






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


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


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

UpperCAmelCase__							  =						250004
UpperCAmelCase__							  =						250020






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






      '''simple docstring'''




      __snake_case	    =    MBartTokenizer
      __snake_case	    =    MBartTokenizerFast
      __snake_case	    =    True
      __snake_case	    =    True







      def  __lowerCAmelCase   ( self :		str    )       ->Optional[int]:




       """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 :		List[str]    )       ->Optional[int]:




       """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 :		Tuple    )       ->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'''




      __snake_case	    =    '''facebook/mbart-large-en-ro'''
      __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.''',
      ]
      __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.''',
      ]
      __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 :		int    )       ->str:




       """simple docstring"""


       a						    = MBartTokenizer.from_pretrained(
           cls.checkpoint_name					,   src_lang='''en_XX'''					,   tgt_lang='''ro_RO'''    )
       a						    = 1
       return cls







      def  __lowerCAmelCase   ( self :		Dict    )       ->Union[str, 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    )







      def  __lowerCAmelCase   ( self :		List[Any]    )       ->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 :		Optional[Any]    )       ->int:




       """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 :		Any    )       ->List[str]:




       """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 :		Any    )       ->Dict:




       """simple docstring"""


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







      def  __lowerCAmelCase   ( self :		List[Any]    )       ->Optional[Any]:




       """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 :		Dict    )       ->Optional[Any]:




       """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 :		Optional[Any]    )       ->Optional[int]:




       """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]    )       ->Tuple:




       """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 :		Dict    )       ->Dict:




       """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,
           }					,   )










from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


UpperCAmelCase__							  =						{"processing_layoutxlm": ["LayoutXLMProcessor"]}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase__							  =						["LayoutXLMTokenizer"]

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase__							  =						["LayoutXLMTokenizerFast"]

if TYPE_CHECKING:
     from .processing_layoutxlm import LayoutXLMProcessor

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_layoutxlm import LayoutXLMTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_layoutxlm_fast import LayoutXLMTokenizerFast

else:
     import sys

     UpperCAmelCase__							  =						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


