
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


_UpperCAmelCase					: Any      =       get_tests_dir("fixtures/test_sentencepiece.model")

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

_UpperCAmelCase					: Tuple      =       250_004
_UpperCAmelCase					: Optional[Any]      =       250_020


@require_sentencepiece
@require_tokenizers
class 				lowercase					(		_SCREAMING_SNAKE_CASE  ,   unittest.TestCase   ):
		__lowercase       :       Tuple	     =				MBartaaTokenizer
		__lowercase       :       Dict	     =				MBartaaTokenizerFast
		__lowercase       :       Any	     =				True
		__lowercase       :       Optional[Any]	     =				True



		def __UpperCamelCase ( self       )  ->					List[str]:
				"""simple docstring"""
				super().setUp()

				# We have a SentencePiece fixture for testing
				UpperCamelCase		=     MBartaaTokenizer(A_				,      src_lang='en_XX'				,      tgt_lang='ro_RO'				,      keep_accents=A_       )
				tokenizer.save_pretrained(self.tmpdirname       )



		def __UpperCamelCase ( self       )  ->					Dict:
				"""simple docstring"""
				UpperCamelCase		=     '<s>'
				UpperCamelCase		=     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       )  ->					Optional[int]:
				"""simple docstring"""
				UpperCamelCase		=     list(self.get_tokenizer().get_vocab().keys()       )

				self.assertEqual(vocab_keys[0]				,      '<s>'       )
				self.assertEqual(vocab_keys[1]				,      '<pad>'       )
				self.assertEqual(vocab_keys[-1]				,      '<mask>'       )
				self.assertEqual(len(A_       )				,      1_054       )



		def __UpperCamelCase ( self       )  ->					str:
				"""simple docstring"""
				self.assertEqual(self.get_tokenizer().vocab_size				,      1_054       )



		def __UpperCamelCase ( self       )  ->					Dict:
				"""simple docstring"""
				UpperCamelCase		=     MBartaaTokenizer(A_				,      src_lang='en_XX'				,      tgt_lang='ro_RO'				,      keep_accents=A_       )

				UpperCamelCase		=     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 [285, 46, 10, 170, 382]]				,      )

				UpperCamelCase		=     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', '.']				,      )
				UpperCamelCase		=     tokenizer.convert_tokens_to_ids(A_       )
				self.assertListEqual(
				    A_				,      [
				        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]
				    ]				,      )

				UpperCamelCase		=     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>', '.']				,      )



		@slow
		def __UpperCamelCase ( self       )  ->					Tuple:
				"""simple docstring"""
				# fmt: off
				UpperCamelCase		=     {'input_ids': [[250_004, 11_062, 82_772, 7, 15, 82_772, 538, 51_529, 237, 17_198, 1_290, 206, 9, 215_175, 1_314, 136, 17_198, 1_290, 206, 9, 56_359, 42, 122_009, 9, 16_466, 16, 87_344, 4_537, 9, 4_717, 78_381, 6, 159_958, 7, 15, 24_480, 618, 4, 527, 22_693, 5_428, 4, 2_777, 24_480, 9_874, 4, 43_523, 594, 4, 803, 18_392, 33_189, 18, 4, 43_523, 24_447, 12_399, 100, 24_955, 83_658, 9_626, 144_057, 15, 839, 22_335, 16, 136, 24_955, 83_658, 83_479, 15, 39_102, 724, 16, 678, 645, 2_789, 1_328, 4_589, 42, 122_009, 115_774, 23, 805, 1_328, 46_876, 7, 136, 53_894, 1_940, 42_227, 41_159, 17_721, 823, 425, 4, 27_512, 98_722, 206, 136, 5_531, 4_970, 919, 17_336, 5, 2], [250_004, 20_080, 618, 83, 82_775, 47, 479, 9, 1_517, 73, 53_894, 333, 80_581, 110_117, 18_811, 5_256, 1_295, 51, 152_526, 297, 7_986, 390, 124_416, 538, 35_431, 214, 98, 15_044, 25_737, 136, 7_108, 43_701, 23, 756, 135_355, 7, 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], [250_004, 581, 63_773, 119_455, 6, 147_797, 88_203, 7, 645, 70, 21, 3_285, 10_269, 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]], '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, 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], [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]]}  # noqa: E501
				# fmt: on

				self.tokenizer_integration_test_util(
				    expected_encoding=A_				,      model_name='facebook/mbart-large-50'				,      revision='d3913889c59cd5c9e456b269c376325eabad57e2'				,      )



		def __UpperCamelCase ( self       )  ->					Optional[Any]:
				"""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

				UpperCamelCase		=     (self.rust_tokenizer_class, 'hf-internal-testing/tiny-random-mbart50', {})
				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(A_				,      **A_       )
								UpperCamelCase		=     self.tokenizer_class.from_pretrained(A_				,      **A_       )

								UpperCamelCase		=     tempfile.mkdtemp()

								UpperCamelCase		=     tokenizer_r.save_pretrained(A_       )
								UpperCamelCase		=     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       )       )
								UpperCamelCase		=     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
								UpperCamelCase		=     tokenizer_r.from_pretrained(A_       )
								UpperCamelCase		=     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_       )       )
										# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
										# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

								shutil.rmtree(A_       )

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

								UpperCamelCase		=     tokenizer_r.save_pretrained(A_				,      legacy_format=A_       )
								UpperCamelCase		=     tokenizer_p.save_pretrained(A_       )

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

								# Checks everything loads correctly in the same way
								UpperCamelCase		=     tokenizer_r.from_pretrained(A_       )
								UpperCamelCase		=     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
								UpperCamelCase		=     tempfile.mkdtemp()

								UpperCamelCase		=     tokenizer_r.save_pretrained(A_				,      legacy_format=A_       )
								UpperCamelCase		=     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
								UpperCamelCase		=     tokenizer_r.from_pretrained(A_       )
								UpperCamelCase		=     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
@require_sentencepiece
@require_tokenizers
class 				lowercase					(		unittest.TestCase   ):
		__lowercase       :       Optional[int]	     =				"facebook/mbart-large-50-one-to-many-mmt"
		__lowercase       :       List[str]	     =				[
		    " 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       :       Optional[int]	     =				[
		    "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       :       str	     =				[EN_CODE, 8_274, 127_873, 25_916, 7, 8_622, 2_071, 438, 67_485, 53, 187_895, 23, 51_712, 2]



		@classmethod
		def __UpperCamelCase ( cls       )  ->					List[Any]:
				"""simple docstring"""
				UpperCamelCase		=     MBartaaTokenizer.from_pretrained(
				    cls.checkpoint_name				,      src_lang='en_XX'				,      tgt_lang='ro_RO'       )
				UpperCamelCase		=     1
				return cls



		def __UpperCamelCase ( self       )  ->					List[Any]:
				"""simple docstring"""
				self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']				,      250_001       )
				self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']				,      250_004       )
				self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']				,      250_020       )
				self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['mr_IN']				,      250_038       )



		def __UpperCamelCase ( self       )  ->					Optional[Any]:
				"""simple docstring"""
				UpperCamelCase		=     self.tokenizer.batch_encode_plus(self.src_text       ).input_ids[0]
				self.assertListEqual(self.expected_src_tokens				,      A_       )



		def __UpperCamelCase ( self       )  ->					Optional[Any]:
				"""simple docstring"""
				self.assertIn(A_				,      self.tokenizer.all_special_ids       )
				UpperCamelCase		=     [RO_CODE, 884, 9_019, 96, 9, 916, 86_792, 36, 18_743, 15_596, 5, 2]
				UpperCamelCase		=     self.tokenizer.decode(A_				,      skip_special_tokens=A_       )
				UpperCamelCase		=     self.tokenizer.decode(generated_ids[1:]				,      skip_special_tokens=A_       )
				self.assertEqual(A_				,      A_       )
				self.assertNotIn(self.tokenizer.eos_token				,      A_       )



		def __UpperCamelCase ( self       )  ->					Optional[int]:
				"""simple docstring"""
				UpperCamelCase		=     ['this is gunna be a long sentence ' * 20]
				assert isinstance(src_text[0]				,      A_       )
				UpperCamelCase		=     10
				UpperCamelCase		=     self.tokenizer(A_				,      max_length=A_				,      truncation=A_       ).input_ids[0]
				self.assertEqual(ids[0]				,      A_       )
				self.assertEqual(ids[-1]				,      2       )
				self.assertEqual(len(A_       )				,      A_       )



		def __UpperCamelCase ( self       )  ->					Optional[int]:
				"""simple docstring"""
				self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']       )				,      [250_053, 250_001]       )



		def __UpperCamelCase ( self       )  ->					Any:
				"""simple docstring"""
				UpperCamelCase		=     tempfile.mkdtemp()
				UpperCamelCase		=     self.tokenizer.fairseq_tokens_to_ids
				self.tokenizer.save_pretrained(A_       )
				UpperCamelCase		=     MBartaaTokenizer.from_pretrained(A_       )
				self.assertDictEqual(new_tok.fairseq_tokens_to_ids				,      A_       )



		@require_torch
		def __UpperCamelCase ( self       )  ->					Tuple:
				"""simple docstring"""
				UpperCamelCase		=     self.tokenizer(self.src_text				,      text_target=self.tgt_text				,      padding=A_				,      return_tensors='pt'       )
				UpperCamelCase		=     shift_tokens_right(batch['labels']				,      self.tokenizer.pad_token_id       )

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



		@require_torch
		def __UpperCamelCase ( self       )  ->					Tuple:
				"""simple docstring"""
				UpperCamelCase		=     self.tokenizer(
				    self.src_text				,      text_target=self.tgt_text				,      padding=A_				,      truncation=A_				,      max_length=len(self.expected_src_tokens       )				,      return_tensors='pt'				,      )
				UpperCamelCase		=     shift_tokens_right(batch['labels']				,      self.tokenizer.pad_token_id       )

				self.assertIsInstance(A_				,      A_       )

				self.assertEqual((2, 14)				,      batch.input_ids.shape       )
				self.assertEqual((2, 14)				,      batch.attention_mask.shape       )
				UpperCamelCase		=     batch.input_ids.tolist()[0]
				self.assertListEqual(self.expected_src_tokens				,      A_       )
				self.assertEqual(2				,      batch.decoder_input_ids[0, 0]       )  # decoder_start_token_id
				# 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 __UpperCamelCase ( self       )  ->					Tuple:
				"""simple docstring"""
				UpperCamelCase		=     self.tokenizer(self.src_text				,      padding=A_				,      truncation=A_				,      max_length=3				,      return_tensors='pt'       )
				UpperCamelCase		=     self.tokenizer(
				    text_target=self.tgt_text				,      padding=A_				,      truncation=A_				,      max_length=10				,      return_tensors='pt'       )
				UpperCamelCase		=     targets['input_ids']
				UpperCamelCase		=     shift_tokens_right(A_				,      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       )  ->					str:
				"""simple docstring"""
				UpperCamelCase		=     self.tokenizer._build_translation_inputs(
				    'A test'				,      return_tensors='pt'				,      src_lang='en_XX'				,      tgt_lang='ar_AR'       )

				self.assertEqual(
				    nested_simplify(A_       )				,      {
				        # en_XX, A, test, EOS
				        'input_ids': [[250_004, 62, 3_034, 2]],
				        'attention_mask': [[1, 1, 1, 1]],
				        # ar_AR
				        'forced_bos_token_id': 250_001,
				    }				,      )


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCAmelCase					: Union[str, Any]      =       {
    "configuration_instructblip": [
        "INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "InstructBlipConfig",
        "InstructBlipQFormerConfig",
        "InstructBlipVisionConfig",
    ],
    "processing_instructblip": ["InstructBlipProcessor"],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase					: List[Any]      =       [
					    "INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "InstructBlipQFormerModel",
					    "InstructBlipPreTrainedModel",
					    "InstructBlipForConditionalGeneration",
					    "InstructBlipVisionModel",
					]

if TYPE_CHECKING:
					from .configuration_instructblip import (
					    INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    InstructBlipConfig,
					    InstructBlipQFormerConfig,
					    InstructBlipVisionConfig,
					)
					from .processing_instructblip import InstructBlipProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_instructblip import (
										    INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
										    InstructBlipForConditionalGeneration,
										    InstructBlipPreTrainedModel,
										    InstructBlipQFormerModel,
										    InstructBlipVisionModel,
										)

else:
					import sys

					_UpperCAmelCase					: Union[str, Any]      =       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
