





'''simple docstring'''




import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


a__					:			List[Any]          =     get_tests_dir('''fixtures/test_sentencepiece.model''')






@require_sentencepiece
@require_tokenizers
class 				__snake_case     (					__magic_name__       ,       unittest.TestCase							):
	__lowerCAmelCase       						=  ReformerTokenizer
	__lowerCAmelCase       						=  ReformerTokenizerFast
	__lowerCAmelCase       						=  True
	__lowerCAmelCase       						=  False
	__lowerCAmelCase       						=  True





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

		snake_case__	       =   ReformerTokenizer(UpperCamelCase_      ,       keep_accents=UpperCamelCase_		)
		tokenizer.save_pretrained(self.tmpdirname		)





	def   _snake_case   (		self		)      ->		Optional[Any]:
		snake_case__	       =   '<s>'
		snake_case__	       =   1

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





	def   _snake_case   (		self		)      ->		Any:
		snake_case__	       =   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(UpperCamelCase_		)      ,       1000		)





	def   _snake_case   (		self		)      ->		Optional[int]:
		self.assertEqual(self.get_tokenizer().vocab_size      ,       1000		)





	def   _snake_case   (		self		)      ->		Dict:
		if not self.test_rust_tokenizer:
			return

		snake_case__	       =   self.get_tokenizer()
		snake_case__	       =   self.get_rust_tokenizer()

		snake_case__	       =   'I was born in 92000, and this is falsé.'

		snake_case__	       =   tokenizer.tokenize(UpperCamelCase_		)
		snake_case__	       =   rust_tokenizer.tokenize(UpperCamelCase_		)
		self.assertListEqual(UpperCamelCase_      ,       UpperCamelCase_		)

		snake_case__	       =   tokenizer.encode(UpperCamelCase_      ,       add_special_tokens=UpperCamelCase_		)
		snake_case__	       =   rust_tokenizer.encode(UpperCamelCase_      ,       add_special_tokens=UpperCamelCase_		)
		self.assertListEqual(UpperCamelCase_      ,       UpperCamelCase_		)

		snake_case__	       =   self.get_rust_tokenizer()
		snake_case__	       =   tokenizer.encode(UpperCamelCase_		)
		snake_case__	       =   rust_tokenizer.encode(UpperCamelCase_		)
		self.assertListEqual(UpperCamelCase_      ,       UpperCamelCase_		)





	def   _snake_case   (		self      ,       UpperCamelCase_=15		)      ->		List[str]:
		for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
			with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''		):
				snake_case__	       =   self.rust_tokenizer_class.from_pretrained(UpperCamelCase_      ,       **UpperCamelCase_		)

				# Simple input
				snake_case__	       =   'This is a simple input'
				snake_case__	       =   ['This is a simple input 1', 'This is a simple input 2']
				snake_case__	       =   ('This is a simple input', 'This is a pair')
				snake_case__	       =   [
				    ('This is a simple input 1', 'This is a simple input 2'),
				    ('This is a simple pair 1', 'This is a simple pair 2'),
				]

				# Simple input tests
				self.assertRaises(UpperCamelCase_      ,       tokenizer_r.encode      ,       UpperCamelCase_      ,       max_length=UpperCamelCase_      ,       padding='max_length'		)

				# Simple input
				self.assertRaises(UpperCamelCase_      ,       tokenizer_r.encode_plus      ,       UpperCamelCase_      ,       max_length=UpperCamelCase_      ,       padding='max_length'		)

				# Simple input
				self.assertRaises(
				    UpperCamelCase_      ,       tokenizer_r.batch_encode_plus      ,       UpperCamelCase_      ,       max_length=UpperCamelCase_      ,       padding='max_length'      ,       )

				# Pair input
				self.assertRaises(UpperCamelCase_      ,       tokenizer_r.encode      ,       UpperCamelCase_      ,       max_length=UpperCamelCase_      ,       padding='max_length'		)

				# Pair input
				self.assertRaises(UpperCamelCase_      ,       tokenizer_r.encode_plus      ,       UpperCamelCase_      ,       max_length=UpperCamelCase_      ,       padding='max_length'		)

				# Pair input
				self.assertRaises(
				    UpperCamelCase_      ,       tokenizer_r.batch_encode_plus      ,       UpperCamelCase_      ,       max_length=UpperCamelCase_      ,       padding='max_length'      ,       )





	def   _snake_case   (		self		)      ->		Union[str, Any]:
		pass





	def   _snake_case   (		self		)      ->		str:
		snake_case__	       =   ReformerTokenizer(UpperCamelCase_      ,       keep_accents=UpperCamelCase_		)

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

		self.assertListEqual(
		    tokenizer.convert_tokens_to_ids(UpperCamelCase_		)      ,       [285, 46, 10, 170, 382]      ,       )

		snake_case__	       =   tokenizer.tokenize('I was born in 92000, and this is falsé.'		)
		self.assertListEqual(
		    UpperCamelCase_      ,       [
		        SPIECE_UNDERLINE + 'I',
		        SPIECE_UNDERLINE + 'was',
		        SPIECE_UNDERLINE + 'b',
		        'or',
		        'n',
		        SPIECE_UNDERLINE + 'in',
		        SPIECE_UNDERLINE + '',
		        '9',
		        '2',
		        '0',
		        '0',
		        '0',
		        ',',
		        SPIECE_UNDERLINE + 'and',
		        SPIECE_UNDERLINE + 'this',
		        SPIECE_UNDERLINE + 'is',
		        SPIECE_UNDERLINE + 'f',
		        'al',
		        's',
		        'é',
		        '.',
		    ]      ,       )
		snake_case__	       =   tokenizer.convert_tokens_to_ids(UpperCamelCase_		)
		self.assertListEqual(
		    UpperCamelCase_      ,       [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]      ,       )

		snake_case__	       =   tokenizer.convert_ids_to_tokens(UpperCamelCase_		)
		self.assertListEqual(
		    UpperCamelCase_      ,       [
		        SPIECE_UNDERLINE + 'I',
		        SPIECE_UNDERLINE + 'was',
		        SPIECE_UNDERLINE + 'b',
		        'or',
		        'n',
		        SPIECE_UNDERLINE + 'in',
		        SPIECE_UNDERLINE + '',
		        '<unk>',
		        '2',
		        '0',
		        '0',
		        '0',
		        ',',
		        SPIECE_UNDERLINE + 'and',
		        SPIECE_UNDERLINE + 'this',
		        SPIECE_UNDERLINE + 'is',
		        SPIECE_UNDERLINE + 'f',
		        'al',
		        's',
		        '<unk>',
		        '.',
		    ]      ,       )





	@cached_property
	def   _snake_case   (		self		)      ->		Optional[int]:
		return ReformerTokenizer.from_pretrained('google/reformer-crime-and-punishment'		)





	@slow
	def   _snake_case   (		self		)      ->		List[Any]:
		snake_case__	       =   'Hello World!'
		snake_case__	       =   [126, 32, 262, 152, 38, 72, 287]

		self.assertListEqual(UpperCamelCase_      ,       self.big_tokenizer.encode(UpperCamelCase_		)		)





	@slow
	def   _snake_case   (		self		)      ->		str:
		snake_case__	       =   (
		    'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
		    ' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'
		)
		snake_case__	       =   [
		    108,
		    265,
		    24,
		    111,
		    4,
		    258,
		    156,
		    35,
		    28,
		    275,
		    3,
		    259,
		    297,
		    260,
		    84,
		    4,
		    35,
		    110,
		    44,
		    8,
		    259,
		    91,
		    268,
		    21,
		    11,
		    209,
		    274,
		    109,
		    266,
		    277,
		    117,
		    86,
		    93,
		    315,
		    258,
		    278,
		    258,
		    277,
		    258,
		    0,
		    258,
		    288,
		    258,
		    319,
		    258,
		    0,
		    258,
		    0,
		    258,
		    0,
		    258,
		    0,
		    258,
		    287,
		    258,
		    315,
		    258,
		    289,
		    258,
		    278,
		    99,
		    269,
		    266,
		    262,
		    8,
		    259,
		    241,
		    4,
		    217,
		    230,
		    268,
		    266,
		    55,
		    168,
		    106,
		    75,
		    193,
		    266,
		    223,
		    27,
		    49,
		    26,
		    282,
		    25,
		    264,
		    299,
		    19,
		    26,
		    0,
		    258,
		    277,
		    117,
		    86,
		    93,
		    176,
		    183,
		    270,
		    11,
		    262,
		    42,
		    61,
		    265,
		]

		self.assertListEqual(UpperCamelCase_      ,       self.big_tokenizer.encode(UpperCamelCase_		)		)





	@require_torch
	@slow
	def   _snake_case   (		self		)      ->		str:
		import torch

		from transformers import ReformerConfig, ReformerModel

		# Build sequence
		snake_case__	       =   list(self.big_tokenizer.get_vocab().keys()		)[:10]
		snake_case__	       =   ' '.join(UpperCamelCase_		)
		snake_case__	       =   self.big_tokenizer.encode_plus(UpperCamelCase_      ,       return_tensors='pt'		)
		snake_case__	       =   self.big_tokenizer.batch_encode_plus([sequence, sequence]      ,       return_tensors='pt'		)

		snake_case__	       =   ReformerConfig()
		# The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
		snake_case__	       =   encoded_sequence['input_ids'].shape
		snake_case__	       =   ReformerModel(UpperCamelCase_		)

		# Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
		assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

		with torch.no_grad():
			model(**UpperCamelCase_		)
			model(**UpperCamelCase_		)





	@slow
	def   _snake_case   (		self		)      ->		Union[str, Any]:
		# fmt: off
		snake_case__	       =   {'input_ids': [[108, 265, 24, 111, 4, 258, 156, 7, 51, 279, 58, 7, 76, 25, 69, 278], [140, 243, 264, 134, 17, 267, 77, 263, 22, 262, 297, 258, 304, 177, 279, 266, 14, 89, 13, 35, 261, 299, 272, 137, 275, 278]], '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]]}  # noqa: E501
		# fmt: on

		# This tokenizer does not know some characters like ")".
		# That is the reason why we use very simple texts here.
		# Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
		snake_case__	       =   [
		    'This is a very simple sentence.',
		    'The quick brown fox jumps over the lazy dog.',
		]

		self.tokenizer_integration_test_util(
		    expected_encoding=UpperCamelCase_      ,       model_name='google/reformer-crime-and-punishment'      ,       revision='0e6c3decb8211d49bf881013425dc8b0448b3f5a'      ,       padding=UpperCamelCase_      ,       sequences=UpperCamelCase_      ,       )










'''simple docstring'''




import cmath
import math




def 						__lowerCamelCase			(	UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_							)   ->complex:
	snake_case__	       =   math.radians(UpperCAmelCase_							)
	snake_case__	       =   math.radians(UpperCAmelCase_							)

	# Convert voltage and current to rectangular form
	snake_case__	       =   cmath.rect(UpperCAmelCase_					,				UpperCAmelCase_							)
	snake_case__	       =   cmath.rect(UpperCAmelCase_					,				UpperCAmelCase_							)

	# Calculate apparent power
	return voltage_rect * current_rect


if __name__ == "__main__":
			import doctest

			doctest.testmod()



