

'''simple docstring'''





import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, 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


A_	= get_tests_dir("fixtures/test_sentencepiece.model")


if is_torch_available():
				from transformers.models.mbart.modeling_mbart import shift_tokens_right

A_	= 250_004
A_	= 250_020


@require_sentencepiece
@require_tokenizers
class  UpperCAmelCase (							UpperCAmelCase__  , unittest.TestCase    ):

		'''simple docstring'''






		SCREAMING_SNAKE_CASE_           =					MBartTokenizer
		SCREAMING_SNAKE_CASE_           =					MBartTokenizerFast
		SCREAMING_SNAKE_CASE_           =					True
		SCREAMING_SNAKE_CASE_           =					True
		def 			UpperCamelCase(					self		)  ->     List[Any]:






							'''simple docstring'''



							super().setUp()

							# We have a SentencePiece fixture for testing
							lowerCamelCase_  				=      MBartTokenizer(SCREAMING_SNAKE_CASE_   ,			keep_accents=SCREAMING_SNAKE_CASE_		)
							tokenizer.save_pretrained(self.tmpdirname		)
		def 			UpperCamelCase(					self		)  ->     List[Any]:






							'''simple docstring'''



							lowerCamelCase_  				=      MBartTokenizer(SCREAMING_SNAKE_CASE_   ,			keep_accents=SCREAMING_SNAKE_CASE_		)

							lowerCamelCase_  				=      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_		)   ,			[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]   ,			)

							lowerCamelCase_  				=      tokenizer.tokenize('I was born in 92000, and this is falsé.'		)
							self.assertListEqual(
							    SCREAMING_SNAKE_CASE_   ,			[
							        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',
							        '.',
							    ]   ,			)
							lowerCamelCase_  				=      tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_		)
							self.assertListEqual(
							    SCREAMING_SNAKE_CASE_   ,			[
							        value + tokenizer.fairseq_offset
							        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
							        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
							    ]   ,			)

							lowerCamelCase_  				=      tokenizer.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_		)
							self.assertListEqual(
							    SCREAMING_SNAKE_CASE_   ,			[
							        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 			UpperCamelCase(					self		)  ->     int:






							'''simple docstring'''



							if not self.test_slow_tokenizer:
												# as we don't have a slow version, we can't compare the outputs between slow and fast versions
												return

							lowerCamelCase_  				=      (self.rust_tokenizer_class, 'hf-internal-testing/tiny-random-mbart', {})
							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
												with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''		):
																	lowerCamelCase_  				=      self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE_   ,			**SCREAMING_SNAKE_CASE_		)
																	lowerCamelCase_  				=      self.tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE_   ,			**SCREAMING_SNAKE_CASE_		)

																	lowerCamelCase_  				=      tempfile.mkdtemp()

																	lowerCamelCase_  				=      tokenizer_r.save_pretrained(SCREAMING_SNAKE_CASE_		)
																	lowerCamelCase_  				=      tokenizer_p.save_pretrained(SCREAMING_SNAKE_CASE_		)

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

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

																	# Check special tokens are set accordingly on Rust and Python
																	for key in tokenizer_pp.special_tokens_map:
																						self.assertTrue(hasattr(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)		)
																						# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
																						# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

																	shutil.rmtree(SCREAMING_SNAKE_CASE_		)

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

																	lowerCamelCase_  				=      tokenizer_r.save_pretrained(SCREAMING_SNAKE_CASE_   ,			legacy_format=SCREAMING_SNAKE_CASE_		)
																	lowerCamelCase_  				=      tokenizer_p.save_pretrained(SCREAMING_SNAKE_CASE_		)

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

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

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

																	shutil.rmtree(SCREAMING_SNAKE_CASE_		)

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

																	lowerCamelCase_  				=      tokenizer_r.save_pretrained(SCREAMING_SNAKE_CASE_   ,			legacy_format=SCREAMING_SNAKE_CASE_		)
																	lowerCamelCase_  				=      tokenizer_p.save_pretrained(SCREAMING_SNAKE_CASE_		)

																	# 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
																	lowerCamelCase_  				=      tokenizer_r.from_pretrained(SCREAMING_SNAKE_CASE_		)
																	lowerCamelCase_  				=      tokenizer_p.from_pretrained(SCREAMING_SNAKE_CASE_		)

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

																	shutil.rmtree(SCREAMING_SNAKE_CASE_		)


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

		'''simple docstring'''






		SCREAMING_SNAKE_CASE_           =					'facebook/mbart-large-en-ro'
		SCREAMING_SNAKE_CASE_           =					[
		    ' 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.',
		]
		SCREAMING_SNAKE_CASE_           =					[
		    '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.',
		]
		SCREAMING_SNAKE_CASE_           =					[82_74, 12_78_73, 2_59_16, 7, 86_22, 20_71, 4_38, 6_74_85, 53, 18_78_95, 23, 5_17_12, 2, EN_CODE]
		@classmethod
		def 			UpperCamelCase(					cls		)  ->     Optional[Any]:






							'''simple docstring'''



							lowerCamelCase_  				=      MBartTokenizer.from_pretrained(
							    cls.checkpoint_name   ,			src_lang='en_XX'   ,			tgt_lang='ro_RO'		)
							lowerCamelCase_  				=      1
							return cls
		def 			UpperCamelCase(					self		)  ->     List[Any]:






							'''simple docstring'''



							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']   ,			250001		)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']   ,			250004		)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']   ,			250020		)
		def 			UpperCamelCase(					self		)  ->     Dict:






							'''simple docstring'''



							lowerCamelCase_  				=      self.tokenizer.batch_encode_plus(self.src_text		).input_ids[0]
							self.assertListEqual(self.expected_src_tokens   ,			SCREAMING_SNAKE_CASE_		)
		def 			UpperCamelCase(					self		)  ->     Optional[int]:






							'''simple docstring'''



							self.assertIn(SCREAMING_SNAKE_CASE_   ,			self.tokenizer.all_special_ids		)
							lowerCamelCase_  				=      [RO_CODE, 884, 9019, 96, 9, 916, 86792, 36, 18743, 15596, 5, 2]
							lowerCamelCase_  				=      self.tokenizer.decode(SCREAMING_SNAKE_CASE_   ,			skip_special_tokens=SCREAMING_SNAKE_CASE_		)
							lowerCamelCase_  				=      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 			UpperCamelCase(					self		)  ->     List[Any]:






							'''simple docstring'''



							lowerCamelCase_  				=      ['this is gunna be a long sentence ' * 20]
							assert isinstance(src_text[0]   ,			SCREAMING_SNAKE_CASE_		)
							lowerCamelCase_  				=      10
							lowerCamelCase_  				=      self.tokenizer(SCREAMING_SNAKE_CASE_   ,			max_length=SCREAMING_SNAKE_CASE_   ,			truncation=SCREAMING_SNAKE_CASE_		).input_ids[0]
							self.assertEqual(ids[-2]   ,			2		)
							self.assertEqual(ids[-1]   ,			SCREAMING_SNAKE_CASE_		)
							self.assertEqual(len(SCREAMING_SNAKE_CASE_		)   ,			SCREAMING_SNAKE_CASE_		)
		def 			UpperCamelCase(					self		)  ->     Tuple:






							'''simple docstring'''



							self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']		)   ,			[250026, 250001]		)
		def 			UpperCamelCase(					self		)  ->     List[str]:






							'''simple docstring'''



							lowerCamelCase_  				=      tempfile.mkdtemp()
							lowerCamelCase_  				=      self.tokenizer.fairseq_tokens_to_ids
							self.tokenizer.save_pretrained(SCREAMING_SNAKE_CASE_		)
							lowerCamelCase_  				=      MBartTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_		)
							self.assertDictEqual(new_tok.fairseq_tokens_to_ids   ,			SCREAMING_SNAKE_CASE_		)
		@require_torch
		def 			UpperCamelCase(					self		)  ->     Dict:






							'''simple docstring'''



							lowerCamelCase_  				=      self.tokenizer(self.src_text   ,			text_target=self.tgt_text   ,			padding=SCREAMING_SNAKE_CASE_   ,			return_tensors='pt'		)
							lowerCamelCase_  				=      shift_tokens_right(batch['labels']   ,			self.tokenizer.pad_token_id		)

							# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
							assert batch.input_ids[1][-2:].tolist() == [2, EN_CODE]
							assert batch.decoder_input_ids[1][0].tolist() == RO_CODE
							assert batch.decoder_input_ids[1][-1] == 2
							assert batch.labels[1][-2:].tolist() == [2, RO_CODE]
		@require_torch
		def 			UpperCamelCase(					self		)  ->     Dict:






							'''simple docstring'''



							lowerCamelCase_  				=      self.tokenizer(
							    self.src_text   ,			text_target=self.tgt_text   ,			padding=SCREAMING_SNAKE_CASE_   ,			truncation=SCREAMING_SNAKE_CASE_   ,			max_length=len(self.expected_src_tokens		)   ,			return_tensors='pt'   ,			)

							lowerCamelCase_  				=      shift_tokens_right(batch['labels']   ,			self.tokenizer.pad_token_id		)

							self.assertIsInstance(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)

							self.assertEqual((2, 14)   ,			batch.input_ids.shape		)
							self.assertEqual((2, 14)   ,			batch.attention_mask.shape		)
							lowerCamelCase_  				=      batch.input_ids.tolist()[0]
							self.assertListEqual(self.expected_src_tokens   ,			SCREAMING_SNAKE_CASE_		)
							self.assertEqual(2   ,			batch.decoder_input_ids[0, -1]		)  # EOS
							# Test that special tokens are reset
							self.assertEqual(self.tokenizer.prefix_tokens   ,			[]		)
							self.assertEqual(self.tokenizer.suffix_tokens   ,			[self.tokenizer.eos_token_id, EN_CODE]		)
		def 			UpperCamelCase(					self		)  ->     Optional[Any]:






							'''simple docstring'''



							lowerCamelCase_  				=      self.tokenizer(self.src_text   ,			padding=SCREAMING_SNAKE_CASE_   ,			truncation=SCREAMING_SNAKE_CASE_   ,			max_length=3   ,			return_tensors='pt'		)
							lowerCamelCase_  				=      self.tokenizer(
							    text_target=self.tgt_text   ,			padding=SCREAMING_SNAKE_CASE_   ,			truncation=SCREAMING_SNAKE_CASE_   ,			max_length=10   ,			return_tensors='pt'		)
							lowerCamelCase_  				=      targets['input_ids']
							lowerCamelCase_  				=      shift_tokens_right(SCREAMING_SNAKE_CASE_   ,			self.tokenizer.pad_token_id		)

							self.assertEqual(batch.input_ids.shape[1]   ,			3		)
							self.assertEqual(batch.decoder_input_ids.shape[1]   ,			10		)






		@require_torch
		def 			UpperCamelCase(					self		)  ->     Any:






							'''simple docstring'''



							lowerCamelCase_  				=      self.tokenizer._build_translation_inputs(
							    'A test'   ,			return_tensors='pt'   ,			src_lang='en_XX'   ,			tgt_lang='ar_AR'		)

							self.assertEqual(
							    nested_simplify(SCREAMING_SNAKE_CASE_		)   ,			{
							        # A, test, EOS, en_XX
							        'input_ids': [[62, 3034, 2, 250004]],
							        'attention_mask': [[1, 1, 1, 1]],
							        # ar_AR
							        'forced_bos_token_id': 250001,
							    }   ,			)









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCamelCase   :			Optional[int]          = {
    "configuration_jukebox": [
        "JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "JukeboxConfig",
        "JukeboxPriorConfig",
        "JukeboxVQVAEConfig",
    ],
    "tokenization_jukebox": ["JukeboxTokenizer"],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCamelCase   :			int          = [
		    "JUKEBOX_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "JukeboxModel",
		    "JukeboxPreTrainedModel",
		    "JukeboxVQVAE",
		    "JukeboxPrior",
		]

if TYPE_CHECKING:
		from .configuration_jukebox import (
		    JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    JukeboxConfig,
		    JukeboxPriorConfig,
		    JukeboxVQVAEConfig,
		)
		from .tokenization_jukebox import JukeboxTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_jukebox import (
				    JUKEBOX_PRETRAINED_MODEL_ARCHIVE_LIST,
				    JukeboxModel,
				    JukeboxPreTrainedModel,
				    JukeboxPrior,
				    JukeboxVQVAE,
				)

else:
		import sys

		__UpperCamelCase   :			List[str]          = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

