


'''simple docstring'''




import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests

def 			__UpperCamelCase    (    _A    :				str				)    ->      str:




	"""simple docstring"""





	lowerCAmelCase					:    List[str]      							= {}

	lowerCAmelCase					:    Any      							= job['started_at']
	lowerCAmelCase					:    List[Any]      							= job['completed_at']

	lowerCAmelCase					:    Dict      							= date_parser.parse(_A				)
	lowerCAmelCase					:    Union[str, Any]      							= date_parser.parse(_A				)

	lowerCAmelCase					:    str      							= round((end_datetime - start_datetime).total_seconds() / 60.0				)

	lowerCAmelCase					:    str      							= start
	lowerCAmelCase					:    List[str]      							= end
	lowerCAmelCase					:    str      							= duration_in_min

	return job_info

def 			__UpperCamelCase    (    _A    :				Optional[Any]					,   _A    :				int=None				)    ->      str:




	"""simple docstring"""





	lowerCAmelCase					:    List[Any]      							= None
	if token is not None:
		lowerCAmelCase					:    Union[str, Any]      							= {'Accept': 'application/vnd.github+json', 'Authorization': F"Bearer {token}"}

	lowerCAmelCase					:    int      							= F"https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100"
	lowerCAmelCase					:    List[Any]      							= requests.get(_A					,   headers=_A				).json()
	lowerCAmelCase					:    Optional[int]      							= {}

	try:
		job_time.update({job['name']: extract_time_from_single_job(_A				) for job in result['jobs']}				)
		lowerCAmelCase					:    str      							= math.ceil((result['total_count'] - 1_00) / 1_00				)

		for i in range(_A				):
			lowerCAmelCase					:    Optional[int]      							= requests.get(url + F"&page={i + 2}"					,   headers=_A				).json()
			job_time.update({job['name']: extract_time_from_single_job(_A				) for job in result['jobs']}				)

		return job_time
	except Exception:
		print(F"Unknown error, could not fetch links:\n{traceback.format_exc()}"				)

	return {}


if __name__ == "__main__":
				_lowerCAmelCase  :		str		     =	argparse.ArgumentParser()
				# Required parameters
				parser.add_argument('--workflow_run_id', type=str, required=True, help='A GitHub Actions workflow run id.')
				_lowerCAmelCase  :		int		     =	parser.parse_args()

				_lowerCAmelCase  :		Union[str, Any]		     =	get_job_time(args.workflow_run_id)
				_lowerCAmelCase  :		List[str]		     =	dict(sorted(job_time.items(), key=lambda item: item[1]["duration"], reverse=True))

				for k, v in job_time.items():
								print(f"""{k}: {v['duration']}""")




'''simple docstring'''




import unittest

from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


_lowerCAmelCase  :		Union[str, Any]		     =	get_tests_dir('fixtures/test_sentencepiece_with_bytefallback.model')



@require_sentencepiece
@require_tokenizers
class  lowerCAmelCase				(				a      ,				unittest.TestCase							):
	_lowerCamelCase   :					Tuple			      = GPTSwaTokenizer
	_lowerCamelCase   :					str			      = False
	_lowerCamelCase   :					Dict			      = True
	_lowerCamelCase   :					Optional[Any]			      = False



	def 				lowercase     (					self    ):
		super().setUp()

		# We have a SentencePiece fixture for testing
		lowerCAmelCase					:    Tuple      							= GPTSwaTokenizer(snake_case__ ,					eos_token='<unk>' ,					bos_token='<unk>' ,					pad_token='<unk>'    )

		tokenizer.save_pretrained(self.tmpdirname    )



	def 				lowercase     (					self ,					snake_case__    ):
		lowerCAmelCase					:    List[Any]      							= 'This is a test'
		lowerCAmelCase					:    List[Any]      							= 'This is a test'
		return input_text, output_text



	def 				lowercase     (					self    ):
		lowerCAmelCase					:    Tuple      							= '<s>'
		lowerCAmelCase					:    Optional[int]      							= 1

		self.assertEqual(self.get_tokenizer()._convert_token_to_id(snake_case__    ) ,					snake_case__    )
		self.assertEqual(self.get_tokenizer()._convert_id_to_token(snake_case__    ) ,					snake_case__    )



	def 				lowercase     (					self    ):
		lowerCAmelCase					:    List[Any]      							= list(self.get_tokenizer().get_vocab().keys()    )

		self.assertEqual(vocab_keys[0] ,					'<unk>'    )
		self.assertEqual(vocab_keys[1] ,					'<s>'    )
		self.assertEqual(vocab_keys[-1] ,					'j'    )
		self.assertEqual(len(snake_case__    ) ,					2000    )



	def 				lowercase     (					self    ):
		self.assertEqual(self.get_tokenizer().vocab_size ,					2000    )



	def 				lowercase     (					self    ):
		lowerCAmelCase					:    List[Any]      							= GPTSwaTokenizer(snake_case__    )

		lowerCAmelCase					:    Optional[Any]      							= tokenizer.tokenize('This is a test'    )
		self.assertListEqual(snake_case__ ,					['▁This', '▁is', '▁a', '▁t', 'est']    )

		self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case__    ) ,					[465, 287, 265, 631, 842]    )

		lowerCAmelCase					:    Tuple      							= tokenizer.tokenize('I was born in 92000, and this is falsé.'    )
		# fmt: off
		self.assertListEqual(
		    snake_case__ ,					['▁I', '▁was', '▁bor', 'n', '▁in', '▁', '<0x39>', '2', '0', '0', '0', ',', '▁and', '▁this', '▁is', '▁f', 'al', 's', '<0xC3>', '<0xA9>', '.'] ,					)
		# fmt: on

		lowerCAmelCase					:    Optional[Any]      							= tokenizer.convert_tokens_to_ids(snake_case__    )
		self.assertListEqual(
		    snake_case__ ,					[262, 272, 1525, 286, 271, 268, 60, 916, 633, 633, 633, 259, 266, 301, 287, 384, 367, 263, 198, 172, 260] ,					)

		lowerCAmelCase					:    int      							= tokenizer.convert_ids_to_tokens(snake_case__    )
		# fmt: off
		self.assertListEqual(
		    snake_case__ ,					['▁I', '▁was', '▁bor', 'n', '▁in', '▁', '<0x39>', '2', '0', '0', '0', ',', '▁and', '▁this', '▁is', '▁f', 'al', 's', '<0xC3>', '<0xA9>', '.']    )
		# fmt: on



	def 				lowercase     (					self    ):
		lowerCAmelCase					:    str      							= GPTSwaTokenizer(snake_case__    )
		lowerCAmelCase					:    Optional[int]      							= ['This is a test', 'I was born in 92000, and this is falsé.']
		lowerCAmelCase					:    Tuple      							= [
		    [465, 287, 265, 631, 842],
		    [262, 272, 1525, 286, 271, 268, 60, 916, 633, 633, 633, 259, 266, 301, 287, 384, 367, 263, 198, 172, 260],
		]

		# Test that encode_fast returns the same as tokenize + convert_tokens_to_ids
		for text, expected_ids in zip(snake_case__ ,					snake_case__    ):
			self.assertListEqual(tokenizer.encode_fast(snake_case__    ) ,					snake_case__    )

		# Test that decode_fast returns the input text
		for text, token_ids in zip(snake_case__ ,					snake_case__    ):
			self.assertEqual(tokenizer.decode_fast(snake_case__    ) ,					snake_case__    )



	@slow
	def 				lowercase     (					self    ):
		lowerCAmelCase					:    str      							= [
		    '<|python|>def fibonacci(n)\n    if n < 0:\n        print(\'Incorrect input\')',
		    'Hey there, how are you doing this fine day?',
		    'This is a text with a trailing spaces followed by a dot     .',
		    'Häj sväjs lillebrör! =)',
		    'Det är inget fel på Mr. Cool',
		]

		# fmt: off
		lowerCAmelCase					:    Tuple      							= {'input_ids': [[6_3423, 5, 6811, 1_4954, 282, 816, 3821, 6_3466, 6_3425, 6_3462, 18, 6_3978, 678, 301, 1320, 6_3423, 6_3455, 6_3458, 18, 6_3982, 4246, 3940, 1901, 4_7789, 5547, 1_8994], [1_9630, 1100, 6_3446, 1342, 633, 544, 4488, 593, 5102, 2416, 6_3495, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1652, 428, 268, 1936, 515, 268, 5_8593, 2_2413, 9106, 546, 268, 3_3213, 6_3979, 698, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [5_5130, 6_3450, 924, 6_3449, 2249, 4062, 1558, 318, 6_3504, 2_1498, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [509, 377, 2827, 2559, 332, 6575, 6_3443, 2_6801, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], 'token_type_ids': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}
		# fmt: on
		self.tokenizer_integration_test_util(
		    expected_encoding=snake_case__ ,					model_name='AI-Sweden/gpt-sw3-126m' ,					sequences=snake_case__ ,					)
