






import json
import logging
import os
import sys
from time import time
from unittest.mock import patch

from transformers.testing_utils import TestCasePlus, require_torch_tpu


logging.basicConfig(level=logging.DEBUG)

snake_case__      :	List[Any]       	=      logging.getLogger()






def     _snake_case    (__lowercase):
   UpperCamelCase_									=     {}
   UpperCamelCase_									=     os.path.join(__lowercase    ,      'all_results.json')
   if os.path.exists(__lowercase):
      with open(__lowercase    ,      'r') as f:
         UpperCamelCase_									=     json.load(__lowercase)
   else:
      raise ValueError(f"""can't find {path}""")
   return results


snake_case__      :	Optional[int]       	=      logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)


@require_torch_tpu
class 						_a       (  UpperCAmelCase__    ):






  """simple docstring"""





  def    _UpperCAmelCase     (     self )			-> str:
     import xla_spawn

     UpperCamelCase_									=     self.get_auto_remove_tmp_dir()
     UpperCamelCase_									=     f"""
            ./examples/pytorch/text-classification/run_glue.py
            --num_cores=8
            ./examples/pytorch/text-classification/run_glue.py
            --model_name_or_path distilbert-base-uncased
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv
            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv
            --do_train
            --do_eval
            --debug tpu_metrics_debug
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --learning_rate=1e-4
            --max_steps=10
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            """.split()

     with patch.object(_UpperCAmelCase		,		'argv'		,		_UpperCAmelCase ):
        UpperCamelCase_									=     time()
        xla_spawn.main()
        UpperCamelCase_									=     time()

        UpperCamelCase_									=     get_results(_UpperCAmelCase )
        self.assertGreaterEqual(result['eval_accuracy']		,		0.7_5 )

        # Assert that the script takes less than 500 seconds to make sure it doesn't hang.
        self.assertLess(end - start		,		500 )




  def    _UpperCAmelCase     (     self )			-> int:
     import xla_spawn

     UpperCamelCase_									=     '\n            ./tests/test_trainer_tpu.py\n            --num_cores=8\n            ./tests/test_trainer_tpu.py\n            '.split()
     with patch.object(_UpperCAmelCase		,		'argv'		,		_UpperCAmelCase ):
        xla_spawn.main()













def     _snake_case    (__lowercase    ,      __lowercase    ,      __lowercase):
   return not any(
       neighbour == 1 and colored_vertices[i] == color
       for i, neighbour in enumerate(__lowercase))






def     _snake_case    (__lowercase    ,      __lowercase    ,      __lowercase    ,      __lowercase):

   # Base Case
   if index == len(__lowercase):
      return True

   # Recursive Step
   for i in range(__lowercase):
      if valid_coloring(graph[index]    ,      __lowercase    ,      __lowercase):
         # Color current vertex
         UpperCamelCase_									=     i
         # Validate coloring
         if util_color(__lowercase    ,      __lowercase    ,      __lowercase    ,      index + 1):
            return True
         # Backtrack
         UpperCamelCase_									=     -1
   return False






def     _snake_case    (__lowercase    ,      __lowercase):
   UpperCamelCase_									=     [-1] * len(__lowercase)

   if util_color(__lowercase    ,      __lowercase    ,      __lowercase    ,      0):
      return colored_vertices

   return []





