

'''simple docstring'''

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


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

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

a        =						250004
a        =						250020







@require_sentencepiece
@require_tokenizers
class __a (   _snake_case,   unittest.TestCase			):
   __UpperCamelCase   : Optional[int]	      =	MBartaaTokenizer
   __UpperCamelCase   : Optional[Any]	      =	MBartaaTokenizerFast
   __UpperCamelCase   : Optional[Any]	      =	True
   __UpperCamelCase   : Dict	      =	True





   def      UpperCAmelCase__     (					self				:			int    ):

      '''simple docstring'''

      super().setUp()

      # We have a SentencePiece fixture for testing
      __SCREAMING_SNAKE_CASE      							=       MBartaaTokenizer(lowerCamelCase				,src_lang="""en_XX"""				,tgt_lang="""ro_RO"""				,keep_accents=lowerCamelCase    )
      tokenizer.save_pretrained(self.tmpdirname    )





   def      UpperCAmelCase__     (					self				:			Dict    ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE      							=       """<s>"""
      __SCREAMING_SNAKE_CASE      							=       0

      self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCamelCase    )				,lowerCamelCase    )
      self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCamelCase    )				,lowerCamelCase    )





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

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE      							=       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(lowerCamelCase    )				,1054    )





   def      UpperCAmelCase__     (					self				:			str    ):

      '''simple docstring'''

      self.assertEqual(self.get_tokenizer().vocab_size				,1054    )





   def      UpperCAmelCase__     (					self				:			List[Any]    ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE      							=       MBartaaTokenizer(lowerCamelCase				,src_lang="""en_XX"""				,tgt_lang="""ro_RO"""				,keep_accents=lowerCamelCase    )

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

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

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

      __SCREAMING_SNAKE_CASE      							=       tokenizer.convert_ids_to_tokens(lowerCamelCase    )
      self.assertListEqual(
          lowerCamelCase				,[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				:			Optional[Any]    ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE      							=       {"""input_ids""": [[25_0004, 1_1062, 8_2772, 7, 15, 8_2772, 538, 5_1529, 237, 1_7198, 1290, 206, 9, 21_5175, 1314, 136, 1_7198, 1290, 206, 9, 5_6359, 42, 12_2009, 9, 1_6466, 16, 8_7344, 4537, 9, 4717, 7_8381, 6, 15_9958, 7, 15, 2_4480, 618, 4, 527, 2_2693, 5428, 4, 2777, 2_4480, 9874, 4, 4_3523, 594, 4, 803, 1_8392, 3_3189, 18, 4, 4_3523, 2_4447, 1_2399, 100, 2_4955, 8_3658, 9626, 14_4057, 15, 839, 2_2335, 16, 136, 2_4955, 8_3658, 8_3479, 15, 3_9102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 12_2009, 11_5774, 23, 805, 1328, 4_6876, 7, 136, 5_3894, 1940, 4_2227, 4_1159, 1_7721, 823, 425, 4, 2_7512, 9_8722, 206, 136, 5531, 4970, 919, 1_7336, 5, 2], [25_0004, 2_0080, 618, 83, 8_2775, 47, 479, 9, 1517, 73, 5_3894, 333, 8_0581, 11_0117, 1_8811, 5256, 1295, 51, 15_2526, 297, 7986, 390, 12_4416, 538, 3_5431, 214, 98, 1_5044, 2_5737, 136, 7108, 4_3701, 23, 756, 13_5355, 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], [25_0004, 581, 6_3773, 11_9455, 6, 14_7797, 8_8203, 7, 645, 70, 21, 3285, 1_0269, 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=lowerCamelCase				,model_name="""facebook/mbart-large-50"""				,revision="""d3913889c59cd5c9e456b269c376325eabad57e2"""				,)





   def      UpperCAmelCase__     (					self				:			Tuple    ):

      '''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

      __SCREAMING_SNAKE_CASE      							=       (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})"""    ):
            __SCREAMING_SNAKE_CASE      							=       self.rust_tokenizer_class.from_pretrained(lowerCamelCase				,**lowerCamelCase    )
            __SCREAMING_SNAKE_CASE      							=       self.tokenizer_class.from_pretrained(lowerCamelCase				,**lowerCamelCase    )

            __SCREAMING_SNAKE_CASE      							=       tempfile.mkdtemp()

            __SCREAMING_SNAKE_CASE      							=       tokenizer_r.save_pretrained(lowerCamelCase    )
            __SCREAMING_SNAKE_CASE      							=       tokenizer_p.save_pretrained(lowerCamelCase    )

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

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

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

            shutil.rmtree(lowerCamelCase    )

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

            __SCREAMING_SNAKE_CASE      							=       tokenizer_r.save_pretrained(lowerCamelCase				,legacy_format=lowerCamelCase    )
            __SCREAMING_SNAKE_CASE      							=       tokenizer_p.save_pretrained(lowerCamelCase    )

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

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

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

            shutil.rmtree(lowerCamelCase    )

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

            __SCREAMING_SNAKE_CASE      							=       tokenizer_r.save_pretrained(lowerCamelCase				,legacy_format=lowerCamelCase    )
            __SCREAMING_SNAKE_CASE      							=       tokenizer_p.save_pretrained(lowerCamelCase    )

            # 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
            __SCREAMING_SNAKE_CASE      							=       tokenizer_r.from_pretrained(lowerCamelCase    )
            __SCREAMING_SNAKE_CASE      							=       tokenizer_p.from_pretrained(lowerCamelCase    )

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

            shutil.rmtree(lowerCamelCase    )







@require_torch
@require_sentencepiece
@require_tokenizers
class __a (   unittest.TestCase			):
   __UpperCamelCase   : str	      =	'facebook/mbart-large-50-one-to-many-mmt'
   __UpperCamelCase   : Optional[Any]	      =	[
       ' 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.',
   ]
   __UpperCamelCase   : Union[str, Any]	      =	[
       '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.',
   ]
   __UpperCamelCase   : Tuple	      =	[EN_CODE, 8274, 12_7873, 2_5916, 7, 8622, 2071, 438, 6_7485, 53, 18_7895, 23, 5_1712, 2]





   @classmethod
   def      UpperCAmelCase__     (					cls				:			List[str]    ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE      							=       MBartaaTokenizer.from_pretrained(
          cls.checkpoint_name				,src_lang="""en_XX"""				,tgt_lang="""ro_RO"""    )
      __SCREAMING_SNAKE_CASE      							=       1
      return cls





   def      UpperCAmelCase__     (					self				:			Tuple    ):

      '''simple docstring'''

      self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ar_AR"""]				,25_0001    )
      self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""en_EN"""]				,25_0004    )
      self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ro_RO"""]				,25_0020    )
      self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""mr_IN"""]				,25_0038    )





   def      UpperCAmelCase__     (					self				:			List[str]    ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE      							=       self.tokenizer.batch_encode_plus(self.src_text    ).input_ids[0]
      self.assertListEqual(self.expected_src_tokens				,lowerCamelCase    )





   def      UpperCAmelCase__     (					self				:			Dict    ):

      '''simple docstring'''

      self.assertIn(lowerCamelCase				,self.tokenizer.all_special_ids    )
      __SCREAMING_SNAKE_CASE      							=       [RO_CODE, 884, 9019, 96, 9, 916, 8_6792, 36, 1_8743, 1_5596, 5, 2]
      __SCREAMING_SNAKE_CASE      							=       self.tokenizer.decode(lowerCamelCase				,skip_special_tokens=lowerCamelCase    )
      __SCREAMING_SNAKE_CASE      							=       self.tokenizer.decode(generated_ids[1:]				,skip_special_tokens=lowerCamelCase    )
      self.assertEqual(lowerCamelCase				,lowerCamelCase    )
      self.assertNotIn(self.tokenizer.eos_token				,lowerCamelCase    )





   def      UpperCAmelCase__     (					self				:			str    ):

      '''simple docstring'''

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





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

      '''simple docstring'''

      self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]    )				,[25_0053, 25_0001]    )





   def      UpperCAmelCase__     (					self				:			Optional[Any]    ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE      							=       tempfile.mkdtemp()
      __SCREAMING_SNAKE_CASE      							=       self.tokenizer.fairseq_tokens_to_ids
      self.tokenizer.save_pretrained(lowerCamelCase    )
      __SCREAMING_SNAKE_CASE      							=       MBartaaTokenizer.from_pretrained(lowerCamelCase    )
      self.assertDictEqual(new_tok.fairseq_tokens_to_ids				,lowerCamelCase    )





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

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE      							=       self.tokenizer(self.src_text				,text_target=self.tgt_text				,padding=lowerCamelCase				,return_tensors="""pt"""    )
      __SCREAMING_SNAKE_CASE      							=       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				:			List[str]    ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE      							=       self.tokenizer(
          self.src_text				,text_target=self.tgt_text				,padding=lowerCamelCase				,truncation=lowerCamelCase				,max_length=len(self.expected_src_tokens    )				,return_tensors="""pt"""				,)
      __SCREAMING_SNAKE_CASE      							=       shift_tokens_right(batch["""labels"""]				,self.tokenizer.pad_token_id    )

      self.assertIsInstance(lowerCamelCase				,lowerCamelCase    )

      self.assertEqual((2, 14)				,batch.input_ids.shape    )
      self.assertEqual((2, 14)				,batch.attention_mask.shape    )
      __SCREAMING_SNAKE_CASE      							=       batch.input_ids.tolist()[0]
      self.assertListEqual(self.expected_src_tokens				,lowerCamelCase    )
      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				:			List[Any]    ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE      							=       self.tokenizer(self.src_text				,padding=lowerCamelCase				,truncation=lowerCamelCase				,max_length=3				,return_tensors="""pt"""    )
      __SCREAMING_SNAKE_CASE      							=       self.tokenizer(
          text_target=self.tgt_text				,padding=lowerCamelCase				,truncation=lowerCamelCase				,max_length=10				,return_tensors="""pt"""    )
      __SCREAMING_SNAKE_CASE      							=       targets["""input_ids"""]
      __SCREAMING_SNAKE_CASE      							=       shift_tokens_right(lowerCamelCase				,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				:			List[str]    ):

      '''simple docstring'''

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

      self.assertEqual(
          nested_simplify(lowerCamelCase    )				,{
              # en_XX, A, test, EOS
              """input_ids""": [[25_0004, 62, 3034, 2]],
              """attention_mask""": [[1, 1, 1, 1]],
              # ar_AR
              """forced_bos_token_id""": 25_0001,
          }				,)












'''simple docstring'''

from ...utils import (
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_torch_available,
    is_transformers_available,
)


try:
    if not (is_transformers_available() and is_torch_available()):
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
    from .multicontrolnet import MultiControlNetModel
    from .pipeline_controlnet import StableDiffusionControlNetPipeline
    from .pipeline_controlnet_imgaimg import StableDiffusionControlNetImgaImgPipeline
    from .pipeline_controlnet_inpaint import StableDiffusionControlNetInpaintPipeline


if is_transformers_available() and is_flax_available():
    from .pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline





