Replace reduce_labels with do_reduce_labels

src/transformers/models/maskformer/image_processing_maskformer.py

@@ -373,7 +373,7 @@ class MaskFormerImageProcessor(BaseImageProcessor):
         ignore_index (`int`, *optional*):
             Label to be assigned to background pixels in segmentation maps. If provided, segmentation map pixels
             denoted with 0 (background) will be replaced with `ignore_index`.
-        reduce_labels (`bool`, *optional*, defaults to `False`):
+        do_reduce_labels (`bool`, *optional*, defaults to `False`):
             Whether or not to decrement all label values of segmentation maps by 1. Usually used for datasets where 0
             is used for background, and background itself is not included in all classes of a dataset (e.g. ADE20k).
             The background label will be replaced by `ignore_index`.
@@ -394,7 +394,7 @@ def __init__(
         image_mean: Union[float, List[float]] = None,
         image_std: Union[float, List[float]] = None,
         ignore_index: Optional[int] = None,
-        reduce_labels: bool = False,
+        do_reduce_labels: bool = False,
         **kwargs
     ):
         if "size_divisibility" in kwargs:
@@ -415,6 +415,13 @@ def __init__(
             self._max_size = kwargs.pop("max_size")
         else:
             self._max_size = 1333
+        if "reduce_labels" in kwargs:
+            warnings.warn(
+                "The `reduce_labels` argument is deprecated and will be removed in v4.27. Please use "
+                "`do_reduce_labels` instead.",
+                FutureWarning,
+            )
+            do_reduce_labels = kwargs.pop("reduce_labels")
 
         size = size if size is not None else {"shortest_edge": 800, "longest_edge": self._max_size}
         size = get_size_dict(size, max_size=self._max_size, default_to_square=False)
@@ -430,7 +437,7 @@ def __init__(
         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.ignore_index = ignore_index
-        self.reduce_labels = reduce_labels
+        self.do_reduce_labels = do_reduce_labels
 
     @classmethod
     def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs):
@@ -463,6 +470,15 @@ def max_size(self):
         )
         return self.size["longest_edge"]
 
+    @property
+    def reduce_labels(self):
+        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
+
     def resize(
         self,
         image: np.ndarray,
@@ -532,6 +548,7 @@ def convert_segmentation_map_to_binary_masks(
         instance_id_to_semantic_id: Optional[Dict[int, int]] = None,
         ignore_index: Optional[int] = None,
         reduce_labels: bool = False,
+        **kwargs
     ):
         reduce_labels = reduce_labels if reduce_labels is not None else self.reduce_labels
         ignore_index = ignore_index if ignore_index is not None else self.ignore_index
@@ -645,16 +662,26 @@ def preprocess(
         image_mean: Optional[Union[float, List[float]]] = None,
         image_std: Optional[Union[float, List[float]]] = None,
         ignore_index: Optional[int] = None,
-        reduce_labels: Optional[bool] = None,
+        do_reduce_labels: Optional[bool] = None,
         return_tensors: Optional[Union[str, TensorType]] = None,
         data_format: Union[str, ChannelDimension] = ChannelDimension.FIRST,
         **kwargs
     ) -> BatchFeature:
         if "pad_and_return_pixel_mask" in kwargs:
             warnings.warn(
-                "The `pad_and_return_pixel_mask` argument is deprecated and will be removed in a future version",
+                "The `pad_and_return_pixel_mask` argument is deprecated and will be removed in v4.27",
                 FutureWarning,
             )
+        if "reduce_labels" in kwargs:
+            warnings.warn(
+                "The `reduce_labels` argument is deprecated and will be removed in v4.27. Please use"
+                " `do_reduce_labels` instead.",
+                FutureWarning,
+            )
+            if do_reduce_labels is not None:
+                raise ValueError(
+                    "Cannot use both `reduce_labels` and `do_reduce_labels`. Please use `do_reduce_labels` instead."
+                )
 
         do_resize = do_resize if do_resize is not None else self.do_resize
         size = size if size is not None else self.size
@@ -667,7 +694,7 @@ def preprocess(
         image_mean = image_mean if image_mean is not None else self.image_mean
         image_std = image_std if image_std is not None else self.image_std
         ignore_index = ignore_index if ignore_index is not None else self.ignore_index
-        reduce_labels = reduce_labels if reduce_labels is not None else self.reduce_labels
+        do_reduce_labels = do_reduce_labels if do_reduce_labels is not None else self.do_reduce_labels
 
         if do_resize is not None and size is None or size_divisor is None:
             raise ValueError("If `do_resize` is True, `size` and `size_divisor` must be provided.")
@@ -720,7 +747,7 @@ def preprocess(
                 for segmentation_map in segmentation_maps
             ]
         encoded_inputs = self.encode_inputs(
-            images, segmentation_maps, instance_id_to_semantic_id, ignore_index, reduce_labels, return_tensors
+            images, segmentation_maps, instance_id_to_semantic_id, ignore_index, do_reduce_labels, return_tensors
         )
         return encoded_inputs
 
@@ -842,13 +869,12 @@ def encode_inputs(
               `annotations` are provided). They identify the labels of `mask_labels`, e.g. the label of
               `mask_labels[i][j]` if `class_labels[i][j]`.
         """
-        ignore_index = self.ignore_index if ignore_index is None else ignore_index
-        reduce_labels = self.reduce_labels if reduce_labels is None else reduce_labels
-
         if "pad_and_return_pixel_mask" in kwargs:
             warnings.warn(
                 "The `pad_and_return_pixel_mask` argument has no effect and will be removed in v4.27", FutureWarning
             )
+        ignore_index = self.ignore_index if ignore_index is None else ignore_index
+        reduce_labels = self.do_reduce_labels if reduce_labels is None else reduce_labels
 
         pixel_values_list = [to_numpy_array(pixel_values) for pixel_values in pixel_values_list]
         encoded_inputs = self.pad(pixel_values_list, return_tensors=return_tensors)

src/transformers/models/oneformer/image_processing_oneformer.py

@@ -373,7 +373,7 @@ class OneFormerImageProcessor(BaseImageProcessor):
         ignore_index (`int`, *optional*):
             Label to be assigned to background pixels in segmentation maps. If provided, segmentation map pixels
             denoted with 0 (background) will be replaced with `ignore_index`.
-        reduce_labels (`bool`, *optional*, defaults to `False`):
+        do_reduce_labels (`bool`, *optional*, defaults to `False`):
             Whether or not to decrement all label values of segmentation maps by 1. Usually used for datasets where 0
             is used for background, and background itself is not included in all classes of a dataset (e.g. ADE20k).
             The background label will be replaced by `ignore_index`.
@@ -399,7 +399,7 @@ def __init__(
         image_mean: Union[float, List[float]] = None,
         image_std: Union[float, List[float]] = None,
         ignore_index: Optional[int] = None,
-        reduce_labels: bool = False,
+        do_reduce_labels: bool = False,
         repo_path: str = "shi-labs/oneformer_demo",
         class_info_file: str = None,
         num_text: Optional[int] = None,
@@ -413,6 +413,14 @@ def __init__(
         size = size if size is not None else {"shortest_edge": 800, "longest_edge": self._max_size}
         size = get_size_dict(size, max_size=self._max_size, default_to_square=False)
 
+        if "reduce_labels" in kwargs:
+            warnings.warn(
+                "The `reduce_labels` argument is deprecated and will be removed in v4.27. "
+                "Please use `do_reduce_labels` instead.",
+                FutureWarning,
+            )
+            do_reduce_labels = kwargs.pop("reduce_labels")
+
         super().__init__(**kwargs)
         self.do_resize = do_resize
         self.size = size
@@ -423,7 +431,7 @@ def __init__(
         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.ignore_index = ignore_index
-        self.reduce_labels = reduce_labels
+        self.do_reduce_labels = do_reduce_labels
         self.class_info_file = class_info_file
         self.repo_path = repo_path
         self.metadata = prepare_metadata(repo_path, class_info_file)
@@ -499,6 +507,7 @@ def convert_segmentation_map_to_binary_masks(
         instance_id_to_semantic_id: Optional[Dict[int, int]] = None,
         ignore_index: Optional[int] = None,
         reduce_labels: bool = False,
+        **kwargs
     ):
         reduce_labels = reduce_labels if reduce_labels is not None else self.reduce_labels
         ignore_index = ignore_index if ignore_index is not None else self.ignore_index
@@ -607,16 +616,28 @@ def preprocess(
         image_mean: Optional[Union[float, List[float]]] = None,
         image_std: Optional[Union[float, List[float]]] = None,
         ignore_index: Optional[int] = None,
-        reduce_labels: Optional[bool] = None,
+        do_reduce_labels: Optional[bool] = None,
         return_tensors: Optional[Union[str, TensorType]] = None,
         data_format: Union[str, ChannelDimension] = ChannelDimension.FIRST,
         **kwargs
     ) -> BatchFeature:
         if "pad_and_return_pixel_mask" in kwargs:
             warnings.warn(
-                "The `pad_and_return_pixel_mask` argument is deprecated and will be removed in a future version",
+                "The `pad_and_return_pixel_mask` argument is deprecated and will be removed in v4.27",
                 FutureWarning,
             )
+        if "reduce_labels" in kwargs:
+            warnings.warn(
+                "The `reduce_labels` argument is deprecated and will be removed in a v4.27. Please use"
+                " `do_reduce_labels` instead.",
+                FutureWarning,
+            )
+            if do_reduce_labels is not None:
+                raise ValueError(
+                    "You cannot use both `reduce_labels` and `do_reduce_labels` arguments. Please use"
+                    " `do_reduce_labels` instead."
+                )
+            do_reduce_labels = kwargs.pop("reduce_labels")
 
         do_resize = do_resize if do_resize is not None else self.do_resize
         size = size if size is not None else self.size
@@ -628,7 +649,7 @@ def preprocess(
         image_mean = image_mean if image_mean is not None else self.image_mean
         image_std = image_std if image_std is not None else self.image_std
         ignore_index = ignore_index if ignore_index is not None else self.ignore_index
-        reduce_labels = reduce_labels if reduce_labels is not None else self.reduce_labels
+        do_reduce_labels = do_reduce_labels if do_reduce_labels is not None else self.do_reduce_labels
 
         if do_resize is not None and size is None:
             raise ValueError("If `do_resize` is True, `size` must be provided.")
@@ -684,7 +705,7 @@ def preprocess(
             segmentation_maps,
             instance_id_to_semantic_id,
             ignore_index,
-            reduce_labels,
+            do_reduce_labels,
             return_tensors,
         )
         return encoded_inputs
@@ -910,14 +931,13 @@ def encode_inputs(
             - **text_inputs** -- Optional list of text string entries to be fed to a model (when `annotations` are
               provided). They identify the binary masks present in the image.
         """
-        ignore_index = self.ignore_index if ignore_index is None else ignore_index
-        reduce_labels = self.reduce_labels if reduce_labels is None else reduce_labels
-
         if "pad_and_return_pixel_mask" in kwargs:
             warnings.warn(
                 "The `pad_and_return_pixel_mask` argument has no effect and will be removed in v4.27", FutureWarning
             )
 
+        ignore_index = self.ignore_index if ignore_index is None else ignore_index
+        reduce_labels = self.do_reduce_labels if reduce_labels is None else reduce_labels
         pixel_values_list = [to_numpy_array(pixel_values) for pixel_values in pixel_values_list]
         pad_size = get_max_height_width(pixel_values_list)
         encoded_inputs = self.pad(pixel_values_list, return_tensors=return_tensors)

src/transformers/models/segformer/image_processing_segformer.py

@@ -122,8 +122,8 @@ def __init__(
     @classmethod
     def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs):
         """
-        Overrides the `from_dict` method from the base class to make sure `reduce_labels` is updated if image processor
-        is created using from_dict and kwargs e.g. `SegformerImageProcessor.from_pretrained(checkpoint,
+        Overrides the `from_dict` method from the base class to make sure `do_reduce_labels` is updated if image
+        processor is created using from_dict and kwargs e.g. `SegformerImageProcessor.from_pretrained(checkpoint,
         reduce_labels=True)`
         """
         image_processor_dict = image_processor_dict.copy()

tests/models/maskformer/test_image_processing_maskformer.py

@@ -52,7 +52,7 @@ def __init__(
         image_mean=[0.5, 0.5, 0.5],
         image_std=[0.5, 0.5, 0.5],
         num_labels=10,
-        reduce_labels=True,
+        do_reduce_labels=True,
         ignore_index=255,
     ):
         self.parent = parent
@@ -73,7 +73,7 @@ def __init__(
         self.height = 3
         self.width = 4
         self.num_labels = num_labels
-        self.reduce_labels = reduce_labels
+        self.do_reduce_labels = do_reduce_labels
         self.ignore_index = ignore_index
 
     def prepare_feat_extract_dict(self):
@@ -85,7 +85,7 @@ def prepare_feat_extract_dict(self):
             "image_std": self.image_std,
             "size_divisor": self.size_divisor,
             "num_labels": self.num_labels,
-            "reduce_labels": self.reduce_labels,
+            "do_reduce_labels": self.do_reduce_labels,
             "ignore_index": self.ignore_index,
         }
 

tests/models/oneformer/test_image_processing_oneformer.py

@@ -68,7 +68,7 @@ def __init__(
         image_mean=[0.5, 0.5, 0.5],
         image_std=[0.5, 0.5, 0.5],
         num_labels=10,
-        reduce_labels=False,
+        do_reduce_labels=False,
         ignore_index=255,
         repo_path="shi-labs/oneformer_demo",
         class_info_file="ade20k_panoptic.json",
@@ -96,7 +96,7 @@ def __init__(
         self.height = 3
         self.width = 4
         self.num_labels = num_labels
-        self.reduce_labels = reduce_labels
+        self.do_reduce_labels = do_reduce_labels
         self.ignore_index = ignore_index
 
     def prepare_feat_extract_dict(self):
@@ -107,7 +107,7 @@ def prepare_feat_extract_dict(self):
             "image_mean": self.image_mean,
             "image_std": self.image_std,
             "num_labels": self.num_labels,
-            "reduce_labels": self.reduce_labels,
+            "do_reduce_labels": self.do_reduce_labels,
             "ignore_index": self.ignore_index,
             "class_info_file": self.class_info_file,
             "metadata": self.metadata,
@@ -179,7 +179,7 @@ def test_feat_extract_properties(self):
         self.assertTrue(hasattr(image_processor, "num_text"))
         self.assertTrue(hasattr(image_processor, "repo_path"))
         self.assertTrue(hasattr(image_processor, "metadata"))
-        self.assertTrue(hasattr(image_processor, "reduce_labels"))
+        self.assertTrue(hasattr(image_processor, "do_reduce_labels"))
 
     def test_batch_feature(self):
         pass