




# as due to their complexity multi-gpu tests could impact other tests, and to aid debug we have those in a separate module.

import os
import sys

from transformers.testing_utils import TestCasePlus, execute_subprocess_async, get_gpu_count, require_torch_gpu, slow

from .utils import load_json







class 	lowercase_					(				_a     ):


   """simple docstring"""

   @classmethod
   def 							lowerCAmelCase_    (					cls      :			Tuple					):

      """simple docstring"""
      return cls



   @slow
   @require_torch_gpu
   def 							lowerCAmelCase_    (					self      :			str					):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE =   self.get_auto_remove_tmp_dir()
      _SCREAMING_SNAKE_CASE =   F"""\n            --model_name Helsinki-NLP/opus-mt-en-ro\n            --save_dir {output_dir}\n            --data_dir {self.test_file_dir_str}/test_data/wmt_en_ro\n            --num_beams 2\n            --task translation\n        """.split()

      # we want this test to run even if there is only one GPU, but if there are more we use them all
      _SCREAMING_SNAKE_CASE =   get_gpu_count()
      _SCREAMING_SNAKE_CASE =   F"""\n            -m torch.distributed.launch\n            --nproc_per_node={n_gpu}\n            {self.test_file_dir}/run_distributed_eval.py\n        """.split()
      _SCREAMING_SNAKE_CASE =   [sys.executable] + distributed_args + args
      execute_subprocess_async(lowerCamelCase__						,   env=self.get_env()					)

      _SCREAMING_SNAKE_CASE =   os.path.join(lowerCamelCase__						,   "test_bleu.json"					)
      _SCREAMING_SNAKE_CASE =   load_json(lowerCamelCase__					)
      # print(metrics)
      self.assertGreaterEqual(metrics["bleu"]						,   2_5					)







'''simple docstring'''



lowerCamelCase_	 =		[[0, 1, 1], [0, 0, 1], [1, 0, 0]]







class 	lowercase_					:


   """simple docstring"""

   def __init__(					self      :			List[Any]						,   __lowerCamelCase      :			str					):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE =   name
      _SCREAMING_SNAKE_CASE =   []
      _SCREAMING_SNAKE_CASE =   []



   def 							lowerCAmelCase_    (					self      :			int						,   __lowerCamelCase      :			Union[str, Any]					):

      """simple docstring"""
      self.inbound.append(__lowerCamelCase					)



   def 							lowerCAmelCase_    (					self      :			int						,   __lowerCamelCase      :			Any					):

      """simple docstring"""
      self.outbound.append(__lowerCamelCase					)



   def __repr__(					self      :			List[str]					):

      """simple docstring"""
      return F"""<node={self.name} inbound={self.inbound} outbound={self.outbound}>"""


def 				SCREAMING_SNAKE_CASE_				(							__A       :				Tuple ,  __A       :				List[Any]=3 ,  __A       :				Optional[int]=0.8_5						)				->				Optional[Any]:
   _SCREAMING_SNAKE_CASE =   {}
   for node in nodes:
      _SCREAMING_SNAKE_CASE =   1

   _SCREAMING_SNAKE_CASE =   {}
   for node in nodes:
      _SCREAMING_SNAKE_CASE =   len(node.outbound						)

   for i in range(__A						):
      print(f"""======= Iteration {i + 1} ======="""						)
      for _, node in enumerate(__A						):
         _SCREAMING_SNAKE_CASE =   (1 - d) + d * sum(
             ranks[ib] / outbounds[ib] for ib in node.inbound						)
      print(__A						)
def 				SCREAMING_SNAKE_CASE_				(							)				->				List[str]:
   _SCREAMING_SNAKE_CASE =   list(input("Enter Names of the Nodes: "						).split()						)

   _SCREAMING_SNAKE_CASE =   [Node(__A						) for name in names]

   for ri, row in enumerate(__A						):
      for ci, col in enumerate(__A						):
         if col == 1:
            nodes[ci].add_inbound(names[ri]						)
            nodes[ri].add_outbound(names[ci]						)

   print("======= Nodes ======="						)
   for node in nodes:
      print(__A						)

   page_rank(__A						)


if __name__ == "__main__":
 main()

