Unverified Commit c18b4fbe authored by amyeroberts's avatar amyeroberts Committed by GitHub
Browse files

Add class properties with warnings (#21195)

* Replace reduce_labels with do_reduce_labels

* Replace only for __init__ and preprocess

* Add class properties with warnings

* Update tests
parent b80b2218
...@@ -131,6 +131,15 @@ class BeitImageProcessor(BaseImageProcessor): ...@@ -131,6 +131,15 @@ class BeitImageProcessor(BaseImageProcessor):
self.image_std = image_std if image_std is not None else IMAGENET_STANDARD_STD self.image_std = image_std if image_std is not None else IMAGENET_STANDARD_STD
self.do_reduce_labels = do_reduce_labels self.do_reduce_labels = do_reduce_labels
@property
def reduce_labels(self) -> bool:
warnings.warn(
"The `reduce_labels` property is deprecated and will be removed in v4.27. Please use"
" `do_reduce_labels` instead.",
FutureWarning,
)
return self.do_reduce_labels
@classmethod @classmethod
def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs): def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs):
""" """
......
...@@ -815,6 +815,16 @@ class ConditionalDetrImageProcessor(BaseImageProcessor): ...@@ -815,6 +815,16 @@ class ConditionalDetrImageProcessor(BaseImageProcessor):
self.image_std = image_std if image_std is not None else IMAGENET_DEFAULT_STD self.image_std = image_std if image_std is not None else IMAGENET_DEFAULT_STD
self.do_pad = do_pad self.do_pad = do_pad
@property
# Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.max_size
def max_size(self):
warnings.warn(
"The `max_size` parameter is deprecated and will be removed in v4.27. "
"Please specify in `size['longest_edge'] instead`.",
FutureWarning,
)
return self.size["longest_edge"]
@classmethod @classmethod
# Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.from_dict with Detr->ConditionalDetr # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.from_dict with Detr->ConditionalDetr
def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs): def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs):
......
...@@ -813,6 +813,16 @@ class DeformableDetrImageProcessor(BaseImageProcessor): ...@@ -813,6 +813,16 @@ class DeformableDetrImageProcessor(BaseImageProcessor):
self.image_std = image_std if image_std is not None else IMAGENET_DEFAULT_STD self.image_std = image_std if image_std is not None else IMAGENET_DEFAULT_STD
self.do_pad = do_pad self.do_pad = do_pad
@property
# Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.max_size
def max_size(self):
warnings.warn(
"The `max_size` parameter is deprecated and will be removed in v4.27. "
"Please specify in `size['longest_edge'] instead`.",
FutureWarning,
)
return self.size["longest_edge"]
@classmethod @classmethod
# Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.from_dict with Detr->DeformableDetr # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.from_dict with Detr->DeformableDetr
def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs): def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs):
......
...@@ -797,6 +797,15 @@ class DetrImageProcessor(BaseImageProcessor): ...@@ -797,6 +797,15 @@ class DetrImageProcessor(BaseImageProcessor):
self.image_std = image_std if image_std is not None else IMAGENET_DEFAULT_STD self.image_std = image_std if image_std is not None else IMAGENET_DEFAULT_STD
self.do_pad = do_pad self.do_pad = do_pad
@property
def max_size(self):
warnings.warn(
"The `max_size` parameter is deprecated and will be removed in v4.27. "
"Please specify in `size['longest_edge'] instead`.",
FutureWarning,
)
return self.size["longest_edge"]
@classmethod @classmethod
def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs): def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs):
""" """
......
...@@ -119,6 +119,15 @@ class SegformerImageProcessor(BaseImageProcessor): ...@@ -119,6 +119,15 @@ class SegformerImageProcessor(BaseImageProcessor):
self.image_std = image_std if image_std is not None else IMAGENET_DEFAULT_STD self.image_std = image_std if image_std is not None else IMAGENET_DEFAULT_STD
self.do_reduce_labels = do_reduce_labels self.do_reduce_labels = do_reduce_labels
@property
def reduce_labels(self):
warnings.warn(
"The `reduce_labels` property is deprecated and will be removed in a v4.27. Please use "
"`do_reduce_labels` instead.",
FutureWarning,
)
return self.do_reduce_labels
@classmethod @classmethod
def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs): def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs):
""" """
......
...@@ -725,6 +725,16 @@ class YolosImageProcessor(BaseImageProcessor): ...@@ -725,6 +725,16 @@ class YolosImageProcessor(BaseImageProcessor):
self.image_std = image_std if image_std is not None else IMAGENET_DEFAULT_STD self.image_std = image_std if image_std is not None else IMAGENET_DEFAULT_STD
self.do_pad = do_pad self.do_pad = do_pad
@property
# Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.max_size
def max_size(self):
warnings.warn(
"The `max_size` parameter is deprecated and will be removed in v4.27. "
"Please specify in `size['longest_edge'] instead`.",
FutureWarning,
)
return self.size["longest_edge"]
@classmethod @classmethod
# Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.from_dict with Detr->Yolos # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.from_dict with Detr->Yolos
def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs): def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs):
......
...@@ -353,7 +353,7 @@ class BeitImageProcessingTest(ImageProcessingSavingTestMixin, unittest.TestCase) ...@@ -353,7 +353,7 @@ class BeitImageProcessingTest(ImageProcessingSavingTestMixin, unittest.TestCase)
self.assertTrue(encoding["labels"].min().item() >= 0) self.assertTrue(encoding["labels"].min().item() >= 0)
self.assertTrue(encoding["labels"].max().item() <= 150) self.assertTrue(encoding["labels"].max().item() <= 150)
image_processing.reduce_labels = True image_processing.do_reduce_labels = True
encoding = image_processing(image, map, return_tensors="pt") encoding = image_processing(image, map, return_tensors="pt")
self.assertTrue(encoding["labels"].min().item() >= 0) self.assertTrue(encoding["labels"].min().item() >= 0)
self.assertTrue(encoding["labels"].max().item() <= 255) self.assertTrue(encoding["labels"].max().item() <= 255)
...@@ -339,7 +339,7 @@ class SegformerImageProcessingTest(ImageProcessingSavingTestMixin, unittest.Test ...@@ -339,7 +339,7 @@ class SegformerImageProcessingTest(ImageProcessingSavingTestMixin, unittest.Test
self.assertTrue(encoding["labels"].min().item() >= 0) self.assertTrue(encoding["labels"].min().item() >= 0)
self.assertTrue(encoding["labels"].max().item() <= 150) self.assertTrue(encoding["labels"].max().item() <= 150)
image_processing.reduce_labels = True image_processing.do_reduce_labels = True
encoding = image_processing(image, map, return_tensors="pt") encoding = image_processing(image, map, return_tensors="pt")
self.assertTrue(encoding["labels"].min().item() >= 0) self.assertTrue(encoding["labels"].min().item() >= 0)
self.assertTrue(encoding["labels"].max().item() <= 255) self.assertTrue(encoding["labels"].max().item() <= 255)
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