




import numpy as np

a__		     =     [
    ['''a''', '''b''', '''c''', '''d''', '''e'''],
    ['''f''', '''g''', '''h''', '''i''', '''k'''],
    ['''l''', '''m''', '''n''', '''o''', '''p'''],
    ['''q''', '''r''', '''s''', '''t''', '''u'''],
    ['''v''', '''w''', '''x''', '''y''', '''z'''],
]


class    SCREAMING_SNAKE_CASE_				:



	"""simple docstring"""


	def __init__(					self		:						Optional[Any]	)	->       None:







						"""simple docstring"""







						__UpperCamelCase					:	Optional[Any]             =      np.array(lowerCAmelCase	)






	def 					lowerCamelCase__     (					self		:						Any					,     lowerCAmelCase		:						str	)	->       np.ndarray:







						"""simple docstring"""







						__UpperCamelCase      ,			__UpperCamelCase					:	int             =      np.where(letter == self.SQUARE	)
						__UpperCamelCase					:	Any             =      np.concatenate([indexa + 1, indexa + 1]	)
						return indexes






	def 					lowerCamelCase__     (					self		:						Union[str, Any]					,     lowerCAmelCase		:						int					,     lowerCAmelCase		:						int	)	->       str:







						"""simple docstring"""







						__UpperCamelCase					:	List[Any]             =      self.SQUARE[indexa - 1, indexa - 1]
						return letter






	def 					lowerCamelCase__     (					self		:						List[Any]					,     lowerCAmelCase		:						str	)	->       str:







						"""simple docstring"""







						__UpperCamelCase					:	int             =      message.lower()
						__UpperCamelCase					:	Optional[int]             =      message.replace(""" """					,     """"""	)
						__UpperCamelCase					:	List[str]             =      message.replace("""j"""					,     """i"""	)

						__UpperCamelCase					:	str             =      np.empty((2, len(lowerCAmelCase	))	)
						for letter_index in range(len(lowerCAmelCase	)	):
											__UpperCamelCase					:	Dict             =      self.letter_to_numbers(message[letter_index]	)

											__UpperCamelCase					:	Any             =      numbers[0]
											__UpperCamelCase					:	Optional[Any]             =      numbers[1]

						__UpperCamelCase					:	Any             =      first_step.reshape(2 * len(lowerCAmelCase	)	)
						__UpperCamelCase					:	Any             =      """"""
						for numbers_index in range(len(lowerCAmelCase	)	):
											__UpperCamelCase					:	Optional[Any]             =      int(second_step[numbers_index * 2]	)
											__UpperCamelCase					:	List[str]             =      int(second_step[(numbers_index * 2) + 1]	)
											__UpperCamelCase					:	Dict             =      self.numbers_to_letter(lowerCAmelCase					,     lowerCAmelCase	)
											__UpperCamelCase					:	int             =      encoded_message + letter

						return encoded_message






	def 					lowerCamelCase__     (					self		:						str					,     lowerCAmelCase		:						str	)	->       str:







						"""simple docstring"""







						__UpperCamelCase					:	Dict             =      message.lower()
						message.replace(""" """					,     """"""	)
						__UpperCamelCase					:	Dict             =      np.empty(2 * len(lowerCAmelCase	)	)
						for letter_index in range(len(lowerCAmelCase	)	):
											__UpperCamelCase					:	Union[str, Any]             =      self.letter_to_numbers(message[letter_index]	)
											__UpperCamelCase					:	str             =      numbers[0]
											__UpperCamelCase					:	Optional[Any]             =      numbers[1]

						__UpperCamelCase					:	Tuple             =      first_step.reshape((2, len(lowerCAmelCase	))	)
						__UpperCamelCase					:	Union[str, Any]             =      """"""
						for numbers_index in range(len(lowerCAmelCase	)	):
											__UpperCamelCase					:	Tuple             =      int(second_step[0, numbers_index]	)
											__UpperCamelCase					:	Union[str, Any]             =      int(second_step[1, numbers_index]	)
											__UpperCamelCase					:	Dict             =      self.numbers_to_letter(lowerCAmelCase					,     lowerCAmelCase	)
											__UpperCamelCase					:	Tuple             =      decoded_message + letter

						return decoded_message












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__ (snake_case   :		Tuple				)     ->						Dict:
					__UpperCamelCase					:	Dict             =      {}
					__UpperCamelCase					:	Dict             =      os.path.join(snake_case		,	"""all_results.json"""				)
					if os.path.exists(snake_case				):
										with open(snake_case		,	"""r"""				) as f:
															__UpperCamelCase					:	List[Any]             =      json.load(snake_case				)
					else:
										raise ValueError(F'''can\'t find {path}'''				)
					return results


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







@require_torch_tpu
class    SCREAMING_SNAKE_CASE_				(       _UpperCamelCase   ):



	"""simple docstring"""


	def 					lowerCamelCase__     (					self		:						Dict	)	->       Dict:







						"""simple docstring"""







						import xla_spawn

						__UpperCamelCase					:	Dict             =      self.get_auto_remove_tmp_dir()
						__UpperCamelCase					:	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(lowerCAmelCase					,     """argv"""					,     lowerCAmelCase	):
											__UpperCamelCase					:	Union[str, Any]             =      time()
											xla_spawn.main()
											__UpperCamelCase					:	List[str]             =      time()

											__UpperCamelCase					:	Optional[int]             =      get_results(lowerCAmelCase	)
											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 					lowerCamelCase__     (					self		:						int	)	->       List[Any]:







						"""simple docstring"""







						import xla_spawn

						__UpperCamelCase					:	List[Any]             =      """
            ./tests/test_trainer_tpu.py
            --num_cores=8
            ./tests/test_trainer_tpu.py
            """.split()
						with patch.object(lowerCAmelCase					,     """argv"""					,     lowerCAmelCase	):
											xla_spawn.main()






