'''simple docstring'''







import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)
from transformers.utils import is_sentencepiece_available


if is_sentencepiece_available():
		from transformers.models.mam_aaa.tokenization_mam_aaa import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


if is_sentencepiece_available():
		UpperCamelCase_      	=	get_tests_dir('''fixtures/test_sentencepiece.model''')


if is_torch_available():
		from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

UpperCamelCase_      	=	12_80_22
UpperCamelCase_      	=	12_80_28




@require_sentencepiece
class _SCREAMING_SNAKE_CASE(							_SCREAMING_SNAKE_CASE						,						unittest.TestCase					):
						A_			:							Any     		= MaMaaaTokenizer
						A_			:							Optional[int]     		= False
						A_			:							Optional[int]     		= False
						A_			:							List[str]     		= True




						def      __lowerCamelCase       (    self :       List[str]      )     ->				Dict:
													super().setUp()

													SCREAMING_SNAKE_CASE__     :int						    = ['</s>', '<unk>', '▁This', '▁is', '▁a', '▁t', 'est', '\u0120', '<pad>']
													SCREAMING_SNAKE_CASE__     :Tuple						    = dict(zip(SCREAMING_SNAKE_CASE_							,							range(len(SCREAMING_SNAKE_CASE_      )      )      )      )
													SCREAMING_SNAKE_CASE__     :List[str]						    = Path(self.tmpdirname      )
													save_json(SCREAMING_SNAKE_CASE_							,							save_dir / VOCAB_FILES_NAMES['vocab_file']      )
													if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
																				copyfile(SCREAMING_SNAKE_CASE_							,							save_dir / VOCAB_FILES_NAMES['spm_file']      )

													SCREAMING_SNAKE_CASE__     :Optional[Any]						    = MaMaaaTokenizer.from_pretrained(self.tmpdirname      )
													tokenizer.save_pretrained(self.tmpdirname      )




						def      __lowerCamelCase       (    self :       List[Any]							,							**UpperCamelCase_ :       List[Any]      )     ->				Optional[int]:
													return MaMaaaTokenizer.from_pretrained(self.tmpdirname							,							**SCREAMING_SNAKE_CASE_      )




						def      __lowerCamelCase       (    self :       int							,							UpperCamelCase_ :       List[Any]      )     ->				Dict:
													return (
													    "This is a test",
													    "This is a test",
													)




						def      __lowerCamelCase       (    self :       Union[str, Any]      )     ->				Dict:
													SCREAMING_SNAKE_CASE__     :Optional[Any]						    = '</s>'
													SCREAMING_SNAKE_CASE__     :int						    = 0

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




						def      __lowerCamelCase       (    self :       Tuple      )     ->				Optional[Any]:
													SCREAMING_SNAKE_CASE__     :Optional[int]						    = self.get_tokenizer()
													SCREAMING_SNAKE_CASE__     :Tuple						    = list(tokenizer.get_vocab().keys()      )

													self.assertEqual(vocab_keys[0]							,							'</s>'      )
													self.assertEqual(vocab_keys[1]							,							'<unk>'      )
													self.assertEqual(vocab_keys[-1]							,							'<s>'      )
													self.assertEqual(len(SCREAMING_SNAKE_CASE_      )							,							tokenizer.vocab_size + len(tokenizer.get_added_vocab()      )      )




						@unittest.skip('Skip this test while all models are still to be uploaded.'      )
						def      __lowerCamelCase       (    self :       Union[str, Any]      )     ->				str:
													pass




						def      __lowerCamelCase       (    self :       Any      )     ->				List[Any]:
													SCREAMING_SNAKE_CASE__     :int						    = self.get_tokenizer()

													SCREAMING_SNAKE_CASE__     :Tuple						    = tokenizer.tokenize('This is a test'      )
													self.assertListEqual(SCREAMING_SNAKE_CASE_							,							['▁This', '▁is', '▁a', '▁t', 'est']      )

													self.assertListEqual(
													    tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_      )							,							[2, 3, 4, 5, 6]							,							)

													SCREAMING_SNAKE_CASE__     :Dict						    = tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]      )
													self.assertListEqual(SCREAMING_SNAKE_CASE_							,							['▁This', '▁is', '▁a', '▁t', 'est']      )

													SCREAMING_SNAKE_CASE__     :List[Any]						    = tokenizer.convert_tokens_to_string(SCREAMING_SNAKE_CASE_      )
													self.assertEqual(SCREAMING_SNAKE_CASE_							,							'This is a test'      )




						@slow
						def      __lowerCamelCase       (    self :       Dict      )     ->				Optional[Any]:
													# fmt: off
													SCREAMING_SNAKE_CASE__     :Any						    = {'input_ids': [[12_80_22, 11_01_08, 3_97, 11, 3_82_72, 22_47, 12_48_11, 2_85, 1_81_05, 15_86, 2_07, 7, 3_95_34, 44_28, 3_97, 10_19, 1_81_05, 15_86, 2_07, 7, 4_13_37, 1_67_86, 2_41, 7, 2_02_14, 17, 12_56_90, 1_03_98, 7, 4_43_78, 5_80_69, 6_83_42, 77_98, 73_43, 11, 2_99, 3_33_10, 4, 1_58, 3_73_50, 9_40_77, 45_69, 2_99, 3_33_10, 90, 4, 5_28_40, 2_90, 4, 3_12_70, 1_12, 2_99, 6_82, 4, 5_28_40, 3_99_53, 1_40_79, 1_93, 5_25_19, 9_08_94, 1_78_94, 12_06_97, 11, 4_04_45, 5_51, 17, 10_19, 5_25_19, 9_08_94, 1_77_56, 9_63, 11, 4_04_45, 4_80, 17, 97_92, 11_20, 51_73, 13_93, 62_40, 1_67_86, 2_41, 12_09_96, 28, 12_45, 13_93, 11_82_40, 1_11_23, 10_19, 9_36_12, 26_91, 1_06_18, 9_80_58, 12_04_09, 19_28, 2_79, 4, 4_06_83, 3_67, 1_78, 2_07, 10_19, 1_03, 10_31_21, 5_06, 6_52_96, 5, 2], [12_80_22, 2_12_17, 3_67, 1_17, 12_54_50, 1_28, 7_19, 7, 73_08, 40, 9_36_12, 1_26_69, 11_16, 1_67_04, 71, 1_77_85, 36_99, 1_55_92, 35, 1_44, 95_84, 2_41, 1_19_43, 7_13, 9_50, 7_99, 22_47, 8_84_27, 1_50, 1_49, 11_88_13, 12_07_06, 10_19, 10_69_06, 8_15_18, 28, 12_24, 2_27_99, 3_97, 5, 2, 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, 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], [12_80_22, 16_58, 12_33_11, 51_55, 55_78, 47_22, 2_79, 1_49_47, 23_66, 11_20, 11_97, 14, 13_48, 92_32, 5, 2, 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, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], '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, 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, 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, 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, 1, 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], [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, 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]]}  # noqa: E501
													# fmt: on

													self.tokenizer_integration_test_util(
													    expected_encoding=SCREAMING_SNAKE_CASE_							,							model_name='facebook/m2m100_418M'							,							revision='c168bae485c864188cf9aa0e4108b0b6934dc91e'							,							)




@require_torch
@require_sentencepiece
@require_tokenizers
class _SCREAMING_SNAKE_CASE(							unittest.TestCase					):
						A_			:							Any     		= 'facebook/m2m100_418M'
						A_			:							Tuple     		= [
						    'In my opinion, there are two levels of response from the French government.',
						    'NSA Affair Emphasizes Complete Lack of Debate on Intelligence',
						]
						A_			:							Dict     		= [
						    'Selon moi, il y a deux niveaux de réponse de la part du gouvernement français.',
						    'L\'affaire NSA souligne l\'absence totale de débat sur le renseignement',
						]

						# fmt: off
						A_			:							List[str]     		= [EN_CODE, 593, 1_949, 115_781, 4, 71_586, 4_234, 60_633, 126_233, 432, 123_808, 15_592, 1_197, 117_132, 120_618, 5, 2]




						@classmethod
						def      __lowerCamelCase       (    cls :       Union[str, Any]      )     ->				Tuple:
													SCREAMING_SNAKE_CASE__     :List[str]						    = MaMaaaTokenizer.from_pretrained(
													    cls.checkpoint_name							,							src_lang='en'							,							tgt_lang='fr'      )
													SCREAMING_SNAKE_CASE__     :Optional[Any]						    = 1
													return cls




						def      __lowerCamelCase       (    self :       Optional[Any]      )     ->				str:
													self.assertEqual(self.tokenizer.get_lang_id('ar'      )							,							12_80_06      )
													self.assertEqual(self.tokenizer.get_lang_id('en'      )							,							12_80_22      )
													self.assertEqual(self.tokenizer.get_lang_id('ro'      )							,							12_80_76      )
													self.assertEqual(self.tokenizer.get_lang_id('mr'      )							,							12_80_63      )




						def      __lowerCamelCase       (    self :       Dict      )     ->				str:
													SCREAMING_SNAKE_CASE__     :str						    = self.tokenizer.get_vocab()
													self.assertEqual(len(SCREAMING_SNAKE_CASE_      )							,							self.tokenizer.vocab_size      )
													self.assertEqual(vocab['<unk>']							,							3      )
													self.assertIn(self.tokenizer.get_lang_token('en'      )							,							SCREAMING_SNAKE_CASE_      )




						def      __lowerCamelCase       (    self :       Tuple      )     ->				List[str]:
													SCREAMING_SNAKE_CASE__     :Any						    = 'en'
													SCREAMING_SNAKE_CASE__     :Tuple						    = self.tokenizer.batch_encode_plus(self.src_text      ).input_ids[0]
													self.assertListEqual(self.expected_src_tokens							,							SCREAMING_SNAKE_CASE_      )




						def      __lowerCamelCase       (    self :       Tuple      )     ->				Union[str, Any]:
													self.assertIn(SCREAMING_SNAKE_CASE_							,							self.tokenizer.all_special_ids      )
													# fmt: off
													SCREAMING_SNAKE_CASE__     :List[str]						    = [FR_CODE, 53_64, 82, 86_42, 4, 2_94, 47, 8, 1_40_28, 1_36, 32_86, 97_06, 6, 9_07_97, 6, 14_40_12, 1_62, 8_81_28, 3_00_61, 5, 2]
													# fmt: on
													SCREAMING_SNAKE_CASE__     :Optional[Any]						    = self.tokenizer.decode(SCREAMING_SNAKE_CASE_							,							skip_special_tokens=SCREAMING_SNAKE_CASE_      )
													SCREAMING_SNAKE_CASE__     :Dict						    = self.tokenizer.decode(generated_ids[1:]							,							skip_special_tokens=SCREAMING_SNAKE_CASE_      )
													self.assertEqual(SCREAMING_SNAKE_CASE_							,							SCREAMING_SNAKE_CASE_      )
													self.assertNotIn(self.tokenizer.eos_token							,							SCREAMING_SNAKE_CASE_      )




						def      __lowerCamelCase       (    self :       Optional[Any]      )     ->				Union[str, Any]:
													SCREAMING_SNAKE_CASE__     :Optional[int]						    = tempfile.mkdtemp()
													SCREAMING_SNAKE_CASE__     :Tuple						    = self.tokenizer.lang_token_to_id
													self.tokenizer.save_pretrained(SCREAMING_SNAKE_CASE_      )
													SCREAMING_SNAKE_CASE__     :Tuple						    = MaMaaaTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_      )
													self.assertDictEqual(new_tok.lang_token_to_id							,							SCREAMING_SNAKE_CASE_      )




						@require_torch
						def      __lowerCamelCase       (    self :       str      )     ->				Tuple:
													SCREAMING_SNAKE_CASE__     :int						    = 'en'
													SCREAMING_SNAKE_CASE__     :Union[str, Any]						    = 'fr'

													SCREAMING_SNAKE_CASE__     :List[str]						    = self.tokenizer(self.src_text							,							text_target=self.tgt_text							,							padding=SCREAMING_SNAKE_CASE_							,							return_tensors='pt'      )

													SCREAMING_SNAKE_CASE__     :int						    = shift_tokens_right(
													    batch['labels']							,							self.tokenizer.pad_token_id							,							self.tokenizer.eos_token_id      )

													for k in batch:
																				SCREAMING_SNAKE_CASE__     :List[str]						    = batch[k].tolist()
													# batch = {k: v.tolist() for k,v in batch.items()}
													# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
													# batch.decoder_inputs_ids[0][0] ==
													assert batch.input_ids[1][0] == EN_CODE
													assert batch.input_ids[1][-1] == 2
													assert batch.labels[1][0] == FR_CODE
													assert batch.labels[1][-1] == 2
													assert batch.decoder_input_ids[1][:2] == [2, FR_CODE]




						@require_torch
						def      __lowerCamelCase       (    self :       int      )     ->				Tuple:
													SCREAMING_SNAKE_CASE__     :Any						    = 'mr'
													self.assertListEqual(self.tokenizer.prefix_tokens							,							[self.tokenizer.get_lang_id('mr'      )]      )
													self.assertListEqual(self.tokenizer.suffix_tokens							,							[self.tokenizer.eos_token_id]      )

													SCREAMING_SNAKE_CASE__     :List[Any]						    = 'zh'
													self.assertListEqual(self.tokenizer.prefix_tokens							,							[self.tokenizer.get_lang_id('zh'      )]      )
													self.assertListEqual(self.tokenizer.suffix_tokens							,							[self.tokenizer.eos_token_id]      )




						@require_torch
						def      __lowerCamelCase       (    self :       Optional[Any]      )     ->				Optional[Any]:
													SCREAMING_SNAKE_CASE__     :Any						    = 'mr'
													self.tokenizer._switch_to_target_mode()
													self.assertListEqual(self.tokenizer.prefix_tokens							,							[self.tokenizer.get_lang_id('mr'      )]      )
													self.assertListEqual(self.tokenizer.suffix_tokens							,							[self.tokenizer.eos_token_id]      )
													self.tokenizer._switch_to_input_mode()
													self.assertListEqual(self.tokenizer.prefix_tokens							,							[self.tokenizer.get_lang_id(self.tokenizer.src_lang      )]      )

													SCREAMING_SNAKE_CASE__     :Optional[int]						    = 'zh'
													self.tokenizer._switch_to_target_mode()
													self.assertListEqual(self.tokenizer.prefix_tokens							,							[self.tokenizer.get_lang_id('zh'      )]      )
													self.assertListEqual(self.tokenizer.suffix_tokens							,							[self.tokenizer.eos_token_id]      )
													self.tokenizer._switch_to_input_mode()
													self.assertListEqual(self.tokenizer.prefix_tokens							,							[self.tokenizer.get_lang_id(self.tokenizer.src_lang      )]      )




						@require_torch
						def      __lowerCamelCase       (    self :       Optional[int]      )     ->				Optional[int]:
													SCREAMING_SNAKE_CASE__     :List[str]						    = self.tokenizer._build_translation_inputs('A test'							,							return_tensors='pt'							,							src_lang='en'							,							tgt_lang='ar'      )

													self.assertEqual(
													    nested_simplify(SCREAMING_SNAKE_CASE_      )							,							{
													        # en_XX, A, test, EOS
													        'input_ids': [[12_80_22, 58, 41_83, 2]],
													        'attention_mask': [[1, 1, 1, 1]],
													        # ar_AR
													        'forced_bos_token_id': 12_80_06,
													    }							,							)








from __future__ import annotations

from math import pi, sqrt




def 							a		(				snake_case__:   float		,  snake_case__:   float   ):


				'''simple docstring'''

				if inductance <= 0:
								raise ValueError('''Inductance cannot be 0 or negative'''   )

				elif capacitance <= 0:
								raise ValueError('''Capacitance cannot be 0 or negative'''   )

				else:
								return (
								    "Resonant frequency",
								    float(1 / (2 * pi * (sqrt(inductance * capacitance   )))   ),
								)


if __name__ == "__main__":
						import doctest

						doctest.testmod()




