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


UpperCAmelCase      		=					logging.get_logger(__name__)

UpperCAmelCase      		=					{
    '''openbmb/cpm-ant-10b''': '''https://huggingface.co/openbmb/cpm-ant-10b/blob/main/config.json'''
    # See all CPMAnt models at https://huggingface.co/models?filter=cpmant
}




class  __lowerCAmelCase	(							a_    ):



 '''simple docstring'''
 _lowerCamelCase    :						Any					     =			'cpmant'

 def __init__(      self							:		List[Any]							,      lowerCamelCase							:		int = 3_0_7_2_0							,      lowerCamelCase							:		int = 4_0_9_6							,      lowerCamelCase							:		int = 3_2							,      lowerCamelCase							:		int = 1_2_8							,      lowerCamelCase							:		int = 1_0_2_4_0							,      lowerCamelCase							:		int = 4_8							,      lowerCamelCase							:		int = 0.0							,      lowerCamelCase							:		int = 5_1_2							,      lowerCamelCase							:		int = 2_0_4_8							,      lowerCamelCase							:		int = 1e-6							,      lowerCamelCase							:		float = 1.0							,      lowerCamelCase							:		int = 3_2							,      lowerCamelCase							:		int = 3_2							,      lowerCamelCase							:		int = 3_2							,      lowerCamelCase							:		bool = True							,      **lowerCamelCase							:		int							,      )			->				Dict:
        super().__init__(**lowerCamelCase	)
        _UpperCamelCase  :							Union[str, Any]	    =	prompt_types
        _UpperCamelCase  :							Optional[Any]	    =	prompt_length
        _UpperCamelCase  :							Optional[int]	    =	segment_types
        _UpperCamelCase  :							List[str]	    =	hidden_size
        _UpperCamelCase  :							List[str]	    =	num_attention_heads
        _UpperCamelCase  :							str	    =	dim_head
        _UpperCamelCase  :							Optional[int]	    =	dim_ff
        _UpperCamelCase  :							List[str]	    =	num_hidden_layers
        _UpperCamelCase  :							List[Any]	    =	position_bias_num_buckets
        _UpperCamelCase  :							Optional[Any]	    =	position_bias_max_distance
        _UpperCamelCase  :							Dict	    =	dropout_p
        _UpperCamelCase  :							int	    =	eps
        _UpperCamelCase  :							List[str]	    =	use_cache
        _UpperCamelCase  :							List[Any]	    =	vocab_size
        _UpperCamelCase  :							int	    =	init_std










from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_		  =			{
    """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:
      SCREAMING_SNAKE_CASE_		  =			["""MarkupLMTokenizerFast"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE_		  =			[
          """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

      SCREAMING_SNAKE_CASE_		  =			_LazyModule(__name__, globals()["""__file__"""], _import_structure)


