



from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase_     :       Optional[Any]								=						logging.get_logger(__name__)

lowerCAmelCase_     :       int								=						{
    'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/config.json',
    # See all Cvt models at https://huggingface.co/models?filter=cvt
}
class 	lowerCamelCase_							(					__lowerCAmelCase			):
						_lowerCAmelCase     :   List[Any]	     =				'''cvt'''







						def __init__(  self   :      List[Any]				,    lowerCAmelCase__   :      int=3				,    lowerCAmelCase__   :      str=[7, 3, 3]				,    lowerCAmelCase__   :      Tuple=[4, 2, 2]				,    lowerCAmelCase__   :      Optional[int]=[2, 1, 1]				,    lowerCAmelCase__   :      str=[64, 1_92, 3_84]				,    lowerCAmelCase__   :      List[str]=[1, 3, 6]				,    lowerCAmelCase__   :      Optional[int]=[1, 2, 10]				,    lowerCAmelCase__   :      int=[4.0, 4.0, 4.0]				,    lowerCAmelCase__   :      int=[0.0, 0.0, 0.0]				,    lowerCAmelCase__   :      Union[str, Any]=[0.0, 0.0, 0.0]				,    lowerCAmelCase__   :      List[Any]=[0.0, 0.0, 0.1]				,    lowerCAmelCase__   :      List[Any]=[True, True, True]				,    lowerCAmelCase__   :      str=[False, False, True]				,    lowerCAmelCase__   :      Dict=["dw_bn", "dw_bn", "dw_bn"]				,    lowerCAmelCase__   :      int=[3, 3, 3]				,    lowerCAmelCase__   :      Any=[1, 1, 1]				,    lowerCAmelCase__   :      List[Any]=[2, 2, 2]				,    lowerCAmelCase__   :      Tuple=[1, 1, 1]				,    lowerCAmelCase__   :      Optional[Any]=[1, 1, 1]				,    lowerCAmelCase__   :      Optional[int]=0.02				,    lowerCAmelCase__   :      str=1e-12				,    **lowerCAmelCase__   :      Union[str, Any]				,    ):

													"""simple docstring"""
													super().__init__(**lowerCAmelCase_				)
													SCREAMING_SNAKE_CASE					:      int     					=			num_channels
													SCREAMING_SNAKE_CASE					:      int     					=			patch_sizes
													SCREAMING_SNAKE_CASE					:      int     					=			patch_stride
													SCREAMING_SNAKE_CASE					:      Any     					=			patch_padding
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			embed_dim
													SCREAMING_SNAKE_CASE					:      str     					=			num_heads
													SCREAMING_SNAKE_CASE					:      Tuple     					=			depth
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			mlp_ratio
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			attention_drop_rate
													SCREAMING_SNAKE_CASE					:      List[str]     					=			drop_rate
													SCREAMING_SNAKE_CASE					:      Any     					=			drop_path_rate
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			qkv_bias
													SCREAMING_SNAKE_CASE					:      Any     					=			cls_token
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			qkv_projection_method
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			kernel_qkv
													SCREAMING_SNAKE_CASE					:      str     					=			padding_kv
													SCREAMING_SNAKE_CASE					:      int     					=			stride_kv
													SCREAMING_SNAKE_CASE					:      List[str]     					=			padding_q
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			stride_q
													SCREAMING_SNAKE_CASE					:      Any     					=			initializer_range
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			layer_norm_eps









'''simple docstring'''



import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union

# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...image_processing_utils import ImageProcessingMixin
from ...utils import CONFIG_NAME, IMAGE_PROCESSOR_NAME, get_file_from_repo, logging
from .auto_factory import _LazyAutoMapping
from .configuration_auto import (
    CONFIG_MAPPING_NAMES,
    AutoConfig,
    model_type_to_module_name,
    replace_list_option_in_docstrings,
)


lowerCAmelCase_     :       str								=						logging.get_logger(__name__)

lowerCAmelCase_     :       List[Any]								=						OrderedDict(
    [
        ('align', 'EfficientNetImageProcessor'),
        ('beit', 'BeitImageProcessor'),
        ('bit', 'BitImageProcessor'),
        ('blip', 'BlipImageProcessor'),
        ('blip-2', 'BlipImageProcessor'),
        ('bridgetower', 'BridgeTowerImageProcessor'),
        ('chinese_clip', 'ChineseCLIPImageProcessor'),
        ('clip', 'CLIPImageProcessor'),
        ('clipseg', 'ViTImageProcessor'),
        ('conditional_detr', 'ConditionalDetrImageProcessor'),
        ('convnext', 'ConvNextImageProcessor'),
        ('convnextv2', 'ConvNextImageProcessor'),
        ('cvt', 'ConvNextImageProcessor'),
        ('data2vec-vision', 'BeitImageProcessor'),
        ('deformable_detr', 'DeformableDetrImageProcessor'),
        ('deit', 'DeiTImageProcessor'),
        ('deta', 'DetaImageProcessor'),
        ('detr', 'DetrImageProcessor'),
        ('dinat', 'ViTImageProcessor'),
        ('donut-swin', 'DonutImageProcessor'),
        ('dpt', 'DPTImageProcessor'),
        ('efficientformer', 'EfficientFormerImageProcessor'),
        ('efficientnet', 'EfficientNetImageProcessor'),
        ('flava', 'FlavaImageProcessor'),
        ('focalnet', 'BitImageProcessor'),
        ('git', 'CLIPImageProcessor'),
        ('glpn', 'GLPNImageProcessor'),
        ('groupvit', 'CLIPImageProcessor'),
        ('imagegpt', 'ImageGPTImageProcessor'),
        ('instructblip', 'BlipImageProcessor'),
        ('layoutlmv2', 'LayoutLMv2ImageProcessor'),
        ('layoutlmv3', 'LayoutLMv3ImageProcessor'),
        ('levit', 'LevitImageProcessor'),
        ('mask2former', 'Mask2FormerImageProcessor'),
        ('maskformer', 'MaskFormerImageProcessor'),
        ('mgp-str', 'ViTImageProcessor'),
        ('mobilenet_v1', 'MobileNetV1ImageProcessor'),
        ('mobilenet_v2', 'MobileNetV2ImageProcessor'),
        ('mobilevit', 'MobileViTImageProcessor'),
        ('mobilevit', 'MobileViTImageProcessor'),
        ('mobilevitv2', 'MobileViTImageProcessor'),
        ('nat', 'ViTImageProcessor'),
        ('oneformer', 'OneFormerImageProcessor'),
        ('owlvit', 'OwlViTImageProcessor'),
        ('perceiver', 'PerceiverImageProcessor'),
        ('pix2struct', 'Pix2StructImageProcessor'),
        ('poolformer', 'PoolFormerImageProcessor'),
        ('regnet', 'ConvNextImageProcessor'),
        ('resnet', 'ConvNextImageProcessor'),
        ('sam', 'SamImageProcessor'),
        ('segformer', 'SegformerImageProcessor'),
        ('swiftformer', 'ViTImageProcessor'),
        ('swin', 'ViTImageProcessor'),
        ('swin2sr', 'Swin2SRImageProcessor'),
        ('swinv2', 'ViTImageProcessor'),
        ('table-transformer', 'DetrImageProcessor'),
        ('timesformer', 'VideoMAEImageProcessor'),
        ('tvlt', 'TvltImageProcessor'),
        ('upernet', 'SegformerImageProcessor'),
        ('van', 'ConvNextImageProcessor'),
        ('videomae', 'VideoMAEImageProcessor'),
        ('vilt', 'ViltImageProcessor'),
        ('vit', 'ViTImageProcessor'),
        ('vit_hybrid', 'ViTHybridImageProcessor'),
        ('vit_mae', 'ViTImageProcessor'),
        ('vit_msn', 'ViTImageProcessor'),
        ('xclip', 'CLIPImageProcessor'),
        ('yolos', 'YolosImageProcessor'),
    ]
)

lowerCAmelCase_     :       List[str]								=						_LazyAutoMapping(CONFIG_MAPPING_NAMES, IMAGE_PROCESSOR_MAPPING_NAMES)
def 					UpperCAmelCase   (						A  :				str				):
							for module_name, extractors in IMAGE_PROCESSOR_MAPPING_NAMES.items():
														if class_name in extractors:
																					SCREAMING_SNAKE_CASE					:      Tuple     					=			model_type_to_module_name(A				)

																					SCREAMING_SNAKE_CASE					:      List[Any]     					=			importlib.import_module(F""".{module_name}"""					,		'''transformers.models'''				)
																					try:
																												return getattr(A					,		A				)
																					except AttributeError:
																												continue

							for _, extractor in IMAGE_PROCESSOR_MAPPING._extra_content.items():
														if getattr(A					,		'''__name__'''					,		A				) == class_name:
																					return extractor

    # We did not fine the class, but maybe it's because a dep is missing. In that case, the class will be in the main
    # init and we return the proper dummy to get an appropriate error message.
							SCREAMING_SNAKE_CASE					:      List[str]     					=			importlib.import_module('''transformers'''				)
							if hasattr(A					,		A				):
														return getattr(A					,		A				)

							return None
def 					UpperCAmelCase   (						A  :				Union[str, os.PathLike]					,		A  :				Optional[Union[str, os.PathLike]] = None					,		A  :				bool = False					,		A  :				bool = False					,		A  :				Optional[Dict[str, str]] = None					,		A  :				Optional[Union[bool, str]] = None					,		A  :				Optional[str] = None					,		A  :				bool = False					,		**A  :				List[str]					,		):
							SCREAMING_SNAKE_CASE					:      List[Any]     					=			get_file_from_repo(
							    A					,		A					,		cache_dir=A					,		force_download=A					,		resume_download=A					,		proxies=A					,		use_auth_token=A					,		revision=A					,		local_files_only=A					,		)
							if resolved_config_file is None:
														logger.info(
														    '''Could not locate the image processor configuration file, will try to use the model config instead.'''				)
														return {}

							with open(A					,		encoding='''utf-8'''				) as reader:
														return json.load(A				)






class 	lowerCamelCase_							:







						def __init__(  self   :      Tuple				):

													"""simple docstring"""
													raise EnvironmentError(
													    '''AutoImageProcessor is designed to be instantiated '''
													    '''using the `AutoImageProcessor.from_pretrained(pretrained_model_name_or_path)` method.'''				)







						@classmethod
						@replace_list_option_in_docstrings(lowerCAmelCase__				)
						def 					__lowercase    (  cls   :      int				,    lowerCAmelCase__   :      Optional[int]				,    **lowerCAmelCase__   :      List[Any]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Any     					=			kwargs.pop('''config'''				,    lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Tuple     					=			kwargs.pop('''trust_remote_code'''				,    lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      List[str]     					=			True

													SCREAMING_SNAKE_CASE					,SCREAMING_SNAKE_CASE					:      str     					=			ImageProcessingMixin.get_image_processor_dict(lowerCAmelCase__				,    **lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Tuple     					=			config_dict.get('''image_processor_type'''				,    lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      str     					=			None
													if "AutoImageProcessor" in config_dict.get('''auto_map'''				,    {}				):
																				SCREAMING_SNAKE_CASE					:      List[Any]     					=			config_dict['''auto_map''']['''AutoImageProcessor''']

													# If we still don't have the image processor class, check if we're loading from a previous feature extractor config
													# and if so, infer the image processor class from there.
													if image_processor_class is None and image_processor_auto_map is None:
																				SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			config_dict.pop('''feature_extractor_type'''				,    lowerCAmelCase__				)
																				if feature_extractor_class is not None:
																											logger.warning(
																											    '''Could not find image processor class in the image processor config or the model config. Loading'''
																											    ''' based on pattern matching with the model\'s feature extractor configuration.'''				)
																											SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			feature_extractor_class.replace('''FeatureExtractor'''				,    '''ImageProcessor'''				)
																				if "AutoFeatureExtractor" in config_dict.get('''auto_map'''				,    {}				):
																											SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			config_dict['''auto_map''']['''AutoFeatureExtractor''']
																											SCREAMING_SNAKE_CASE					:      str     					=			feature_extractor_auto_map.replace('''FeatureExtractor'''				,    '''ImageProcessor'''				)
																											logger.warning(
																											    '''Could not find image processor auto map in the image processor config or the model config.'''
																											    ''' Loading based on pattern matching with the model\'s feature extractor configuration.'''				)

        # If we don't find the image processor class in the image processor config, let's try the model config.
													if image_processor_class is None and image_processor_auto_map is None:
																				if not isinstance(lowerCAmelCase__				,    lowerCAmelCase__				):
																											SCREAMING_SNAKE_CASE					:      List[str]     					=			AutoConfig.from_pretrained(lowerCAmelCase__				,    **lowerCAmelCase__				)
																				# It could be in `config.image_processor_type``
																				SCREAMING_SNAKE_CASE					:      Any     					=			getattr(lowerCAmelCase__				,    '''image_processor_type'''				,    lowerCAmelCase__				)
																				if hasattr(lowerCAmelCase__				,    '''auto_map'''				) and "AutoImageProcessor" in config.auto_map:
																											SCREAMING_SNAKE_CASE					:      Tuple     					=			config.auto_map['''AutoImageProcessor''']

													if image_processor_class is not None:
																				SCREAMING_SNAKE_CASE					:      List[str]     					=			image_processor_class_from_name(lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      Tuple     					=			image_processor_auto_map is not None
													SCREAMING_SNAKE_CASE					:      str     					=			image_processor_class is not None or type(lowerCAmelCase__				) in IMAGE_PROCESSOR_MAPPING
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			resolve_trust_remote_code(
													    lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__				)

													if has_remote_code and trust_remote_code:
																				SCREAMING_SNAKE_CASE					:      List[Any]     					=			get_class_from_dynamic_module(
																				    lowerCAmelCase__				,    lowerCAmelCase__				,    **lowerCAmelCase__				)
																				SCREAMING_SNAKE_CASE					:      Optional[int]     					=			kwargs.pop('''code_revision'''				,    lowerCAmelCase__				)
																				if os.path.isdir(lowerCAmelCase__				):
																											image_processor_class.register_for_auto_class()
																				return image_processor_class.from_dict(lowerCAmelCase__				,    **lowerCAmelCase__				)
													elif image_processor_class is not None:
																				return image_processor_class.from_dict(lowerCAmelCase__				,    **lowerCAmelCase__				)
													# Last try: we use the IMAGE_PROCESSOR_MAPPING.
													elif type(lowerCAmelCase__				) in IMAGE_PROCESSOR_MAPPING:
																				SCREAMING_SNAKE_CASE					:      List[str]     					=			IMAGE_PROCESSOR_MAPPING[type(lowerCAmelCase__				)]
																				return image_processor_class.from_dict(lowerCAmelCase__				,    **lowerCAmelCase__				)

													raise ValueError(
													    F"""Unrecognized image processor in {pretrained_model_name_or_path}. Should have a """
													    F"""`image_processor_type` key in its {IMAGE_PROCESSOR_NAME} of {CONFIG_NAME}, or one of the following """
													    F"""`model_type` keys in its {CONFIG_NAME}: {", ".join(c for c in IMAGE_PROCESSOR_MAPPING_NAMES.keys()				)}"""				)







						@staticmethod
						def 					__lowercase    (  lowerCAmelCase__   :      Optional[int]				,    lowerCAmelCase__   :      Optional[int]				):

													"""simple docstring"""
													IMAGE_PROCESSOR_MAPPING.register(lowerCAmelCase__				,    lowerCAmelCase__				)




