





"""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											=		25_0004
__A											=		25_0020






@require_sentencepiece
@require_tokenizers
class 					_lowerCAmelCase   (     a  ,   unittest.TestCase       ):
       """simple docstring"""




       __magic_name__     :Optional[int]		  =					MBartaaTokenizer
       __magic_name__     :List[Any]		  =					MBartaaTokenizerFast
       __magic_name__     :str		  =					True
       __magic_name__     :int		  =					True






       def      snake_case						(    self      ):



         '''simple docstring'''

         super().setUp()

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






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Tuple											=							'<s>'
         lowerCAmelCase__			:Optional[Any]											=							0

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






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:int											=							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(__UpperCAmelCase      )    , 1_0_5_4      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         self.assertEqual(self.get_tokenizer().vocab_size    , 1_0_5_4      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Tuple											=							MBartaaTokenizer(__UpperCAmelCase    , src_lang='en_XX'    , tgt_lang='ro_RO'    , keep_accents=__UpperCAmelCase      )

         lowerCAmelCase__			:Any											=							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 [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]    , )

         lowerCAmelCase__			:List[str]											=							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', '.']    , )
         lowerCAmelCase__			:List[Any]											=							tokenizer.convert_tokens_to_ids(__UpperCAmelCase      )
         self.assertListEqual(
             __UpperCAmelCase    , [
                 value + tokenizer.fairseq_offset
                 for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
             ]    , )

         lowerCAmelCase__			:str											=							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>', '.']    , )






       @slow
       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Any											=							{'input_ids': [[2_5_0_0_0_4, 1_1_0_6_2, 8_2_7_7_2, 7, 1_5, 8_2_7_7_2, 5_3_8, 5_1_5_2_9, 2_3_7, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 2_1_5_1_7_5, 1_3_1_4, 1_3_6, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 5_6_3_5_9, 4_2, 1_2_2_0_0_9, 9, 1_6_4_6_6, 1_6, 8_7_3_4_4, 4_5_3_7, 9, 4_7_1_7, 7_8_3_8_1, 6, 1_5_9_9_5_8, 7, 1_5, 2_4_4_8_0, 6_1_8, 4, 5_2_7, 2_2_6_9_3, 5_4_2_8, 4, 2_7_7_7, 2_4_4_8_0, 9_8_7_4, 4, 4_3_5_2_3, 5_9_4, 4, 8_0_3, 1_8_3_9_2, 3_3_1_8_9, 1_8, 4, 4_3_5_2_3, 2_4_4_4_7, 1_2_3_9_9, 1_0_0, 2_4_9_5_5, 8_3_6_5_8, 9_6_2_6, 1_4_4_0_5_7, 1_5, 8_3_9, 2_2_3_3_5, 1_6, 1_3_6, 2_4_9_5_5, 8_3_6_5_8, 8_3_4_7_9, 1_5, 3_9_1_0_2, 7_2_4, 1_6, 6_7_8, 6_4_5, 2_7_8_9, 1_3_2_8, 4_5_8_9, 4_2, 1_2_2_0_0_9, 1_1_5_7_7_4, 2_3, 8_0_5, 1_3_2_8, 4_6_8_7_6, 7, 1_3_6, 5_3_8_9_4, 1_9_4_0, 4_2_2_2_7, 4_1_1_5_9, 1_7_7_2_1, 8_2_3, 4_2_5, 4, 2_7_5_1_2, 9_8_7_2_2, 2_0_6, 1_3_6, 5_5_3_1, 4_9_7_0, 9_1_9, 1_7_3_3_6, 5, 2], [2_5_0_0_0_4, 2_0_0_8_0, 6_1_8, 8_3, 8_2_7_7_5, 4_7, 4_7_9, 9, 1_5_1_7, 7_3, 5_3_8_9_4, 3_3_3, 8_0_5_8_1, 1_1_0_1_1_7, 1_8_8_1_1, 5_2_5_6, 1_2_9_5, 5_1, 1_5_2_5_2_6, 2_9_7, 7_9_8_6, 3_9_0, 1_2_4_4_1_6, 5_3_8, 3_5_4_3_1, 2_1_4, 9_8, 1_5_0_4_4, 2_5_7_3_7, 1_3_6, 7_1_0_8, 4_3_7_0_1, 2_3, 7_5_6, 1_3_5_3_5_5, 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], [2_5_0_0_0_4, 5_8_1, 6_3_7_7_3, 1_1_9_4_5_5, 6, 1_4_7_7_9_7, 8_8_2_0_3, 7, 6_4_5, 7_0, 2_1, 3_2_8_5, 1_0_2_6_9, 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=__UpperCAmelCase    , model_name='facebook/mbart-large-50'    , revision='d3913889c59cd5c9e456b269c376325eabad57e2'    , )






       def      snake_case						(    self      ):



         '''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

         lowerCAmelCase__			:Optional[Any]											=							(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__			:Union[str, Any]											=							self.rust_tokenizer_class.from_pretrained(__UpperCAmelCase    , **__UpperCAmelCase      )
             lowerCAmelCase__			:Optional[Any]											=							self.tokenizer_class.from_pretrained(__UpperCAmelCase    , **__UpperCAmelCase      )

             lowerCAmelCase__			:List[str]											=							tempfile.mkdtemp()

             lowerCAmelCase__			:int											=							tokenizer_r.save_pretrained(__UpperCAmelCase      )
             lowerCAmelCase__			:List[Any]											=							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      )      )
             lowerCAmelCase__			:List[Any]											=							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
             lowerCAmelCase__			:Any											=							tokenizer_r.from_pretrained(__UpperCAmelCase      )
             lowerCAmelCase__			:Optional[Any]											=							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
             lowerCAmelCase__			:Any											=							tempfile.mkdtemp()

             lowerCAmelCase__			:str											=							tokenizer_r.save_pretrained(__UpperCAmelCase    , legacy_format=__UpperCAmelCase      )
             lowerCAmelCase__			:List[Any]											=							tokenizer_p.save_pretrained(__UpperCAmelCase      )

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

             # Checks everything loads correctly in the same way
             lowerCAmelCase__			:int											=							tokenizer_r.from_pretrained(__UpperCAmelCase      )
             lowerCAmelCase__			:int											=							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
             lowerCAmelCase__			:str											=							tempfile.mkdtemp()

             lowerCAmelCase__			:str											=							tokenizer_r.save_pretrained(__UpperCAmelCase    , legacy_format=__UpperCAmelCase      )
             lowerCAmelCase__			:List[str]											=							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
             lowerCAmelCase__			:Optional[int]											=							tokenizer_r.from_pretrained(__UpperCAmelCase      )
             lowerCAmelCase__			:Optional[int]											=							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 					_lowerCAmelCase   (     unittest.TestCase       ):
       """simple docstring"""




       __magic_name__     :List[str]		  =					"""facebook/mbart-large-50-one-to-many-mmt"""
       __magic_name__     :Dict		  =					[
           """ 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.""",
       ]
       __magic_name__     :str		  =					[
           """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.""",
       ]
       __magic_name__     :Union[str, Any]		  =					[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      snake_case						(    cls      ):



         '''simple docstring'''

         lowerCAmelCase__			:MBartaaTokenizer											=							MBartaaTokenizer.from_pretrained(
             cls.checkpoint_name    , src_lang='en_XX'    , tgt_lang='ro_RO'      )
         lowerCAmelCase__			:List[Any]											=							1
         return cls






       def      snake_case						(    self      ):



         '''simple docstring'''

         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']    , 2_5_0_0_0_1      )
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']    , 2_5_0_0_0_4      )
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']    , 2_5_0_0_2_0      )
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['mr_IN']    , 2_5_0_0_3_8      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Optional[int]											=							self.tokenizer.batch_encode_plus(self.src_text      ).input_ids[0]
         self.assertListEqual(self.expected_src_tokens    , __UpperCAmelCase      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         self.assertIn(__UpperCAmelCase    , self.tokenizer.all_special_ids      )
         lowerCAmelCase__			:Dict											=							[RO_CODE, 8_8_4, 9_0_1_9, 9_6, 9, 9_1_6, 8_6_7_9_2, 3_6, 1_8_7_4_3, 1_5_5_9_6, 5, 2]
         lowerCAmelCase__			:str											=							self.tokenizer.decode(__UpperCAmelCase    , skip_special_tokens=__UpperCAmelCase      )
         lowerCAmelCase__			:Dict											=							self.tokenizer.decode(generated_ids[1:]    , skip_special_tokens=__UpperCAmelCase      )
         self.assertEqual(__UpperCAmelCase    , __UpperCAmelCase      )
         self.assertNotIn(self.tokenizer.eos_token    , __UpperCAmelCase      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:str											=							['this is gunna be a long sentence ' * 2_0]
         assert isinstance(src_text[0]    , __UpperCAmelCase      )
         lowerCAmelCase__			:Dict											=							1_0
         lowerCAmelCase__			:List[str]											=							self.tokenizer(__UpperCAmelCase    , max_length=__UpperCAmelCase    , truncation=__UpperCAmelCase      ).input_ids[0]
         self.assertEqual(ids[0]    , __UpperCAmelCase      )
         self.assertEqual(ids[-1]    , 2      )
         self.assertEqual(len(__UpperCAmelCase      )    , __UpperCAmelCase      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']      )    , [2_5_0_0_5_3, 2_5_0_0_0_1]      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Optional[int]											=							tempfile.mkdtemp()
         lowerCAmelCase__			:List[str]											=							self.tokenizer.fairseq_tokens_to_ids
         self.tokenizer.save_pretrained(__UpperCAmelCase      )
         lowerCAmelCase__			:Optional[int]											=							MBartaaTokenizer.from_pretrained(__UpperCAmelCase      )
         self.assertDictEqual(new_tok.fairseq_tokens_to_ids    , __UpperCAmelCase      )






       @require_torch
       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:List[str]											=							self.tokenizer(self.src_text    , text_target=self.tgt_text    , padding=__UpperCAmelCase    , return_tensors='pt'      )
         lowerCAmelCase__			:Dict											=							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      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Any											=							self.tokenizer(
             self.src_text    , text_target=self.tgt_text    , padding=__UpperCAmelCase    , truncation=__UpperCAmelCase    , max_length=len(self.expected_src_tokens      )    , return_tensors='pt'    , )
         lowerCAmelCase__			:List[Any]											=							shift_tokens_right(batch['labels']    , self.tokenizer.pad_token_id      )

         self.assertIsInstance(__UpperCAmelCase    , __UpperCAmelCase      )

         self.assertEqual((2, 1_4)    , batch.input_ids.shape      )
         self.assertEqual((2, 1_4)    , batch.attention_mask.shape      )
         lowerCAmelCase__			:Dict											=							batch.input_ids.tolist()[0]
         self.assertListEqual(self.expected_src_tokens    , __UpperCAmelCase      )
         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      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Any											=							self.tokenizer(self.src_text    , padding=__UpperCAmelCase    , truncation=__UpperCAmelCase    , max_length=3    , return_tensors='pt'      )
         lowerCAmelCase__			:Optional[Any]											=							self.tokenizer(
             text_target=self.tgt_text    , padding=__UpperCAmelCase    , truncation=__UpperCAmelCase    , max_length=1_0    , return_tensors='pt'      )
         lowerCAmelCase__			:str											=							targets['input_ids']
         lowerCAmelCase__			:Union[str, Any]											=							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]    , 1_0      )






       @require_torch
       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Dict											=							self.tokenizer._build_translation_inputs(
             'A test'    , return_tensors='pt'    , src_lang='en_XX'    , tgt_lang='ar_AR'      )

         self.assertEqual(
             nested_simplify(__UpperCAmelCase      )    , {
                 # en_XX, A, test, EOS
                 'input_ids': [[2_5_0_0_0_4, 6_2, 3_0_3_4, 2]],
                 'attention_mask': [[1, 1, 1, 1]],
                 # ar_AR
                 'forced_bos_token_id': 2_5_0_0_0_1,
             }    , )







"""simple docstring"""





import tempfile
import unittest

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
    is_torch_available,
    require_optimum,
    require_torch,
    slow,
)


if is_torch_available():
  import torch






@require_torch
@require_optimum
@slow
class 					_lowerCAmelCase   (     unittest.TestCase       ):
       """simple docstring"""




       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:Optional[Any]											=							'hf-internal-testing/tiny-random-t5'
         lowerCAmelCase__			:List[Any]											=							AutoTokenizer.from_pretrained(__UpperCAmelCase      )
         lowerCAmelCase__			:str											=							AutoModelForSeqaSeqLM.from_pretrained(__UpperCAmelCase      )

         lowerCAmelCase__			:Any											=							tokenizer('This is me'    , return_tensors='pt'      )

         lowerCAmelCase__			:Dict											=							model.to_bettertransformer()

         self.assertTrue(any('BetterTransformer' in mod.__class__.__name__ for _, mod in model.named_modules()      )      )

         lowerCAmelCase__			:Optional[Any]											=							model.generate(**__UpperCAmelCase      )

         lowerCAmelCase__			:List[Any]											=							model.reverse_bettertransformer()

         self.assertFalse(any('BetterTransformer' in mod.__class__.__name__ for _, mod in model.named_modules()      )      )

         with tempfile.TemporaryDirectory() as tmpdirname:
           model.save_pretrained(__UpperCAmelCase      )

           lowerCAmelCase__			:Any											=							AutoModelForSeqaSeqLM.from_pretrained(__UpperCAmelCase      )

           self.assertFalse(
               any('BetterTransformer' in mod.__class__.__name__ for _, mod in model_reloaded.named_modules()      )      )

           lowerCAmelCase__			:Union[str, Any]											=							model_reloaded.generate(**__UpperCAmelCase      )
           self.assertTrue(torch.allclose(__UpperCAmelCase    , __UpperCAmelCase      )      )






       def      snake_case						(    self      ):



         '''simple docstring'''

         lowerCAmelCase__			:int											=							'hf-internal-testing/tiny-random-t5'
         lowerCAmelCase__			:Union[str, Any]											=							AutoModelForSeqaSeqLM.from_pretrained(__UpperCAmelCase      )

         lowerCAmelCase__			:str											=							model.to_bettertransformer()

         with tempfile.TemporaryDirectory() as tmpdirname:
           with self.assertRaises(__UpperCAmelCase      ):
             model.save_pretrained(__UpperCAmelCase      )

           lowerCAmelCase__			:Optional[int]											=							model.reverse_bettertransformer()
           model.save_pretrained(__UpperCAmelCase      )
