




'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


a__         =     {
    '''configuration_markuplm''': ['''MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MarkupLMConfig'''],
    '''feature_extraction_markuplm''': ['''MarkupLMFeatureExtractor'''],
    '''processing_markuplm''': ['''MarkupLMProcessor'''],
    '''tokenization_markuplm''': ['''MarkupLMTokenizer'''],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a__         =     ['''MarkupLMTokenizerFast''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a__         =     [
		    '''MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''MarkupLMForQuestionAnswering''',
		    '''MarkupLMForSequenceClassification''',
		    '''MarkupLMForTokenClassification''',
		    '''MarkupLMModel''',
		    '''MarkupLMPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_markuplm import MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP, MarkupLMConfig
		from .feature_extraction_markuplm import MarkupLMFeatureExtractor
		from .processing_markuplm import MarkupLMProcessor
		from .tokenization_markuplm import MarkupLMTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_markuplm_fast import MarkupLMTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_markuplm import (
				    MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST,
				    MarkupLMForQuestionAnswering,
				    MarkupLMForSequenceClassification,
				    MarkupLMForTokenClassification,
				    MarkupLMModel,
				    MarkupLMPreTrainedModel,
				)


else:
		import sys

		a__         =     _LazyModule(__name__, globals()['''__file__'''], _import_structure)





'''simple docstring'''

import warnings

from ...utils import logging
from .image_processing_vit import ViTImageProcessor


a__         =     logging.get_logger(__name__)





class __magic_name__(						__lowerCAmelCase      ):






						def __init__(   self						:						List[str]					,   *__UpperCamelCase						:						Tuple					,   **__UpperCamelCase						:						Tuple       ):



									'''simple docstring'''






									warnings.warn(
									    """The class ViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
									    """ use ViTImageProcessor instead."""					,   __UpperCamelCase					,   )
									super().__init__(*__UpperCamelCase					,   **__UpperCamelCase       )