up with skyreelsv2 fixes.

tests/pipelines/skyreels_v2/test_skyreels_v2.py

@@ -16,22 +16,13 @@ import unittest
 
 import numpy as np
 import torch
-from transformers import AutoConfig, AutoTokenizer, T5EncoderModel
+from transformers import AutoTokenizer, T5EncoderModel
 
-from diffusers import (
-    AutoencoderKLWan,
-    SkyReelsV2Pipeline,
-    SkyReelsV2Transformer3DModel,
-    UniPCMultistepScheduler,
-)
+from diffusers import AutoencoderKLWan, SkyReelsV2Pipeline, SkyReelsV2Transformer3DModel, UniPCMultistepScheduler
 
-from ...testing_utils import (
-    enable_full_determinism,
-)
+from ...testing_utils import enable_full_determinism
 from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_PARAMS
-from ..test_pipelines_common import (
-    PipelineTesterMixin,
-)
+from ..test_pipelines_common import PipelineTesterMixin
 
 
 enable_full_determinism()
@@ -68,8 +59,7 @@ class SkyReelsV2PipelineFastTests(PipelineTesterMixin, unittest.TestCase):
 
         torch.manual_seed(0)
         scheduler = UniPCMultistepScheduler(flow_shift=8.0, use_flow_sigmas=True)
-        config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5")
-        text_encoder = T5EncoderModel(config)
+        text_encoder = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5")
         tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5")
 
         torch.manual_seed(0)

tests/pipelines/skyreels_v2/test_skyreels_v2_df.py

@@ -16,7 +16,7 @@ import unittest
 
 import numpy as np
 import torch
-from transformers import AutoConfig, AutoTokenizer, T5EncoderModel
+from transformers import AutoTokenizer, T5EncoderModel
 
 from diffusers import (
     AutoencoderKLWan,
@@ -25,13 +25,9 @@ from diffusers import (
     UniPCMultistepScheduler,
 )
 
-from ...testing_utils import (
-    enable_full_determinism,
-)
+from ...testing_utils import enable_full_determinism
 from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_PARAMS
-from ..test_pipelines_common import (
-    PipelineTesterMixin,
-)
+from ..test_pipelines_common import PipelineTesterMixin
 
 
 enable_full_determinism()
@@ -68,8 +64,7 @@ class SkyReelsV2DiffusionForcingPipelineFastTests(PipelineTesterMixin, unittest.
 
         torch.manual_seed(0)
         scheduler = UniPCMultistepScheduler(flow_shift=8.0, use_flow_sigmas=True)
-        config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5")
-        text_encoder = T5EncoderModel(config)
+        text_encoder = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5")
         tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5")
 
         torch.manual_seed(0)

tests/pipelines/skyreels_v2/test_skyreels_v2_df_image_to_video.py

@@ -17,11 +17,7 @@ import unittest
 import numpy as np
 import torch
 from PIL import Image
-from transformers import (
-    AutoConfig,
-    AutoTokenizer,
-    T5EncoderModel,
-)
+from transformers import AutoTokenizer, T5EncoderModel
 
 from diffusers import (
     AutoencoderKLWan,
@@ -69,8 +65,7 @@ class SkyReelsV2DiffusionForcingImageToVideoPipelineFastTests(PipelineTesterMixi
 
         torch.manual_seed(0)
         scheduler = UniPCMultistepScheduler(flow_shift=5.0, use_flow_sigmas=True)
-        config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5")
-        text_encoder = T5EncoderModel(config)
+        text_encoder = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5")
         tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5")
 
         torch.manual_seed(0)
@@ -161,8 +156,7 @@ class SkyReelsV2DiffusionForcingImageToVideoPipelineFastTests(SkyReelsV2Diffusio
 
         torch.manual_seed(0)
         scheduler = UniPCMultistepScheduler(flow_shift=5.0, use_flow_sigmas=True)
-        config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5")
-        text_encoder = T5EncoderModel(config)
+        text_encoder = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5")
         tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5")
 
         torch.manual_seed(0)

tests/pipelines/skyreels_v2/test_skyreels_v2_df_video_to_video.py

@@ -18,7 +18,7 @@ import unittest
 import numpy as np
 import torch
 from PIL import Image
-from transformers import AutoConfig, AutoTokenizer, T5EncoderModel
+from transformers import AutoTokenizer, T5EncoderModel
 
 from diffusers import (
     AutoencoderKLWan,
@@ -27,14 +27,9 @@ from diffusers import (
     UniPCMultistepScheduler,
 )
 
-from ...testing_utils import (
-    enable_full_determinism,
-    torch_device,
-)
+from ...testing_utils import enable_full_determinism, torch_device
 from ..pipeline_params import TEXT_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_PARAMS
-from ..test_pipelines_common import (
-    PipelineTesterMixin,
-)
+from ..test_pipelines_common import PipelineTesterMixin
 
 
 enable_full_determinism()
@@ -70,8 +65,7 @@ class SkyReelsV2DiffusionForcingVideoToVideoPipelineFastTests(PipelineTesterMixi
 
         torch.manual_seed(0)
         scheduler = UniPCMultistepScheduler(flow_shift=5.0, use_flow_sigmas=True)
-        config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5")
-        text_encoder = T5EncoderModel(config)
+        text_encoder = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5")
         tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5")
 
         torch.manual_seed(0)

tests/pipelines/skyreels_v2/test_skyreels_v2_image_to_video.py

@@ -18,7 +18,6 @@ import numpy as np
 import torch
 from PIL import Image
 from transformers import (
-    AutoConfig,
     AutoTokenizer,
     CLIPImageProcessor,
     CLIPVisionConfig,
@@ -72,8 +71,7 @@ class SkyReelsV2ImageToVideoPipelineFastTests(PipelineTesterMixin, unittest.Test
 
         torch.manual_seed(0)
         scheduler = UniPCMultistepScheduler(flow_shift=5.0, use_flow_sigmas=True)
-        config = AutoConfig.from_pretrained("hf-internal-testing/tiny-random-t5")
-        text_encoder = T5EncoderModel(config)
+        text_encoder = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5")
         tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5")
 
         torch.manual_seed(0)