





'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


A         =				{
    '''configuration_layoutlmv2''': ['''LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LayoutLMv2Config'''],
    '''processing_layoutlmv2''': ['''LayoutLMv2Processor'''],
    '''tokenization_layoutlmv2''': ['''LayoutLMv2Tokenizer'''],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A         =				['''LayoutLMv2TokenizerFast''']

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A         =				['''LayoutLMv2FeatureExtractor''']
    A         =				['''LayoutLMv2ImageProcessor''']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A         =				[
        '''LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''LayoutLMv2ForQuestionAnswering''',
        '''LayoutLMv2ForSequenceClassification''',
        '''LayoutLMv2ForTokenClassification''',
        '''LayoutLMv2Layer''',
        '''LayoutLMv2Model''',
        '''LayoutLMv2PreTrainedModel''',
    ]

if TYPE_CHECKING:
    from .configuration_layoutlmva import LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMvaConfig
    from .processing_layoutlmva import LayoutLMvaProcessor
    from .tokenization_layoutlmva import LayoutLMvaTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor, LayoutLMvaImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_layoutlmva import (
            LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
            LayoutLMvaForQuestionAnswering,
            LayoutLMvaForSequenceClassification,
            LayoutLMvaForTokenClassification,
            LayoutLMvaLayer,
            LayoutLMvaModel,
            LayoutLMvaPreTrainedModel,
        )
else:
    import sys

    A         =				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






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


UpperCAmelCase_							=				logging.get_logger(__name__)

UpperCAmelCase_							=				{
    """google/canine-s""": """https://huggingface.co/google/canine-s/resolve/main/config.json""",
    # See all CANINE models at https://huggingface.co/models?filter=canine
}
class     UpperCamelCase__					(     lowerCamelCase__				):






		'''simple docstring'''






		__a       :       Optional[int]       =	"""canine"""






		def __init__(							self,   snake_case__=7_68,   snake_case__=12,   snake_case__=12,   snake_case__=30_72,   snake_case__="gelu",   snake_case__=0.1,   snake_case__=0.1,   snake_case__=1_63_84,   snake_case__=16,   snake_case__=0.02,   snake_case__=1E-12,   snake_case__=0,   snake_case__=0XE_0_0_0,   snake_case__=0XE_0_0_1,   snake_case__=4,   snake_case__=4,   snake_case__=8,   snake_case__=1_63_84,   snake_case__=1_28,   **snake_case__,   )       -> Optional[int]:






									"""simple docstring"""
									super().__init__(pad_token_id=snake_case__,   bos_token_id=snake_case__,   eos_token_id=snake_case__,   **snake_case__  )

									lowercase_	:   int  				=     max_position_embeddings
									lowercase_	:   Union[str, Any]  				=     hidden_size
									lowercase_	:   Optional[Any]  				=     num_hidden_layers
									lowercase_	:   str  				=     num_attention_heads
									lowercase_	:   List[Any]  				=     intermediate_size
									lowercase_	:   Optional[Any]  				=     hidden_act
									lowercase_	:   List[str]  				=     hidden_dropout_prob
									lowercase_	:   Any  				=     attention_probs_dropout_prob
									lowercase_	:   Union[str, Any]  				=     initializer_range
									lowercase_	:   Optional[Any]  				=     type_vocab_size
									lowercase_	:   Dict  				=     layer_norm_eps

									# Character config:
									lowercase_	:   Optional[int]  				=     downsampling_rate
									lowercase_	:   List[str]  				=     upsampling_kernel_size
									lowercase_	:   int  				=     num_hash_functions
									lowercase_	:   List[str]  				=     num_hash_buckets
									lowercase_	:   List[str]  				=     local_transformer_stride