




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a_ 		=  {
    "configuration_prophetnet": ["PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ProphetNetConfig"],
    "tokenization_prophetnet": ["ProphetNetTokenizer"],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a_ 		=  [
     "PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST",
     "ProphetNetDecoder",
     "ProphetNetEncoder",
     "ProphetNetForCausalLM",
     "ProphetNetForConditionalGeneration",
     "ProphetNetModel",
     "ProphetNetPreTrainedModel",
 ]


if TYPE_CHECKING:
 from .configuration_prophetnet import PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ProphetNetConfig
 from .tokenization_prophetnet import ProphetNetTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_prophetnet import (
      PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
      ProphetNetDecoder,
      ProphetNetEncoder,
      ProphetNetForCausalLM,
      ProphetNetForConditionalGeneration,
      ProphetNetModel,
      ProphetNetPreTrainedModel,
  )

else:
 import sys

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












import copy

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


UpperCamelCase__						=		logging.get_logger(__name__)

UpperCamelCase__						=		{}


class 							__SCREAMING_SNAKE_CASE				(						lowerCamelCase    ):
					_lowerCamelCase						    =					"""fsmt_decoder"""

					def __init__(							self					,			__lowercase=0					,			__lowercase=0   ):







						'''simple docstring'''




						super().__init__()
						lowerCamelCase_				:						Tuple				  =				vocab_size
						lowerCamelCase_				:						Union[str, Any]				  =				bos_token_id


class 							__SCREAMING_SNAKE_CASE				(						lowerCamelCase    ):
					_lowerCamelCase						    =					"""fsmt"""
					_lowerCamelCase						    =					{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}

					def __init__(							self					,			__lowercase=["en", "de"]					,			__lowercase=42_024					,			__lowercase=42_024					,			__lowercase="relu"					,			__lowercase=1_024					,			__lowercase=200					,			__lowercase=1_024					,			__lowercase=4_096					,			__lowercase=12					,			__lowercase=16					,			__lowercase=0.0					,			__lowercase=4_096					,			__lowercase=12					,			__lowercase=16					,			__lowercase=0.0					,			__lowercase=0.0					,			__lowercase=0.1					,			__lowercase=0.0					,			__lowercase=0.02					,			__lowercase=2					,			__lowercase=True					,			__lowercase=True					,			__lowercase=False					,			__lowercase=5					,			__lowercase=1.0					,			__lowercase=False					,			__lowercase=True					,			__lowercase=1					,			__lowercase=0					,			__lowercase=2					,			__lowercase=2					,			**__lowercase					,			):







						'''simple docstring'''




						lowerCamelCase_				:						Any				  =				langs
						lowerCamelCase_				:						Union[str, Any]				  =				src_vocab_size
						lowerCamelCase_				:						Tuple				  =				tgt_vocab_size
						lowerCamelCase_				:						List[Any]				  =				d_model  # encoder_embed_dim and decoder_embed_dim

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

						lowerCamelCase_				:						Union[str, Any]				  =				DecoderConfig(vocab_size=__lowercase					,			bos_token_id=__lowercase   )
						if "decoder" in common_kwargs:
							del common_kwargs["decoder"]

						lowerCamelCase_				:						int				  =				scale_embedding  # scale factor will be sqrt(d_model) if True

						# 3 Types of Dropout
						lowerCamelCase_				:						Optional[int]				  =				attention_dropout
						lowerCamelCase_				:						Union[str, Any]				  =				activation_dropout
						lowerCamelCase_				:						Dict				  =				dropout

						lowerCamelCase_				:						Optional[int]				  =				use_cache
						super().__init__(
						    pad_token_id=__lowercase					,			bos_token_id=__lowercase					,			eos_token_id=__lowercase					,			decoder_start_token_id=__lowercase					,			is_encoder_decoder=__lowercase					,			tie_word_embeddings=__lowercase					,			forced_eos_token_id=__lowercase					,			max_length=__lowercase					,			num_beams=__lowercase					,			length_penalty=__lowercase					,			early_stopping=__lowercase					,			**__lowercase					,			)





					def       lowercase_				(							self   ):







						'''simple docstring'''




						lowerCamelCase_				:						List[Any]				  =				copy.deepcopy(self.__dict__   )
						lowerCamelCase_				:						Optional[int]				  =				self.decoder.to_dict()
						lowerCamelCase_				:						Dict				  =				self.__class__.model_type
						return output
