





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


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

UpperCAmelCase						:   Dict			  =     12_80_22
UpperCAmelCase						:   Any			  =     12_80_28





@require_sentencepiece
class 						_A(					snake_case__				, unittest.TestCase   ):


				"""simple docstring"""


				UpperCamelCase    :  Optional[int]					    =	MaMaaaTokenizer
				UpperCamelCase    :  Optional[Any]					    =	False
				UpperCamelCase    :  str					    =	False
				UpperCamelCase    :  Any					    =	True



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

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

									__A	:						Optional[int]       =				MaMaaaTokenizer.from_pretrained(self.tmpdirname     )
									tokenizer.save_pretrained(self.tmpdirname     )



				def 					UpperCAmelCase_		(			self     ,					**_A     ):
									return MaMaaaTokenizer.from_pretrained(self.tmpdirname     ,					**_A     )



				def 					UpperCAmelCase_		(			self     ,					_A     ):
									return (
									    "This is a test",
									    "This is a test",
									)



				def 					UpperCAmelCase_		(			self     ):
									__A	:						Tuple       =				'</s>'
									__A	:						Dict       =				0

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



				def 					UpperCAmelCase_		(			self     ):
									__A	:						List[Any]       =				self.get_tokenizer()
									__A	:						Dict       =				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(_A     )     ,					tokenizer.vocab_size + len(tokenizer.get_added_vocab()     )     )



				@unittest.skip('Skip this test while all models are still to be uploaded.'     )
				def 					UpperCAmelCase_		(			self     ):
									pass



				def 					UpperCAmelCase_		(			self     ):
									__A	:						List[str]       =				self.get_tokenizer()

									__A	:						List[str]       =				tokenizer.tokenize('This is a test'     )
									self.assertListEqual(_A     ,					['▁This', '▁is', '▁a', '▁t', 'est']     )

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

									__A	:						Optional[int]       =				tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]     )
									self.assertListEqual(_A     ,					['▁This', '▁is', '▁a', '▁t', 'est']     )

									__A	:						str       =				tokenizer.convert_tokens_to_string(_A     )
									self.assertEqual(_A     ,					'This is a test'     )





				@slow
				def 					UpperCAmelCase_		(			self     ):
									# fmt: off
									__A	:						List[Any]       =				{'input_ids': [[128022, 110108, 397, 11, 38272, 2247, 124811, 285, 18105, 1586, 207, 7, 39534, 4428, 397, 1019, 18105, 1586, 207, 7, 41337, 16786, 241, 7, 20214, 17, 125690, 10398, 7, 44378, 58069, 68342, 7798, 7343, 11, 299, 33310, 4, 158, 37350, 94077, 4569, 299, 33310, 90, 4, 52840, 290, 4, 31270, 112, 299, 682, 4, 52840, 39953, 14079, 193, 52519, 90894, 17894, 120697, 11, 40445, 551, 17, 1019, 52519, 90894, 17756, 963, 11, 40445, 480, 17, 9792, 1120, 5173, 1393, 6240, 16786, 241, 120996, 28, 1245, 1393, 118240, 11123, 1019, 93612, 2691, 10618, 98058, 120409, 1928, 279, 4, 40683, 367, 178, 207, 1019, 103, 103121, 506, 65296, 5, 2], [128022, 21217, 367, 117, 125450, 128, 719, 7, 7308, 40, 93612, 12669, 1116, 16704, 71, 17785, 3699, 15592, 35, 144, 9584, 241, 11943, 713, 950, 799, 2247, 88427, 150, 149, 118813, 120706, 1019, 106906, 81518, 28, 1224, 22799, 397, 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], [128022, 1658, 123311, 5155, 5578, 4722, 279, 14947, 2366, 1120, 1197, 14, 1348, 9232, 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=_A     ,					model_name='facebook/m2m100_418M'     ,					revision='c168bae485c864188cf9aa0e4108b0b6934dc91e'     ,					)





@require_torch
@require_sentencepiece
@require_tokenizers
class 						_A(					unittest.TestCase   ):


				"""simple docstring"""


				UpperCamelCase    :  List[Any]					    =	'''facebook/m2m100_418M'''
				UpperCamelCase    :  Any					    =	[
				    '''In my opinion, there are two levels of response from the French government.''',
				    '''NSA Affair Emphasizes Complete Lack of Debate on Intelligence''',
				]
				UpperCamelCase    :  Optional[Any]					    =	[
				    '''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
				UpperCamelCase    :  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 					UpperCAmelCase_		(			cls     ):
									__A	:						MaMaaaTokenizer       =				MaMaaaTokenizer.from_pretrained(
									    cls.checkpoint_name     ,					src_lang='en'     ,					tgt_lang='fr'     )
									__A	:						Optional[Any]       =				1
									return cls



				def 					UpperCAmelCase_		(			self     ):
									self.assertEqual(self.tokenizer.get_lang_id('ar'     )     ,					128006     )
									self.assertEqual(self.tokenizer.get_lang_id('en'     )     ,					128022     )
									self.assertEqual(self.tokenizer.get_lang_id('ro'     )     ,					128076     )
									self.assertEqual(self.tokenizer.get_lang_id('mr'     )     ,					128063     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						List[Any]       =				self.tokenizer.get_vocab()
									self.assertEqual(len(_A     )     ,					self.tokenizer.vocab_size     )
									self.assertEqual(vocab['<unk>']     ,					3     )
									self.assertIn(self.tokenizer.get_lang_token('en'     )     ,					_A     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						Any       =				'en'
									__A	:						int       =				self.tokenizer.batch_encode_plus(self.src_text     ).input_ids[0]
									self.assertListEqual(self.expected_src_tokens     ,					_A     )



				def 					UpperCAmelCase_		(			self     ):
									self.assertIn(_A     ,					self.tokenizer.all_special_ids     )
									# fmt: off
									__A	:						str       =				[FR_CODE, 5364, 82, 8642, 4, 294, 47, 8, 14028, 136, 3286, 9706, 6, 90797, 6, 144012, 162, 88128, 30061, 5, 2]
									# fmt: on
									__A	:						str       =				self.tokenizer.decode(_A     ,					skip_special_tokens=_A     )
									__A	:						int       =				self.tokenizer.decode(generated_ids[1:]     ,					skip_special_tokens=_A     )
									self.assertEqual(_A     ,					_A     )
									self.assertNotIn(self.tokenizer.eos_token     ,					_A     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						int       =				tempfile.mkdtemp()
									__A	:						int       =				self.tokenizer.lang_token_to_id
									self.tokenizer.save_pretrained(_A     )
									__A	:						Union[str, Any]       =				MaMaaaTokenizer.from_pretrained(_A     )
									self.assertDictEqual(new_tok.lang_token_to_id     ,					_A     )



				@require_torch
				def 					UpperCAmelCase_		(			self     ):
									__A	:						List[Any]       =				'en'
									__A	:						Tuple       =				'fr'

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

									__A	:						Union[str, Any]       =				shift_tokens_right(
									    batch['labels']     ,					self.tokenizer.pad_token_id     ,					self.tokenizer.eos_token_id     )

									for k in batch:
														__A	:						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 					UpperCAmelCase_		(			self     ):
									__A	:						Tuple       =				'mr'
									self.assertListEqual(self.tokenizer.prefix_tokens     ,					[self.tokenizer.get_lang_id('mr'     )]     )
									self.assertListEqual(self.tokenizer.suffix_tokens     ,					[self.tokenizer.eos_token_id]     )

									__A	:						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 					UpperCAmelCase_		(			self     ):
									__A	:						int       =				'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     )]     )

									__A	:						Optional[Any]       =				'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 					UpperCAmelCase_		(			self     ):
									__A	:						Any       =				self.tokenizer._build_translation_inputs('A test'     ,					return_tensors='pt'     ,					src_lang='en'     ,					tgt_lang='ar'     )

									self.assertEqual(
									    nested_simplify(_A     )     ,					{
									        # en_XX, A, test, EOS
									        'input_ids': [[128022, 58, 4183, 2]],
									        'attention_mask': [[1, 1, 1, 1]],
									        # ar_AR
									        'forced_bos_token_id': 128006,
									    }     ,					)











import colorsys

from PIL import Image  # type: ignore







def  _SCREAMING_SNAKE_CASE				(   a					,						a					,						a  )      ->      float:
					__A	:						List[str]       =				x
					__A	:						str       =				y
					for step in range(a  ):  # noqa: B007
										__A	:						Union[str, Any]       =				a * a - b * b + x
										__A	:						Optional[int]       =				2 * a * b + y
										__A	:						List[str]       =				a_new

										# divergence happens for all complex number with an absolute value
										# greater than 4
										if a * a + b * b > 4:
															break
					return step / (max_step - 1)







def  _SCREAMING_SNAKE_CASE				(   a  )      ->      tuple:
					if distance == 1:
										return (0, 0, 0)
					else:
										return (2_55, 2_55, 2_55)







def  _SCREAMING_SNAKE_CASE				(   a  )      ->      tuple:
					if distance == 1:
										return (0, 0, 0)
					else:
										return tuple(round(i * 2_55  ) for i in colorsys.hsv_to_rgb(a					,						1					,						1  )  )







def  _SCREAMING_SNAKE_CASE				(   a = 8_00					,						a = 6_00					,						a = -0.6					,						a = 0					,						a = 3.2					,						a = 50					,						a = True					,						)      ->      Image.Image:
					__A	:						str       =				Image.new('RGB'					,						(image_width, image_height)  )
					__A	:						Dict       =				img.load()

					# loop through the image-coordinates
					for image_x in range(a  ):
										for image_y in range(a  ):
															# determine the figure-coordinates based on the image-coordinates
															__A	:						Dict       =				figure_width / image_width * image_height
															__A	:						Union[str, Any]       =				figure_center_x + (image_x / image_width - 0.5) * figure_width
															__A	:						Optional[Any]       =				figure_center_y + (image_y / image_height - 0.5) * figure_height

															__A	:						Union[str, Any]       =				get_distance(a					,						a					,						a  )

															# color the corresponding pixel based on the selected coloring-function
															if use_distance_color_coding:
																				__A	:						Optional[Any]       =				get_color_coded_rgb(a  )
															else:
																				__A	:						Dict       =				get_black_and_white_rgb(a  )

					return img


if __name__ == "__main__":
				import doctest

				doctest.testmod()

				# colored version, full figure
				UpperCAmelCase						:   str			  =     get_image()

				# uncomment for colored version, different section, zoomed in
				# img = get_image(figure_center_x = -0.6, figure_center_y = -0.4,
				# figure_width = 0.8)

				# uncomment for black and white version, full figure
				# img = get_image(use_distance_color_coding = False)

				# uncomment to save the image
				# img.save("mandelbrot.png")

				img.show()




