



'''simple docstring'''

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				:    Union[str, Any]     						=logging.getLogger()







def 						__UpperCamelCase				(							_lowercase					) ->			Optional[int]:
	_lowercase					:       Dict       =		{}
	_lowercase					:       Optional[int]       =		os.path.join(_lowercase,				'all_results.json'					)
	if os.path.exists(_lowercase					):
		with open(_lowercase,				'r'					) as f:
			_lowercase					:       int       =		json.load(_lowercase					)
	else:
		raise ValueError(f'''can\'t find {path}'''					)
	return results


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






@require_torch_tpu
class 		lowerCamelCase__      (						A     ):




					'''simple docstring'''



					def 						__UpperCAmelCase     (  self				:	str					)  ->       Tuple:



						'''simple docstring'''





						import xla_spawn

						_lowercase					:       List[Any]       =		self.get_auto_remove_tmp_dir()
						_lowercase					:       List[str]       =		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_					):
							_lowercase					:       Union[str, Any]       =		time()
							xla_spawn.main()
							_lowercase					:       Tuple       =		time()

							_lowercase					:       Optional[Any]       =		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					)  ->       List[str]:



						'''simple docstring'''





						import xla_spawn

						_lowercase					:       List[str]       =		'\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()





'''simple docstring'''

import argparse
from collections import defaultdict







def 						__UpperCamelCase				(							_lowercase,				_lowercase,				_lowercase,				_lowercase,				_lowercase					) ->			int:
	_lowercase					:       Optional[int]       =		f'''{file}_{class_name}_{test_name}'''
	done_test[_id] += 1

	with open(_lowercase,				'r'					) as f:
		_lowercase					:       Optional[int]       =		f.readlines()

	_lowercase					:       Dict       =		f'''class {class_name}('''
	_lowercase					:       List[Any]       =		f'''{4 * " "}def {test_name}('''
	_lowercase					:       List[str]       =		f'''{8 * " "}{correct_line.split()[0]}'''
	_lowercase					:       List[str]       =		f'''{16 * " "}{correct_line.split()[0]}'''
	_lowercase					:       Dict       =		False
	_lowercase					:       str       =		False
	_lowercase					:       List[Any]       =		False
	_lowercase					:       Union[str, Any]       =		False
	_lowercase					:       Any       =		0
	_lowercase					:       Tuple       =		0

	_lowercase					:       Optional[int]       =		[]
	for line in lines:
		if line.startswith(_lowercase					):
			_lowercase					:       int       =		True
		elif in_class and line.startswith(_lowercase					):
			_lowercase					:       List[Any]       =		True
		elif in_class and in_func and (line.startswith(_lowercase					) or line.startswith(_lowercase					)):
			_lowercase					:       str       =		len(line.split(correct_line.split()[0]					)[0]					)
			count += 1

			if count == done_test[_id]:
				_lowercase					:       List[Any]       =		True

		if in_class and in_func and in_line:
			if ")" not in line:
				continue
			else:
				_lowercase					:       Any       =		True

		if in_class and in_func and in_line and insert_line:
			new_lines.append(f'''{spaces * " "}{correct_line}'''					)
			_lowercase					:       Any       =		False
		else:
			new_lines.append(_lowercase					)

	with open(_lowercase,				'w'					) as f:
		for line in new_lines:
			f.write(_lowercase					)







def 						__UpperCamelCase				(							_lowercase,				_lowercase=None					) ->			Optional[Any]:
	if fail is not None:
		with open(_lowercase,				'r'					) as f:
			_lowercase					:       Any       =		{l.strip() for l in f.readlines()}
	else:
		_lowercase					:       str       =		None

	with open(_lowercase,				'r'					) as f:
		_lowercase					:       str       =		f.readlines()

	_lowercase					:       Union[str, Any]       =		defaultdict(_lowercase					)
	for line in correct_lines:
		_lowercase  ,    _lowercase  ,    _lowercase  ,    _lowercase					:       Union[str, Any]       =		line.split(';'					)
		if test_failures is None or "::".join([file, class_name, test_name]					) in test_failures:
			overwrite_file(_lowercase,				_lowercase,				_lowercase,				_lowercase,				_lowercase					)


if __name__ == "__main__":
		_A				:    str     						=argparse.ArgumentParser()
		parser.add_argument('''--correct_filename''', help='''filename of tests with expected result''')
		parser.add_argument('''--fail_filename''', help='''filename of test failures''', type=str, default=None)
		_A				:    Union[str, Any]     						=parser.parse_args()

		main(args.correct_filename, args.fail_filename)
