



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCamelCase_									=   logging.get_logger(__name__)

UpperCamelCase_									=   {
    '''mnaylor/mega-base-wikitext''': '''https://huggingface.co/mnaylor/mega-base-wikitext/resolve/main/config.json''',
}







class       _snake_case				(     __snake_case ):






   '''simple docstring'''






   A__      : List[str]       =						"mega"


   def __init__(    self:     List[Any]  ,lowerCamelCase_:     Union[str, Any]=30522  ,lowerCamelCase_:     Union[str, Any]=128  ,lowerCamelCase_:     Optional[int]=4  ,lowerCamelCase_:     int=256  ,lowerCamelCase_:     Optional[Any]=16  ,lowerCamelCase_:     Dict=True  ,lowerCamelCase_:     str=64  ,lowerCamelCase_:     List[str]=False  ,lowerCamelCase_:     int=-1  ,lowerCamelCase_:     Union[str, Any]=None  ,lowerCamelCase_:     Optional[int]=True  ,lowerCamelCase_:     Optional[Any]="scalenorm"  ,lowerCamelCase_:     str=True  ,lowerCamelCase_:     Union[str, Any]="silu"  ,lowerCamelCase_:     Optional[int]="softmax"  ,lowerCamelCase_:     str=0.1  ,lowerCamelCase_:     List[str]=0.1  ,lowerCamelCase_:     Any=0.1  ,lowerCamelCase_:     Dict=False  ,lowerCamelCase_:     Optional[int]=True  ,lowerCamelCase_:     List[Any]=256  ,lowerCamelCase_:     int=True  ,lowerCamelCase_:     int=0.1  ,lowerCamelCase_:     Any=2048  ,lowerCamelCase_:     List[str]=False  ,lowerCamelCase_:     Dict=2  ,lowerCamelCase_:     Union[str, Any]=0.0_2  ,lowerCamelCase_:     List[str]=0.2  ,lowerCamelCase_:     Optional[Any]=0.0_2  ,lowerCamelCase_:     str=1.0  ,lowerCamelCase_:     Optional[int]=1  ,lowerCamelCase_:     Any=0  ,lowerCamelCase_:     Dict=2  ,lowerCamelCase_:     List[str]="rotary"  ,lowerCamelCase_:     Any=None  ,lowerCamelCase_:     List[str]=True  ,lowerCamelCase_:     Tuple=True  ,**lowerCamelCase_:     int  ,)	->      List[Any]:
       super().__init__(pad_token_id=lowerCamelCase_  ,bos_token_id=lowerCamelCase_  ,eos_token_id=lowerCamelCase_  ,**lowerCamelCase_							)

       UpperCAmelCase_     :       List[Any]  		=					vocab_size
       UpperCAmelCase_     :       Any  		=					hidden_size
       UpperCAmelCase_     :       int  		=					num_hidden_layers
       UpperCAmelCase_     :       Any  		=					activation
       UpperCAmelCase_     :       Any  		=					attention_activation
       UpperCAmelCase_     :       Optional[int]  		=					intermediate_size
       UpperCAmelCase_     :       Optional[Any]  		=					ema_projection_size
       UpperCAmelCase_     :       List[Any]  		=					bidirectional
       UpperCAmelCase_     :       Union[str, Any]  		=					shared_representation_size
       UpperCAmelCase_     :       str  		=					use_chunking
       UpperCAmelCase_     :       int  		=					chunk_size
       UpperCAmelCase_     :       Dict  		=					truncation
       UpperCAmelCase_     :       Tuple  		=					normalize_before_mega
       UpperCAmelCase_     :       int  		=					normalization_type
       UpperCAmelCase_     :       Tuple  		=					norm_affine
       UpperCAmelCase_     :       Optional[Any]  		=					dropout_prob
       UpperCAmelCase_     :       int  		=					hidden_dropout_prob
       UpperCAmelCase_     :       Union[str, Any]  		=					attention_probs_dropout_prob
       UpperCAmelCase_     :       Any  		=					use_feature_dropout
       UpperCAmelCase_     :       str  		=					use_normalized_ffn
       UpperCAmelCase_     :       List[Any]  		=					nffn_hidden_size
       UpperCAmelCase_     :       int  		=					normalize_before_ffn
       UpperCAmelCase_     :       List[Any]  		=					nffn_activation_dropout_prob
       UpperCAmelCase_     :       Optional[int]  		=					max_positions
       UpperCAmelCase_     :       str  		=					add_token_type_embeddings
       UpperCAmelCase_     :       int  		=					type_vocab_size
       UpperCAmelCase_     :       int  		=					initializer_range
       UpperCAmelCase_     :       Optional[Any]  		=					ema_delta_alpha_range
       UpperCAmelCase_     :       Any  		=					ema_beta_range
       UpperCAmelCase_     :       Optional[int]  		=					ema_gamma_omega_range
       UpperCAmelCase_     :       List[Any]  		=					relative_positional_bias
       UpperCAmelCase_     :       Tuple  		=					use_cache
       UpperCAmelCase_     :       str  		=					classifier_dropout
       UpperCAmelCase_     :       Union[str, Any]  		=					add_lm_hidden_dense_layer
       UpperCAmelCase_     :       Optional[int]  		=					1  # not used but required by Hugging Face







class       _snake_case				(     __snake_case ):






   '''simple docstring'''






   @property
   def       A__    (    self:     str							)	->      Mapping[str, Mapping[int, str]]:
       if self.task == "multiple-choice":
           UpperCAmelCase_     :       Optional[int]  		=					{0: """batch""", 1: """choice""", 2: """sequence"""}
       else:
           UpperCAmelCase_     :       Union[str, Any]  		=					{0: """batch""", 1: """sequence"""}
       return OrderedDict(
           [
               ("""input_ids""", dynamic_axis),
               ("""attention_mask""", dynamic_axis),
           ]							)





import copy

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


UpperCamelCase_									=   logging.get_logger(__name__)

UpperCamelCase_									=   {}







class       _snake_case				(     __snake_case ):






   '''simple docstring'''






   A__      : List[str]       =						"fsmt_decoder"


   def __init__(    self:     Optional[Any]  ,lowerCamelCase_:     Tuple=0  ,lowerCamelCase_:     List[str]=0							)	->      Any:
       super().__init__()
       UpperCAmelCase_     :       Optional[Any]  		=					vocab_size
       UpperCAmelCase_     :       Union[str, Any]  		=					bos_token_id







class       _snake_case				(     __snake_case ):






   '''simple docstring'''






   A__      : Dict       =						"fsmt"
   A__      : int       =						{"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}


   def __init__(    self:     int  ,lowerCamelCase_:     Optional[Any]=["en", "de"]  ,lowerCamelCase_:     Any=42024  ,lowerCamelCase_:     Any=42024  ,lowerCamelCase_:     List[str]="relu"  ,lowerCamelCase_:     Any=1024  ,lowerCamelCase_:     Optional[int]=200  ,lowerCamelCase_:     str=1024  ,lowerCamelCase_:     Any=4096  ,lowerCamelCase_:     Dict=12  ,lowerCamelCase_:     Tuple=16  ,lowerCamelCase_:     List[Any]=0.0  ,lowerCamelCase_:     str=4096  ,lowerCamelCase_:     Union[str, Any]=12  ,lowerCamelCase_:     Any=16  ,lowerCamelCase_:     List[str]=0.0  ,lowerCamelCase_:     str=0.0  ,lowerCamelCase_:     Optional[int]=0.1  ,lowerCamelCase_:     List[Any]=0.0  ,lowerCamelCase_:     Tuple=0.0_2  ,lowerCamelCase_:     str=2  ,lowerCamelCase_:     List[str]=True  ,lowerCamelCase_:     Dict=True  ,lowerCamelCase_:     Any=False  ,lowerCamelCase_:     Any=5  ,lowerCamelCase_:     Optional[int]=1.0  ,lowerCamelCase_:     List[str]=False  ,lowerCamelCase_:     List[Any]=True  ,lowerCamelCase_:     List[str]=1  ,lowerCamelCase_:     int=0  ,lowerCamelCase_:     Optional[Any]=2  ,lowerCamelCase_:     Any=2  ,**lowerCamelCase_:     Optional[Any]  ,)	->      int:
       UpperCAmelCase_     :       Dict  		=					langs
       UpperCAmelCase_     :       Tuple  		=					src_vocab_size
       UpperCAmelCase_     :       Optional[int]  		=					tgt_vocab_size
       UpperCAmelCase_     :       Optional[Any]  		=					d_model  # encoder_embed_dim and decoder_embed_dim

       UpperCAmelCase_     :       List[str]  		=					encoder_ffn_dim
       UpperCAmelCase_     :       List[Any]  		=					encoder_layers
       UpperCAmelCase_     :       List[Any]  		=					encoder_attention_heads
       UpperCAmelCase_     :       Union[str, Any]  		=					encoder_layerdrop
       UpperCAmelCase_     :       List[Any]  		=					decoder_layerdrop
       UpperCAmelCase_     :       str  		=					decoder_ffn_dim
       UpperCAmelCase_     :       Optional[int]  		=					decoder_layers
       UpperCAmelCase_     :       int  		=					decoder_attention_heads
       UpperCAmelCase_     :       List[Any]  		=					max_position_embeddings
       UpperCAmelCase_     :       Dict  		=					init_std  # Normal(0, this parameter)
       UpperCAmelCase_     :       Dict  		=					activation_function

       UpperCAmelCase_     :       List[str]  		=					DecoderConfig(vocab_size=lowerCamelCase_  ,bos_token_id=lowerCamelCase_							)
       if "decoder" in common_kwargs:
           del common_kwargs["decoder"]

       UpperCAmelCase_     :       Any  		=					scale_embedding  # scale factor will be sqrt(d_model) if True

       # 3 Types of Dropout
       UpperCAmelCase_     :       int  		=					attention_dropout
       UpperCAmelCase_     :       int  		=					activation_dropout
       UpperCAmelCase_     :       Any  		=					dropout

       UpperCAmelCase_     :       Any  		=					use_cache
       super().__init__(
           pad_token_id=lowerCamelCase_  ,bos_token_id=lowerCamelCase_  ,eos_token_id=lowerCamelCase_  ,decoder_start_token_id=lowerCamelCase_  ,is_encoder_decoder=lowerCamelCase_  ,tie_word_embeddings=lowerCamelCase_  ,forced_eos_token_id=lowerCamelCase_  ,max_length=lowerCamelCase_  ,num_beams=lowerCamelCase_  ,length_penalty=lowerCamelCase_  ,early_stopping=lowerCamelCase_  ,**lowerCamelCase_  ,)






   def       A__    (    self:     List[str]							)	->      Union[str, Any]:
       UpperCAmelCase_     :       str  		=					copy.deepcopy(self.__dict__							)
       UpperCAmelCase_     :       int  		=					self.decoder.to_dict()
       UpperCAmelCase_     :       Dict  		=					self.__class__.model_type
       return output
