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Update old existing feature extractor references (#24552)

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* Update old existing feature extractor references

* Typo

* Apply suggestions from code review

* Apply suggestions from code review

* Apply suggestions from code review

* Address comments from review - update 'feature extractor'
Co-authored by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
This commit is contained in:
amyeroberts
2023-06-29 10:17:36 +01:00
committed by GitHub
parent 10c2ac7bc6
commit ae454f41d4
138 changed files with 762 additions and 743 deletions
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10
tests/models/swinv2/test_modeling_swinv2.py
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@@ -36,7 +36,7 @@ if is_torch_available():
if is_vision_available():
from PIL import Image
from transformers import AutoFeatureExtractor
from transformers import AutoImageProcessor
class Swinv2ModelTester:
@@ -412,9 +412,9 @@ class Swinv2ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
@require_torch
class Swinv2ModelIntegrationTest(unittest.TestCase):
@cached_property
def default_feature_extractor(self):
def default_image_processor(self):
return (
AutoFeatureExtractor.from_pretrained("microsoft/swinv2-tiny-patch4-window8-256")
AutoImageProcessor.from_pretrained("microsoft/swinv2-tiny-patch4-window8-256")
if is_vision_available()
else None
)
@@ -424,10 +424,10 @@ class Swinv2ModelIntegrationTest(unittest.TestCase):
model = Swinv2ForImageClassification.from_pretrained("microsoft/swinv2-tiny-patch4-window8-256").to(
torch_device
)
feature_extractor = self.default_feature_extractor
image_processor = self.default_image_processor
image = Image.open("./tests/fixtures/tests_samples/COCO/000000039769.png")
inputs = feature_extractor(images=image, return_tensors="pt").to(torch_device)
inputs = image_processor(images=image, return_tensors="pt").to(torch_device)
# forward pass
with torch.no_grad():