





from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


SCREAMING_SNAKE_CASE_						       =	{
    """susnato/ernie-m-base_pytorch""": """https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json""",
    """susnato/ernie-m-large_pytorch""": """https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json""",
}

class 		UpperCamelCase__			(				lowerCAmelCase_       ):



     '''simple docstring'''

     __snake_case   :     Union[str, Any]		     =      "ernie_m"
     __snake_case   :     Dict[str, str]		     =      {"dropout": "classifier_dropout", "num_classes": "num_labels"}






     def __init__(							self						:   Optional[Any]						,lowerCamelCase__						:   int = 250002						,lowerCamelCase__						:   int = 768						,lowerCamelCase__						:   int = 12						,lowerCamelCase__						:   int = 12						,lowerCamelCase__						:   int = 3072						,lowerCamelCase__						:   str = "gelu"						,lowerCamelCase__						:   float = 0.1						,lowerCamelCase__						:   float = 0.1						,lowerCamelCase__						:   int = 514						,lowerCamelCase__						:   float = 0.02						,lowerCamelCase__						:   int = 1						,lowerCamelCase__						:   float = 1e-0_5						,lowerCamelCase__						:   str=None						,lowerCamelCase__						:   str=False						,lowerCamelCase__						:   str=0.0						,**lowerCamelCase__						:   Tuple						,)					->		int:




           '''simple docstring'''


           super().__init__(pad_token_id=lowerCamelCase__						,**lowerCamelCase__	)
           SCREAMING_SNAKE_CASE		=						vocab_size
           SCREAMING_SNAKE_CASE		=						hidden_size
           SCREAMING_SNAKE_CASE		=						num_hidden_layers
           SCREAMING_SNAKE_CASE		=						num_attention_heads
           SCREAMING_SNAKE_CASE		=						intermediate_size
           SCREAMING_SNAKE_CASE		=						hidden_act
           SCREAMING_SNAKE_CASE		=						hidden_dropout_prob
           SCREAMING_SNAKE_CASE		=						attention_probs_dropout_prob
           SCREAMING_SNAKE_CASE		=						max_position_embeddings
           SCREAMING_SNAKE_CASE		=						initializer_range
           SCREAMING_SNAKE_CASE		=						layer_norm_eps
           SCREAMING_SNAKE_CASE		=						classifier_dropout
           SCREAMING_SNAKE_CASE		=						is_decoder
           SCREAMING_SNAKE_CASE		=						act_dropout









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE_						       =	{
    """configuration_megatron_bert""": ["""MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MegatronBertConfig"""],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE_						       =	[
          """MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """MegatronBertForCausalLM""",
          """MegatronBertForMaskedLM""",
          """MegatronBertForMultipleChoice""",
          """MegatronBertForNextSentencePrediction""",
          """MegatronBertForPreTraining""",
          """MegatronBertForQuestionAnswering""",
          """MegatronBertForSequenceClassification""",
          """MegatronBertForTokenClassification""",
          """MegatronBertModel""",
          """MegatronBertPreTrainedModel""",
      ]

if TYPE_CHECKING:
      from .configuration_megatron_bert import MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MegatronBertConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_megatron_bert import (
                MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                MegatronBertForCausalLM,
                MegatronBertForMaskedLM,
                MegatronBertForMultipleChoice,
                MegatronBertForNextSentencePrediction,
                MegatronBertForPreTraining,
                MegatronBertForQuestionAnswering,
                MegatronBertForSequenceClassification,
                MegatronBertForTokenClassification,
                MegatronBertModel,
                MegatronBertPreTrainedModel,
            )

else:
      import sys

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


