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Add Fast Image Processor for MobileNetV1 (#37111)

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* fast image processor template for MobileNetV1 via transformers-cli

* Add fast image processors and unify tests for slow/fast image processor classes

* added loop over image_processor_list for all tests and removed boilerplate comments.

---------

Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
This commit is contained in:
Daksh Maheshwari
2025-04-23 15:55:41 -04:00
committed by GitHub
parent dea1919be4
commit b6d65e40b2
5 changed files with 72 additions and 13 deletions
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30
tests/models/mobilenet_v1/test_image_processing_mobilenet_v1.py
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@@ -16,7 +16,7 @@
import unittest
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_vision_available
from transformers.utils import is_torchvision_available, is_vision_available
from ...test_image_processing_common import ImageProcessingTestMixin, prepare_image_inputs
@@ -24,6 +24,9 @@ from ...test_image_processing_common import ImageProcessingTestMixin, prepare_im
if is_vision_available():
from transformers import MobileNetV1ImageProcessor
if is_torchvision_available():
from transformers import MobileNetV1ImageProcessorFast
class MobileNetV1ImageProcessingTester:
def __init__(
@@ -79,6 +82,7 @@ class MobileNetV1ImageProcessingTester:
@require_vision
class MobileNetV1ImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase):
image_processing_class = MobileNetV1ImageProcessor if is_vision_available() else None
fast_image_processing_class = MobileNetV1ImageProcessorFast if is_torchvision_available() else None
def setUp(self):
super().setUp()
@@ -89,17 +93,19 @@ class MobileNetV1ImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase
return self.image_processor_tester.prepare_image_processor_dict()
def test_image_processor_properties(self):
image_processing = self.image_processing_class(**self.image_processor_dict)
self.assertTrue(hasattr(image_processing, "do_resize"))
self.assertTrue(hasattr(image_processing, "size"))
self.assertTrue(hasattr(image_processing, "do_center_crop"))
self.assertTrue(hasattr(image_processing, "center_crop"))
for image_processing_class in self.image_processor_list:
image_processing = image_processing_class(**self.image_processor_dict)
self.assertTrue(hasattr(image_processing, "do_resize"))
self.assertTrue(hasattr(image_processing, "size"))
self.assertTrue(hasattr(image_processing, "do_center_crop"))
self.assertTrue(hasattr(image_processing, "center_crop"))
def test_image_processor_from_dict_with_kwargs(self):
image_processor = self.image_processing_class.from_dict(self.image_processor_dict)
self.assertEqual(image_processor.size, {"shortest_edge": 20})
self.assertEqual(image_processor.crop_size, {"height": 18, "width": 18})
for image_processing_class in self.image_processor_list:
image_processor = image_processing_class.from_dict(self.image_processor_dict)
self.assertEqual(image_processor.size, {"shortest_edge": 20})
self.assertEqual(image_processor.crop_size, {"height": 18, "width": 18})
image_processor = self.image_processing_class.from_dict(self.image_processor_dict, size=42, crop_size=84)
self.assertEqual(image_processor.size, {"shortest_edge": 42})
self.assertEqual(image_processor.crop_size, {"height": 84, "width": 84})
image_processor = image_processing_class.from_dict(self.image_processor_dict, size=42, crop_size=84)
self.assertEqual(image_processor.size, {"shortest_edge": 42})
self.assertEqual(image_processor.crop_size, {"height": 84, "width": 84})