



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)

UpperCamelCase__ =						logging.getLogger()






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


UpperCamelCase__ =						logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)







@require_torch_tpu
class 			_lowerCAmelCase   ( _UpperCAmelCase			):






			"""simple docstring"""





			def 		snake_case__			(				self	:       int   )						->					Optional[int]:
									"""simple docstring"""







									import xla_spawn

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

									with patch.object(lowercase			,     """argv"""			,     lowercase   ):
															__lowercase					=				time()
															xla_spawn.main()
															__lowercase					=				time()

															__lowercase					=				get_results(lowercase   )
															self.assertGreaterEqual(result["""eval_accuracy"""]			,     0.75   )

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







			def 		snake_case__			(				self	:       Dict   )						->					List[str]:
									"""simple docstring"""







									import xla_spawn

									__lowercase					=				"""
            ./tests/test_trainer_tpu.py
            --num_cores=8
            ./tests/test_trainer_tpu.py
            """.split()
									with patch.object(lowercase			,     """argv"""			,     lowercase   ):
															xla_spawn.main()










import random






def  UpperCAmelCase__    (    lowercase__						,       lowercase__						,       lowercase__ = False   ) ->      dict:
						__lowercase					=				{i: [] for i in range(lowercase__   )}

						# if probability is greater or equal than 1, then generate a complete graph
						if probability >= 1:
												return complete_graph(lowercase__   )
						# if probability is lower or equal than 0, then return a graph without edges
						if probability <= 0:
												return graph

						# for each couple of nodes, add an edge from u to v
						# if the number randomly generated is greater than probability probability
						for i in range(lowercase__   ):
												for j in range(i + 1						,       lowercase__   ):
																		if random.random() < probability:
																								graph[i].append(lowercase__   )
																								if not directed:
																														# if the graph is undirected, add an edge in from j to i, either
																														graph[j].append(lowercase__   )
						return graph






def  UpperCAmelCase__    (    lowercase__   ) ->      dict:
						return {
						    i: [j for j in range(lowercase__   ) if i != j] for i in range(lowercase__   )
						}


if __name__ == "__main__":
			import doctest

			doctest.testmod()





