


"""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


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

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

_snake_case          =							25_0004
_snake_case          =							25_0020



@require_sentencepiece
@require_tokenizers
class   _a      (      UpperCAmelCase__		,		unittest.TestCase ):
    a_    :				List[Any]             =    MBartaaTokenizer
    a_    :				List[str]             =    MBartaaTokenizerFast
    a_    :				int             =    True
    a_    :				str             =    True
    def      _UpperCamelCase       ( self							:					str				):
          super().setUp()

          # We have a SentencePiece fixture for testing
          lowerCamelCase__           =		MBartaaTokenizer(__lowerCAmelCase							,					src_lang='en_XX'							,					tgt_lang='ro_RO'							,					keep_accents=__lowerCAmelCase				)
          tokenizer.save_pretrained(self.tmpdirname				)
    def      _UpperCamelCase       ( self							:					int				):
          lowerCamelCase__           =		'<s>'
          lowerCamelCase__           =		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							:					int				):
          lowerCamelCase__           =		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				)							,					10_54				)
    def      _UpperCamelCase       ( self							:					Union[str, Any]				):
          self.assertEqual(self.get_tokenizer().vocab_size							,					10_54				)
    def      _UpperCamelCase       ( self							:					Tuple				):
          lowerCamelCase__           =		MBartaaTokenizer(__lowerCAmelCase							,					src_lang='en_XX'							,					tgt_lang='ro_RO'							,					keep_accents=__lowerCAmelCase				)

          lowerCamelCase__           =		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 [2_85, 46, 10, 1_70, 3_82]]							,					)

          lowerCamelCase__           =		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', '.']							,					)
          lowerCamelCase__           =		tokenizer.convert_tokens_to_ids(__lowerCAmelCase				)
          self.assertListEqual(
              __lowerCAmelCase							,					[
                  value + tokenizer.fairseq_offset
                  for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
              ]							,					)

          lowerCamelCase__           =		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							:					Dict				):
          lowerCamelCase__           =		{'input_ids': [[25_00_04, 1_10_62, 8_27_72, 7, 15, 8_27_72, 5_38, 5_15_29, 2_37, 1_71_98, 12_90, 2_06, 9, 21_51_75, 13_14, 1_36, 1_71_98, 12_90, 2_06, 9, 5_63_59, 42, 12_20_09, 9, 1_64_66, 16, 8_73_44, 45_37, 9, 47_17, 7_83_81, 6, 15_99_58, 7, 15, 2_44_80, 6_18, 4, 5_27, 2_26_93, 54_28, 4, 27_77, 2_44_80, 98_74, 4, 4_35_23, 5_94, 4, 8_03, 1_83_92, 3_31_89, 18, 4, 4_35_23, 2_44_47, 1_23_99, 1_00, 2_49_55, 8_36_58, 96_26, 14_40_57, 15, 8_39, 2_23_35, 16, 1_36, 2_49_55, 8_36_58, 8_34_79, 15, 3_91_02, 7_24, 16, 6_78, 6_45, 27_89, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 8_05, 13_28, 4_68_76, 7, 1_36, 5_38_94, 19_40, 4_22_27, 4_11_59, 1_77_21, 8_23, 4_25, 4, 2_75_12, 9_87_22, 2_06, 1_36, 55_31, 49_70, 9_19, 1_73_36, 5, 2], [25_00_04, 2_00_80, 6_18, 83, 8_27_75, 47, 4_79, 9, 15_17, 73, 5_38_94, 3_33, 8_05_81, 11_01_17, 1_88_11, 52_56, 12_95, 51, 15_25_26, 2_97, 79_86, 3_90, 12_44_16, 5_38, 3_54_31, 2_14, 98, 1_50_44, 2_57_37, 1_36, 71_08, 4_37_01, 23, 7_56, 13_53_55, 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_00_04, 5_81, 6_37_73, 11_94_55, 6, 14_77_97, 8_82_03, 7, 6_45, 70, 21, 32_85, 1_02_69, 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							:					Dict				):






          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-mbart50', {})
          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(__lowerCAmelCase							,					**__lowerCAmelCase				)
                      lowerCamelCase__           =		self.tokenizer_class.from_pretrained(__lowerCAmelCase							,					**__lowerCAmelCase				)

                      lowerCamelCase__           =		tempfile.mkdtemp()

                      lowerCamelCase__           =		tokenizer_r.save_pretrained(__lowerCAmelCase				)
                      lowerCamelCase__           =		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				)				)
                      lowerCamelCase__           =		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
                      lowerCamelCase__           =		tokenizer_r.from_pretrained(__lowerCAmelCase				)
                      lowerCamelCase__           =		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
                      lowerCamelCase__           =		tempfile.mkdtemp()

                      lowerCamelCase__           =		tokenizer_r.save_pretrained(__lowerCAmelCase							,					legacy_format=__lowerCAmelCase				)
                      lowerCamelCase__           =		tokenizer_p.save_pretrained(__lowerCAmelCase				)

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

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

                      lowerCamelCase__           =		tokenizer_r.save_pretrained(__lowerCAmelCase							,					legacy_format=__lowerCAmelCase				)
                      lowerCamelCase__           =		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
                      lowerCamelCase__           =		tokenizer_r.from_pretrained(__lowerCAmelCase				)
                      lowerCamelCase__           =		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 ):
    a_    :				Optional[Any]             =    'facebook/mbart-large-50-one-to-many-mmt'
    a_    :				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.',
    ]
    a_    :				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.',
    ]
    a_    :				Any             =    [EN_CODE, 8274, 127873, 25916, 7, 8622, 2071, 438, 67485, 53, 187895, 23, 51712, 2]
    @classmethod
    def      _UpperCamelCase       ( cls							:					List[str]				):
          lowerCamelCase__           =		MBartaaTokenizer.from_pretrained(
              cls.checkpoint_name							,					src_lang='en_XX'							,					tgt_lang='ro_RO'				)
          lowerCamelCase__           =		1
          return cls
    def      _UpperCamelCase       ( self							:					Tuple				):
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']							,					25_00_01				)
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']							,					25_00_04				)
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']							,					25_00_20				)
          self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['mr_IN']							,					25_00_38				)
    def      _UpperCamelCase       ( self							:					str				):
          lowerCamelCase__           =		self.tokenizer.batch_encode_plus(self.src_text				).input_ids[0]
          self.assertListEqual(self.expected_src_tokens							,					__lowerCAmelCase				)
    def      _UpperCamelCase       ( self							:					Optional[Any]				):
          self.assertIn(__lowerCAmelCase							,					self.tokenizer.all_special_ids				)
          lowerCamelCase__           =		[RO_CODE, 8_84, 90_19, 96, 9, 9_16, 8_67_92, 36, 1_87_43, 1_55_96, 5, 2]
          lowerCamelCase__           =		self.tokenizer.decode(__lowerCAmelCase							,					skip_special_tokens=__lowerCAmelCase				)
          lowerCamelCase__           =		self.tokenizer.decode(generated_ids[1:]							,					skip_special_tokens=__lowerCAmelCase				)
          self.assertEqual(__lowerCAmelCase							,					__lowerCAmelCase				)
          self.assertNotIn(self.tokenizer.eos_token							,					__lowerCAmelCase				)
    def      _UpperCamelCase       ( self							:					Any				):
          lowerCamelCase__           =		['this is gunna be a long sentence ' * 20]
          assert isinstance(src_text[0]							,					__lowerCAmelCase				)
          lowerCamelCase__           =		10
          lowerCamelCase__           =		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							:					Optional[int]				):
          self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']				)							,					[25_00_53, 25_00_01]				)
    def      _UpperCamelCase       ( self							:					str				):
          lowerCamelCase__           =		tempfile.mkdtemp()
          lowerCamelCase__           =		self.tokenizer.fairseq_tokens_to_ids
          self.tokenizer.save_pretrained(__lowerCAmelCase				)
          lowerCamelCase__           =		MBartaaTokenizer.from_pretrained(__lowerCAmelCase				)
          self.assertDictEqual(new_tok.fairseq_tokens_to_ids							,					__lowerCAmelCase				)
    @require_torch
    def      _UpperCamelCase       ( self							:					Optional[Any]				):
          lowerCamelCase__           =		self.tokenizer(self.src_text							,					text_target=self.tgt_text							,					padding=__lowerCAmelCase							,					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][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							:					str				):
          lowerCamelCase__           =		self.tokenizer(
              self.src_text							,					text_target=self.tgt_text							,					padding=__lowerCAmelCase							,					truncation=__lowerCAmelCase							,					max_length=len(self.expected_src_tokens				)							,					return_tensors='pt'							,					)
          lowerCamelCase__           =		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				)
          lowerCamelCase__           =		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							:					Optional[int]				):
          lowerCamelCase__           =		self.tokenizer(self.src_text							,					padding=__lowerCAmelCase							,					truncation=__lowerCAmelCase							,					max_length=3							,					return_tensors='pt'				)
          lowerCamelCase__           =		self.tokenizer(
              text_target=self.tgt_text							,					padding=__lowerCAmelCase							,					truncation=__lowerCAmelCase							,					max_length=10							,					return_tensors='pt'				)
          lowerCamelCase__           =		targets['input_ids']
          lowerCamelCase__           =		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							:					Optional[int]				):
          lowerCamelCase__           =		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_00_04, 62, 30_34, 2]],
                  'attention_mask': [[1, 1, 1, 1]],
                  # ar_AR
                  'forced_bos_token_id': 25_00_01,
              }							,					)









"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_snake_case          =							{
    "configuration_blenderbot": [
        "BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BlenderbotConfig",
        "BlenderbotOnnxConfig",
    ],
    "tokenization_blenderbot": ["BlenderbotTokenizer"],
}

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

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case          =							[
       "BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST",
       "BlenderbotForCausalLM",
       "BlenderbotForConditionalGeneration",
       "BlenderbotModel",
       "BlenderbotPreTrainedModel",
   ]


try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case          =							[
       "TFBlenderbotForConditionalGeneration",
       "TFBlenderbotModel",
       "TFBlenderbotPreTrainedModel",
   ]


try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case          =							[
       "FlaxBlenderbotForConditionalGeneration",
       "FlaxBlenderbotModel",
       "FlaxBlenderbotPreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_blenderbot import (
       BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
       BlenderbotConfig,
       BlenderbotOnnxConfig,
   )
   from .tokenization_blenderbot import BlenderbotTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_blenderbot import (
          BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
          BlenderbotForCausalLM,
          BlenderbotForConditionalGeneration,
          BlenderbotModel,
          BlenderbotPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_blenderbot import (
          TFBlenderbotForConditionalGeneration,
          TFBlenderbotModel,
          TFBlenderbotPreTrainedModel,
      )

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_blenderbot import (
          FlaxBlenderbotForConditionalGeneration,
          FlaxBlenderbotModel,
          FlaxBlenderbotPreTrainedModel,
      )

else:
   import sys

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



