Update warning levels (#22727)

* Use different level

* Remove futurewarning

* Use warning_once

* Update copies

src/transformers/models/conditional_detr/image_processing_conditional_detr.py

@@ -16,7 +16,6 @@
 
 import io
 import pathlib
-import warnings
 from collections import defaultdict
 from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Tuple, Union
 
@@ -61,6 +60,7 @@
     is_torch_available,
     is_torch_tensor,
     is_vision_available,
+    logging,
 )
 
 
@@ -78,6 +78,8 @@
     import scipy.stats
 
 
+logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
+
 AnnotationType = Dict[str, Union[int, str, List[Dict]]]
 
 
@@ -795,10 +797,9 @@ def __init__(
             do_pad = kwargs.pop("pad_and_return_pixel_mask")
 
         if "max_size" in kwargs:
-            warnings.warn(
+            logger.warning_once(
                 "The `max_size` parameter is deprecated and will be removed in v4.26. "
                 "Please specify in `size['longest_edge'] instead`.",
-                FutureWarning,
             )
             max_size = kwargs.pop("max_size")
         else:
@@ -822,10 +823,9 @@ def __init__(
     @property
     # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.max_size
     def max_size(self):
-        warnings.warn(
+        logger.warning(
             "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"]
 
@@ -872,7 +872,7 @@ def prepare_annotation(
 
     # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.prepare
     def prepare(self, image, target, return_segmentation_masks=False, masks_path=None):
-        warnings.warn(
+        logger.warning_once(
             "The `prepare` method is deprecated and will be removed in a future version. "
             "Please use `prepare_annotation` instead. Note: the `prepare_annotation` method "
             "does not return the image anymore.",
@@ -882,17 +882,23 @@ def prepare(self, image, target, return_segmentation_masks=False, masks_path=Non
 
     # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.convert_coco_poly_to_mask
     def convert_coco_poly_to_mask(self, *args, **kwargs):
-        warnings.warn("The `convert_coco_poly_to_mask` method is deprecated and will be removed in a future version. ")
+        logger.warning_once(
+            "The `convert_coco_poly_to_mask` method is deprecated and will be removed in a future version. "
+        )
         return convert_coco_poly_to_mask(*args, **kwargs)
 
     # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.prepare_coco_detection with DETR->ConditionalDetr
     def prepare_coco_detection(self, *args, **kwargs):
-        warnings.warn("The `prepare_coco_detection` method is deprecated and will be removed in a future version. ")
+        logger.warning_once(
+            "The `prepare_coco_detection` method is deprecated and will be removed in a future version. "
+        )
         return prepare_coco_detection_annotation(*args, **kwargs)
 
     # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.prepare_coco_panoptic
     def prepare_coco_panoptic(self, *args, **kwargs):
-        warnings.warn("The `prepare_coco_panoptic` method is deprecated and will be removed in a future version. ")
+        logger.warning_once(
+            "The `prepare_coco_panoptic` method is deprecated and will be removed in a future version. "
+        )
         return prepare_coco_panoptic_annotation(*args, **kwargs)
 
     # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.resize
@@ -909,10 +915,9 @@ def resize(
         int, smaller edge of the image will be matched to this number.
         """
         if "max_size" in kwargs:
-            warnings.warn(
+            logger.warning_once(
                 "The `max_size` parameter is deprecated and will be removed in v4.26. "
                 "Please specify in `size['longest_edge'] instead`.",
-                FutureWarning,
             )
             max_size = kwargs.pop("max_size")
         else:
@@ -998,9 +1003,7 @@ def pad_and_create_pixel_mask(
             data_format (`str` or `ChannelDimension`, *optional*):
                 The channel dimension format of the image. If not provided, it will be the same as the input image.
         """
-        warnings.warn(
-            "This method is deprecated and will be removed in v4.27.0. Please use pad instead.", FutureWarning
-        )
+        logger.warning_once("This method is deprecated and will be removed in v4.27.0. Please use pad instead.")
         # pad expects a list of np.ndarray, but the previous feature extractors expected torch tensors
         images = [to_numpy_array(image) for image in pixel_values_list]
         return self.pad(
@@ -1139,19 +1142,17 @@ def preprocess(
                 The channel dimension format of the image. If not provided, it will be the same as the input image.
         """
         if "pad_and_return_pixel_mask" in kwargs:
-            warnings.warn(
+            logger.warning_once(
                 "The `pad_and_return_pixel_mask` argument is deprecated and will be removed in a future version, "
-                "use `do_pad` instead.",
-                FutureWarning,
+                "use `do_pad` instead."
             )
             do_pad = kwargs.pop("pad_and_return_pixel_mask")
 
         max_size = None
         if "max_size" in kwargs:
-            warnings.warn(
+            logger.warning_once(
                 "The `max_size` argument is deprecated and will be removed in a future version, use"
-                " `size['longest_edge']` instead.",
-                FutureWarning,
+                " `size['longest_edge']` instead."
             )
             size = kwargs.pop("max_size")
 
@@ -1296,10 +1297,9 @@ def post_process(self, outputs, target_sizes):
             `List[Dict]`: A list of dictionaries, each dictionary containing the scores, labels and boxes for an image
             in the batch as predicted by the model.
         """
-        warnings.warn(
+        logging.warning_once(
             "`post_process` is deprecated and will be removed in v5 of Transformers, please use"
             " `post_process_object_detection`",
-            FutureWarning,
         )
 
         out_logits, out_bbox = outputs.logits, outputs.pred_boxes
@@ -1560,7 +1560,7 @@ def post_process_panoptic_segmentation(
         """
 
         if label_ids_to_fuse is None:
-            warnings.warn("`label_ids_to_fuse` unset. No instance will be fused.")
+            logger.warning_once("`label_ids_to_fuse` unset. No instance will be fused.")
             label_ids_to_fuse = set()
 
         class_queries_logits = outputs.logits  # [batch_size, num_queries, num_classes+1]

src/transformers/models/deformable_detr/image_processing_deformable_detr.py

@@ -16,7 +16,6 @@
 
 import io
 import pathlib
-import warnings
 from collections import defaultdict
 from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Tuple, Union
 
@@ -61,6 +60,7 @@
     is_torch_available,
     is_torch_tensor,
     is_vision_available,
+    logging,
 )
 
 
@@ -77,6 +77,8 @@
     import scipy.stats
 
 
+logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
+
 AnnotationType = Dict[str, Union[int, str, List[Dict]]]
 
 
@@ -793,10 +795,9 @@ def __init__(
             do_pad = kwargs.pop("pad_and_return_pixel_mask")
 
         if "max_size" in kwargs:
-            warnings.warn(
+            logger.warning_once(
                 "The `max_size` parameter is deprecated and will be removed in v4.26. "
                 "Please specify in `size['longest_edge'] instead`.",
-                FutureWarning,
             )
             max_size = kwargs.pop("max_size")
         else:
@@ -820,10 +821,9 @@ def __init__(
     @property
     # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.max_size
     def max_size(self):
-        warnings.warn(
+        logger.warning(
             "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"]
 
@@ -870,7 +870,7 @@ def prepare_annotation(
 
     # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.prepare
     def prepare(self, image, target, return_segmentation_masks=None, masks_path=None):
-        warnings.warn(
+        logger.warning_once(
             "The `prepare` method is deprecated and will be removed in a future version. "
             "Please use `prepare_annotation` instead. Note: the `prepare_annotation` method "
             "does not return the image anymore.",
@@ -880,17 +880,23 @@ def prepare(self, image, target, return_segmentation_masks=None, masks_path=None
 
     # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.convert_coco_poly_to_mask
     def convert_coco_poly_to_mask(self, *args, **kwargs):
-        warnings.warn("The `convert_coco_poly_to_mask` method is deprecated and will be removed in a future version. ")
+        logger.warning_once(
+            "The `convert_coco_poly_to_mask` method is deprecated and will be removed in a future version. "
+        )
         return convert_coco_poly_to_mask(*args, **kwargs)
 
     # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.prepare_coco_detection
     def prepare_coco_detection(self, *args, **kwargs):
-        warnings.warn("The `prepare_coco_detection` method is deprecated and will be removed in a future version. ")
+        logger.warning_once(
+            "The `prepare_coco_detection` method is deprecated and will be removed in a future version. "
+        )
         return prepare_coco_detection_annotation(*args, **kwargs)
 
     # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.prepare_coco_panoptic
     def prepare_coco_panoptic(self, *args, **kwargs):
-        warnings.warn("The `prepare_coco_panoptic` method is deprecated and will be removed in a future version. ")
+        logger.warning_once(
+            "The `prepare_coco_panoptic` method is deprecated and will be removed in a future version. "
+        )
         return prepare_coco_panoptic_annotation(*args, **kwargs)
 
     # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.resize
@@ -907,10 +913,9 @@ def resize(
         int, smaller edge of the image will be matched to this number.
         """
         if "max_size" in kwargs:
-            warnings.warn(
+            logger.warning_once(
                 "The `max_size` parameter is deprecated and will be removed in v4.26. "
                 "Please specify in `size['longest_edge'] instead`.",
-                FutureWarning,
             )
             max_size = kwargs.pop("max_size")
         else:
@@ -996,9 +1001,7 @@ def pad_and_create_pixel_mask(
             data_format (`str` or `ChannelDimension`, *optional*):
                 The channel dimension format of the image. If not provided, it will be the same as the input image.
         """
-        warnings.warn(
-            "This method is deprecated and will be removed in v4.27.0. Please use pad instead.", FutureWarning
-        )
+        logger.warning_once("This method is deprecated and will be removed in v4.27.0. Please use pad instead.")
         # pad expects a list of np.ndarray, but the previous feature extractors expected torch tensors
         images = [to_numpy_array(image) for image in pixel_values_list]
         return self.pad(
@@ -1137,19 +1140,17 @@ def preprocess(
                 The channel dimension format of the image. If not provided, it will be the same as the input image.
         """
         if "pad_and_return_pixel_mask" in kwargs:
-            warnings.warn(
+            logger.warning_once(
                 "The `pad_and_return_pixel_mask` argument is deprecated and will be removed in a future version, "
-                "use `do_pad` instead.",
-                FutureWarning,
+                "use `do_pad` instead."
             )
             do_pad = kwargs.pop("pad_and_return_pixel_mask")
 
         max_size = None
         if "max_size" in kwargs:
-            warnings.warn(
+            logger.warning_once(
                 "The `max_size` argument is deprecated and will be removed in a future version, use"
-                " `size['longest_edge']` instead.",
-                FutureWarning,
+                " `size['longest_edge']` instead."
             )
             size = kwargs.pop("max_size")
 
@@ -1294,10 +1295,9 @@ def post_process(self, outputs, target_sizes):
             `List[Dict]`: A list of dictionaries, each dictionary containing the scores, labels and boxes for an image
             in the batch as predicted by the model.
         """
-        warnings.warn(
+        logger.warning_once(
             "`post_process` is deprecated and will be removed in v5 of Transformers, please use"
             " `post_process_object_detection`.",
-            FutureWarning,
         )
 
         out_logits, out_bbox = outputs.logits, outputs.pred_boxes

src/transformers/models/deta/image_processing_deta.py

@@ -15,7 +15,6 @@
 """Image processor class for Deformable DETR."""
 
 import pathlib
-import warnings
 from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple, Union
 
 import numpy as np
@@ -56,6 +55,7 @@
     is_torch_tensor,
     is_torchvision_available,
     is_vision_available,
+    logging,
 )
 from ...utils.generic import ExplicitEnum, TensorType
 
@@ -71,6 +71,9 @@
     import PIL
 
 
+logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
+
+
 class AnnotionFormat(ExplicitEnum):
     COCO_DETECTION = "coco_detection"
     COCO_PANOPTIC = "coco_panoptic"
@@ -540,7 +543,7 @@ def prepare_annotation(
 
     # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.prepare
     def prepare(self, image, target, return_segmentation_masks=None, masks_path=None):
-        warnings.warn(
+        logger.warning_once(
             "The `prepare` method is deprecated and will be removed in a future version. "
             "Please use `prepare_annotation` instead. Note: the `prepare_annotation` method "
             "does not return the image anymore.",
@@ -550,17 +553,23 @@ def prepare(self, image, target, return_segmentation_masks=None, masks_path=None
 
     # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.convert_coco_poly_to_mask
     def convert_coco_poly_to_mask(self, *args, **kwargs):
-        warnings.warn("The `convert_coco_poly_to_mask` method is deprecated and will be removed in a future version. ")
+        logger.warning_once(
+            "The `convert_coco_poly_to_mask` method is deprecated and will be removed in a future version. "
+        )
         return convert_coco_poly_to_mask(*args, **kwargs)
 
     # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.prepare_coco_detection
     def prepare_coco_detection(self, *args, **kwargs):
-        warnings.warn("The `prepare_coco_detection` method is deprecated and will be removed in a future version. ")
+        logger.warning_once(
+            "The `prepare_coco_detection` method is deprecated and will be removed in a future version. "
+        )
         return prepare_coco_detection_annotation(*args, **kwargs)
 
     # Copied from transformers.models.detr.image_processing_detr.DetrImageProcessor.prepare_coco_panoptic
     def prepare_coco_panoptic(self, *args, **kwargs):
-        warnings.warn("The `prepare_coco_panoptic` method is deprecated and will be removed in a future version. ")
+        logger.warning_once(
+            "The `prepare_coco_panoptic` method is deprecated and will be removed in a future version. "
+        )
         return prepare_coco_panoptic_annotation(*args, **kwargs)
 
     def resize(
@@ -656,9 +665,7 @@ def pad_and_create_pixel_mask(
             data_format (`str` or `ChannelDimension`, *optional*):
                 The channel dimension format of the image. If not provided, it will be the same as the input image.
         """
-        warnings.warn(
-            "This method is deprecated and will be removed in v4.27.0. Please use pad instead.", FutureWarning
-        )
+        logger.warning_once("This method is deprecated and will be removed in v4.27.0. Please use pad instead.")
         # pad expects a list of np.ndarray, but the previous feature extractors expected torch tensors
         images = [to_numpy_array(image) for image in pixel_values_list]
         return self.pad(
@@ -796,10 +803,9 @@ def preprocess(
                 The channel dimension format of the image. If not provided, it will be the same as the input image.
         """
         if "pad_and_return_pixel_mask" in kwargs:
-            warnings.warn(
+            logger.warning_once(
                 "The `pad_and_return_pixel_mask` argument is deprecated and will be removed in a future version, "
                 "use `do_pad` instead.",
-                FutureWarning,
             )
             do_pad = kwargs.pop("pad_and_return_pixel_mask")