
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


lowercase__	:int										=					get_tests_dir("fixtures/test_sentencepiece.model")


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

lowercase__	:Dict										=					25_6047
lowercase__	:int										=					25_6145







@require_sentencepiece
@require_tokenizers
class        lowercase	(      SCREAMING_SNAKE_CASE__ ,						unittest.TestCase	):
							lowercase_ : Tuple       =NllbTokenizer
							lowercase_ : Optional[int]       =NllbTokenizerFast
							lowercase_ : Optional[int]       =True
							lowercase_ : Dict       =True
							lowercase_ : Optional[int]       ={}




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

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




							def 				A__   (       self):
												lowercase					=		NllbTokenizer(A__     ,keep_accents=A__)

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

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

												lowercase					=		tokenizer.tokenize('''I was born in 92000, and this is falsé.''')
												self.assertListEqual(
												    A__     ,[
												        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''',
												        '''.''',
												    ]     ,)
												lowercase					=		tokenizer.convert_tokens_to_ids(A__)
												self.assertListEqual(
												    A__     ,[
												        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]
												    ]     ,)

												lowercase					=		tokenizer.convert_ids_to_tokens(A__)
												self.assertListEqual(
												    A__     ,[
												        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 				A__   (       self):
												lowercase					=		(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})'):
																						lowercase					=		self.rust_tokenizer_class.from_pretrained(A__     ,**A__)
																						lowercase					=		self.tokenizer_class.from_pretrained(A__     ,**A__)

																						lowercase					=		tempfile.mkdtemp()

																						lowercase					=		tokenizer_r.save_pretrained(A__)
																						lowercase					=		tokenizer_p.save_pretrained(A__)

																						# 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))
																						lowercase					=		tuple(f for f in tokenizer_r_files if '''tokenizer.json''' not in f)
																						self.assertSequenceEqual(A__     ,A__)

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

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

																						shutil.rmtree(A__)

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

																						lowercase					=		tokenizer_r.save_pretrained(A__     ,legacy_format=A__)
																						lowercase					=		tokenizer_p.save_pretrained(A__)

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

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

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

																						shutil.rmtree(A__)

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

																						lowercase					=		tokenizer_r.save_pretrained(A__     ,legacy_format=A__)
																						lowercase					=		tokenizer_p.save_pretrained(A__)

																						# 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
																						lowercase					=		tokenizer_r.from_pretrained(A__)
																						lowercase					=		tokenizer_p.from_pretrained(A__)

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

																						shutil.rmtree(A__)




							@require_torch
							def 				A__   (       self):
												if not self.test_seqaseq:
																	return

												lowercase					=		self.get_tokenizers()
												for tokenizer in tokenizers:
																	with self.subTest(f'{tokenizer.__class__.__name__}'):
																						# Longer text that will definitely require truncation.
																						lowercase					=		[
																						    ''' 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.''',
																						]
																						lowercase					=		[
																						    '''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:
																											lowercase					=		tokenizer.prepare_seqaseq_batch(
																											    src_texts=A__     ,tgt_texts=A__     ,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
																						lowercase					=		tokenizer.prepare_seqaseq_batch(
																						    A__     ,tgt_texts=A__     ,max_length=3     ,return_tensors='''pt''')
																						self.assertEqual(batch.input_ids.shape[1]     ,3)
																						self.assertEqual(batch.labels.shape[1]     ,3)

																						lowercase					=		tokenizer.prepare_seqaseq_batch(
																						    src_texts=A__     ,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'''     ,A__)




							@unittest.skip('''Unfortunately way too slow to build a BPE with SentencePiece.''')
							def 				A__   (       self):
												pass





							def 				A__   (       self):
												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'):
																						lowercase					=		[AddedToken('''<special>'''     ,lstrip=A__)]

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

																						lowercase					=		tokenizer_r.encode('''<special>'''     ,add_special_tokens=A__)[0]

																						self.assertTrue(special_token_id in r_output)

																						if self.test_slow_tokenizer:
																											lowercase					=		self.rust_tokenizer_class.from_pretrained(
																											    A__     ,additional_special_tokens=A__     ,**A__     ,)
																											lowercase					=		self.tokenizer_class.from_pretrained(
																											    A__     ,additional_special_tokens=A__     ,**A__)

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

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

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







@require_torch
@require_sentencepiece
@require_tokenizers
class        lowercase	(      unittest.TestCase	):
							lowercase_ : int       ='''facebook/nllb-200-distilled-600M'''
							lowercase_ : Optional[int]       =[
							    ''' 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.''',
							]
							lowercase_ : str       =[
							    '''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.''',
							]
							lowercase_ : Tuple       =[
							    256047,
							    16297,
							    134408,
							    8165,
							    248066,
							    14734,
							    950,
							    1135,
							    105721,
							    3573,
							    83,
							    27352,
							    108,
							    49486,
							    2,
							]




							@classmethod
							def 				A__   (       cls):
												lowercase					=		NllbTokenizer.from_pretrained(
												    cls.checkpoint_name     ,src_lang='''eng_Latn'''     ,tgt_lang='''ron_Latn''')
												lowercase					=		1
												return cls




							def 				A__   (       self):
												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 				A__   (       self):
												lowercase					=		self.tokenizer.batch_encode_plus(self.src_text).input_ids[0]
												self.assertListEqual(self.expected_src_tokens     ,A__)




							def 				A__   (       self):
												self.assertIn(A__     ,self.tokenizer.all_special_ids)
												# fmt: off
												lowercase					=		[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

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




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




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




							def 				A__   (       self):
												lowercase					=		tempfile.mkdtemp()
												lowercase					=		self.tokenizer.fairseq_tokens_to_ids
												self.tokenizer.save_pretrained(A__)
												lowercase					=		NllbTokenizer.from_pretrained(A__)
												self.assertDictEqual(new_tok.fairseq_tokens_to_ids     ,A__)




							@require_torch
							def 				A__   (       self):
												lowercase					=		self.tokenizer(
												    self.src_text     ,text_target=self.tgt_text     ,padding=A__     ,truncation=A__     ,max_length=len(self.expected_src_tokens)     ,return_tensors='''pt'''     ,)
												lowercase					=		shift_tokens_right(
												    batch['''labels''']     ,self.tokenizer.pad_token_id     ,self.tokenizer.lang_code_to_id['''ron_Latn'''])

												self.assertIsInstance(A__     ,A__)

												self.assertEqual((2, 1_5)     ,batch.input_ids.shape)
												self.assertEqual((2, 1_5)     ,batch.attention_mask.shape)
												lowercase					=		batch.input_ids.tolist()[0]
												self.assertListEqual(self.expected_src_tokens     ,A__)
												self.assertEqual(A__     ,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 				A__   (       self):
												lowercase					=		self.tokenizer(self.src_text     ,padding=A__     ,truncation=A__     ,max_length=3     ,return_tensors='''pt''')
												lowercase					=		self.tokenizer(
												    text_target=self.tgt_text     ,padding=A__     ,truncation=A__     ,max_length=1_0     ,return_tensors='''pt''')
												lowercase					=		targets['''input_ids''']
												lowercase					=		shift_tokens_right(
												    A__     ,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 				A__   (       self):
												lowercase					=		self.tokenizer._build_translation_inputs(
												    '''A test'''     ,return_tensors='''pt'''     ,src_lang='''eng_Latn'''     ,tgt_lang='''fra_Latn''')

												self.assertEqual(
												    nested_simplify(A__)     ,{
												        # 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 				A__   (       self):
												lowercase					=		True
												lowercase					=		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])

												lowercase					=		False
												lowercase					=		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])






import argparse
from collections import defaultdict

import yaml


lowercase__	:Optional[int]										=					"docs/source/en/_toctree.yml"



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					lowercase					=		defaultdict(lowerCAmelCase__	)
					for doc in model_doc:
										counts[doc["local"]] += 1
					lowercase					=		[key for key, value in counts.items() if value > 1]

					lowercase					=		[]
					for duplicate_key in duplicates:
										lowercase					=		list({doc['''title'''] for doc in model_doc if doc['''local'''] == duplicate_key}	)
										if len(lowerCAmelCase__	) > 1:
															raise ValueError(
															    f'{duplicate_key} is present several times in the documentation table of content at '
															    '''`docs/source/en/_toctree.yml` with different *Title* values. Choose one of those and remove the '''
															    '''others.'''	)
										# Only add this once
										new_doc.append({'''local''': duplicate_key, '''title''': titles[0]}	)

					# Add none duplicate-keys
					new_doc.extend([doc for doc in model_doc if counts[doc['''local''']] == 1]	)

					# Sort
					return sorted(lowerCAmelCase__				,    key=lambda lowerCAmelCase__	: s["title"].lower()	)



def  UpperCamelCase					(							lowerCAmelCase__=False	):
					'''simple docstring'''
					with open(lowerCAmelCase__				,    encoding='''utf-8'''	) as f:
										lowercase					=		yaml.safe_load(f.read()	)

					# Get to the API doc
					lowercase					=		0
					while content[api_idx]["title"] != "API":
										api_idx += 1
					lowercase					=		content[api_idx]['''sections''']

					# Then to the model doc
					lowercase					=		0
					while api_doc[model_idx]["title"] != "Models":
										model_idx += 1

					lowercase					=		api_doc[model_idx]['''sections''']

					lowercase					=		[(idx, section) for idx, section in enumerate(lowerCAmelCase__	) if '''sections''' in section]
					lowercase					=		False
					for idx, modality_doc in modalities_docs:
										lowercase					=		modality_doc['''sections''']
										lowercase					=		clean_model_doc_toc(lowerCAmelCase__	)

										if old_modality_doc != new_modality_doc:
															lowercase					=		True
															if overwrite:
																				lowercase					=		new_modality_doc

					if diff:
										if overwrite:
															lowercase					=		model_doc
															lowercase					=		api_doc
															with open(lowerCAmelCase__				,    '''w'''				,    encoding='''utf-8'''	) as f:
																				f.write(yaml.dump(lowerCAmelCase__				,    allow_unicode=lowerCAmelCase__	)	)
										else:
															raise ValueError(
															    '''The model doc part of the table of content is not properly sorted, run `make style` to fix this.'''	)


if __name__ == "__main__":
							lowercase__	:Any										=					argparse.ArgumentParser()
							parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
							lowercase__	:int										=					parser.parse_args()

							check_model_doc(args.fix_and_overwrite)




