
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)

lowercase__		:Any   =    logging.getLogger()



def        UpperCamelCase    (							lowerCAmelCase__		):
					'''simple docstring'''
					lowercase							=						{}
					lowercase							=						os.path.join(lowerCAmelCase__ ,			'''all_results.json'''		)
					if os.path.exists(lowerCAmelCase__		):
										with open(lowerCAmelCase__ ,			'''r'''		) as f:
															lowercase							=						json.load(lowerCAmelCase__		)
					else:
										raise ValueError(f'can\'t find {path}'		)
					return results


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







@require_torch_tpu
class 				lowercase		(					SCREAMING_SNAKE_CASE__		):




							def  A__      (				self):
												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(A__   ,'''argv'''   ,A__):
																	lowercase							=						time()
																	xla_spawn.main()
																	lowercase							=						time()

																	lowercase							=						get_results(A__)
																	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   ,5_0_0)





							def  A__      (				self):
												import xla_spawn

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






import random

from .binary_exp_mod import bin_exp_mod



def        UpperCamelCase    (							lowerCAmelCase__ ,			lowerCAmelCase__=1000		):
					'''simple docstring'''
					if n < 2:
										return False

					if n % 2 == 0:
										return n == 2

					# this means n is odd
					lowercase							=						n - 1
					lowercase							=						0
					while d % 2 == 0:
										d /= 2
										exp += 1

					# n - 1=d*(2**exp)
					lowercase							=						0
					while count < prec:
										lowercase							=						random.randint(2 ,			n - 1		)
										lowercase							=						bin_exp_mod(lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__		)
										if b != 1:
															lowercase							=						True
															for _ in range(lowerCAmelCase__		):
																				if b == n - 1:
																									lowercase							=						False
																									break
																				lowercase							=						b * b
																				b %= n
															if flag:
																				return False
															count += 1
					return True


if __name__ == "__main__":
							lowercase__		:Tuple   =    abs(int(input("Enter bound : ").strip()))
							print("Here's the list of primes:")
							print(", ".join(str(i) for i in range(n + 1) if is_prime_big(i)))




