import copy

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


UpperCamelCase    				=		logging.get_logger(__name__)

UpperCamelCase    				=		{}



class     snake_case_			(						__A			):
   __A      :						List[str]   =							"fsmt_decoder"






   def __init__( self							:	Union[str, Any]      ,		lowercase_							:	Dict=0      ,		lowercase_							:	Optional[int]=0    )   ->		List[Any]:
       super().__init__()
       lowercase__					:  List[str]          =							vocab_size
       lowercase__					:  Optional[int]          =							bos_token_id



class     snake_case_			(						__A			):
   __A      :						Any   =							"fsmt"
   __A      :						Dict   =							{"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}






   def __init__( self							:	Union[str, Any]      ,		lowercase_							:	Optional[Any]=["en", "de"]      ,		lowercase_							:	Dict=4_20_24      ,		lowercase_							:	List[Any]=4_20_24      ,		lowercase_							:	List[Any]="relu"      ,		lowercase_							:	str=10_24      ,		lowercase_							:	int=2_00      ,		lowercase_							:	Optional[Any]=10_24      ,		lowercase_							:	Any=40_96      ,		lowercase_							:	List[Any]=12      ,		lowercase_							:	Dict=16      ,		lowercase_							:	List[Any]=0.0      ,		lowercase_							:	Any=40_96      ,		lowercase_							:	List[Any]=12      ,		lowercase_							:	str=16      ,		lowercase_							:	List[str]=0.0      ,		lowercase_							:	Tuple=0.0      ,		lowercase_							:	str=0.1      ,		lowercase_							:	Dict=0.0      ,		lowercase_							:	Optional[Any]=0.02      ,		lowercase_							:	Tuple=2      ,		lowercase_							:	Tuple=True      ,		lowercase_							:	str=True      ,		lowercase_							:	Tuple=False      ,		lowercase_							:	int=5      ,		lowercase_							:	str=1.0      ,		lowercase_							:	Union[str, Any]=False      ,		lowercase_							:	str=True      ,		lowercase_							:	Dict=1      ,		lowercase_							:	Optional[Any]=0      ,		lowercase_							:	Tuple=2      ,		lowercase_							:	Union[str, Any]=2      ,		**lowercase_							:	Any      ,		)   ->		List[str]:
       lowercase__					:  Any          =							langs
       lowercase__					:  int          =							src_vocab_size
       lowercase__					:  Optional[int]          =							tgt_vocab_size
       lowercase__					:  Union[str, Any]          =							d_model  # encoder_embed_dim and decoder_embed_dim

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

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

       lowercase__					:  Union[str, Any]          =							scale_embedding  # scale factor will be sqrt(d_model) if True

       # 3 Types of Dropout
       lowercase__					:  List[Any]          =							attention_dropout
       lowercase__					:  str          =							activation_dropout
       lowercase__					:  Optional[Any]          =							dropout

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







   def  __UpperCamelCase	( self							:	Any    )   ->		List[str]:
       lowercase__					:  Tuple          =							copy.deepcopy(self.__dict__    )
       lowercase__					:  str          =							self.decoder.to_dict()
       lowercase__					:  Optional[Any]          =							self.__class__.model_type
       return output






"""simple docstring"""

from typing import TYPE_CHECKING

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


a__			:						str							=			{
    """configuration_rwkv""": ["""RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RwkvConfig""", """RwkvOnnxConfig"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a__			:						Optional[int]							=			[
							    """RWKV_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """RwkvForCausalLM""",
							    """RwkvModel""",
							    """RwkvPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_rwkv import RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP, RwkvConfig, RwkvOnnxConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_rwkv import (
														    RWKV_PRETRAINED_MODEL_ARCHIVE_LIST,
														    RwkvForCausalLM,
														    RwkvModel,
														    RwkvPreTrainedModel,
														)
else:
							import sys

							a__			:						List[str]							=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


