






'''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


SCREAMING_SNAKE_CASE__     =       get_tests_dir('fixtures/test_sentencepiece.model')

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

SCREAMING_SNAKE_CASE__     =       2_5_0_0_0_4
SCREAMING_SNAKE_CASE__     =       2_5_0_0_2_0






@require_sentencepiece
@require_tokenizers
class     a_						(      lowerCamelCase     ,	unittest.TestCase    ):
     lowercase							=				MBartaaTokenizer
     lowercase							=				MBartaaTokenizerFast
     lowercase							=				True
     lowercase							=				True

     def   A__						(				self				)  ->				str:



           """simple docstring"""






           super().setUp()

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

     def   A__						(				self				)  ->				List[Any]:



           """simple docstring"""






           UpperCamelCase      = """<s>"""
           UpperCamelCase      = 0

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

     def   A__						(				self				)  ->				Optional[Any]:



           """simple docstring"""






           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(_SCREAMING_SNAKE_CASE				)      ,		1054				)

     def   A__						(				self				)  ->				List[Any]:



           """simple docstring"""






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

     def   A__						(				self				)  ->				Optional[int]:



           """simple docstring"""






           UpperCamelCase      = MBartaaTokenizer(_SCREAMING_SNAKE_CASE      ,		src_lang="""en_XX"""      ,		tgt_lang="""ro_RO"""      ,		keep_accents=_SCREAMING_SNAKE_CASE				)

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

           self.assertListEqual(
               tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE				)      ,		[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(
               _SCREAMING_SNAKE_CASE      ,		[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(_SCREAMING_SNAKE_CASE				)
           self.assertListEqual(
               _SCREAMING_SNAKE_CASE      ,		[
                   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(_SCREAMING_SNAKE_CASE				)
           self.assertListEqual(
               _SCREAMING_SNAKE_CASE      ,		[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   A__						(				self				)  ->				Union[str, Any]:



           """simple docstring"""






           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=_SCREAMING_SNAKE_CASE      ,		model_name="""facebook/mbart-large-50"""      ,		revision="""d3913889c59cd5c9e456b269c376325eabad57e2"""      ,		)


     def   A__						(				self				)  ->				int:



           """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

           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(_SCREAMING_SNAKE_CASE      ,		**_SCREAMING_SNAKE_CASE				)
                       UpperCamelCase      = self.tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE      ,		**_SCREAMING_SNAKE_CASE				)

                       UpperCamelCase      = tempfile.mkdtemp()

                       UpperCamelCase      = tokenizer_r.save_pretrained(_SCREAMING_SNAKE_CASE				)
                       UpperCamelCase      = tokenizer_p.save_pretrained(_SCREAMING_SNAKE_CASE				)

                       # 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(_SCREAMING_SNAKE_CASE      ,		_SCREAMING_SNAKE_CASE				)

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

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

                       shutil.rmtree(_SCREAMING_SNAKE_CASE				)

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

                       UpperCamelCase      = tokenizer_r.save_pretrained(_SCREAMING_SNAKE_CASE      ,		legacy_format=_SCREAMING_SNAKE_CASE				)
                       UpperCamelCase      = tokenizer_p.save_pretrained(_SCREAMING_SNAKE_CASE				)

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

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

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

                       shutil.rmtree(_SCREAMING_SNAKE_CASE				)

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

                       UpperCamelCase      = tokenizer_r.save_pretrained(_SCREAMING_SNAKE_CASE      ,		legacy_format=_SCREAMING_SNAKE_CASE				)
                       UpperCamelCase      = tokenizer_p.save_pretrained(_SCREAMING_SNAKE_CASE				)

                       # 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(_SCREAMING_SNAKE_CASE				)
                       UpperCamelCase      = tokenizer_p.from_pretrained(_SCREAMING_SNAKE_CASE				)

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

                       shutil.rmtree(_SCREAMING_SNAKE_CASE				)






@require_torch
@require_sentencepiece
@require_tokenizers
class     a_						(      unittest.TestCase    ):
     lowercase							=				"""facebook/mbart-large-50-one-to-many-mmt"""
     lowercase							=				[
         """ 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.""",
     ]
     lowercase							=				[
         """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.""",
     ]
     lowercase							=				[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   A__						(				cls				)  ->				Union[str, Any]:



           """simple docstring"""






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

     def   A__						(				self				)  ->				str:



           """simple docstring"""






           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   A__						(				self				)  ->				Union[str, Any]:



           """simple docstring"""






           UpperCamelCase      = self.tokenizer.batch_encode_plus(self.src_text				).input_ids[0]
           self.assertListEqual(self.expected_src_tokens      ,		_SCREAMING_SNAKE_CASE				)

     def   A__						(				self				)  ->				List[Any]:



           """simple docstring"""






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

     def   A__						(				self				)  ->				List[Any]:



           """simple docstring"""






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

     def   A__						(				self				)  ->				Union[str, Any]:



           """simple docstring"""






           self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]				)      ,		[250053, 250001]				)

     def   A__						(				self				)  ->				Dict:



           """simple docstring"""






           UpperCamelCase      = tempfile.mkdtemp()
           UpperCamelCase      = self.tokenizer.fairseq_tokens_to_ids
           self.tokenizer.save_pretrained(_SCREAMING_SNAKE_CASE				)
           UpperCamelCase      = MBartaaTokenizer.from_pretrained(_SCREAMING_SNAKE_CASE				)
           self.assertDictEqual(new_tok.fairseq_tokens_to_ids      ,		_SCREAMING_SNAKE_CASE				)

     @require_torch
     def   A__						(				self				)  ->				int:



           """simple docstring"""






           UpperCamelCase      = self.tokenizer(self.src_text      ,		text_target=self.tgt_text      ,		padding=_SCREAMING_SNAKE_CASE      ,		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   A__						(				self				)  ->				Optional[int]:



           """simple docstring"""






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

           self.assertIsInstance(_SCREAMING_SNAKE_CASE      ,		_SCREAMING_SNAKE_CASE				)

           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      ,		_SCREAMING_SNAKE_CASE				)
           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   A__						(				self				)  ->				Tuple:



           """simple docstring"""






           UpperCamelCase      = self.tokenizer(self.src_text      ,		padding=_SCREAMING_SNAKE_CASE      ,		truncation=_SCREAMING_SNAKE_CASE      ,		max_length=3      ,		return_tensors="""pt"""				)
           UpperCamelCase      = self.tokenizer(
               text_target=self.tgt_text      ,		padding=_SCREAMING_SNAKE_CASE      ,		truncation=_SCREAMING_SNAKE_CASE      ,		max_length=10      ,		return_tensors="""pt"""				)
           UpperCamelCase      = targets["""input_ids"""]
           UpperCamelCase      = shift_tokens_right(_SCREAMING_SNAKE_CASE      ,		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   A__						(				self				)  ->				Optional[Any]:



           """simple docstring"""






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

           self.assertEqual(
               nested_simplify(_SCREAMING_SNAKE_CASE				)      ,		{
                   # 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'''

import unittest

from transformers.utils.backbone_utils import (
    BackboneMixin,
    get_aligned_output_features_output_indices,
    verify_out_features_out_indices,
)






class     a_						(      unittest.TestCase    ):

  def   A__						(				self				)  ->				Tuple:



        """simple docstring"""






        UpperCamelCase      = ["""a""", """b""", """c"""]

        # Defaults to last layer if both are None
        UpperCamelCase  ,UpperCamelCase      = get_aligned_output_features_output_indices(_SCREAMING_SNAKE_CASE      ,		_SCREAMING_SNAKE_CASE      ,		_SCREAMING_SNAKE_CASE				)
        self.assertEqual(_SCREAMING_SNAKE_CASE      ,		["""c"""]				)
        self.assertEqual(_SCREAMING_SNAKE_CASE      ,		[2]				)

        # Out indices set to match out features
        UpperCamelCase  ,UpperCamelCase      = get_aligned_output_features_output_indices(["""a""", """c"""]      ,		_SCREAMING_SNAKE_CASE      ,		_SCREAMING_SNAKE_CASE				)
        self.assertEqual(_SCREAMING_SNAKE_CASE      ,		["""a""", """c"""]				)
        self.assertEqual(_SCREAMING_SNAKE_CASE      ,		[0, 2]				)

        # Out features set to match out indices
        UpperCamelCase  ,UpperCamelCase      = get_aligned_output_features_output_indices(_SCREAMING_SNAKE_CASE      ,		[0, 2]      ,		_SCREAMING_SNAKE_CASE				)
        self.assertEqual(_SCREAMING_SNAKE_CASE      ,		["""a""", """c"""]				)
        self.assertEqual(_SCREAMING_SNAKE_CASE      ,		[0, 2]				)

        # Out features selected from negative indices
        UpperCamelCase  ,UpperCamelCase      = get_aligned_output_features_output_indices(_SCREAMING_SNAKE_CASE      ,		[-3, -1]      ,		_SCREAMING_SNAKE_CASE				)
        self.assertEqual(_SCREAMING_SNAKE_CASE      ,		["""a""", """c"""]				)
        self.assertEqual(_SCREAMING_SNAKE_CASE      ,		[-3, -1]				)

  def   A__						(				self				)  ->				str:



        """simple docstring"""






        with self.assertRaises(_SCREAMING_SNAKE_CASE				):
              verify_out_features_out_indices(["""a""", """b"""]      ,		(0, 1)      ,		_SCREAMING_SNAKE_CASE				)

        # Out features must be a list
        with self.assertRaises(_SCREAMING_SNAKE_CASE				):
              verify_out_features_out_indices(("""a""", """b""")      ,		(0, 1)      ,		["""a""", """b"""]				)

        # Out features must be a subset of stage names
        with self.assertRaises(_SCREAMING_SNAKE_CASE				):
              verify_out_features_out_indices(["""a""", """b"""]      ,		(0, 1)      ,		["""a"""]				)

        # Out indices must be a list or tuple
        with self.assertRaises(_SCREAMING_SNAKE_CASE				):
              verify_out_features_out_indices(_SCREAMING_SNAKE_CASE      ,		0      ,		["""a""", """b"""]				)

        # Out indices must be a subset of stage names
        with self.assertRaises(_SCREAMING_SNAKE_CASE				):
              verify_out_features_out_indices(_SCREAMING_SNAKE_CASE      ,		(0, 1)      ,		["""a"""]				)

        # Out features and out indices must be the same length
        with self.assertRaises(_SCREAMING_SNAKE_CASE				):
              verify_out_features_out_indices(["""a""", """b"""]      ,		(0,)      ,		["""a""", """b""", """c"""]				)

        # Out features should match out indices
        with self.assertRaises(_SCREAMING_SNAKE_CASE				):
              verify_out_features_out_indices(["""a""", """b"""]      ,		(0, 2)      ,		["""a""", """b""", """c"""]				)

        # Out features and out indices should be in order
        with self.assertRaises(_SCREAMING_SNAKE_CASE				):
              verify_out_features_out_indices(["""b""", """a"""]      ,		(0, 1)      ,		["""a""", """b"""]				)

        # Check passes with valid inputs
        verify_out_features_out_indices(["""a""", """b""", """d"""]      ,		(0, 1, -1)      ,		["""a""", """b""", """c""", """d"""]				)


  def   A__						(				self				)  ->				Union[str, Any]:



        """simple docstring"""






        UpperCamelCase      = BackboneMixin()

        UpperCamelCase      = ["""a""", """b""", """c"""]
        UpperCamelCase      = ["""a""", """c"""]
        UpperCamelCase      = [0, 2]

        # Check that the output features and indices are set correctly
        self.assertEqual(backbone.out_features      ,		["""a""", """c"""]				)
        self.assertEqual(backbone.out_indices      ,		[0, 2]				)

        # Check out features and indices are updated correctly
        UpperCamelCase      = ["""a""", """b"""]
        self.assertEqual(backbone.out_features      ,		["""a""", """b"""]				)
        self.assertEqual(backbone.out_indices      ,		[0, 1]				)

        UpperCamelCase      = [-3, -1]
        self.assertEqual(backbone.out_features      ,		["""a""", """c"""]				)
        self.assertEqual(backbone.out_indices      ,		[-3, -1]				)
