'''simple docstring'''


import shutil
import tempfile
import unittest

from transformers import (
    SPIECE_UNDERLINE,
    AddedToken,
    BatchEncoding,
    NllbTokenizer,
    NllbTokenizerFast,
    is_torch_available,
)
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


__lowerCAmelCase	:       Optional[int]						       =	get_tests_dir("fixtures/test_sentencepiece.model")


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

__lowerCAmelCase	:       List[Any]						       =	256_047
__lowerCAmelCase	:       Dict						       =	256_145






@require_sentencepiece
@require_tokenizers
class 						SCREAMING_SNAKE_CASE_   (   UpperCAmelCase       ,	unittest.TestCase   ):
							a_        =      NllbTokenizer
							a_        =      NllbTokenizerFast
							a_        =      True
							a_        =      True
							a_        =      {}





							def       snake_case__						(      self				:							Any	)							->	Dict:
								super().setUp()

								# We have a SentencePiece fixture for testing
								__UpperCAmelCase							=			NllbTokenizer(_lowerCAmelCase     ,		keep_accents=_lowerCAmelCase	)
								tokenizer.save_pretrained(self.tmpdirname	)





							def       snake_case__						(      self				:							str	)							->	Optional[int]:
								__UpperCAmelCase							=			NllbTokenizer(_lowerCAmelCase     ,		keep_accents=_lowerCAmelCase	)

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

								self.assertListEqual(
								    tokenizer.convert_tokens_to_ids(_lowerCAmelCase	)     ,		[value + tokenizer.fairseq_offset for value in [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]     ,		)

								__UpperCAmelCase							=			tokenizer.tokenize('''I was born in 92000, and this is falsé.'''	)
								self.assertListEqual(
								    _lowerCAmelCase     ,		[
								        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''',
								        '''.''',
								    ]     ,		)
								__UpperCAmelCase							=			tokenizer.convert_tokens_to_ids(_lowerCAmelCase	)
								self.assertListEqual(
								    _lowerCAmelCase     ,		[
								        value + tokenizer.fairseq_offset
								        for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
								    ]     ,		)

								__UpperCAmelCase							=			tokenizer.convert_ids_to_tokens(_lowerCAmelCase	)
								self.assertListEqual(
								    _lowerCAmelCase     ,		[
								        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>''',
								        '''.''',
								    ]     ,		)





							def       snake_case__						(      self				:							str	)							->	Union[str, Any]:
								__UpperCAmelCase							=			(self.rust_tokenizer_class, '''hf-internal-testing/tiny-random-nllb''', {})
								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""	):
										__UpperCAmelCase							=			self.rust_tokenizer_class.from_pretrained(_lowerCAmelCase     ,		**_lowerCAmelCase	)
										__UpperCAmelCase							=			self.tokenizer_class.from_pretrained(_lowerCAmelCase     ,		**_lowerCAmelCase	)

										__UpperCAmelCase							=			tempfile.mkdtemp()

										__UpperCAmelCase							=			tokenizer_r.save_pretrained(_lowerCAmelCase	)
										__UpperCAmelCase							=			tokenizer_p.save_pretrained(_lowerCAmelCase	)

										# Checks it save with the same files + the tokenizer.json file for the fast one
										self.assertTrue(any('''tokenizer.json''' in f for f in tokenizer_r_files	)	)
										__UpperCAmelCase							=			tuple(f for f in tokenizer_r_files if '''tokenizer.json''' not in f	)
										self.assertSequenceEqual(_lowerCAmelCase     ,		_lowerCAmelCase	)

										# Checks everything loads correctly in the same way
										__UpperCAmelCase							=			tokenizer_r.from_pretrained(_lowerCAmelCase	)
										__UpperCAmelCase							=			tokenizer_p.from_pretrained(_lowerCAmelCase	)

										# Check special tokens are set accordingly on Rust and Python
										for key in tokenizer_pp.special_tokens_map:
											self.assertTrue(hasattr(_lowerCAmelCase     ,		_lowerCAmelCase	)	)

										shutil.rmtree(_lowerCAmelCase	)

										# Save tokenizer rust, legacy_format=True
										__UpperCAmelCase							=			tempfile.mkdtemp()

										__UpperCAmelCase							=			tokenizer_r.save_pretrained(_lowerCAmelCase     ,		legacy_format=_lowerCAmelCase	)
										__UpperCAmelCase							=			tokenizer_p.save_pretrained(_lowerCAmelCase	)

										# Checks it save with the same files
										self.assertSequenceEqual(_lowerCAmelCase     ,		_lowerCAmelCase	)

										# Checks everything loads correctly in the same way
										__UpperCAmelCase							=			tokenizer_r.from_pretrained(_lowerCAmelCase	)
										__UpperCAmelCase							=			tokenizer_p.from_pretrained(_lowerCAmelCase	)

										# Check special tokens are set accordingly on Rust and Python
										for key in tokenizer_pp.special_tokens_map:
											self.assertTrue(hasattr(_lowerCAmelCase     ,		_lowerCAmelCase	)	)

										shutil.rmtree(_lowerCAmelCase	)

										# Save tokenizer rust, legacy_format=False
										__UpperCAmelCase							=			tempfile.mkdtemp()

										__UpperCAmelCase							=			tokenizer_r.save_pretrained(_lowerCAmelCase     ,		legacy_format=_lowerCAmelCase	)
										__UpperCAmelCase							=			tokenizer_p.save_pretrained(_lowerCAmelCase	)

										# Checks it saved the tokenizer.json file
										self.assertTrue(any('''tokenizer.json''' in f for f in tokenizer_r_files	)	)

										# Checks everything loads correctly in the same way
										__UpperCAmelCase							=			tokenizer_r.from_pretrained(_lowerCAmelCase	)
										__UpperCAmelCase							=			tokenizer_p.from_pretrained(_lowerCAmelCase	)

										# Check special tokens are set accordingly on Rust and Python
										for key in tokenizer_pp.special_tokens_map:
											self.assertTrue(hasattr(_lowerCAmelCase     ,		_lowerCAmelCase	)	)

										shutil.rmtree(_lowerCAmelCase	)





							@require_torch
							def       snake_case__						(      self				:							Any	)							->	int:
								if not self.test_seqaseq:
									return

								__UpperCAmelCase							=			self.get_tokenizers()
								for tokenizer in tokenizers:
									with self.subTest(f"""{tokenizer.__class__.__name__}"""	):
										# Longer text that will definitely require truncation.
										__UpperCAmelCase							=			[
										    ''' UN Chief Says There Is No Military Solution in Syria''',
										    ''' Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for'''
										    ''' Syria is that \'there is no military solution\' to the nearly five-year conflict and more weapons'''
										    ''' will only worsen the violence and misery for millions of people.''',
										]
										__UpperCAmelCase							=			[
										    '''Şeful ONU declară că nu există o soluţie militară în Siria''',
										    '''Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al'''
										    ''' Rusiei pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi'''
										    ''' că noi arme nu vor face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.''',
										]
										try:
											__UpperCAmelCase							=			tokenizer.prepare_seqaseq_batch(
											    src_texts=_lowerCAmelCase     ,		tgt_texts=_lowerCAmelCase     ,		max_length=3     ,		max_target_length=1_0     ,		return_tensors='''pt'''     ,		src_lang='''eng_Latn'''     ,		tgt_lang='''ron_Latn'''     ,		)
										except NotImplementedError:
											return
										self.assertEqual(batch.input_ids.shape[1]     ,		3	)
										self.assertEqual(batch.labels.shape[1]     ,		1_0	)
										# max_target_length will default to max_length if not specified
										__UpperCAmelCase							=			tokenizer.prepare_seqaseq_batch(
										    _lowerCAmelCase     ,		tgt_texts=_lowerCAmelCase     ,		max_length=3     ,		return_tensors='''pt'''	)
										self.assertEqual(batch.input_ids.shape[1]     ,		3	)
										self.assertEqual(batch.labels.shape[1]     ,		3	)

										__UpperCAmelCase							=			tokenizer.prepare_seqaseq_batch(
										    src_texts=_lowerCAmelCase     ,		max_length=3     ,		max_target_length=1_0     ,		return_tensors='''pt'''	)
										self.assertEqual(batch_encoder_only.input_ids.shape[1]     ,		3	)
										self.assertEqual(batch_encoder_only.attention_mask.shape[1]     ,		3	)
										self.assertNotIn('''decoder_input_ids'''     ,		_lowerCAmelCase	)





							@unittest.skip('''Unfortunately way too slow to build a BPE with SentencePiece.'''	)
							def       snake_case__						(      self				:							Optional[int]	)							->	Any:
								pass






							def       snake_case__						(      self				:							int	)							->	str:
								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""	):
										__UpperCAmelCase							=			[AddedToken('''<special>'''     ,		lstrip=_lowerCAmelCase	)]

										__UpperCAmelCase							=			self.rust_tokenizer_class.from_pretrained(
										    _lowerCAmelCase     ,		additional_special_tokens=_lowerCAmelCase     ,		**_lowerCAmelCase	)
										__UpperCAmelCase							=			tokenizer_r.encode('''Hey this is a <special> token'''	)

										__UpperCAmelCase							=			tokenizer_r.encode('''<special>'''     ,		add_special_tokens=_lowerCAmelCase	)[0]

										self.assertTrue(special_token_id in r_output	)

										if self.test_slow_tokenizer:
											__UpperCAmelCase							=			self.rust_tokenizer_class.from_pretrained(
											    _lowerCAmelCase     ,		additional_special_tokens=_lowerCAmelCase     ,		**_lowerCAmelCase     ,		)
											__UpperCAmelCase							=			self.tokenizer_class.from_pretrained(
											    _lowerCAmelCase     ,		additional_special_tokens=_lowerCAmelCase     ,		**_lowerCAmelCase	)

											__UpperCAmelCase							=			tokenizer_p.encode('''Hey this is a <special> token'''	)

											__UpperCAmelCase							=			tokenizer_cr.encode('''Hey this is a <special> token'''	)

											self.assertEqual(_lowerCAmelCase     ,		_lowerCAmelCase	)
											self.assertEqual(_lowerCAmelCase     ,		_lowerCAmelCase	)
											self.assertTrue(special_token_id in p_output	)
											self.assertTrue(special_token_id in cr_output	)






@require_torch
@require_sentencepiece
@require_tokenizers
class 						SCREAMING_SNAKE_CASE_   (   unittest.TestCase   ):
							a_        =      '''facebook/nllb-200-distilled-600M'''
							a_        =      [
							    ''' UN Chief Says There Is No Military Solution in Syria''',
							    ''' Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for Syria is that "there is no military solution" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.''',
							]
							a_        =      [
							    '''Şeful ONU declară că nu există o soluţie militară în Siria''',
							    '''Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei'''
							    ''' pentru Siria este că "nu există o soluţie militară" la conflictul de aproape cinci ani şi că noi arme nu vor'''
							    ''' face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.''',
							]
							a_        =      [
							    2_5_6_0_4_7,
							    1_6_2_9_7,
							    1_3_4_4_0_8,
							    8_1_6_5,
							    2_4_8_0_6_6,
							    1_4_7_3_4,
							    9_5_0,
							    1_1_3_5,
							    1_0_5_7_2_1,
							    3_5_7_3,
							    8_3,
							    2_7_3_5_2,
							    1_0_8,
							    4_9_4_8_6,
							    2,
							]





							@classmethod
							def       snake_case__						(      cls				:							Tuple	)							->	List[str]:
								__UpperCAmelCase							=			NllbTokenizer.from_pretrained(
								    cls.checkpoint_name     ,		src_lang='''eng_Latn'''     ,		tgt_lang='''ron_Latn'''	)
								__UpperCAmelCase							=			1
								return cls





							def       snake_case__						(      self				:							Any	)							->	str:
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''ace_Arab''']     ,		2_5_6_0_0_1	)
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''ace_Latn''']     ,		2_5_6_0_0_2	)
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''fra_Latn''']     ,		2_5_6_0_5_7	)





							def       snake_case__						(      self				:							str	)							->	Optional[int]:
								__UpperCAmelCase							=			self.tokenizer.batch_encode_plus(self.src_text	).input_ids[0]
								self.assertListEqual(self.expected_src_tokens     ,		_lowerCAmelCase	)





							def       snake_case__						(      self				:							int	)							->	str:
								self.assertIn(_lowerCAmelCase     ,		self.tokenizer.all_special_ids	)
								# fmt: off
								__UpperCAmelCase							=			[RO_CODE, 4_2_5_4, 9_8_0_6_8, 1_1_2_9_2_3, 3_9_0_7_2, 3_9_0_9, 7_1_3, 1_0_2_7_6_7, 2_6, 1_7_3_1_4, 3_5_6_4_2, 1_4_6_8_3, 3_3_1_1_8, 2_0_2_2, 6_6_9_8_7, 2, 2_5_6_0_4_7]
								# fmt: on

								__UpperCAmelCase							=			self.tokenizer.decode(_lowerCAmelCase     ,		skip_special_tokens=_lowerCAmelCase	)
								__UpperCAmelCase							=			self.tokenizer.decode(generated_ids[1:]     ,		skip_special_tokens=_lowerCAmelCase	)
								self.assertEqual(_lowerCAmelCase     ,		_lowerCAmelCase	)
								self.assertNotIn(self.tokenizer.eos_token     ,		_lowerCAmelCase	)





							def       snake_case__						(      self				:							Tuple	)							->	Any:
								__UpperCAmelCase							=			['''this is gunna be a long sentence ''' * 2_0]
								assert isinstance(src_text[0]     ,		_lowerCAmelCase	)
								__UpperCAmelCase							=			1_0
								__UpperCAmelCase							=			self.tokenizer(_lowerCAmelCase     ,		max_length=_lowerCAmelCase     ,		truncation=_lowerCAmelCase	).input_ids[0]
								self.assertEqual(ids[-1]     ,		2	)
								self.assertEqual(ids[0]     ,		_lowerCAmelCase	)
								self.assertEqual(len(_lowerCAmelCase	)     ,		_lowerCAmelCase	)





							def       snake_case__						(      self				:							Tuple	)							->	int:
								self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['''<mask>''', '''ar_AR''']	)     ,		[2_5_6_2_0_3, 3]	)





							def       snake_case__						(      self				:							List[Any]	)							->	Union[str, Any]:
								__UpperCAmelCase							=			tempfile.mkdtemp()
								__UpperCAmelCase							=			self.tokenizer.fairseq_tokens_to_ids
								self.tokenizer.save_pretrained(_lowerCAmelCase	)
								__UpperCAmelCase							=			NllbTokenizer.from_pretrained(_lowerCAmelCase	)
								self.assertDictEqual(new_tok.fairseq_tokens_to_ids     ,		_lowerCAmelCase	)





							@require_torch
							def       snake_case__						(      self				:							Tuple	)							->	Any:
								__UpperCAmelCase							=			self.tokenizer(
								    self.src_text     ,		text_target=self.tgt_text     ,		padding=_lowerCAmelCase     ,		truncation=_lowerCAmelCase     ,		max_length=len(self.expected_src_tokens	)     ,		return_tensors='''pt'''     ,		)
								__UpperCAmelCase							=			shift_tokens_right(
								    batch['''labels''']     ,		self.tokenizer.pad_token_id     ,		self.tokenizer.lang_code_to_id['''ron_Latn''']	)

								self.assertIsInstance(_lowerCAmelCase     ,		_lowerCAmelCase	)

								self.assertEqual((2, 1_5)     ,		batch.input_ids.shape	)
								self.assertEqual((2, 1_5)     ,		batch.attention_mask.shape	)
								__UpperCAmelCase							=			batch.input_ids.tolist()[0]
								self.assertListEqual(self.expected_src_tokens     ,		_lowerCAmelCase	)
								self.assertEqual(_lowerCAmelCase     ,		batch.decoder_input_ids[0, 0]	)  # EOS
								# Test that special tokens are reset
								self.assertEqual(self.tokenizer.prefix_tokens     ,		[EN_CODE]	)
								self.assertEqual(self.tokenizer.suffix_tokens     ,		[self.tokenizer.eos_token_id]	)





							def       snake_case__						(      self				:							Optional[int]	)							->	Any:
								__UpperCAmelCase							=			self.tokenizer(self.src_text     ,		padding=_lowerCAmelCase     ,		truncation=_lowerCAmelCase     ,		max_length=3     ,		return_tensors='''pt'''	)
								__UpperCAmelCase							=			self.tokenizer(
								    text_target=self.tgt_text     ,		padding=_lowerCAmelCase     ,		truncation=_lowerCAmelCase     ,		max_length=1_0     ,		return_tensors='''pt'''	)
								__UpperCAmelCase							=			targets['''input_ids''']
								__UpperCAmelCase							=			shift_tokens_right(
								    _lowerCAmelCase     ,		self.tokenizer.pad_token_id     ,		decoder_start_token_id=self.tokenizer.lang_code_to_id[self.tokenizer.tgt_lang]     ,		)

								self.assertEqual(batch.input_ids.shape[1]     ,		3	)
								self.assertEqual(batch.decoder_input_ids.shape[1]     ,		1_0	)





							@require_torch
							def       snake_case__						(      self				:							Union[str, Any]	)							->	List[str]:
								__UpperCAmelCase							=			self.tokenizer._build_translation_inputs(
								    '''A test'''     ,		return_tensors='''pt'''     ,		src_lang='''eng_Latn'''     ,		tgt_lang='''fra_Latn'''	)

								self.assertEqual(
								    nested_simplify(_lowerCAmelCase	)     ,		{
								        # A, test, EOS, en_XX
								        '''input_ids''': [[2_5_6_0_4_7, 7_0, 7_3_5_6, 2]],
								        '''attention_mask''': [[1, 1, 1, 1]],
								        # ar_AR
								        '''forced_bos_token_id''': 2_5_6_0_5_7,
								    }     ,		)






							@require_torch
							def       snake_case__						(      self				:							Tuple	)							->	Union[str, Any]:
								__UpperCAmelCase							=			True
								__UpperCAmelCase							=			self.tokenizer(
								    '''UN Chief says there is no military solution in Syria'''     ,		src_lang='''eng_Latn'''     ,		tgt_lang='''fra_Latn'''	)
								self.assertEqual(
								    inputs.input_ids     ,		[1_6_2_9_7, 1_3_4_4_0_8, 2_5_6_5_3, 6_3_7_0, 2_4_8, 2_5_4, 1_0_3_9_2_9, 9_4_9_9_5, 1_0_8, 4_9_4_8_6, 2, 2_5_6_0_4_7]	)

								__UpperCAmelCase							=			False
								__UpperCAmelCase							=			self.tokenizer(
								    '''UN Chief says there is no military solution in Syria'''     ,		src_lang='''eng_Latn'''     ,		tgt_lang='''fra_Latn'''	)
								self.assertEqual(
								    inputs.input_ids     ,		[2_5_6_0_4_7, 1_6_2_9_7, 1_3_4_4_0_8, 2_5_6_5_3, 6_3_7_0, 2_4_8, 2_5_4, 1_0_3_9_2_9, 9_4_9_9_5, 1_0_8, 4_9_4_8_6, 2]	)

'''simple docstring'''


def       lowerCAmelCase					(		UpperCamelCase__				:   Tuple       ):


	"""simple docstring"""
	# if the collection is empty, returns empty
	if collection == []:
		return []

	# get some information about the collection
	__UpperCAmelCase							=			len(UpperCamelCase__       )
	__UpperCAmelCase							=			max(UpperCamelCase__       )
	__UpperCAmelCase							=			min(UpperCamelCase__       )

	# create the counting array
	__UpperCAmelCase							=			coll_max + 1 - coll_min
	__UpperCAmelCase							=			[0] * counting_arr_length

	# count how much a number appears in the collection
	for number in collection:
		counting_arr[number - coll_min] += 1

	# sum each position with it's predecessors. now, counting_arr[i] tells
	# us how many elements <= i has in the collection
	for i in range(1    ,					UpperCamelCase__       ):
		__UpperCAmelCase							=			counting_arr[i] + counting_arr[i - 1]

	# create the output collection
	__UpperCAmelCase							=			[0] * coll_len

	# place the elements in the output, respecting the original order (stable
	# sort) from end to begin, updating counting_arr
	for i in reversed(range(0    ,					UpperCamelCase__       )       ):
		__UpperCAmelCase							=			collection[i]
		counting_arr[collection[i] - coll_min] -= 1

	return ordered





def       lowerCAmelCase					(		UpperCamelCase__				:   Any       ):


	"""simple docstring"""
	return "".join([chr(UpperCamelCase__       ) for i in counting_sort([ord(UpperCamelCase__       ) for c in string]       )]       )


if __name__ == "__main__":
					# Test string sort
					assert counting_sort_string("thisisthestring") == "eghhiiinrsssttt"

					__lowerCAmelCase	:       str						       =	input("Enter numbers separated by a comma:\n").strip()
					__lowerCAmelCase	:       List[Any]						       =	[int(item) for item in user_input.split(",")]
					print(counting_sort(unsorted))
