






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


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

__a   :							int						= 250004
__a   :							Any						= 250020


@require_sentencepiece
@require_tokenizers
class    __lowercase   (						lowercase_      ,   unittest.TestCase	):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE     =					MBartTokenizer
     SCREAMING_SNAKE_CASE     =					MBartTokenizerFast
     SCREAMING_SNAKE_CASE     =					True
     SCREAMING_SNAKE_CASE     =					True




     def 		lowerCAmelCase_  (					self							:      Union[str, Any]					):


         """simple docstring"""



         super().setUp()

         # We have a SentencePiece fixture for testing
         __A       =						MBartTokenizer(UpperCamelCase_			,						keep_accents=UpperCamelCase_					)
         tokenizer.save_pretrained(self.tmpdirname					)




     def 		lowerCAmelCase_  (					self							:      Union[str, Any]					):


         """simple docstring"""



         __A       =						MBartTokenizer(UpperCamelCase_			,						keep_accents=UpperCamelCase_					)

         __A       =						tokenizer.tokenize("""This is a test"""					)
         self.assertListEqual(UpperCamelCase_			,						["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]					)

         self.assertListEqual(
             tokenizer.convert_tokens_to_ids(UpperCamelCase_					)			,						[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]			,						)

         __A       =						tokenizer.tokenize("""I was born in 92000, and this is falsé."""					)
         self.assertListEqual(
             UpperCamelCase_			,						[
                 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""",
                 """.""",
             ]			,						)
         __A       =						tokenizer.convert_tokens_to_ids(UpperCamelCase_					)
         self.assertListEqual(
             UpperCamelCase_			,						[
                 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 ^
             ]			,						)

         __A       =						tokenizer.convert_ids_to_tokens(UpperCamelCase_					)
         self.assertListEqual(
             UpperCamelCase_			,						[
                 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 		lowerCAmelCase_  (					self							:      List[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

         __A       =						(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})"					):
                 __A       =						self.rust_tokenizer_class.from_pretrained(UpperCamelCase_			,						**UpperCamelCase_					)
                 __A       =						self.tokenizer_class.from_pretrained(UpperCamelCase_			,						**UpperCamelCase_					)

                 __A       =						tempfile.mkdtemp()

                 __A       =						tokenizer_r.save_pretrained(UpperCamelCase_					)
                 __A       =						tokenizer_p.save_pretrained(UpperCamelCase_					)

                 # 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					)					)
                 __A       =						tuple(f for f in tokenizer_r_files if """tokenizer.json""" not in f					)
                 self.assertSequenceEqual(UpperCamelCase_			,						UpperCamelCase_					)

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

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

                 shutil.rmtree(UpperCamelCase_					)

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

                 __A       =						tokenizer_r.save_pretrained(UpperCamelCase_			,						legacy_format=UpperCamelCase_					)
                 __A       =						tokenizer_p.save_pretrained(UpperCamelCase_					)

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

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

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

                 shutil.rmtree(UpperCamelCase_					)

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

                 __A       =						tokenizer_r.save_pretrained(UpperCamelCase_			,						legacy_format=UpperCamelCase_					)
                 __A       =						tokenizer_p.save_pretrained(UpperCamelCase_					)

                 # 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
                 __A       =						tokenizer_r.from_pretrained(UpperCamelCase_					)
                 __A       =						tokenizer_p.from_pretrained(UpperCamelCase_					)

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

                 shutil.rmtree(UpperCamelCase_					)


@require_torch
@require_sentencepiece
@require_tokenizers
class    __lowercase   (						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 		lowerCAmelCase_  (					cls							:      Tuple					):


         """simple docstring"""



         __A       =						MBartTokenizer.from_pretrained(
             cls.checkpoint_name			,						src_lang="""en_XX"""			,						tgt_lang="""ro_RO"""					)
         __A       =						1
         return cls




     def 		lowerCAmelCase_  (					self							:      int					):


         """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					)




     def 		lowerCAmelCase_  (					self							:      List[Any]					):


         """simple docstring"""



         __A       =						self.tokenizer.batch_encode_plus(self.src_text					).input_ids[0]
         self.assertListEqual(self.expected_src_tokens			,						UpperCamelCase_					)




     def 		lowerCAmelCase_  (					self							:      Tuple					):


         """simple docstring"""



         self.assertIn(UpperCamelCase_			,						self.tokenizer.all_special_ids					)
         __A       =						[RO_CODE, 884, 9_019, 96, 9, 916, 86_792, 36, 18_743, 15_596, 5, 2]
         __A       =						self.tokenizer.decode(UpperCamelCase_			,						skip_special_tokens=UpperCamelCase_					)
         __A       =						self.tokenizer.decode(generated_ids[1:]			,						skip_special_tokens=UpperCamelCase_					)
         self.assertEqual(UpperCamelCase_			,						UpperCamelCase_					)
         self.assertNotIn(self.tokenizer.eos_token			,						UpperCamelCase_					)




     def 		lowerCAmelCase_  (					self							:      int					):


         """simple docstring"""



         __A       =						["""this is gunna be a long sentence """ * 20]
         assert isinstance(src_text[0]			,						UpperCamelCase_					)
         __A       =						10
         __A       =						self.tokenizer(UpperCamelCase_			,						max_length=UpperCamelCase_			,						truncation=UpperCamelCase_					).input_ids[0]
         self.assertEqual(ids[-2]			,						2					)
         self.assertEqual(ids[-1]			,						UpperCamelCase_					)
         self.assertEqual(len(UpperCamelCase_					)			,						UpperCamelCase_					)




     def 		lowerCAmelCase_  (					self							:      int					):


         """simple docstring"""



         self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]					)			,						[250_026, 250_001]					)




     def 		lowerCAmelCase_  (					self							:      Optional[int]					):


         """simple docstring"""



         __A       =						tempfile.mkdtemp()
         __A       =						self.tokenizer.fairseq_tokens_to_ids
         self.tokenizer.save_pretrained(UpperCamelCase_					)
         __A       =						MBartTokenizer.from_pretrained(UpperCamelCase_					)
         self.assertDictEqual(new_tok.fairseq_tokens_to_ids			,						UpperCamelCase_					)




     @require_torch
     def 		lowerCAmelCase_  (					self							:      Optional[int]					):


         """simple docstring"""



         __A       =						self.tokenizer(self.src_text			,						text_target=self.tgt_text			,						padding=UpperCamelCase_			,						return_tensors="""pt"""					)
         __A       =						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 		lowerCAmelCase_  (					self							:      Tuple					):


         """simple docstring"""



         __A       =						self.tokenizer(
             self.src_text			,						text_target=self.tgt_text			,						padding=UpperCamelCase_			,						truncation=UpperCamelCase_			,						max_length=len(self.expected_src_tokens					)			,						return_tensors="""pt"""			,						)

         __A       =						shift_tokens_right(batch["""labels"""]			,						self.tokenizer.pad_token_id					)

         self.assertIsInstance(UpperCamelCase_			,						UpperCamelCase_					)

         self.assertEqual((2, 14)			,						batch.input_ids.shape					)
         self.assertEqual((2, 14)			,						batch.attention_mask.shape					)
         __A       =						batch.input_ids.tolist()[0]
         self.assertListEqual(self.expected_src_tokens			,						UpperCamelCase_					)
         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 		lowerCAmelCase_  (					self							:      Optional[int]					):


         """simple docstring"""



         __A       =						self.tokenizer(self.src_text			,						padding=UpperCamelCase_			,						truncation=UpperCamelCase_			,						max_length=3			,						return_tensors="""pt"""					)
         __A       =						self.tokenizer(
             text_target=self.tgt_text			,						padding=UpperCamelCase_			,						truncation=UpperCamelCase_			,						max_length=10			,						return_tensors="""pt"""					)
         __A       =						targets["""input_ids"""]
         __A       =						shift_tokens_right(UpperCamelCase_			,						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 		lowerCAmelCase_  (					self							:      Union[str, Any]					):


         """simple docstring"""



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

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












import warnings

from ...utils import logging
from .image_processing_deit import DeiTImageProcessor


__a   :							Any						= logging.get_logger(__name__)


class    __lowercase   (						lowercase_	):







     '''simple docstring'''




     def __init__(					self							:      Union[str, Any]			,						*UpperCamelCase_							:      Tuple			,						**UpperCamelCase_							:      Tuple					):


         """simple docstring"""



         warnings.warn(
             """The class DeiTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
             """ use DeiTImageProcessor instead."""			,						UpperCamelCase_			,						)
         super().__init__(*UpperCamelCase_			,						**UpperCamelCase_					)




