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

# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...feature_extraction_utils import FeatureExtractionMixin
from ...utils import CONFIG_NAME, FEATURE_EXTRACTOR_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,
)


A_:   Tuple   =      logging.get_logger(__name__)

A_:   Tuple   =      OrderedDict(
    [
        ('audio-spectrogram-transformer', 'ASTFeatureExtractor'),
        ('beit', 'BeitFeatureExtractor'),
        ('chinese_clip', 'ChineseCLIPFeatureExtractor'),
        ('clap', 'ClapFeatureExtractor'),
        ('clip', 'CLIPFeatureExtractor'),
        ('clipseg', 'ViTFeatureExtractor'),
        ('conditional_detr', 'ConditionalDetrFeatureExtractor'),
        ('convnext', 'ConvNextFeatureExtractor'),
        ('cvt', 'ConvNextFeatureExtractor'),
        ('data2vec-audio', 'Wav2Vec2FeatureExtractor'),
        ('data2vec-vision', 'BeitFeatureExtractor'),
        ('deformable_detr', 'DeformableDetrFeatureExtractor'),
        ('deit', 'DeiTFeatureExtractor'),
        ('detr', 'DetrFeatureExtractor'),
        ('dinat', 'ViTFeatureExtractor'),
        ('donut-swin', 'DonutFeatureExtractor'),
        ('dpt', 'DPTFeatureExtractor'),
        ('encodec', 'EncodecFeatureExtractor'),
        ('flava', 'FlavaFeatureExtractor'),
        ('glpn', 'GLPNFeatureExtractor'),
        ('groupvit', 'CLIPFeatureExtractor'),
        ('hubert', 'Wav2Vec2FeatureExtractor'),
        ('imagegpt', 'ImageGPTFeatureExtractor'),
        ('layoutlmv2', 'LayoutLMv2FeatureExtractor'),
        ('layoutlmv3', 'LayoutLMv3FeatureExtractor'),
        ('levit', 'LevitFeatureExtractor'),
        ('maskformer', 'MaskFormerFeatureExtractor'),
        ('mctct', 'MCTCTFeatureExtractor'),
        ('mobilenet_v1', 'MobileNetV1FeatureExtractor'),
        ('mobilenet_v2', 'MobileNetV2FeatureExtractor'),
        ('mobilevit', 'MobileViTFeatureExtractor'),
        ('nat', 'ViTFeatureExtractor'),
        ('owlvit', 'OwlViTFeatureExtractor'),
        ('perceiver', 'PerceiverFeatureExtractor'),
        ('poolformer', 'PoolFormerFeatureExtractor'),
        ('regnet', 'ConvNextFeatureExtractor'),
        ('resnet', 'ConvNextFeatureExtractor'),
        ('segformer', 'SegformerFeatureExtractor'),
        ('sew', 'Wav2Vec2FeatureExtractor'),
        ('sew-d', 'Wav2Vec2FeatureExtractor'),
        ('speech_to_text', 'Speech2TextFeatureExtractor'),
        ('speecht5', 'SpeechT5FeatureExtractor'),
        ('swiftformer', 'ViTFeatureExtractor'),
        ('swin', 'ViTFeatureExtractor'),
        ('swinv2', 'ViTFeatureExtractor'),
        ('table-transformer', 'DetrFeatureExtractor'),
        ('timesformer', 'VideoMAEFeatureExtractor'),
        ('tvlt', 'TvltFeatureExtractor'),
        ('unispeech', 'Wav2Vec2FeatureExtractor'),
        ('unispeech-sat', 'Wav2Vec2FeatureExtractor'),
        ('van', 'ConvNextFeatureExtractor'),
        ('videomae', 'VideoMAEFeatureExtractor'),
        ('vilt', 'ViltFeatureExtractor'),
        ('vit', 'ViTFeatureExtractor'),
        ('vit_mae', 'ViTFeatureExtractor'),
        ('vit_msn', 'ViTFeatureExtractor'),
        ('wav2vec2', 'Wav2Vec2FeatureExtractor'),
        ('wav2vec2-conformer', 'Wav2Vec2FeatureExtractor'),
        ('wavlm', 'Wav2Vec2FeatureExtractor'),
        ('whisper', 'WhisperFeatureExtractor'),
        ('xclip', 'CLIPFeatureExtractor'),
        ('yolos', 'YolosFeatureExtractor'),
    ]
)

A_:   Any   =      _LazyAutoMapping(CONFIG_MAPPING_NAMES, FEATURE_EXTRACTOR_MAPPING_NAMES)


def        __lowerCAmelCase      (	_A       ):



							"""simple docstring"""


							for module_name, extractors in FEATURE_EXTRACTOR_MAPPING_NAMES.items():
														if class_name in extractors:
																					_lowercase					=						model_type_to_module_name(_UpperCamelCase       )

																					_lowercase					=						importlib.import_module(f'''.{module_name}'''			,"""transformers.models"""       )
																					try:
																												return getattr(_UpperCamelCase			,_UpperCamelCase       )
																					except AttributeError:
																												continue

							for _, extractor in FEATURE_EXTRACTOR_MAPPING._extra_content.items():
														if getattr(_UpperCamelCase			,"""__name__"""			,_UpperCamelCase       ) == 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.
							_lowercase					=						importlib.import_module("""transformers"""       )
							if hasattr(_UpperCamelCase			,_UpperCamelCase       ):
														return getattr(_UpperCamelCase			,_UpperCamelCase       )

							return None


def        __lowerCAmelCase      (	_A			,_A = None			,_A = False			,_A = False			,_A = None			,_A = None			,_A = None			,_A = False			,**_A			,):



							"""simple docstring"""


							_lowercase					=						get_file_from_repo(
							    _UpperCamelCase			,_UpperCamelCase			,cache_dir=_UpperCamelCase			,force_download=_UpperCamelCase			,resume_download=_UpperCamelCase			,proxies=_UpperCamelCase			,use_auth_token=_UpperCamelCase			,revision=_UpperCamelCase			,local_files_only=_UpperCamelCase			,)
							if resolved_config_file is None:
														logger.info(
														    """Could not locate the feature extractor configuration file, will try to use the model config instead."""       )
														return {}

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







class _lowercase       :





							"""simple docstring"""




							def __init__(     self	):







														'''simple docstring'''






														raise EnvironmentError(
														    """AutoFeatureExtractor is designed to be instantiated """
														    """using the `AutoFeatureExtractor.from_pretrained(pretrained_model_name_or_path)` method."""	)



							@classmethod
							@replace_list_option_in_docstrings(snake_case_	)
							def      _UpperCAmelCase							(     cls  , UpperCAmelCase  , **UpperCAmelCase	):







														'''simple docstring'''






														_lowercase					=						kwargs.pop("""config"""  , snake_case_	)
														_lowercase					=						kwargs.pop("""trust_remote_code"""  , snake_case_	)
														_lowercase					=						True

														_lowercase					,							_lowercase					=						FeatureExtractionMixin.get_feature_extractor_dict(snake_case_  , **snake_case_	)
														_lowercase					=						config_dict.get("""feature_extractor_type"""  , snake_case_	)
														_lowercase					=						None
														if "AutoFeatureExtractor" in config_dict.get("""auto_map"""  , {}	):
																					_lowercase					=						config_dict["""auto_map"""]["""AutoFeatureExtractor"""]

														# If we don't find the feature extractor class in the feature extractor config, let's try the model config.
														if feature_extractor_class is None and feature_extractor_auto_map is None:
																					if not isinstance(snake_case_  , snake_case_	):
																												_lowercase					=						AutoConfig.from_pretrained(snake_case_  , **snake_case_	)
																					# It could be in `config.feature_extractor_type``
																					_lowercase					=						getattr(snake_case_  , """feature_extractor_type"""  , snake_case_	)
																					if hasattr(snake_case_  , """auto_map"""	) and "AutoFeatureExtractor" in config.auto_map:
																												_lowercase					=						config.auto_map["""AutoFeatureExtractor"""]

														if feature_extractor_class is not None:
																					_lowercase					=						feature_extractor_class_from_name(snake_case_	)

														_lowercase					=						feature_extractor_auto_map is not None
														_lowercase					=						feature_extractor_class is not None or type(snake_case_	) in FEATURE_EXTRACTOR_MAPPING
														_lowercase					=						resolve_trust_remote_code(
														    snake_case_  , snake_case_  , snake_case_  , snake_case_	)

														if has_remote_code and trust_remote_code:
																					_lowercase					=						get_class_from_dynamic_module(
																					    snake_case_  , snake_case_  , **snake_case_	)
																					_lowercase					=						kwargs.pop("""code_revision"""  , snake_case_	)
																					if os.path.isdir(snake_case_	):
																												feature_extractor_class.register_for_auto_class()
																					return feature_extractor_class.from_dict(snake_case_  , **snake_case_	)
														elif feature_extractor_class is not None:
																					return feature_extractor_class.from_dict(snake_case_  , **snake_case_	)
														# Last try: we use the FEATURE_EXTRACTOR_MAPPING.
														elif type(snake_case_	) in FEATURE_EXTRACTOR_MAPPING:
																					_lowercase					=						FEATURE_EXTRACTOR_MAPPING[type(snake_case_	)]
																					return feature_extractor_class.from_dict(snake_case_  , **snake_case_	)

														raise ValueError(
														    F'''Unrecognized feature extractor in {pretrained_model_name_or_path}. Should have a '''
														    F'''`feature_extractor_type` key in its {FEATURE_EXTRACTOR_NAME} of {CONFIG_NAME}, or one of the following '''
														    F'''`model_type` keys in its {CONFIG_NAME}: {", ".join(c for c in FEATURE_EXTRACTOR_MAPPING_NAMES.keys()	)}'''	)



							@staticmethod
							def      _UpperCAmelCase							(     UpperCAmelCase  , UpperCAmelCase	):







														'''simple docstring'''






														FEATURE_EXTRACTOR_MAPPING.register(snake_case_  , snake_case_	)






a			:			Any												=					[
    '''Audio''',
    '''Array2D''',
    '''Array3D''',
    '''Array4D''',
    '''Array5D''',
    '''ClassLabel''',
    '''Features''',
    '''Sequence''',
    '''Value''',
    '''Image''',
    '''Translation''',
    '''TranslationVariableLanguages''',
]
from .audio import Audio
from .features import ArrayaD, ArrayaD, ArrayaD, ArrayaD, ClassLabel, Features, Sequence, Value
from .image import Image
from .translation import Translation, TranslationVariableLanguages


