import os
import tempfile
import unittest

from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property

@unittest.skipUnless(os.path.exists(UpperCamelCase_						)   ,						'Tatoeba directory does not exist.'						)
class       snake_case					(      unittest.TestCase						):




  @cached_property
  def 	__lowercase(      self     :	str				)->       Optional[int]:




       """simple docstring"""
       SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		tempfile.mkdtemp()
       return TatoebaConverter(save_dir=a_				)




  @slow
  def 	__lowercase(      self     :	Union[str, Any]				)->       Dict:




       """simple docstring"""
       self.resolver.convert_models(['heb-eng']				)




  @slow
  def 	__lowercase(      self     :	Optional[int]				)->       List[str]:




       """simple docstring"""
       SCREAMING_SNAKE_CASE__			,							SCREAMING_SNAKE_CASE__				:				Dict			=		self.resolver.write_model_card('opus-mt-he-en'     , dry_run=a_				)
       assert mmeta["long_pair"] == "heb-eng"




import os
import socket
from contextlib import contextmanager

import torch

from ..commands.config.default import write_basic_config  # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import convert_model
from .versions import is_torch_version


if is_deepspeed_available():
      from deepspeed import DeepSpeedEngine

if is_tpu_available(check_device=False):
      import torch_xla.core.xla_model as xm







def     _a				(      lowercase__  :			int ):







     '''simple docstring'''


     if is_torch_version('<'     ,  '2.0.0' ) or not hasattr(lowercase__     ,  '_dynamo' ):
          return False
     return isinstance(lowercase__     ,  torch._dynamo.eval_frame.OptimizedModule )







def     _a				(      lowercase__  :			Optional[Any]     ,  lowercase__  :			bool = True ):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		(torch.nn.parallel.DistributedDataParallel, torch.nn.DataParallel)

     SCREAMING_SNAKE_CASE__				:				Dict			=		is_compiled_module(lowercase__ )
     if is_compiled:
          SCREAMING_SNAKE_CASE__				:				Tuple			=		model
          SCREAMING_SNAKE_CASE__				:				int			=		model._orig_mod

     if is_deepspeed_available():
          options += (DeepSpeedEngine,)

     while isinstance(lowercase__     ,  lowercase__ ):
          SCREAMING_SNAKE_CASE__				:				Any			=		model.module

     if not keep_fpaa_wrapper:
          SCREAMING_SNAKE_CASE__				:				List[Any]			=		getattr(lowercase__     ,  'forward' )
          SCREAMING_SNAKE_CASE__				:				str			=		model.__dict__.pop('_original_forward'     ,  lowercase__ )
          if original_forward is not None:
               while hasattr(lowercase__     ,  '__wrapped__' ):
                    SCREAMING_SNAKE_CASE__				:				Dict			=		forward.__wrapped__
                    if forward == original_forward:
                         break
               SCREAMING_SNAKE_CASE__				:				Dict			=		forward
          if getattr(lowercase__     ,  '_converted_to_transformer_engine'     ,  lowercase__ ):
               convert_model(lowercase__     ,  to_transformer_engine=lowercase__ )

     if is_compiled:
          SCREAMING_SNAKE_CASE__				:				List[Any]			=		model
          SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		compiled_model

     return model







def     _a				(      ):







     '''simple docstring'''


     PartialState().wait_for_everyone()







def     _a				(      lowercase__  :			str     ,  lowercase__  :			Optional[Any] ):







     '''simple docstring'''


     if PartialState().distributed_type == DistributedType.TPU:
          xm.save(lowercase__     ,  lowercase__ )
     elif PartialState().local_process_index == 0:
          torch.save(lowercase__     ,  lowercase__ )







@contextmanager
def     _a				(      **lowercase__  :			str ):







     '''simple docstring'''


     for key, value in kwargs.items():
          SCREAMING_SNAKE_CASE__				:				int			=		str(lowercase__ )

     yield

     for key in kwargs:
          if key.upper() in os.environ:
               del os.environ[key.upper()]







def     _a				(      lowercase__  :			Optional[Any] ):







     '''simple docstring'''


     if not hasattr(lowercase__     ,  '__qualname__' ) and not hasattr(lowercase__     ,  '__name__' ):
          SCREAMING_SNAKE_CASE__				:				Any			=		getattr(lowercase__     ,  '__class__'     ,  lowercase__ )
     if hasattr(lowercase__     ,  '__qualname__' ):
          return obj.__qualname__
     if hasattr(lowercase__     ,  '__name__' ):
          return obj.__name__
     return str(lowercase__ )







def     _a				(      lowercase__  :			List[str]     ,  lowercase__  :			List[Any] ):







     '''simple docstring'''


     for key, value in source.items():
          if isinstance(lowercase__     ,  lowercase__ ):
               SCREAMING_SNAKE_CASE__				:				List[str]			=		destination.setdefault(lowercase__     ,  {} )
               merge_dicts(lowercase__     ,  lowercase__ )
          else:
               SCREAMING_SNAKE_CASE__				:				List[Any]			=		value

     return destination







def     _a				(      lowercase__  :			int = None ):







     '''simple docstring'''


     if port is None:
          SCREAMING_SNAKE_CASE__				:				int			=		2_95_00
     with socket.socket(socket.AF_INET     ,  socket.SOCK_STREAM ) as s:
          return s.connect_ex(('localhost', port) ) == 0



