



"""simple docstring"""
import json
import os
import tempfile

import transformers

import datasets
from utils import generate_example_dataset, get_duration


__SCREAMING_SNAKE_CASE  :						List[str]    							=      5_0_0_0_0_0

__SCREAMING_SNAKE_CASE							,					__SCREAMING_SNAKE_CASE  :						Union[str, Any]    							=      os.path.split(__file__)
__SCREAMING_SNAKE_CASE  :						Any    							=      os.path.join(RESULTS_BASEPATH, '''results''', RESULTS_FILENAME.replace('''.py''', '''.json'''))



@get_duration
def        lowerCAmelCase_(   lowercase_     :							datasets.Dataset						,   **lowercase_     :							Union[str, Any]							)	->       List[str]:
				_lowerCamelCase        =				dataset.map(**lowercase_							)



@get_duration
def        lowerCAmelCase_(   lowercase_     :							datasets.Dataset						,   **lowercase_     :							Optional[int]							)	->       Any:
				_lowerCamelCase        =				dataset.filter(**lowercase_							)



def        lowerCAmelCase_(   )	->       List[Any]:
				_lowerCamelCase        =				{'''num examples''': SPEED_TEST_N_EXAMPLES}
				with tempfile.TemporaryDirectory() as tmp_dir:
								_lowerCamelCase        =				datasets.Features({'''text''': datasets.Value('''string'''							), '''numbers''': datasets.Value('''float32'''							)}							)
								_lowerCamelCase        =				generate_example_dataset(
								    os.path.join(lowercase_						,   '''dataset.arrow'''							)						,   lowercase_						,   num_examples=lowercase_							)

								_lowerCamelCase        =				transformers.AutoTokenizer.from_pretrained('''bert-base-cased'''						,   use_fast=lowercase_							)

								def tokenize(lowercase_     :							Dict							):
												return tokenizer(examples['''text''']							)

								_lowerCamelCase        =				map(lowercase_							)

								_lowerCamelCase        =				map(lowercase_						,   batched=lowercase_							)

								_lowerCamelCase        =				map(lowercase_						,   function=lambda lowercase_							: None						,   batched=lowercase_							)

								with dataset.formatted_as(type='''numpy'''							):
												_lowerCamelCase        =				map(lowercase_						,   function=lambda lowercase_							: None						,   batched=lowercase_							)

								with dataset.formatted_as(type='''pandas'''							):
												_lowerCamelCase        =				map(lowercase_						,   function=lambda lowercase_							: None						,   batched=lowercase_							)

								with dataset.formatted_as(type='''torch'''						,   columns='''numbers'''							):
												_lowerCamelCase        =				map(lowercase_						,   function=lambda lowercase_							: None						,   batched=lowercase_							)

								with dataset.formatted_as(type='''tensorflow'''						,   columns='''numbers'''							):
												_lowerCamelCase        =				map(lowercase_						,   function=lambda lowercase_							: None						,   batched=lowercase_							)

								_lowerCamelCase        =				map(lowercase_						,   function=lowercase_						,   batched=lowercase_							)

								_lowerCamelCase        =				filter(lowercase_							)

								# 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(lowercase_						,   '''wb'''							) as f:
								f.write(json.dumps(lowercase_							).encode('''utf-8'''							)							)


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





"""simple docstring"""
def        lowerCAmelCase_(   lowercase_     :							str						,   lowercase_     :							str							)	->       bool:
				_lowerCamelCase        =				len(lowercase_							)
				_lowerCamelCase        =				len(lowercase_							)
				_lowerCamelCase        =				[[False for _ in range(m + 1							)] for _ in range(n + 1							)]
				_lowerCamelCase        =				True
				for i in range(lowercase_							):
								for j in range(m + 1							):
												if dp[i][j]:
																if j < m and a[i].upper() == b[j]:
																				_lowerCamelCase        =				True
																if a[i].islower():
																				_lowerCamelCase        =				True
				return dp[n][m]


if __name__ == "__main__":
			import doctest

			doctest.testmod()
