SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

Fast image processor (#28847)

Browse Source 
* Draft fast image processors

* Draft working fast version

* py3.8 compatible cache

* Enable loading fast image processors through auto

* Tidy up; rescale behaviour based on input type

* Enable tests for fast image processors

* Smarter rescaling

* Don't default to Fast

* Safer imports

* Add necessary Pillow requirement

* Woops

* Add AutoImageProcessor test

* Fix up

* Fix test for imagegpt

* Fix test

* Review comments

* Add warning for TF and JAX input types

* Rearrange

* Return transforms

* NumpyToTensor transformation

* Rebase - include changes from upstream in ImageProcessingMixin

* Safe typing

* Fix up

* convert mean/std to tesnor to rescale

* Don't store transforms in state

* Fix up

* Update src/transformers/image_processing_utils_fast.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/auto/image_processing_auto.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/auto/image_processing_auto.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/auto/image_processing_auto.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Warn if fast image processor available

* Update src/transformers/models/vit/image_processing_vit_fast.py

* Transpose incoming numpy images to be in CHW format

* Update mapping names based on packages, auto set fast to None

* Fix up

* Fix

* Add AutoImageProcessor.from_pretrained(checkpoint, use_fast=True) test

* Update src/transformers/models/vit/image_processing_vit_fast.py

Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>

* Add equivalence and speed tests

* Fix up

---------

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
This commit is contained in:
amyeroberts
2024-06-11 15:47:38 +01:00
committed by GitHub
parent edc1dffd00
commit f53fe35b29
64 changed files with 1645 additions and 813 deletions
Download Patch File Download Diff File Expand all files Collapse all files

44
tests/models/imagegpt/test_image_processing_imagegpt.py
View File

@@ -22,7 +22,8 @@ import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers import AutoImageProcessor
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingTestMixin, prepare_image_inputs
@@ -96,6 +97,7 @@ class ImageGPTImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase):
image_processing_class = ImageGPTImageProcessor if is_vision_available() else None
def setUp(self):
super().setUp()
self.image_processor_tester = ImageGPTImageProcessingTester(self)
@property
@@ -141,18 +143,38 @@ class ImageGPTImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase):
self.assertEqual(image_processor_first[key], value)
def test_image_processor_from_and_save_pretrained(self):
image_processor_first = self.image_processing_class(**self.image_processor_dict)
for image_processing_class in self.image_processor_list:
image_processor_first = self.image_processing_class(**self.image_processor_dict)
with tempfile.TemporaryDirectory() as tmpdirname:
image_processor_first.save_pretrained(tmpdirname)
image_processor_second = self.image_processing_class.from_pretrained(tmpdirname).to_dict()
with tempfile.TemporaryDirectory() as tmpdirname:
image_processor_first.save_pretrained(tmpdirname)
image_processor_second = self.image_processing_class.from_pretrained(tmpdirname).to_dict()
image_processor_first = image_processor_first.to_dict()
for key, value in image_processor_first.items():
if key == "clusters":
self.assertTrue(np.array_equal(value, image_processor_second[key]))
else:
self.assertEqual(image_processor_first[key], value)
image_processor_first = image_processor_first.to_dict()
for key, value in image_processor_first.items():
if key == "clusters":
self.assertTrue(np.array_equal(value, image_processor_second[key]))
else:
self.assertEqual(image_processor_first[key], value)
def test_image_processor_save_load_with_autoimageprocessor(self):
for image_processing_class in self.image_processor_list:
image_processor_first = image_processing_class(**self.image_processor_dict)
with tempfile.TemporaryDirectory() as tmpdirname:
saved_file = image_processor_first.save_pretrained(tmpdirname)[0]
check_json_file_has_correct_format(saved_file)
image_processor_second = AutoImageProcessor.from_pretrained(tmpdirname)
image_processor_first = image_processor_first.to_dict()
image_processor_second = image_processor_second.to_dict()
for key, value in image_processor_first.items():
if key == "clusters":
self.assertTrue(np.array_equal(value, image_processor_second[key]))
else:
self.assertEqual(image_processor_first[key], value)
@unittest.skip("ImageGPT requires clusters at initialization")
def test_init_without_params(self):