






from __future__ import annotations


def        _a  (     UpperCamelCase_					:				int   ) ->   Tuple:
						"""simple docstring"""







						lowerCAmelCase__       =						2
						lowerCAmelCase__       =						[]
						while i * i <= n:
												if n % i:
																		i += 1
												else:
																		n //= i
																		factors.append(__lowercase   )
						if n > 1:
												factors.append(__lowercase   )
						return factors


if __name__ == "__main__":
	import doctest

	doctest.testmod()














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)

a_							=    logging.getLogger()


def        _a  (     UpperCamelCase_					:				Union[str, Any]   ) ->   Dict:
						"""simple docstring"""







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


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





@require_torch_tpu
class      lowercase__     (			_UpperCAmelCase	):

	def 		UpperCAmelCase  (							self       )->					Optional[Any]:







							'''simple docstring'''





							import xla_spawn

							lowerCAmelCase__       =						self.get_auto_remove_tmp_dir()
							lowerCAmelCase__       =						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(__UpperCAmelCase		,    "argv"		,    __UpperCAmelCase       ):
													lowerCAmelCase__       =						time()
													xla_spawn.main()
													lowerCAmelCase__       =						time()

													lowerCAmelCase__       =						get_results(__UpperCAmelCase       )
													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 		UpperCAmelCase  (							self       )->					Dict:







							'''simple docstring'''





							import xla_spawn

							lowerCAmelCase__       =						"\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()






