






"""simple docstring"""


import copy

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


lowercase_								=	logging.get_logger(__name__)

lowercase_								=	{}


class    snake_case						(				_lowerCAmelCase		):


   '''simple docstring'''

   A_		:      List[str]							=					"fsmt_decoder"


   def __init__(      self					:	int,			_lowerCamelCase					:	Optional[Any]=0,			_lowerCamelCase					:	int=0    ):

     '''simple docstring'''
     super().__init__()
     __A		     =					vocab_size
     __A		     =					bos_token_id





class    snake_case						(				_lowerCAmelCase		):


   '''simple docstring'''

   A_		:      List[Any]							=					"fsmt"
   A_		:      List[str]							=					{"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}


   def __init__(      self					:	List[str],			_lowerCamelCase					:	List[Any]=["en", "de"],			_lowerCamelCase					:	int=4_20_24,			_lowerCamelCase					:	str=4_20_24,			_lowerCamelCase					:	Dict="relu",			_lowerCamelCase					:	List[str]=10_24,			_lowerCamelCase					:	Union[str, Any]=2_00,			_lowerCamelCase					:	Dict=10_24,			_lowerCamelCase					:	Optional[Any]=40_96,			_lowerCamelCase					:	str=12,			_lowerCamelCase					:	Any=16,			_lowerCamelCase					:	Dict=0.0,			_lowerCamelCase					:	Union[str, Any]=40_96,			_lowerCamelCase					:	List[str]=12,			_lowerCamelCase					:	int=16,			_lowerCamelCase					:	Dict=0.0,			_lowerCamelCase					:	List[Any]=0.0,			_lowerCamelCase					:	Any=0.1,			_lowerCamelCase					:	List[Any]=0.0,			_lowerCamelCase					:	List[Any]=0.02,			_lowerCamelCase					:	Union[str, Any]=2,			_lowerCamelCase					:	List[Any]=True,			_lowerCamelCase					:	Union[str, Any]=True,			_lowerCamelCase					:	Optional[Any]=False,			_lowerCamelCase					:	Tuple=5,			_lowerCamelCase					:	int=1.0,			_lowerCamelCase					:	Union[str, Any]=False,			_lowerCamelCase					:	Optional[Any]=True,			_lowerCamelCase					:	int=1,			_lowerCamelCase					:	Optional[int]=0,			_lowerCamelCase					:	List[str]=2,			_lowerCamelCase					:	List[str]=2,			**_lowerCamelCase					:	Any,			):

     '''simple docstring'''
     __A		     =					langs
     __A		     =					src_vocab_size
     __A		     =					tgt_vocab_size
     __A		     =					d_model  # encoder_embed_dim and decoder_embed_dim

     __A		     =					encoder_ffn_dim
     __A		     =					__A		     =					encoder_layers
     __A		     =					encoder_attention_heads
     __A		     =					encoder_layerdrop
     __A		     =					decoder_layerdrop
     __A		     =					decoder_ffn_dim
     __A		     =					decoder_layers
     __A		     =					decoder_attention_heads
     __A		     =					max_position_embeddings
     __A		     =					init_std  # Normal(0, this parameter)
     __A		     =					activation_function

     __A		     =					DecoderConfig(vocab_size=_lowerCamelCase,			bos_token_id=_lowerCamelCase    )
     if "decoder" in common_kwargs:
       del common_kwargs["decoder"]

     __A		     =					scale_embedding  # scale factor will be sqrt(d_model) if True

     # 3 Types of Dropout
     __A		     =					attention_dropout
     __A		     =					activation_dropout
     __A		     =					dropout

     __A		     =					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 							_SCREAMING_SNAKE_CASE							(      self					:	str    ):

     '''simple docstring'''
     __A		     =					copy.deepcopy(self.__dict__    )
     __A		     =					self.decoder.to_dict()
     __A		     =					self.__class__.model_type
     return output










"""simple docstring"""



import os

from apache_beam.io.filesystems import FileSystems
from apache_beam.pipeline import Pipeline

from .logging import get_logger


SCREAMING_SNAKE_CASE							=			2 << 20  # 2mb
SCREAMING_SNAKE_CASE							=			get_logger(__name__)




class       UpperCAmelCase_    (		A_				):




    def 				__magic_name__				(       self		:			Tuple ) ->				Optional[int]:




     '''simple docstring'''

     A__			=							self._options.get_all_options().get("runner" )
     return runner in [None, "DirectRunner", "PortableRunner"]







def     _SCREAMING_SNAKE_CASE  (				lowercase_     ,					lowercase_     ,					lowercase_=False		)		->						Dict:
 A__			=							FileSystems
 if fs.exists(lowercase_		):
  if force_upload:
   logger.info(f"""Remote path already exist: {remote_file_path}. Overwriting it as force_upload=True."""		)
  else:
   logger.info(f"""Remote path already exist: {remote_file_path}. Skipping it as force_upload=False."""		)
   return
 with fs.create(lowercase_		) as remote_file:
  with open(lowercase_     ,					"rb"		) as local_file:
   A__			=							local_file.read(lowercase_		)
   while chunk:
    remote_file.write(lowercase_		)
    A__			=							local_file.read(lowercase_		)







def     _SCREAMING_SNAKE_CASE  (				lowercase_     ,					lowercase_     ,					lowercase_=False		)		->						int:
 A__			=							FileSystems
 if os.path.exists(lowercase_		):
  if force_download:
   logger.info(f"""Local path already exist: {remote_file_path}. Overwriting it as force_upload=True."""		)
  else:
   logger.info(f"""Local path already exist: {remote_file_path}. Skipping it as force_upload=False."""		)
   return
 with fs.open(lowercase_		) as remote_file:
  with open(lowercase_     ,					"wb"		) as local_file:
   A__			=							remote_file.read(lowercase_		)
   while chunk:
    local_file.write(lowercase_		)
    A__			=							remote_file.read(lowercase_		)





