diff --git a/src/transformers/models/conditional_detr/image_processing_conditional_detr.py b/src/transformers/models/conditional_detr/image_processing_conditional_detr.py index 8a146ccea0d8b..b5b9a576da8ad 100644 --- a/src/transformers/models/conditional_detr/image_processing_conditional_detr.py +++ b/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] diff --git a/src/transformers/models/deformable_detr/image_processing_deformable_detr.py b/src/transformers/models/deformable_detr/image_processing_deformable_detr.py index 07cafe149e156..35a18e23edb38 100644 --- a/src/transformers/models/deformable_detr/image_processing_deformable_detr.py +++ b/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 diff --git a/src/transformers/models/deta/image_processing_deta.py b/src/transformers/models/deta/image_processing_deta.py index eda4fdff167d1..d60f6f838c9ce 100644 --- a/src/transformers/models/deta/image_processing_deta.py +++ b/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") diff --git a/src/transformers/models/detr/image_processing_detr.py b/src/transformers/models/detr/image_processing_detr.py index eaeae66c9654e..f39db7b8de5a9 100644 --- a/src/transformers/models/detr/image_processing_detr.py +++ b/src/transformers/models/detr/image_processing_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 @@ -60,6 +59,7 @@ 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]]] @@ -777,10 +779,9 @@ 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: @@ -803,10 +804,9 @@ def __init__( @property 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"] @@ -850,7 +850,7 @@ def prepare_annotation( return target 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.", @@ -859,15 +859,21 @@ def prepare(self, image, target, return_segmentation_masks=None, masks_path=None return image, target 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) 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) 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( @@ -883,10 +889,9 @@ 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: @@ -967,9 +972,7 @@ 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( @@ -1105,19 +1108,17 @@ 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") @@ -1263,10 +1264,9 @@ 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 @@ -1306,10 +1306,9 @@ def post_process_segmentation(self, outputs, target_sizes, threshold=0.9, mask_t `List[Dict]`: A list of dictionaries, each dictionary containing the scores, labels, and masks for an image in the batch as predicted by the model. """ - warnings.warn( + logger.warning_once( "`post_process_segmentation` is deprecated and will be removed in v5 of Transformers, please use" " `post_process_semantic_segmentation`.", - FutureWarning, ) out_logits, raw_masks = outputs.logits, outputs.pred_masks empty_label = out_logits.shape[-1] - 1 @@ -1358,10 +1357,9 @@ def post_process_instance(self, results, outputs, orig_target_sizes, max_target_ `List[Dict]`: A list of dictionaries, each dictionary containing the scores, labels, boxes and masks for an image in the batch as predicted by the model. """ - warnings.warn( + logger.warning_once( "`post_process_instance` is deprecated and will be removed in v5 of Transformers, please use" " `post_process_instance_segmentation`.", - FutureWarning, ) if len(orig_target_sizes) != len(max_target_sizes): @@ -1405,10 +1403,9 @@ def post_process_panoptic(self, outputs, processed_sizes, target_sizes=None, is_ `List[Dict]`: A list of dictionaries, each dictionary containing a PNG string and segments_info values for an image in the batch as predicted by the model. """ - warnings.warn( + logger.warning_once( "`post_process_panoptic is deprecated and will be removed in v5 of Transformers, please use" " `post_process_panoptic_segmentation`.", - FutureWarning, ) if target_sizes is None: target_sizes = processed_sizes @@ -1751,7 +1748,7 @@ 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] diff --git a/src/transformers/models/yolos/image_processing_yolos.py b/src/transformers/models/yolos/image_processing_yolos.py index 150051fba6619..1aa37fec4219d 100644 --- a/src/transformers/models/yolos/image_processing_yolos.py +++ b/src/transformers/models/yolos/image_processing_yolos.py @@ -15,7 +15,6 @@ """Image processor class for YOLOS.""" import pathlib -import warnings from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Tuple, Union import numpy as np @@ -707,10 +706,9 @@ 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: @@ -734,10 +732,9 @@ 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"] @@ -784,7 +781,7 @@ 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.", @@ -794,17 +791,23 @@ 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->Yolos 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 @@ -821,10 +824,9 @@ 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: @@ -1007,19 +1009,17 @@ 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, ) 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 = kwargs.pop("max_size") @@ -1164,10 +1164,9 @@ 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