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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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14
tests/models/perceiver/test_modeling_perceiver.py
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@@ -61,7 +61,7 @@ if is_torch_available():
if is_vision_available():
from PIL import Image
from transformers import PerceiverFeatureExtractor
from transformers import PerceiverImageProcessor
class PerceiverModelTester:
@@ -899,13 +899,13 @@ class PerceiverModelIntegrationTest(unittest.TestCase):
@slow
def test_inference_image_classification(self):
feature_extractor = PerceiverFeatureExtractor()
image_processor = PerceiverImageProcessor()
model = PerceiverForImageClassificationLearned.from_pretrained("deepmind/vision-perceiver-learned")
model.to(torch_device)
# prepare inputs
image = prepare_img()
inputs = feature_extractor(image, return_tensors="pt").pixel_values.to(torch_device)
inputs = image_processor(image, return_tensors="pt").pixel_values.to(torch_device)
input_mask = None
# forward pass
@@ -923,13 +923,13 @@ class PerceiverModelIntegrationTest(unittest.TestCase):
@slow
def test_inference_image_classification_fourier(self):
feature_extractor = PerceiverFeatureExtractor()
image_processor = PerceiverImageProcessor()
model = PerceiverForImageClassificationFourier.from_pretrained("deepmind/vision-perceiver-fourier")
model.to(torch_device)
# prepare inputs
image = prepare_img()
inputs = feature_extractor(image, return_tensors="pt").pixel_values.to(torch_device)
inputs = image_processor(image, return_tensors="pt").pixel_values.to(torch_device)
input_mask = None
# forward pass
@@ -947,13 +947,13 @@ class PerceiverModelIntegrationTest(unittest.TestCase):
@slow
def test_inference_image_classification_conv(self):
feature_extractor = PerceiverFeatureExtractor()
image_processor = PerceiverImageProcessor()
model = PerceiverForImageClassificationConvProcessing.from_pretrained("deepmind/vision-perceiver-conv")
model.to(torch_device)
# prepare inputs
image = prepare_img()
inputs = feature_extractor(image, return_tensors="pt").pixel_values.to(torch_device)
inputs = image_processor(image, return_tensors="pt").pixel_values.to(torch_device)
input_mask = None
# forward pass