
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


lowercase  :					Union[str, Any]						    =							get_tests_dir("""fixtures/test_sentencepiece.model""")


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

lowercase  :					Optional[Any]						    =							250004
lowercase  :					Optional[int]						    =							250020

@require_sentencepiece
@require_tokenizers
class __snake_case		(      lowerCAmelCase					,	unittest.TestCase     ):
    _a		:						Optional[int]=				MBartTokenizer
    _a		:						str=				MBartTokenizerFast
    _a		:						Dict=				True
    _a		:						int=				True
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           super().setUp()

           # We have a SentencePiece fixture for testing
           lowercase							:     str       	=      MBartTokenizer(snake_case		,keep_accents=snake_case      )
           tokenizer.save_pretrained(self.tmpdirname      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Optional[Any]       	=      MBartTokenizer(snake_case		,keep_accents=snake_case      )

           lowercase							:     Any       	=      tokenizer.tokenize("""This is a test"""      )
           self.assertListEqual(snake_case		,["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]      )

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

           lowercase							:     str       	=      tokenizer.tokenize("""I was born in 92000, and this is falsé."""      )
           self.assertListEqual(
               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""",
                   """.""",
               ]		,)
           lowercase							:     Optional[Any]       	=      tokenizer.convert_tokens_to_ids(snake_case      )
           self.assertListEqual(
               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]
                   #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
               ]		,)

           lowercase							:     str       	=      tokenizer.convert_ids_to_tokens(snake_case      )
           self.assertListEqual(
               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>""",
                   """.""",
               ]		,)
    def       _SCREAMING_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

           lowercase							:     Union[str, Any]       	=      (self.rust_tokenizer_class, """hf-internal-testing/tiny-random-mbart""", {})
           for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                  with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"      ):
                         lowercase							:     Tuple       	=      self.rust_tokenizer_class.from_pretrained(snake_case		,**snake_case      )
                         lowercase							:     Optional[Any]       	=      self.tokenizer_class.from_pretrained(snake_case		,**snake_case      )

                         lowercase							:     Optional[int]       	=      tempfile.mkdtemp()

                         lowercase							:     Dict       	=      tokenizer_r.save_pretrained(snake_case      )
                         lowercase							:     Tuple       	=      tokenizer_p.save_pretrained(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      )      )
                         lowercase							:     Optional[Any]       	=      tuple(f for f in tokenizer_r_files if """tokenizer.json""" not in f      )
                         self.assertSequenceEqual(snake_case		,snake_case      )

                         # Checks everything loads correctly in the same way
                         lowercase							:     Any       	=      tokenizer_r.from_pretrained(snake_case      )
                         lowercase							:     str       	=      tokenizer_p.from_pretrained(snake_case      )

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

                         # Save tokenizer rust, legacy_format=True
                         lowercase							:     int       	=      tempfile.mkdtemp()

                         lowercase							:     Dict       	=      tokenizer_r.save_pretrained(snake_case		,legacy_format=snake_case      )
                         lowercase							:     str       	=      tokenizer_p.save_pretrained(snake_case      )

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

                         # Checks everything loads correctly in the same way
                         lowercase							:     Optional[int]       	=      tokenizer_r.from_pretrained(snake_case      )
                         lowercase							:     Tuple       	=      tokenizer_p.from_pretrained(snake_case      )

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

                         shutil.rmtree(snake_case      )

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

                         lowercase							:     List[Any]       	=      tokenizer_r.save_pretrained(snake_case		,legacy_format=snake_case      )
                         lowercase							:     Union[str, Any]       	=      tokenizer_p.save_pretrained(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
                         lowercase							:     Tuple       	=      tokenizer_r.from_pretrained(snake_case      )
                         lowercase							:     Optional[int]       	=      tokenizer_p.from_pretrained(snake_case      )

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

                         shutil.rmtree(snake_case      )






@require_torch
@require_sentencepiece
@require_tokenizers
class __snake_case		(      unittest.TestCase     ):
    _a		:						Any=				"facebook/mbart-large-en-ro"
    _a		:						Union[str, Any]=				[
        " 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		:						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.",
    ]
    _a		:						Optional[Any]=				[8274, 12_7873, 2_5916, 7, 8622, 2071, 438, 6_7485, 53, 18_7895, 23, 5_1712, 2, EN_CODE]
    @classmethod
    def       _SCREAMING_SNAKE_CASE       (  cls      ):



           '''simple docstring'''







           lowercase							:     MBartTokenizer       	=      MBartTokenizer.from_pretrained(
               cls.checkpoint_name		,src_lang="""en_XX"""		,tgt_lang="""ro_RO"""      )
           lowercase							:     Optional[int]       	=      1
           return cls
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''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      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     List[str]       	=      self.tokenizer.batch_encode_plus(self.src_text      ).input_ids[0]
           self.assertListEqual(self.expected_src_tokens		,snake_case      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







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



           '''simple docstring'''







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



           '''simple docstring'''







           self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]      )		,[250026, 250001]      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Union[str, Any]       	=      tempfile.mkdtemp()
           lowercase							:     Dict       	=      self.tokenizer.fairseq_tokens_to_ids
           self.tokenizer.save_pretrained(snake_case      )
           lowercase							:     List[str]       	=      MBartTokenizer.from_pretrained(snake_case      )
           self.assertDictEqual(new_tok.fairseq_tokens_to_ids		,snake_case      )
    @require_torch
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Optional[int]       	=      self.tokenizer(self.src_text		,text_target=self.tgt_text		,padding=snake_case		,return_tensors="""pt"""      )
           lowercase							:     List[str]       	=      shift_tokens_right(batch["""labels"""]		,self.tokenizer.pad_token_id      )

           # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
           assert batch.input_ids[1][-2:].tolist() == [2, EN_CODE]
           assert batch.decoder_input_ids[1][0].tolist() == RO_CODE
           assert batch.decoder_input_ids[1][-1] == 2
           assert batch.labels[1][-2:].tolist() == [2, RO_CODE]
    @require_torch
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     int       	=      self.tokenizer(
               self.src_text		,text_target=self.tgt_text		,padding=snake_case		,truncation=snake_case		,max_length=len(self.expected_src_tokens      )		,return_tensors="""pt"""		,)

           lowercase							:     Any       	=      shift_tokens_right(batch["""labels"""]		,self.tokenizer.pad_token_id      )

           self.assertIsInstance(snake_case		,snake_case      )

           self.assertEqual((2, 14)		,batch.input_ids.shape      )
           self.assertEqual((2, 14)		,batch.attention_mask.shape      )
           lowercase							:     int       	=      batch.input_ids.tolist()[0]
           self.assertListEqual(self.expected_src_tokens		,snake_case      )
           self.assertEqual(2		,batch.decoder_input_ids[0, -1]      )  # EOS
           # Test that special tokens are reset
           self.assertEqual(self.tokenizer.prefix_tokens		,[]      )
           self.assertEqual(self.tokenizer.suffix_tokens		,[self.tokenizer.eos_token_id, EN_CODE]      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Optional[Any]       	=      self.tokenizer(self.src_text		,padding=snake_case		,truncation=snake_case		,max_length=3		,return_tensors="""pt"""      )
           lowercase							:     Optional[int]       	=      self.tokenizer(
               text_target=self.tgt_text		,padding=snake_case		,truncation=snake_case		,max_length=10		,return_tensors="""pt"""      )
           lowercase							:     Dict       	=      targets["""input_ids"""]
           lowercase							:     int       	=      shift_tokens_right(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       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Union[str, Any]       	=      self.tokenizer._build_translation_inputs(
               """A test"""		,return_tensors="""pt"""		,src_lang="""en_XX"""		,tgt_lang="""ar_AR"""      )

           self.assertEqual(
               nested_simplify(snake_case      )		,{
                   # A, test, EOS, en_XX
                   """input_ids""": [[62, 3034, 2, 250004]],
                   """attention_mask""": [[1, 1, 1, 1]],
                   # ar_AR
                   """forced_bos_token_id""": 250001,
               }		,)


from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass

@dataclass
class __snake_case		:
    _a		:						int
    _a		:						TreeNode | None=				None
    _a		:						TreeNode | None=				None






lowercase  :					Dict						    =							namedtuple("""CoinsDistribResult""", """moves excess""")







def 						_snake_case(  SCREAMING_SNAKE_CASE__				) ->    int:

       if root is None:
              return 0

       # Validation
       def count_nodes(SCREAMING_SNAKE_CASE__				) -> int:
              if node is None:
                     return 0

              return count_nodes(node.left				) + count_nodes(node.right				) + 1

       def count_coins(SCREAMING_SNAKE_CASE__				) -> int:
              if node is None:
                     return 0

              return count_coins(node.left				) + count_coins(node.right				) + node.data

       if count_nodes(SCREAMING_SNAKE_CASE__				) != count_coins(SCREAMING_SNAKE_CASE__				):
              raise ValueError("""The nodes number should be same as the number of coins"""				)

       # Main calculation
       def get_distrib(SCREAMING_SNAKE_CASE__				) -> CoinsDistribResult:

              if node is None:
                     return CoinsDistribResult(0					,	1				)

              lowercase	,			lowercase							:     int       	=      get_distrib(node.left				)
              lowercase	,			lowercase							:     List[Any]       	=      get_distrib(node.right				)

              lowercase							:     Optional[Any]       	=      1 - left_distrib_excess
              lowercase							:     Union[str, Any]       	=      1 - right_distrib_excess

              lowercase							:     List[Any]       	=      (
                  left_distrib_moves
                  + right_distrib_moves
                  + abs(SCREAMING_SNAKE_CASE__				)
                  + abs(SCREAMING_SNAKE_CASE__				)
              )
              lowercase							:     Any       	=      node.data - coins_to_left - coins_to_right

              return CoinsDistribResult(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)

       return get_distrib(SCREAMING_SNAKE_CASE__				)[0]


if __name__ == "__main__":
  import doctest

  doctest.testmod()
