





"""simple docstring"""




from collections import defaultdict
from pathlib import Path

import pandas as pd
from rouge_cli import calculate_rouge_path

from utils import calculate_rouge


__UpperCAmelCase	:       Any    	=							[
    'Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of the'
    ' final seconds on board Flight 9525. The Germanwings co-pilot says he had a "previous episode of severe'
    ' depression\" German airline confirms it knew of Andreas Lubitz\'s depression years before he took control.',
    'The Palestinian Authority officially becomes the 123rd member of the International Criminal Court. The formal'
    ' accession was marked with a ceremony at The Hague, in the Netherlands. The Palestinians signed the ICC\'s'
    ' founding Rome Statute in January. Israel and the United States opposed the Palestinians\' efforts to join the'
    ' body.',
    'Amnesty International releases its annual report on the death penalty. The report catalogs the use of'
    ' state-sanctioned killing as a punitive measure across the globe. At least 607 people were executed around the'
    ' world in 2014, compared to 778 in 2013. The U.S. remains one of the worst offenders for imposing capital'
    ' punishment.',
]

__UpperCAmelCase	:       int    	=							[
    'Marseille prosecutor says "so far no videos were used in the crash investigation" despite media reports .'
    ' Journalists at Bild and Paris Match are "very confident" the video clip is real, an editor says . Andreas Lubitz'
    ' had informed his Lufthansa training school of an episode of severe depression, airline says .',
    'Membership gives the ICC jurisdiction over alleged crimes committed in Palestinian territories since last June .'
    ' Israel and the United States opposed the move, which could open the door to war crimes investigations against'
    ' Israelis .',
    'Amnesty\'s annual death penalty report catalogs encouraging signs, but setbacks in numbers of those sentenced to'
    ' death . Organization claims that governments around the world are using the threat of terrorism to advance'
    ' executions . The number of executions worldwide has gone down by almost 22% compared with 2013, but death'
    ' sentences up by 28% .',
]







def       A__							(   )       ->   Tuple:
  __snake_case:						Any			  =						calculate_rouge(UpperCamelCase__ , UpperCamelCase__ , bootstrap_aggregation=UpperCamelCase__ , rouge_keys=["""rouge2""", """rougeL"""])
  assert isinstance(UpperCamelCase__ , UpperCamelCase__)
  __snake_case:						Dict			  =						calculate_rouge(UpperCamelCase__ , UpperCamelCase__ , bootstrap_aggregation=UpperCamelCase__ , rouge_keys=["""rouge2"""])
  assert (
      pd.DataFrame(no_aggregation["""rouge2"""]).fmeasure.mean()
      == pd.DataFrame(no_aggregation_just_ra["""rouge2"""]).fmeasure.mean()
  )







def       A__							(   )       ->   Any:
  __snake_case:						Dict			  =						'''rougeLsum'''
  __snake_case:						Union[str, Any]			  =						calculate_rouge(UpperCamelCase__ , UpperCamelCase__ , newline_sep=UpperCamelCase__ , rouge_keys=[k])[k]
  __snake_case:						Tuple			  =						calculate_rouge(UpperCamelCase__ , UpperCamelCase__ , newline_sep=UpperCamelCase__ , rouge_keys=[k])[k]
  assert score > score_no_sep







def       A__							(   )       ->   int:
  __snake_case:						str			  =						['''rouge1''', '''rouge2''', '''rougeL''']
  __snake_case:						List[Any]			  =						calculate_rouge(UpperCamelCase__ , UpperCamelCase__ , newline_sep=UpperCamelCase__ , rouge_keys=UpperCamelCase__)
  __snake_case:						Tuple			  =						calculate_rouge(UpperCamelCase__ , UpperCamelCase__ , newline_sep=UpperCamelCase__ , rouge_keys=UpperCamelCase__)
  assert score_sep == score_no_sep







def       A__							(   )       ->   int:
  __snake_case:						Union[str, Any]			  =						[
      '''Her older sister, Margot Frank, died in 1945, a month earlier than previously thought.''',
      '''Marseille prosecutor says "so far no videos were used in the crash investigation" despite media reports .''',
  ]
  __snake_case:						str			  =						[
      '''Margot Frank, died in 1945, a month earlier than previously thought.''',
      '''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of'''
      ''' the final seconds on board Flight 9525.''',
  ]
  assert calculate_rouge(UpperCamelCase__ , UpperCamelCase__ , newline_sep=UpperCamelCase__) == calculate_rouge(UpperCamelCase__ , UpperCamelCase__ , newline_sep=UpperCamelCase__)







def       A__							(   )       ->   Union[str, Any]:
  __snake_case:						Optional[int]			  =						[
      '''" "a person who has such a video needs to immediately give it to the investigators," prosecutor says .<n> "it is a very disturbing scene," editor-in-chief of bild online tells "erin burnett: outfront" '''
  ]
  __snake_case:						Any			  =						[
      ''' Marseille prosecutor says "so far no videos were used in the crash investigation" despite media reports . Journalists at Bild and Paris Match are "very confident" the video clip is real, an editor says . Andreas Lubitz had informed his Lufthansa training school of an episode of severe depression, airline says .'''
  ]

  __snake_case:						str			  =						calculate_rouge(UpperCamelCase__ , UpperCamelCase__ , rouge_keys=["""rougeLsum"""] , newline_sep=UpperCamelCase__)['''rougeLsum''']
  __snake_case:						str			  =						calculate_rouge(UpperCamelCase__ , UpperCamelCase__ , rouge_keys=["""rougeLsum"""])['''rougeLsum''']
  assert new_score > prev_score







def       A__							(   )       ->   int:
  __snake_case:						Optional[Any]			  =						Path("""examples/seq2seq/test_data/wmt_en_ro""")
  __snake_case:						Optional[int]			  =						calculate_rouge_path(data_dir.joinpath("""test.source""") , data_dir.joinpath("""test.target"""))
  assert isinstance(UpperCamelCase__ , UpperCamelCase__)
  __snake_case:						Optional[Any]			  =						calculate_rouge_path(
      data_dir.joinpath("""test.source""") , data_dir.joinpath("""test.target""") , bootstrap_aggregation=UpperCamelCase__)
  assert isinstance(UpperCamelCase__ , UpperCamelCase__)













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	:       str    	=							get_tests_dir("fixtures/test_sentencepiece.model")

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

__UpperCAmelCase	:       Any    	=							250_004
__UpperCAmelCase	:       List[str]    	=							250_020







@require_sentencepiece
@require_tokenizers
class    __snake_case	(							__lowerCamelCase       ,      unittest.TestCase      ):





       '''simple docstring'''







       lowerCAmelCase__						=					MBartaaTokenizer
       lowerCAmelCase__						=					MBartaaTokenizerFast
       lowerCAmelCase__						=					True
       lowerCAmelCase__						=					True




       def 							UpperCAmelCase__			(  self			:   Tuple		):
         super().setUp()

         # We have a SentencePiece fixture for testing
         __snake_case:						Optional[int]			  =						MBartaaTokenizer(A							,    src_lang="""en_XX"""							,    tgt_lang="""ro_RO"""							,    keep_accents=A		)
         tokenizer.save_pretrained(self.tmpdirname		)




       def 							UpperCAmelCase__			(  self			:   Union[str, Any]		):
         __snake_case:						Any			  =						"""<s>"""
         __snake_case:						Tuple			  =						0

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




       def 							UpperCAmelCase__			(  self			:   Any		):
         __snake_case:						Dict			  =						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(A		)							,    1_054		)




       def 							UpperCAmelCase__			(  self			:   Any		):
         self.assertEqual(self.get_tokenizer().vocab_size							,    1_054		)




       def 							UpperCAmelCase__			(  self			:   Union[str, Any]		):
         __snake_case:						Dict			  =						MBartaaTokenizer(A							,    src_lang="""en_XX"""							,    tgt_lang="""ro_RO"""							,    keep_accents=A		)

         __snake_case:						int			  =						tokenizer.tokenize("""This is a test"""		)
         self.assertListEqual(A							,    ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]		)

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

         __snake_case:						Union[str, Any]			  =						tokenizer.tokenize("""I was born in 92000, and this is falsé."""		)
         self.assertListEqual(
             A							,    [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""", """."""]							,    )
         __snake_case:						List[Any]			  =						tokenizer.convert_tokens_to_ids(A		)
         self.assertListEqual(
             A							,    [
                 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]
             ]							,    )

         __snake_case:						int			  =						tokenizer.convert_ids_to_tokens(A		)
         self.assertListEqual(
             A							,    [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[int]		):
         # fmt: off
         __snake_case:						List[str]			  =						{"""input_ids""": [[250_004, 11_062, 82_772, 7, 15, 82_772, 538, 51_529, 237, 17_198, 1_290, 206, 9, 215_175, 1_314, 136, 17_198, 1_290, 206, 9, 56_359, 42, 122_009, 9, 16_466, 16, 87_344, 4_537, 9, 4_717, 78_381, 6, 159_958, 7, 15, 24_480, 618, 4, 527, 22_693, 5_428, 4, 2_777, 24_480, 9_874, 4, 43_523, 594, 4, 803, 18_392, 33_189, 18, 4, 43_523, 24_447, 12_399, 100, 24_955, 83_658, 9_626, 144_057, 15, 839, 22_335, 16, 136, 24_955, 83_658, 83_479, 15, 39_102, 724, 16, 678, 645, 2_789, 1_328, 4_589, 42, 122_009, 115_774, 23, 805, 1_328, 46_876, 7, 136, 53_894, 1_940, 42_227, 41_159, 17_721, 823, 425, 4, 27_512, 98_722, 206, 136, 5_531, 4_970, 919, 17_336, 5, 2], [250_004, 20_080, 618, 83, 82_775, 47, 479, 9, 1_517, 73, 53_894, 333, 80_581, 110_117, 18_811, 5_256, 1_295, 51, 152_526, 297, 7_986, 390, 124_416, 538, 35_431, 214, 98, 15_044, 25_737, 136, 7_108, 43_701, 23, 756, 135_355, 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], [250_004, 581, 63_773, 119_455, 6, 147_797, 88_203, 7, 645, 70, 21, 3_285, 10_269, 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=A							,    model_name="""facebook/mbart-large-50"""							,    revision="""d3913889c59cd5c9e456b269c376325eabad57e2"""							,    )






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

         __snake_case:						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})'''		):
             __snake_case:						Optional[int]			  =						self.rust_tokenizer_class.from_pretrained(A							,    **A		)
             __snake_case:						Union[str, Any]			  =						self.tokenizer_class.from_pretrained(A							,    **A		)

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

             __snake_case:						Tuple			  =						tokenizer_r.save_pretrained(A		)
             __snake_case:						Optional[int]			  =						tokenizer_p.save_pretrained(A		)

             # 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		)		)
             __snake_case:						Dict			  =						tuple(f for f in tokenizer_r_files if """tokenizer.json""" not in f		)
             self.assertSequenceEqual(A							,    A		)

             # Checks everything loads correctly in the same way
             __snake_case:						Tuple			  =						tokenizer_r.from_pretrained(A		)
             __snake_case:						Optional[Any]			  =						tokenizer_p.from_pretrained(A		)

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

             shutil.rmtree(A		)

             # Save tokenizer rust, legacy_format=True
             __snake_case:						Tuple			  =						tempfile.mkdtemp()

             __snake_case:						Any			  =						tokenizer_r.save_pretrained(A							,    legacy_format=A		)
             __snake_case:						List[str]			  =						tokenizer_p.save_pretrained(A		)

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

             # Checks everything loads correctly in the same way
             __snake_case:						List[Any]			  =						tokenizer_r.from_pretrained(A		)
             __snake_case:						Dict			  =						tokenizer_p.from_pretrained(A		)

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

             shutil.rmtree(A		)

             # Save tokenizer rust, legacy_format=False
             __snake_case:						List[str]			  =						tempfile.mkdtemp()

             __snake_case:						Any			  =						tokenizer_r.save_pretrained(A							,    legacy_format=A		)
             __snake_case:						Dict			  =						tokenizer_p.save_pretrained(A		)

             # 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
             __snake_case:						Any			  =						tokenizer_r.from_pretrained(A		)
             __snake_case:						Any			  =						tokenizer_p.from_pretrained(A		)

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

             shutil.rmtree(A		)







@require_torch
@require_sentencepiece
@require_tokenizers
class    __snake_case	(							unittest.TestCase      ):





       '''simple docstring'''







       lowerCAmelCase__						=					"""facebook/mbart-large-50-one-to-many-mmt"""
       lowerCAmelCase__						=					[
           """ 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.""",
       ]
       lowerCAmelCase__						=					[
           """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.""",
       ]
       lowerCAmelCase__						=					[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			:   int		):
         __snake_case:						MBartaaTokenizer			  =						MBartaaTokenizer.from_pretrained(
             cls.checkpoint_name							,    src_lang="""en_XX"""							,    tgt_lang="""ro_RO"""		)
         __snake_case:						str			  =						1
         return cls




       def 							UpperCAmelCase__			(  self			:   Any		):
         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		)
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""mr_IN"""]							,    250_038		)




       def 							UpperCAmelCase__			(  self			:   Optional[int]		):
         __snake_case:						List[str]			  =						self.tokenizer.batch_encode_plus(self.src_text		).input_ids[0]
         self.assertListEqual(self.expected_src_tokens							,    A		)




       def 							UpperCAmelCase__			(  self			:   Union[str, Any]		):
         self.assertIn(A							,    self.tokenizer.all_special_ids		)
         __snake_case:						Dict			  =						[RO_CODE, 884, 9_019, 96, 9, 916, 86_792, 36, 18_743, 15_596, 5, 2]
         __snake_case:						str			  =						self.tokenizer.decode(A							,    skip_special_tokens=A		)
         __snake_case:						Union[str, Any]			  =						self.tokenizer.decode(generated_ids[1:]							,    skip_special_tokens=A		)
         self.assertEqual(A							,    A		)
         self.assertNotIn(self.tokenizer.eos_token							,    A		)




       def 							UpperCAmelCase__			(  self			:   Dict		):
         __snake_case:						List[str]			  =						["""this is gunna be a long sentence """ * 20]
         assert isinstance(src_text[0]							,    A		)
         __snake_case:						Union[str, Any]			  =						10
         __snake_case:						List[Any]			  =						self.tokenizer(A							,    max_length=A							,    truncation=A		).input_ids[0]
         self.assertEqual(ids[0]							,    A		)
         self.assertEqual(ids[-1]							,    2		)
         self.assertEqual(len(A		)							,    A		)




       def 							UpperCAmelCase__			(  self			:   Tuple		):
         self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]		)							,    [250_053, 250_001]		)




       def 							UpperCAmelCase__			(  self			:   List[Any]		):
         __snake_case:						List[Any]			  =						tempfile.mkdtemp()
         __snake_case:						Any			  =						self.tokenizer.fairseq_tokens_to_ids
         self.tokenizer.save_pretrained(A		)
         __snake_case:						Union[str, Any]			  =						MBartaaTokenizer.from_pretrained(A		)
         self.assertDictEqual(new_tok.fairseq_tokens_to_ids							,    A		)




       @require_torch
       def 							UpperCAmelCase__			(  self			:   Optional[int]		):
         __snake_case:						List[str]			  =						self.tokenizer(self.src_text							,    text_target=self.tgt_text							,    padding=A							,    return_tensors="""pt"""		)
         __snake_case:						List[Any]			  =						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			:   Optional[int]		):
         __snake_case:						int			  =						self.tokenizer(
             self.src_text							,    text_target=self.tgt_text							,    padding=A							,    truncation=A							,    max_length=len(self.expected_src_tokens		)							,    return_tensors="""pt"""							,    )
         __snake_case:						Optional[Any]			  =						shift_tokens_right(batch["""labels"""]							,    self.tokenizer.pad_token_id		)

         self.assertIsInstance(A							,    A		)

         self.assertEqual((2, 14)							,    batch.input_ids.shape		)
         self.assertEqual((2, 14)							,    batch.attention_mask.shape		)
         __snake_case:						List[str]			  =						batch.input_ids.tolist()[0]
         self.assertListEqual(self.expected_src_tokens							,    A		)
         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			:   str		):
         __snake_case:						List[Any]			  =						self.tokenizer(self.src_text							,    padding=A							,    truncation=A							,    max_length=3							,    return_tensors="""pt"""		)
         __snake_case:						Union[str, Any]			  =						self.tokenizer(
             text_target=self.tgt_text							,    padding=A							,    truncation=A							,    max_length=10							,    return_tensors="""pt"""		)
         __snake_case:						Dict			  =						targets["""input_ids"""]
         __snake_case:						Any			  =						shift_tokens_right(A							,    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			:   Union[str, Any]		):
         __snake_case:						int			  =						self.tokenizer._build_translation_inputs(
             """A test"""							,    return_tensors="""pt"""							,    src_lang="""en_XX"""							,    tgt_lang="""ar_AR"""		)

         self.assertEqual(
             nested_simplify(A		)							,    {
                 # en_XX, A, test, EOS
                 """input_ids""": [[250_004, 62, 3_034, 2]],
                 """attention_mask""": [[1, 1, 1, 1]],
                 # ar_AR
                 """forced_bos_token_id""": 250_001,
             }							,    )






