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Unverified Commit 1c81132e authored by Pablo Montalvo's avatar Pablo Montalvo Committed by GitHub
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Raise unused kwargs image processor (#29063) 

* draft processor arg capture

* add missing vivit model

* add new common test for image preprocess signature

* fix quality

* fix up

* add back missing validations

* quality

* move info level to warning for unused kwargs
parent b8b16475
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Showing with 169 additions and 2 deletions
src/transformers/models/tvp/image_processing_tvp.py
View file @ 1c81132e
......@@ -36,6 +36,7 @@ from ...image_utils import (
is_valid_image,
to_numpy_array,
valid_images,
validate_kwargs,
validate_preprocess_arguments,
)
from ...utils import TensorType, is_vision_available, logging
......@@ -172,6 +173,27 @@ class TvpImageProcessor(BaseImageProcessor):
self.do_flip_channel_order = do_flip_channel_order
self.image_mean = image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
self.image_std = image_std if image_std is not None else IMAGENET_STANDARD_STD
self._valid_processor_keys = [
"videos",
"do_resize",
"size",
"resample",
"do_center_crop",
"crop_size",
"do_rescale",
"rescale_factor",
"do_pad",
"pad_size",
"constant_values",
"pad_mode",
"do_normalize",
"do_flip_channel_order",
"image_mean",
"image_std",
"return_tensors",
"data_format",
"input_data_format",
]
def resize(
self,
......@@ -437,6 +459,8 @@ class TvpImageProcessor(BaseImageProcessor):
crop_size = crop_size if crop_size is not None else self.crop_size
crop_size = get_size_dict(crop_size, param_name="crop_size")
validate_kwargs(captured_kwargs=kwargs.keys(), valid_processor_keys=self._valid_processor_keys)
if not valid_images(videos):
raise ValueError(
"Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, "
......
src/transformers/models/videomae/image_processing_videomae.py
View file @ 1c81132e
......@@ -35,6 +35,7 @@ from ...image_utils import (
is_valid_image,
to_numpy_array,
valid_images,
validate_kwargs,
validate_preprocess_arguments,
)
from ...utils import TensorType, is_vision_available, logging
......@@ -130,6 +131,22 @@ class VideoMAEImageProcessor(BaseImageProcessor):
self.do_normalize = do_normalize
self.image_mean = image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
self.image_std = image_std if image_std is not None else IMAGENET_STANDARD_STD
self._valid_processor_keys = [
"videos",
"do_resize",
"size",
"resample",
"do_center_crop",
"crop_size",
"do_rescale",
"rescale_factor",
"do_normalize",
"image_mean",
"image_std",
"return_tensors",
"data_format",
"input_data_format",
]
def resize(
self,
......@@ -311,6 +328,8 @@ class VideoMAEImageProcessor(BaseImageProcessor):
crop_size = crop_size if crop_size is not None else self.crop_size
crop_size = get_size_dict(crop_size, param_name="crop_size")
validate_kwargs(captured_kwargs=kwargs.keys(), valid_processor_keys=self._valid_processor_keys)
if not valid_images(videos):
raise ValueError(
"Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, "
......
src/transformers/models/vilt/image_processing_vilt.py
View file @ 1c81132e
......@@ -32,6 +32,7 @@ from ...image_utils import (
make_list_of_images,
to_numpy_array,
valid_images,
validate_kwargs,
validate_preprocess_arguments,
)
from ...utils import TensorType, is_vision_available, logging
......@@ -191,6 +192,22 @@ class ViltImageProcessor(BaseImageProcessor):
self.image_mean = image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
self.image_std = image_std if image_std is not None else IMAGENET_STANDARD_STD
self.do_pad = do_pad
self._valid_processor_keys = [
"images",
"do_resize",
"size",
"size_divisor",
"resample",
"do_rescale",
"rescale_factor",
"do_normalize",
"image_mean",
"image_std",
"do_pad",
"return_tensors",
"data_format",
"input_data_format",
]
@classmethod
def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs):
......@@ -416,6 +433,8 @@ class ViltImageProcessor(BaseImageProcessor):
images = make_list_of_images(images)
validate_kwargs(captured_kwargs=kwargs.keys(), valid_processor_keys=self._valid_processor_keys)
if not valid_images(images):
raise ValueError(
"Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, "
......
src/transformers/models/vit/image_processing_vit.py
View file @ 1c81132e
......@@ -31,6 +31,7 @@ from ...image_utils import (
make_list_of_images,
to_numpy_array,
valid_images,
validate_kwargs,
validate_preprocess_arguments,
)
from ...utils import TensorType, logging
......@@ -95,6 +96,20 @@ class ViTImageProcessor(BaseImageProcessor):
self.rescale_factor = rescale_factor
self.image_mean = image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
self.image_std = image_std if image_std is not None else IMAGENET_STANDARD_STD
self._valid_processor_keys = [
"images",
"do_resize",
"size",
"resample",
"do_rescale",
"rescale_factor",
"do_normalize",
"image_mean",
"image_std",
"return_tensors",
"data_format",
"input_data_format",
]
def resize(
self,
......@@ -217,6 +232,8 @@ class ViTImageProcessor(BaseImageProcessor):
images = make_list_of_images(images)
validate_kwargs(captured_kwargs=kwargs.keys(), valid_processor_keys=self._valid_processor_keys)
if not valid_images(images):
raise ValueError(
"Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, "
......
src/transformers/models/vit_hybrid/image_processing_vit_hybrid.py
View file @ 1c81132e
......@@ -36,6 +36,7 @@ from ...image_utils import (
make_list_of_images,
to_numpy_array,
valid_images,
validate_kwargs,
validate_preprocess_arguments,
)
from ...utils import TensorType, is_vision_available, logging
......@@ -121,6 +122,23 @@ class ViTHybridImageProcessor(BaseImageProcessor):
self.image_mean = image_mean if image_mean is not None else OPENAI_CLIP_MEAN
self.image_std = image_std if image_std is not None else OPENAI_CLIP_STD
self.do_convert_rgb = do_convert_rgb
self._valid_processor_keys = [
"images",
"do_resize",
"size",
"resample",
"do_center_crop",
"crop_size",
"do_rescale",
"rescale_factor",
"do_normalize",
"image_mean",
"image_std",
"do_convert_rgb",
"return_tensors",
"data_format",
"input_data_format",
]
# Copied from transformers.models.clip.image_processing_clip.CLIPImageProcessor.resize
def resize(
......@@ -258,6 +276,8 @@ class ViTHybridImageProcessor(BaseImageProcessor):
images = make_list_of_images(images)
validate_kwargs(captured_kwargs=kwargs.keys(), valid_processor_keys=self._valid_processor_keys)
if not valid_images(images):
raise ValueError(
"Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, "
......
src/transformers/models/vitmatte/image_processing_vitmatte.py
View file @ 1c81132e
......@@ -31,6 +31,7 @@ from ...image_utils import (
make_list_of_images,
to_numpy_array,
valid_images,
validate_kwargs,
validate_preprocess_arguments,
)
from ...utils import TensorType, logging
......@@ -87,6 +88,20 @@ class VitMatteImageProcessor(BaseImageProcessor):
self.image_mean = image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
self.image_std = image_std if image_std is not None else IMAGENET_STANDARD_STD
self.size_divisibility = size_divisibility
self._valid_processor_keys = [
"images",
"trimaps",
"do_rescale",
"rescale_factor",
"do_normalize",
"image_mean",
"image_std",
"do_pad",
"size_divisibility",
"return_tensors",
"data_format",
"input_data_format",
]
def pad_image(
self,
......@@ -198,14 +213,14 @@ class VitMatteImageProcessor(BaseImageProcessor):
images = make_list_of_images(images)
trimaps = make_list_of_images(trimaps, expected_ndims=2)
validate_kwargs(captured_kwargs=kwargs.keys(), valid_processor_keys=self._valid_processor_keys)
if not valid_images(trimaps):
raise ValueError(
"Invalid trimap type. Must be of type PIL.Image.Image, numpy.ndarray, "
"torch.Tensor, tf.Tensor or jax.ndarray."
)
images = make_list_of_images(images)
if not valid_images(images):
raise ValueError(
"Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, "
......
src/transformers/models/vivit/image_processing_vivit.py
View file @ 1c81132e
......@@ -38,6 +38,7 @@ from ...image_utils import (
is_valid_image,
to_numpy_array,
valid_images,
validate_kwargs,
validate_preprocess_arguments,
)
from ...utils import logging
......@@ -137,6 +138,23 @@ class VivitImageProcessor(BaseImageProcessor):
self.do_normalize = do_normalize
self.image_mean = image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
self.image_std = image_std if image_std is not None else IMAGENET_STANDARD_STD
self._valid_processor_keys = [
"videos",
"do_resize",
"size",
"resample",
"do_center_crop",
"crop_size",
"do_rescale",
"rescale_factor",
"offset",
"do_normalize",
"image_mean",
"image_std",
"return_tensors",
"data_format",
"input_data_format",
]
def resize(
self,
......@@ -368,6 +386,8 @@ class VivitImageProcessor(BaseImageProcessor):
crop_size = crop_size if crop_size is not None else self.crop_size
crop_size = get_size_dict(crop_size, param_name="crop_size")
validate_kwargs(captured_kwargs=kwargs.keys(), valid_processor_keys=self._valid_processor_keys)
if not valid_images(videos):
raise ValueError(
"Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, "
......
src/transformers/models/yolos/image_processing_yolos.py
View file @ 1c81132e
......@@ -47,6 +47,7 @@ from ...image_utils import (
to_numpy_array,
valid_images,
validate_annotations,
validate_kwargs,
validate_preprocess_arguments,
)
from ...utils import (
......@@ -750,6 +751,26 @@ class YolosImageProcessor(BaseImageProcessor):
self.image_mean = image_mean if image_mean is not None else IMAGENET_DEFAULT_MEAN
self.image_std = image_std if image_std is not None else IMAGENET_DEFAULT_STD
self.do_pad = do_pad
self._valid_processor_keys = [
"images",
"annotations",
"return_segmentation_masks",
"masks_path",
"do_resize",
"size",
"resample",
"do_rescale",
"rescale_factor",
"do_normalize",
"image_mean",
"image_std",
"do_convert_annotations",
"do_pad",
"format",
"return_tensors",
"data_format",
"input_data_format",
]
@classmethod
# Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.from_dict with Detr->Yolos
......@@ -1185,6 +1206,7 @@ class YolosImageProcessor(BaseImageProcessor):
)
do_pad = self.do_pad if do_pad is None else do_pad
format = self.format if format is None else format
validate_kwargs(captured_kwargs=kwargs.keys(), valid_processor_keys=self._valid_processor_keys)
images = make_list_of_images(images)
......
tests/test_image_processing_common.py
View file @ 1c81132e
......@@ -13,6 +13,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import inspect
import json
import os
import pathlib
......@@ -289,6 +290,16 @@ class ImageProcessingTestMixin:
tuple(encoded_images.shape), (self.image_processor_tester.batch_size, *expected_output_image_shape)
)
def test_image_processor_preprocess_arguments(self):
image_processor = self.image_processing_class(**self.image_processor_dict)
if hasattr(image_processor, "_valid_processor_keys") and hasattr(image_processor, "preprocess"):
preprocess_parameter_names = inspect.getfullargspec(image_processor.preprocess).args
preprocess_parameter_names.remove("self")
preprocess_parameter_names.sort()
valid_processor_keys = image_processor._valid_processor_keys
valid_processor_keys.sort()
self.assertEqual(preprocess_parameter_names, valid_processor_keys)
class AnnotationFormatTestMixin:
# this mixin adds a test to assert that usages of the
......
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