





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


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

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

UpperCAmelCase_           =	25_00_04
UpperCAmelCase_           =	25_00_20




@require_sentencepiece
@require_tokenizers
class 			__UpperCamelCase    (							A__	, unittest.TestCase    ):
     __A	:  Union[str, Any]							  =   MBartaaTokenizer
     __A	:  Any							  =   MBartaaTokenizerFast
     __A	:  Dict							  =   True
     __A	:  Any							  =   True





     def 		UpperCamelCase(     self					):
        super().setUp()

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





     def 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   '''<s>'''
        _UpperCAmelCase           =   0

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





     def 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   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					)				,							1054					)





     def 		UpperCamelCase(     self					):
        self.assertEqual(self.get_tokenizer().vocab_size				,							1054					)





     def 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   MBartaaTokenizer(_UpperCamelCase				,							src_lang='''en_XX'''				,							tgt_lang='''ro_RO'''				,							keep_accents=_UpperCamelCase					)

        _UpperCAmelCase           =   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]]				,							)

        _UpperCAmelCase           =   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''', '''.''']				,							)
        _UpperCAmelCase           =   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]
            ]				,							)

        _UpperCAmelCase           =   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 		UpperCamelCase(     self					):
        # fmt: off
        _UpperCAmelCase           =   {'''input_ids''': [[250004, 11062, 82772, 7, 15, 82772, 538, 51529, 237, 17198, 1290, 206, 9, 215175, 1314, 136, 17198, 1290, 206, 9, 56359, 42, 122009, 9, 16466, 16, 87344, 4537, 9, 4717, 78381, 6, 159958, 7, 15, 24480, 618, 4, 527, 22693, 5428, 4, 2777, 24480, 9874, 4, 43523, 594, 4, 803, 18392, 33189, 18, 4, 43523, 24447, 12399, 100, 24955, 83658, 9626, 144057, 15, 839, 22335, 16, 136, 24955, 83658, 83479, 15, 39102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 122009, 115774, 23, 805, 1328, 46876, 7, 136, 53894, 1940, 42227, 41159, 17721, 823, 425, 4, 27512, 98722, 206, 136, 5531, 4970, 919, 17336, 5, 2], [250004, 20080, 618, 83, 82775, 47, 479, 9, 1517, 73, 53894, 333, 80581, 110117, 18811, 5256, 1295, 51, 152526, 297, 7986, 390, 124416, 538, 35431, 214, 98, 15044, 25737, 136, 7108, 43701, 23, 756, 135355, 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], [250004, 581, 63773, 119455, 6, 147797, 88203, 7, 645, 70, 21, 3285, 10269, 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 		UpperCamelCase(     self					):
        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

        _UpperCAmelCase           =   (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})'''					):
              _UpperCAmelCase           =   self.rust_tokenizer_class.from_pretrained(_UpperCamelCase				,							**_UpperCamelCase					)
              _UpperCAmelCase           =   self.tokenizer_class.from_pretrained(_UpperCamelCase				,							**_UpperCamelCase					)

              _UpperCAmelCase           =   tempfile.mkdtemp()

              _UpperCAmelCase           =   tokenizer_r.save_pretrained(_UpperCamelCase					)
              _UpperCAmelCase           =   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					)					)
              _UpperCAmelCase           =   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
              _UpperCAmelCase           =   tokenizer_r.from_pretrained(_UpperCamelCase					)
              _UpperCAmelCase           =   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
              _UpperCAmelCase           =   tempfile.mkdtemp()

              _UpperCAmelCase           =   tokenizer_r.save_pretrained(_UpperCamelCase				,							legacy_format=_UpperCamelCase					)
              _UpperCAmelCase           =   tokenizer_p.save_pretrained(_UpperCamelCase					)

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

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

              _UpperCAmelCase           =   tokenizer_r.save_pretrained(_UpperCamelCase				,							legacy_format=_UpperCamelCase					)
              _UpperCAmelCase           =   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
              _UpperCAmelCase           =   tokenizer_r.from_pretrained(_UpperCamelCase					)
              _UpperCAmelCase           =   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 			__UpperCamelCase    (							unittest.TestCase    ):
     __A	:  Dict							  =   """facebook/mbart-large-50-one-to-many-mmt"""
     __A	:  Optional[int]							  =   [
         """ 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	:  Optional[int]							  =   [
         """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, 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]





     @classmethod
     def 		UpperCamelCase(     cls					):
        _UpperCAmelCase           =   MBartaaTokenizer.from_pretrained(
            cls.checkpoint_name				,							src_lang='''en_XX'''				,							tgt_lang='''ro_RO'''					)
        _UpperCAmelCase           =   1
        return cls





     def 		UpperCamelCase(     self					):
        self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''ar_AR''']				,							250001					)
        self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''en_EN''']				,							250004					)
        self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''ro_RO''']				,							250020					)
        self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''mr_IN''']				,							250038					)





     def 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   self.tokenizer.batch_encode_plus(self.src_text					).input_ids[0]
        self.assertListEqual(self.expected_src_tokens				,							_UpperCamelCase					)





     def 		UpperCamelCase(     self					):
        self.assertIn(_UpperCamelCase				,							self.tokenizer.all_special_ids					)
        _UpperCAmelCase           =   [RO_CODE, 884, 9019, 96, 9, 916, 86792, 36, 18743, 15596, 5, 2]
        _UpperCAmelCase           =   self.tokenizer.decode(_UpperCamelCase				,							skip_special_tokens=_UpperCamelCase					)
        _UpperCAmelCase           =   self.tokenizer.decode(generated_ids[1:]				,							skip_special_tokens=_UpperCamelCase					)
        self.assertEqual(_UpperCamelCase				,							_UpperCamelCase					)
        self.assertNotIn(self.tokenizer.eos_token				,							_UpperCamelCase					)





     def 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   ['''this is gunna be a long sentence ''' * 20]
        assert isinstance(src_text[0]				,							_UpperCamelCase					)
        _UpperCAmelCase           =   10
        _UpperCAmelCase           =   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 		UpperCamelCase(     self					):
        self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['''<mask>''', '''ar_AR''']					)				,							[250053, 250001]					)





     def 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   tempfile.mkdtemp()
        _UpperCAmelCase           =   self.tokenizer.fairseq_tokens_to_ids
        self.tokenizer.save_pretrained(_UpperCamelCase					)
        _UpperCAmelCase           =   MBartaaTokenizer.from_pretrained(_UpperCamelCase					)
        self.assertDictEqual(new_tok.fairseq_tokens_to_ids				,							_UpperCamelCase					)





     @require_torch
     def 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   self.tokenizer(self.src_text				,							text_target=self.tgt_text				,							padding=_UpperCamelCase				,							return_tensors='''pt'''					)
        _UpperCAmelCase           =   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					):
        _UpperCAmelCase           =   self.tokenizer(
            self.src_text				,							text_target=self.tgt_text				,							padding=_UpperCamelCase				,							truncation=_UpperCamelCase				,							max_length=len(self.expected_src_tokens					)				,							return_tensors='''pt'''				,							)
        _UpperCAmelCase           =   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					)
        _UpperCAmelCase           =   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 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   self.tokenizer(self.src_text				,							padding=_UpperCamelCase				,							truncation=_UpperCamelCase				,							max_length=3				,							return_tensors='''pt'''					)
        _UpperCAmelCase           =   self.tokenizer(
            text_target=self.tgt_text				,							padding=_UpperCamelCase				,							truncation=_UpperCamelCase				,							max_length=10				,							return_tensors='''pt'''					)
        _UpperCAmelCase           =   targets['''input_ids''']
        _UpperCAmelCase           =   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 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   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''': [[250004, 62, 3034, 2]],
                '''attention_mask''': [[1, 1, 1, 1]],
                # ar_AR
                '''forced_bos_token_id''': 250001,
            }				,							)
"""simple docstring"""






# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool





class 					_A		(			lowerCAmelCase      ):
      snake_case__     :  List[Any]				    =      'philschmid/bart-large-cnn-samsum'
      snake_case__     :  int				    =      (
          'This is a tool that summarizes an English text. It takes an input `text` containing the text to summarize, '
          'and returns a summary of the text.'
      )
      snake_case__     :  Tuple				    =      'summarizer'
      snake_case__     :  int				    =      AutoTokenizer
      snake_case__     :  Any				    =      AutoModelForSeqaSeqLM

      snake_case__     :  Optional[int]				    =      ['text']
      snake_case__     :  Optional[int]				    =      ['text']

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            return self.pre_processor(__lowerCAmelCase						,			return_tensors="""pt"""						,			truncation=__lowerCAmelCase		)

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            return self.model.generate(**__lowerCAmelCase		)[0]







      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            return self.pre_processor.decode(__lowerCAmelCase						,			skip_special_tokens=__lowerCAmelCase						,			clean_up_tokenization_spaces=__lowerCAmelCase		)



