






import argparse
import datetime






def 						a    (		lowerCamelCase_       ):






				'''simple docstring'''
				lowercase__     				=    {
				    '''0''': '''Sunday''',
				    '''1''': '''Monday''',
				    '''2''': '''Tuesday''',
				    '''3''': '''Wednesday''',
				    '''4''': '''Thursday''',
				    '''5''': '''Friday''',
				    '''6''': '''Saturday''',
				}

				lowercase__     				=    {0: 1, 1: 2, 2: 3, 3: 4, 4: 5, 5: 6, 6: 0}

				# Validate
				if not 0 < len(lowerCamelCase_       ) < 11:
								raise ValueError('''Must be 10 characters long'''       )

				# Get month
				lowercase__     				=    int(date_input[0] + date_input[1]       )
				# Validate
				if not 0 < m < 13:
								raise ValueError('''Month must be between 1 - 12'''       )

				lowercase__     				=    date_input[2]
				# Validate
				if sep_a not in ["-", "/"]:
								raise ValueError('''Date separator must be \'-\' or \'/\''''       )

				# Get day
				lowercase__     				=    int(date_input[3] + date_input[4]       )
				# Validate
				if not 0 < d < 32:
								raise ValueError('''Date must be between 1 - 31'''       )

				# Get second separator
				lowercase__     				=    date_input[5]
				# Validate
				if sep_a not in ["-", "/"]:
								raise ValueError('''Date separator must be \'-\' or \'/\''''       )

				# Get year
				lowercase__     				=    int(date_input[6] + date_input[7] + date_input[8] + date_input[9]       )
				# Arbitrary year range
				if not 45 < y < 8500:
								raise ValueError(
								    '''Year out of range. There has to be some sort of limit...right?'''       )

				# Get datetime obj for validation
				lowercase__     				=    datetime.date(int(lowerCamelCase_       )	,     int(lowerCamelCase_       )	,     int(lowerCamelCase_       )       )

				# Start math
				if m <= 2:
								lowercase__     				=    y - 1
								lowercase__     				=    m + 12
				# maths var
				lowercase__     				=    int(str(lowerCamelCase_       )[:2]       )
				lowercase__     				=    int(str(lowerCamelCase_       )[2:]       )
				lowercase__     				=    int(2.6 * m - 5.39       )
				lowercase__     				=    int(c / 4       )
				lowercase__     				=    int(k / 4       )
				lowercase__     				=    int(d + k       )
				lowercase__     				=    int(t + u + v + x       )
				lowercase__     				=    int(z - (2 * c)       )
				lowercase__     				=    round(w % 7       )
				# End math

				# Validate math
				if f != convert_datetime_days[dt_ck.weekday()]:
								raise AssertionError('''The date was evaluated incorrectly. Contact developer.'''       )

				# Response
				lowercase__     				=    F"""Your date {date_input}, is a {days[str(lowerCamelCase_       )]}!"""
				return response


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							A__			:    str         =				argparse.ArgumentParser(
							    description=(
							        'Find out what day of the week nearly any date is or was. Enter '
							        'date as a string in the mm-dd-yyyy or mm/dd/yyyy format'
							    )
							)
							parser.add_argument(
							    'date_input', type=str, help='Date as a string (mm-dd-yyyy or mm/dd/yyyy)'
							)
							A__			:    Any         =				parser.parse_args()
							zeller(args.date_input)












import json
import os
import tempfile

import transformers

import datasets
from utils import generate_example_dataset, get_duration


A__			:    Dict         =				50_00_00

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






@get_duration
def 						a    (		lowerCamelCase_	,     **lowerCamelCase_       ):






				'''simple docstring'''
				lowercase__     				=    dataset.map(**lowerCamelCase_       )






@get_duration
def 						a    (		lowerCamelCase_	,     **lowerCamelCase_       ):






				'''simple docstring'''
				lowercase__     				=    dataset.filter(**lowerCamelCase_       )






def 						a    (		):






				'''simple docstring'''
				lowercase__     				=    {'''num examples''': SPEED_TEST_N_EXAMPLES}
				with tempfile.TemporaryDirectory() as tmp_dir:
								lowercase__     				=    datasets.Features({'''text''': datasets.Value('''string'''       ), '''numbers''': datasets.Value('''float32'''       )}       )
								lowercase__     				=    generate_example_dataset(
								    os.path.join(lowerCamelCase_	,     '''dataset.arrow'''       )	,     lowerCamelCase_	,     num_examples=lowerCamelCase_       )

								lowercase__     				=    transformers.AutoTokenizer.from_pretrained('''bert-base-cased'''	,     use_fast=lowerCamelCase_       )

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

								lowercase__     				=    map(lowerCamelCase_       )

								lowercase__     				=    map(lowerCamelCase_	,     batched=lowerCamelCase_       )

								lowercase__     				=    map(lowerCamelCase_	,     function=lambda lowerCamelCase_       : None	,     batched=lowerCamelCase_       )

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

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

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

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

								lowercase__     				=    map(lowerCamelCase_	,     function=lowerCamelCase_	,     batched=lowerCamelCase_       )

								lowercase__     				=    filter(lowerCamelCase_       )

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


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




