


'''simple docstring'''

import json
import os
import tempfile

import transformers

import datasets
from utils import generate_example_dataset, get_duration


lowerCAmelCase :Tuple             =     5_0_0_0_0_0

lowerCAmelCase :Optional[Any]             =     os.path.split(__file__)
lowerCAmelCase :Dict             =     os.path.join(RESULTS_BASEPATH, '''results''', RESULTS_FILENAME.replace('''.py''', '''.json'''))





@get_duration
def lowerCamelCase     (     lowerCAmelCase							:      List[Any]						,						**lowerCAmelCase							:      int						):





	"""simple docstring"""







	__magic_name__			:       Optional[int]	      =	dataset.map(**UpperCamelCase__						)





@get_duration
def lowerCamelCase     (     lowerCAmelCase							:      Any						,						**lowerCAmelCase							:      List[str]						):





	"""simple docstring"""







	__magic_name__			:       List[Any]	      =	dataset.filter(**UpperCamelCase__						)





def lowerCamelCase     (     ):





	"""simple docstring"""







	__magic_name__			:       int	      =	{'num examples': SPEED_TEST_N_EXAMPLES}
	with tempfile.TemporaryDirectory() as tmp_dir:
		__magic_name__			:       Any	      =	datasets.Features({'text': datasets.Value('string'						), 'numbers': datasets.Value('float32'						)}						)
		__magic_name__			:       Optional[Any]	      =	generate_example_dataset(
		    os.path.join(UpperCamelCase__						,						'dataset.arrow'						)						,						UpperCamelCase__						,						num_examples=UpperCamelCase__						)

		__magic_name__			:       int	      =	transformers.AutoTokenizer.from_pretrained('bert-base-cased'						,						use_fast=UpperCamelCase__						)

		def tokenize(lowerCAmelCase							:      Union[str, Any]						):
			return tokenizer(examples['text']						)

		__magic_name__			:       Dict	      =	map(UpperCamelCase__						)

		__magic_name__			:       Tuple	      =	map(UpperCamelCase__						,						batched=UpperCamelCase__						)

		__magic_name__			:       int	      =	map(UpperCamelCase__						,						function=lambda lowerCAmelCase						: None						,						batched=UpperCamelCase__						)

		with dataset.formatted_as(type='numpy'						):
			__magic_name__			:       List[str]	      =	map(UpperCamelCase__						,						function=lambda lowerCAmelCase						: None						,						batched=UpperCamelCase__						)

		with dataset.formatted_as(type='pandas'						):
			__magic_name__			:       Union[str, Any]	      =	map(UpperCamelCase__						,						function=lambda lowerCAmelCase						: None						,						batched=UpperCamelCase__						)

		with dataset.formatted_as(type='torch'						,						columns='numbers'						):
			__magic_name__			:       List[str]	      =	map(UpperCamelCase__						,						function=lambda lowerCAmelCase						: None						,						batched=UpperCamelCase__						)

		with dataset.formatted_as(type='tensorflow'						,						columns='numbers'						):
			__magic_name__			:       List[Any]	      =	map(UpperCamelCase__						,						function=lambda lowerCAmelCase						: None						,						batched=UpperCamelCase__						)

		__magic_name__			:       int	      =	map(UpperCamelCase__						,						function=UpperCamelCase__						,						batched=UpperCamelCase__						)

		__magic_name__			:       Dict	      =	filter(UpperCamelCase__						)

		# Activate later when tokenizer support batched inputs
		# with dataset.formatted_as(type='numpy'):
		#     times[func.__name__ + " fast-tokenizer batched numpy"] = func(dataset, function=tokenize, batched=True)

	with open(UpperCamelCase__						,						'wb'						) as f:
		f.write(json.dumps(UpperCamelCase__						).encode('utf-8'						)						)


if __name__ == "__main__":  # useful to run the profiler
							benchmark_map_filter()


import string





def    __lowerCamelCase      (					UpperCamelCase__ ):







							'''simple docstring'''






							snake_case_     							=       ''
							for i in sequence:
														snake_case_     							=       ord(UpperCamelCase__ )
														if 65 <= extract <= 90:
																					output += chr(155 - extract )
														elif 97 <= extract <= 122:
																					output += chr(219 - extract )
														else:
																					output += i
							return output





def    __lowerCamelCase      (					UpperCamelCase__ ):







							'''simple docstring'''






							snake_case_     							=       string.ascii_letters
							snake_case_     							=       string.ascii_lowercase[::-1] + string.ascii_uppercase[::-1]
							return "".join(
							    letters_reversed[letters.index(UpperCamelCase__ )] if c in letters else c for c in sequence )





def    __lowerCamelCase      (					):







							'''simple docstring'''






							from timeit import timeit

							print('Running performance benchmarks...' )
							snake_case_     							=       'from string import printable ; from __main__ import atbash, atbash_slow'
							print(F'''> atbash_slow(): {timeit("atbash_slow(printable)"  ,				setup=UpperCamelCase__ )} seconds''' )
							print(F'''>      atbash(): {timeit("atbash(printable)"  ,				setup=UpperCamelCase__ )} seconds''' )


if __name__ == "__main__":
					for example in ("ABCDEFGH", "123GGjj", "testStringtest", "with space"):
										print(F'''{example} encrypted in atbash: {atbash(example)}''')
					benchmark()




