineTestCaseMeta
 
@@ -105,7 +98,6 @@ class AutomaticSpeechRecognitionPipelineTests(unittest.TestCase, metaclass=Pipel
                 framework="pt",
             )
 
-    @require_datasets
     @require_torch
     @slow
     def test_torch_large(self):
@@ -128,7 +120,6 @@ class AutomaticSpeechRecognitionPipelineTests(unittest.TestCase, metaclass=Pipel
         output = speech_recognizer(filename)
         self.assertEqual(output, {"text": "A MAN SAID TO THE UNIVERSE SIR I EXIST"})
 
-    @require_datasets
     @require_torch
     @slow
     def test_torch_speech_encoder_decoder(self):
@@ -148,7 +139,6 @@ class AutomaticSpeechRecognitionPipelineTests(unittest.TestCase, metaclass=Pipel
 
     @slow
     @require_torch
-    @require_datasets
     def test_simple_wav2vec2(self):
         import numpy as np
         from datasets import load_dataset
@@ -177,7 +167,6 @@ class AutomaticSpeechRecognitionPipelineTests(unittest.TestCase, metaclass=Pipel
     @slow
     @require_torch
     @require_torchaudio
-    @require_datasets
     def test_simple_s2t(self):
         import numpy as np
         from datasets import load_dataset
@@ -207,7 +196,6 @@ class AutomaticSpeechRecognitionPipelineTests(unittest.TestCase, metaclass=Pipel
     @slow
     @require_torch
     @require_torchaudio
-    @require_datasets
     def test_xls_r_to_en(self):
         speech_recognizer = pipeline(
             task="automatic-speech-recognition",
@@ -226,7 +214,6 @@ class AutomaticSpeechRecognitionPipelineTests(unittest.TestCase, metaclass=Pipel
     @slow
     @require_torch
     @require_torchaudio
-    @require_datasets
     def test_xls_r_from_en(self):
         speech_recognizer = pipeline(
             task="automatic-speech-recognition",

tests/test_pipelines_image_classification.py

@@ -19,7 +19,6 @@ from transformers.pipelines import ImageClassificationPipeline, pipeline
 from transformers.testing_utils import (
     is_pipeline_test,
     nested_simplify,
-    require_datasets,
     require_tf,
     require_torch,
     require_vision,
@@ -53,7 +52,6 @@ class ImageClassificationPipelineTests(unittest.TestCase, metaclass=PipelineTest
         ]
         return image_classifier, examples
 
-    @require_datasets
     def run_pipeline_test(self, image_classifier, examples):
         outputs = image_classifier("./tests/fixtures/tests_samples/COCO/000000039769.png")
 

tests/test_pipelines_image_segmentation.py

@@ -26,7 +26,6 @@ from transformers import (
 from transformers.testing_utils import (
     is_pipeline_test,
     nested_simplify,
-    require_datasets,
     require_tf,
     require_timm,
     require_torch,
@@ -61,7 +60,6 @@ class ImageSegmentationPipelineTests(unittest.TestCase, metaclass=PipelineTestCa
             "./tests/fixtures/tests_samples/COCO/000000039769.png",
         ]
 
-    @require_datasets
     def run_pipeline_test(self, image_segmenter, examples):
         outputs = image_segmenter("./tests/fixtures/tests_samples/COCO/000000039769.png", threshold=0.0)
         self.assertEqual(outputs, [{"score": ANY(float), "label": ANY(str), "mask": ANY(str)}] * 12)

tests/test_pipelines_object_detection.py

@@ -25,7 +25,6 @@ from transformers import (
 from transformers.testing_utils import (
     is_pipeline_test,
     nested_simplify,
-    require_datasets,
     require_tf,
     require_timm,
     require_torch,
@@ -57,7 +56,6 @@ class ObjectDetectionPipelineTests(unittest.TestCase, metaclass=PipelineTestCase
         object_detector = ObjectDetectionPipeline(model=model, feature_extractor=feature_extractor)
         return object_detector, ["./tests/fixtures/tests_samples/COCO/000000039769.png"]
 
-    @require_datasets
     def run_pipeline_test(self, object_detector, examples):
         outputs = object_detector("./tests/fixtures/tests_samples/COCO/000000039769.png", threshold=0.0)
 

tests/test_retrieval_rag.py

@@ -32,13 +32,7 @@ from transformers.models.dpr.tokenization_dpr import DPRContextEncoderTokenizer,
 from transformers.models.rag.configuration_rag import RagConfig
 from transformers.models.rag.retrieval_rag import CustomHFIndex, RagRetriever
 from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES as BART_VOCAB_FILES_NAMES
-from transformers.testing_utils import (
+from transformers.testing_utils import require_faiss, require_sentencepiece, require_tokenizers, require_torch
-    require_datasets,
-    require_faiss,
-    require_sentencepiece,
-    require_tokenizers,
-    require_torch,
-)
 
 
 if is_faiss_available():
@@ -46,7 +40,6 @@ if is_faiss_available():
 
 
 @require_faiss
-@require_datasets
 class RagRetrieverTest(TestCase):
     def setUp(self):
         self.tmpdirname = tempfile.mkdtemp()

tests/test_tokenization_rag.py

@@ -24,7 +24,7 @@ from transformers.models.bart.configuration_bart import BartConfig
 from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES as DPR_VOCAB_FILES_NAMES
 from transformers.models.dpr.configuration_dpr import DPRConfig
 from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES as BART_VOCAB_FILES_NAMES
-from transformers.testing_utils import require_datasets, require_faiss, require_tokenizers, require_torch, slow
+from transformers.testing_utils import require_faiss, require_tokenizers, require_torch, slow
 
 
 if is_torch_available() and is_datasets_available() and is_faiss_available():
@@ -33,7 +33,6 @@ if is_torch_available() and is_datasets_available() and is_faiss_available():
 
 
 @require_faiss
-@require_datasets
 @require_torch
 class RagTokenizerTest(TestCase):
     def setUp(self):

tests/test_trainer.py

@@ -46,7 +46,6 @@ from transformers.testing_utils import (
     get_gpu_count,
     get_tests_dir,
     is_staging_test,
-    require_datasets,
     require_optuna,
     require_ray,
     require_sentencepiece,
@@ -391,7 +390,6 @@ class TrainerIntegrationPrerunTest(TestCasePlus, TrainerIntegrationCommon):
         trainer.train()
         self.check_trained_model(trainer.model, alternate_seed=True)
 
-    @require_datasets
     def test_trainer_with_datasets(self):
         import datasets
 

tests/test_trainer_seq2seq.py

@@ -15,7 +15,7 @@
 
 from transformers import BertTokenizer, EncoderDecoderModel, Seq2SeqTrainer, Seq2SeqTrainingArguments
 from transformers.file_utils import is_datasets_available
-from transformers.testing_utils import TestCasePlus, require_datasets, require_torch, slow
+from transformers.testing_utils import TestCasePlus, require_torch, slow
 
 
 if is_datasets_available():
@@ -25,7 +25,6 @@ if is_datasets_available():
 class Seq2seqTrainerTester(TestCasePlus):
     @slow
     @require_torch
-    @require_datasets
     def test_finetune_bert2bert(self):
         bert2bert = EncoderDecoderModel.from_encoder_decoder_pretrained("prajjwal1/bert-tiny", "prajjwal1/bert-tiny")
         tokenizer = BertTokenizer.from_pretrained("bert-base-uncased")