[tests] further fix Tester object has no attribute '_testMethodName' (

#35781)

* bug fix

* update with more cases

* more entries

* Fix

---------

Co-authored-by: ydshieh <[email protected]>

tests/models/albert/test_modeling_flax_albert.py

@@ -36,7 +36,7 @@
     )
 
 
-class FlaxAlbertModelTester(unittest.TestCase):
+class FlaxAlbertModelTester:
     def __init__(
         self,
         parent,
@@ -80,7 +80,6 @@ def __init__(
         self.type_sequence_label_size = type_sequence_label_size
         self.initializer_range = initializer_range
         self.num_choices = num_choices
-        super().__init__()
 
     def prepare_config_and_inputs(self):
         input_ids = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)

tests/models/aria/test_image_processing_aria.py

@@ -35,7 +35,7 @@
     import torch
 
 
-class AriaImageProcessingTester(unittest.TestCase):
+class AriaImageProcessingTester:
     def __init__(
         self,
         parent,
@@ -55,7 +55,6 @@ def __init__(
         do_convert_rgb=True,
         resample=PILImageResampling.BICUBIC,
     ):
-        super().__init__()
         self.size = size if size is not None else {"longest_edge": max_resolution}
         self.parent = parent
         self.batch_size = batch_size

tests/models/beit/test_modeling_flax_beit.py

@@ -36,7 +36,7 @@
     from transformers import BeitImageProcessor
 
 
-class FlaxBeitModelTester(unittest.TestCase):
+class FlaxBeitModelTester:
     def __init__(
         self,
         parent,
@@ -79,7 +79,6 @@ def __init__(
         # in BeiT, the seq length equals the number of patches + 1 (we add 1 for the [CLS] token)
         num_patches = (image_size // patch_size) ** 2
         self.seq_length = num_patches + 1
-        super().__init__()
 
     def prepare_config_and_inputs(self):
         pixel_values = floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size])

tests/models/bert/test_modeling_flax_bert.py

@@ -35,7 +35,7 @@
     )
 
 
-class FlaxBertModelTester(unittest.TestCase):
+class FlaxBertModelTester:
     def __init__(
         self,
         parent,
@@ -79,7 +79,6 @@ def __init__(
         self.type_sequence_label_size = type_sequence_label_size
         self.initializer_range = initializer_range
         self.num_choices = num_choices
-        super().__init__()
 
     def prepare_config_and_inputs(self):
         input_ids = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)

tests/models/big_bird/test_modeling_flax_big_bird.py

@@ -35,7 +35,7 @@
     )
 
 
-class FlaxBigBirdModelTester(unittest.TestCase):
+class FlaxBigBirdModelTester:
     def __init__(
         self,
         parent,
@@ -90,7 +90,6 @@ def __init__(
         self.use_bias = use_bias
         self.block_size = block_size
         self.num_random_blocks = num_random_blocks
-        super().__init__()
 
     def prepare_config_and_inputs(self):
         input_ids = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)

tests/models/blip/test_image_processing_blip.py

@@ -26,7 +26,7 @@
     from transformers import BlipImageProcessor
 
 
-class BlipImageProcessingTester(unittest.TestCase):
+class BlipImageProcessingTester:
     def __init__(
         self,
         parent,
@@ -43,7 +43,6 @@ def __init__(
         image_std=[0.26862954, 0.26130258, 0.27577711],
         do_convert_rgb=True,
     ):
-        super().__init__()
         size = size if size is not None else {"height": 20, "width": 20}
         self.parent = parent
         self.batch_size = batch_size

tests/models/bridgetower/test_image_processing_bridgetower.py

@@ -31,7 +31,7 @@
     from transformers import BridgeTowerImageProcessor
 
 
-class BridgeTowerImageProcessingTester(unittest.TestCase):
+class BridgeTowerImageProcessingTester:
     def __init__(
         self,
         parent,
@@ -50,7 +50,6 @@ def __init__(
         max_resolution=400,
         num_channels=3,
     ):
-        super().__init__()
         self.parent = parent
         self.do_resize = do_resize
         self.size = size if size is not None else {"shortest_edge": 288}

tests/models/chameleon/test_image_processing_chameleon.py

@@ -32,7 +32,7 @@
     from transformers import ChameleonImageProcessor
 
 
-class ChameleonImageProcessingTester(unittest.TestCase):
+class ChameleonImageProcessingTester:
     def __init__(
         self,
         parent,
@@ -50,7 +50,6 @@ def __init__(
         image_std=[1.0, 1.0, 1.0],
         do_convert_rgb=True,
     ):
-        super().__init__()
         size = size if size is not None else {"shortest_edge": 18}
         crop_size = crop_size if crop_size is not None else {"height": 18, "width": 18}
         self.parent = parent

tests/models/chinese_clip/test_image_processing_chinese_clip.py

@@ -26,7 +26,7 @@
     from transformers import ChineseCLIPImageProcessor
 
 
-class ChineseCLIPImageProcessingTester(unittest.TestCase):
+class ChineseCLIPImageProcessingTester:
     def __init__(
         self,
         parent,
@@ -44,7 +44,6 @@ def __init__(
         image_std=[0.26862954, 0.26130258, 0.27577711],
         do_convert_rgb=True,
     ):
-        super().__init__()
         size = size if size is not None else {"height": 224, "width": 224}
         crop_size = crop_size if crop_size is not None else {"height": 18, "width": 18}
         self.parent = parent

tests/models/convnext/test_image_processing_convnext.py

@@ -26,7 +26,7 @@
     from transformers import ConvNextImageProcessor
 
 
-class ConvNextImageProcessingTester(unittest.TestCase):
+class ConvNextImageProcessingTester:
     def __init__(
         self,
         parent,
@@ -42,7 +42,6 @@ def __init__(
         image_mean=[0.5, 0.5, 0.5],
         image_std=[0.5, 0.5, 0.5],
     ):
-        super().__init__()
         size = size if size is not None else {"shortest_edge": 20}
         self.parent = parent
         self.batch_size = batch_size

tests/models/deformable_detr/test_image_processing_deformable_detr.py

@@ -35,7 +35,7 @@
     from transformers import DeformableDetrImageProcessor, DeformableDetrImageProcessorFast
 
 
-class DeformableDetrImageProcessingTester(unittest.TestCase):
+class DeformableDetrImageProcessingTester:
     def __init__(
         self,
         parent,
@@ -52,7 +52,6 @@ def __init__(
         rescale_factor=1 / 255,
         do_pad=True,
     ):
-        super().__init__()
         # by setting size["longest_edge"] > max_resolution we're effectively not testing this :p
         size = size if size is not None else {"shortest_edge": 18, "longest_edge": 1333}
         self.parent = parent

tests/models/deit/test_image_processing_deit.py

@@ -26,7 +26,7 @@
     from transformers import DeiTImageProcessor
 
 
-class DeiTImageProcessingTester(unittest.TestCase):
+class DeiTImageProcessingTester:
     def __init__(
         self,
         parent,
@@ -43,7 +43,6 @@ def __init__(
         image_mean=[0.5, 0.5, 0.5],
         image_std=[0.5, 0.5, 0.5],
     ):
-        super().__init__()
         size = size if size is not None else {"height": 20, "width": 20}
         crop_size = crop_size if crop_size is not None else {"height": 18, "width": 18}
 

tests/models/detr/test_image_processing_detr.py

@@ -37,7 +37,7 @@
         from transformers import DetrImageProcessorFast
 
 
-class DetrImageProcessingTester(unittest.TestCase):
+class DetrImageProcessingTester:
     def __init__(
         self,
         parent,
@@ -54,7 +54,6 @@ def __init__(
         image_std=[0.5, 0.5, 0.5],
         do_pad=True,
     ):
-        super().__init__()
         # by setting size["longest_edge"] > max_resolution we're effectively not testing this :p
         size = size if size is not None else {"shortest_edge": 18, "longest_edge": 1333}
         self.parent = parent

tests/models/distilbert/test_modeling_flax_distilbert.py

@@ -35,7 +35,7 @@
     )
 
 
-class FlaxDistilBertModelTester(unittest.TestCase):
+class FlaxDistilBertModelTester:
     def __init__(
         self,
         parent,
@@ -79,7 +79,6 @@ def __init__(
         self.type_sequence_label_size = type_sequence_label_size
         self.initializer_range = initializer_range
         self.num_choices = num_choices
-        super().__init__()
 
     def prepare_config_and_inputs(self):
         input_ids = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)

tests/models/donut/test_image_processing_donut.py

@@ -33,7 +33,7 @@
     from transformers import DonutImageProcessor
 
 
-class DonutImageProcessingTester(unittest.TestCase):
+class DonutImageProcessingTester:
     def __init__(
         self,
         parent,
@@ -51,7 +51,6 @@ def __init__(
         image_mean=[0.5, 0.5, 0.5],
         image_std=[0.5, 0.5, 0.5],
     ):
-        super().__init__()
         self.parent = parent
         self.batch_size = batch_size
         self.num_channels = num_channels

tests/models/dpt/test_image_processing_dpt.py

@@ -34,7 +34,7 @@
     from transformers import DPTImageProcessor
 
 
-class DPTImageProcessingTester(unittest.TestCase):
+class DPTImageProcessingTester:
     def __init__(
         self,
         parent,
@@ -50,7 +50,6 @@ def __init__(
         image_std=[0.5, 0.5, 0.5],
         do_reduce_labels=False,
     ):
-        super().__init__()
         size = size if size is not None else {"height": 18, "width": 18}
         self.parent = parent
         self.batch_size = batch_size

tests/models/efficientnet/test_image_processing_efficientnet.py

@@ -28,7 +28,7 @@
     from transformers import EfficientNetImageProcessor
 
 
-class EfficientNetImageProcessorTester(unittest.TestCase):
+class EfficientNetImageProcessorTester:
     def __init__(
         self,
         parent,
@@ -43,7 +43,6 @@ def __init__(
         image_mean=[0.5, 0.5, 0.5],
         image_std=[0.5, 0.5, 0.5],
     ):
-        super().__init__()
         size = size if size is not None else {"height": 18, "width": 18}
         self.parent = parent
         self.batch_size = batch_size

tests/models/electra/test_modeling_flax_electra.py

@@ -21,7 +21,7 @@
     )
 
 
-class FlaxElectraModelTester(unittest.TestCase):
+class FlaxElectraModelTester:
     def __init__(
         self,
         parent,
@@ -67,7 +67,6 @@ def __init__(
         self.type_sequence_label_size = type_sequence_label_size
         self.initializer_range = initializer_range
         self.num_choices = num_choices
-        super().__init__()
 
     def prepare_config_and_inputs(self):
         input_ids = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)

tests/models/flava/test_image_processing_flava.py

@@ -42,7 +42,7 @@
     FLAVA_IMAGE_MEAN = FLAVA_IMAGE_STD = FLAVA_CODEBOOK_MEAN = FLAVA_CODEBOOK_STD = None
 
 
-class FlavaImageProcessingTester(unittest.TestCase):
+class FlavaImageProcessingTester:
     def __init__(
         self,
         parent,
@@ -76,7 +76,6 @@ def __init__(
         codebook_image_mean=FLAVA_CODEBOOK_MEAN,
         codebook_image_std=FLAVA_CODEBOOK_STD,
     ):
-        super().__init__()
         size = size if size is not None else {"height": 224, "width": 224}
         crop_size = crop_size if crop_size is not None else {"height": 224, "width": 224}
         codebook_size = codebook_size if codebook_size is not None else {"height": 112, "width": 112}

tests/models/glpn/test_image_processing_glpn.py

@@ -33,7 +33,7 @@
     from transformers import GLPNImageProcessor
 
 
-class GLPNImageProcessingTester(unittest.TestCase):
+class GLPNImageProcessingTester:
     def __init__(
         self,
         parent,
@@ -46,7 +46,6 @@ def __init__(
         size_divisor=32,
         do_rescale=True,
     ):
-        super().__init__()
         self.parent = parent
         self.batch_size = batch_size
         self.num_channels = num_channels

tests/models/idefics3/test_image_processing_idefics3.py

@@ -35,7 +35,7 @@
     import torch
 
 
-class Idefics3ImageProcessingTester(unittest.TestCase):
+class Idefics3ImageProcessingTester:
     def __init__(
         self,
         parent,
@@ -58,7 +58,6 @@ def __init__(
         do_image_splitting=True,
         resample=PILImageResampling.LANCZOS,
     ):
-        super().__init__()
         self.size = size if size is not None else {"longest_edge": max_resolution}
         self.parent = parent
         self.batch_size = batch_size

tests/models/imagegpt/test_image_processing_imagegpt.py

@@ -38,7 +38,7 @@
     from transformers import ImageGPTImageProcessor
 
 
-class ImageGPTImageProcessingTester(unittest.TestCase):
+class ImageGPTImageProcessingTester:
     def __init__(
         self,
         parent,
@@ -51,7 +51,6 @@ def __init__(
         size=None,
         do_normalize=True,
     ):
-        super().__init__()
         size = size if size is not None else {"height": 18, "width": 18}
         self.parent = parent
         self.batch_size = batch_size

tests/models/instructblipvideo/test_image_processing_instrictblipvideo.py

@@ -33,7 +33,7 @@
     from transformers import InstructBlipVideoImageProcessor
 
 
-class InstructBlipVideoProcessingTester(unittest.TestCase):
+class InstructBlipVideoProcessingTester:
     def __init__(
         self,
         parent,
@@ -50,7 +50,6 @@ def __init__(
         do_convert_rgb=True,
         frames=4,
     ):
-        super().__init__()
         size = size if size is not None else {"height": 18, "width": 18}
         self.parent = parent
         self.batch_size = batch_size