


"""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__       :							Optional[int]        =  get_tests_dir('''fixtures/test_sentencepiece.model''')

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

a__       :							Any        =  2_5_0_0_0_4
a__       :							Optional[int]        =  2_5_0_0_2_0




@require_sentencepiece
@require_tokenizers
class 				UpperCamelCase_			(				UpperCamelCase    ,						unittest.TestCase):

	"""simple docstring"""





	snake_case__       :						Dict					      =    MBartaaTokenizer
	snake_case__       :						Dict					      =    MBartaaTokenizerFast
	snake_case__       :						Optional[int]					      =    True
	snake_case__       :						List[Any]					      =    True




	def 						UpperCAmelCase_   (				self    :       Optional[int]     ) ->			Optional[int]:
						super().setUp()

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




	def 						UpperCAmelCase_   (				self    :       str     ) ->			List[str]:
						__SCREAMING_SNAKE_CASE		     =       "<s>"
						__SCREAMING_SNAKE_CASE		     =       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    :       List[Any]     ) ->			Union[str, Any]:
						__SCREAMING_SNAKE_CASE		     =       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 						UpperCAmelCase_   (				self    :       str     ) ->			Union[str, Any]:
						self.assertEqual(self.get_tokenizer().vocab_size    ,    1_0_5_4     )




	def 						UpperCAmelCase_   (				self    :       Tuple     ) ->			Optional[Any]:
						__SCREAMING_SNAKE_CASE		     =       MBartaaTokenizer(UpperCAmelCase__    ,    src_lang="en_XX"    ,    tgt_lang="ro_RO"    ,    keep_accents=UpperCAmelCase__     )

						__SCREAMING_SNAKE_CASE		     =       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]]    ,    )

						__SCREAMING_SNAKE_CASE		     =       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", "."]    ,    )
						__SCREAMING_SNAKE_CASE		     =       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]
						    ]    ,    )

						__SCREAMING_SNAKE_CASE		     =       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    :       Optional[Any]     ) ->			Any:
						# fmt: off
						__SCREAMING_SNAKE_CASE		     =       {"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 						UpperCAmelCase_   (				self    :       Union[str, Any]     ) ->			str:
						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

						__SCREAMING_SNAKE_CASE		     =       (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})"""     ):
																__SCREAMING_SNAKE_CASE		     =       self.rust_tokenizer_class.from_pretrained(UpperCAmelCase__    ,    **UpperCAmelCase__     )
																__SCREAMING_SNAKE_CASE		     =       self.tokenizer_class.from_pretrained(UpperCAmelCase__    ,    **UpperCAmelCase__     )

																__SCREAMING_SNAKE_CASE		     =       tempfile.mkdtemp()

																__SCREAMING_SNAKE_CASE		     =       tokenizer_r.save_pretrained(UpperCAmelCase__     )
																__SCREAMING_SNAKE_CASE		     =       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     )     )
																__SCREAMING_SNAKE_CASE		     =       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
																__SCREAMING_SNAKE_CASE		     =       tokenizer_r.from_pretrained(UpperCAmelCase__     )
																__SCREAMING_SNAKE_CASE		     =       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
																__SCREAMING_SNAKE_CASE		     =       tempfile.mkdtemp()

																__SCREAMING_SNAKE_CASE		     =       tokenizer_r.save_pretrained(UpperCAmelCase__    ,    legacy_format=UpperCAmelCase__     )
																__SCREAMING_SNAKE_CASE		     =       tokenizer_p.save_pretrained(UpperCAmelCase__     )

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

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

																__SCREAMING_SNAKE_CASE		     =       tokenizer_r.save_pretrained(UpperCAmelCase__    ,    legacy_format=UpperCAmelCase__     )
																__SCREAMING_SNAKE_CASE		     =       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
																__SCREAMING_SNAKE_CASE		     =       tokenizer_r.from_pretrained(UpperCAmelCase__     )
																__SCREAMING_SNAKE_CASE		     =       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):

	"""simple docstring"""





	snake_case__       :						Union[str, Any]					      =    "facebook/mbart-large-50-one-to-many-mmt"
	snake_case__       :						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.",
	]
	snake_case__       :						Any					      =    [
	    "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.",
	]
	snake_case__       :						Tuple					      =    [EN_CODE, 8274, 127873, 25916, 7, 8622, 2071, 438, 67485, 53, 187895, 23, 51712, 2]




	@classmethod
	def 						UpperCAmelCase_   (				cls    :       Union[str, Any]     ) ->			Optional[int]:
						__SCREAMING_SNAKE_CASE		     =       MBartaaTokenizer.from_pretrained(
						    cls.checkpoint_name    ,    src_lang="en_XX"    ,    tgt_lang="ro_RO"     )
						__SCREAMING_SNAKE_CASE		     =       1
						return cls




	def 						UpperCAmelCase_   (				self    :       Optional[Any]     ) ->			str:
						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 						UpperCAmelCase_   (				self    :       List[Any]     ) ->			Optional[Any]:
						__SCREAMING_SNAKE_CASE		     =       self.tokenizer.batch_encode_plus(self.src_text     ).input_ids[0]
						self.assertListEqual(self.expected_src_tokens    ,    UpperCAmelCase__     )




	def 						UpperCAmelCase_   (				self    :       Optional[int]     ) ->			Any:
						self.assertIn(UpperCAmelCase__    ,    self.tokenizer.all_special_ids     )
						__SCREAMING_SNAKE_CASE		     =       [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]
						__SCREAMING_SNAKE_CASE		     =       self.tokenizer.decode(UpperCAmelCase__    ,    skip_special_tokens=UpperCAmelCase__     )
						__SCREAMING_SNAKE_CASE		     =       self.tokenizer.decode(generated_ids[1:]    ,    skip_special_tokens=UpperCAmelCase__     )
						self.assertEqual(UpperCAmelCase__    ,    UpperCAmelCase__     )
						self.assertNotIn(self.tokenizer.eos_token    ,    UpperCAmelCase__     )




	def 						UpperCAmelCase_   (				self    :       Union[str, Any]     ) ->			List[Any]:
						__SCREAMING_SNAKE_CASE		     =       ["this is gunna be a long sentence " * 2_0]
						assert isinstance(src_text[0]    ,    UpperCAmelCase__     )
						__SCREAMING_SNAKE_CASE		     =       1_0
						__SCREAMING_SNAKE_CASE		     =       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    :       Union[str, Any]     ) ->			List[Any]:
						self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"]     )    ,    [2_5_0_0_5_3, 2_5_0_0_0_1]     )




	def 						UpperCAmelCase_   (				self    :       int     ) ->			Optional[Any]:
						__SCREAMING_SNAKE_CASE		     =       tempfile.mkdtemp()
						__SCREAMING_SNAKE_CASE		     =       self.tokenizer.fairseq_tokens_to_ids
						self.tokenizer.save_pretrained(UpperCAmelCase__     )
						__SCREAMING_SNAKE_CASE		     =       MBartaaTokenizer.from_pretrained(UpperCAmelCase__     )
						self.assertDictEqual(new_tok.fairseq_tokens_to_ids    ,    UpperCAmelCase__     )




	@require_torch
	def 						UpperCAmelCase_   (				self    :       List[Any]     ) ->			Optional[int]:
						__SCREAMING_SNAKE_CASE		     =       self.tokenizer(self.src_text    ,    text_target=self.tgt_text    ,    padding=UpperCAmelCase__    ,    return_tensors="pt"     )
						__SCREAMING_SNAKE_CASE		     =       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    :       Tuple     ) ->			Tuple:
						__SCREAMING_SNAKE_CASE		     =       self.tokenizer(
						    self.src_text    ,    text_target=self.tgt_text    ,    padding=UpperCAmelCase__    ,    truncation=UpperCAmelCase__    ,    max_length=len(self.expected_src_tokens     )    ,    return_tensors="pt"    ,    )
						__SCREAMING_SNAKE_CASE		     =       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     )
						__SCREAMING_SNAKE_CASE		     =       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    :       Tuple     ) ->			Union[str, Any]:
						__SCREAMING_SNAKE_CASE		     =       self.tokenizer(self.src_text    ,    padding=UpperCAmelCase__    ,    truncation=UpperCAmelCase__    ,    max_length=3    ,    return_tensors="pt"     )
						__SCREAMING_SNAKE_CASE		     =       self.tokenizer(
						    text_target=self.tgt_text    ,    padding=UpperCAmelCase__    ,    truncation=UpperCAmelCase__    ,    max_length=1_0    ,    return_tensors="pt"     )
						__SCREAMING_SNAKE_CASE		     =       targets["input_ids"]
						__SCREAMING_SNAKE_CASE		     =       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 						UpperCAmelCase_   (				self    :       Any     ) ->			List[str]:
						__SCREAMING_SNAKE_CASE		     =       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"""







from __future__ import annotations

import math




class 				UpperCamelCase_			:

	"""simple docstring"""





	def __init__(				self    :       Union[str, Any]    ,    UpperCAmelCase__    :       int     ) ->			None:
						__SCREAMING_SNAKE_CASE		     =       size
						# approximate the overall size of segment tree with given value
						__SCREAMING_SNAKE_CASE		     =       [0 for i in range(0    ,    4 * size     )]
						# create array to store lazy update
						__SCREAMING_SNAKE_CASE		     =       [0 for i in range(0    ,    4 * size     )]
						__SCREAMING_SNAKE_CASE		     =       [0 for i in range(0    ,    4 * size     )]  # flag for lazy update




	def 						UpperCAmelCase_   (				self    :       str    ,    UpperCAmelCase__    :       int     ) ->			int:
						return idx * 2




	def 						UpperCAmelCase_   (				self    :       Any    ,    UpperCAmelCase__    :       int     ) ->			int:
						return idx * 2 + 1




	def 						UpperCAmelCase_   (				self    :       List[Any]    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       list[int]     ) ->			None:
						if left_element == right_element:
											__SCREAMING_SNAKE_CASE		     =       a[left_element - 1]
						else:
											__SCREAMING_SNAKE_CASE		     =       (left_element + right_element) // 2
											self.build(self.left(UpperCAmelCase__     )    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
											self.build(self.right(UpperCAmelCase__     )    ,    mid + 1    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
											__SCREAMING_SNAKE_CASE		     =       max(
											    self.segment_tree[self.left(UpperCAmelCase__     )]    ,    self.segment_tree[self.right(UpperCAmelCase__     )]     )




	def 						UpperCAmelCase_   (				self    :       Tuple    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int     ) ->			bool:
						if self.flag[idx] is True:
											__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
											__SCREAMING_SNAKE_CASE		     =       False
											if left_element != right_element:
																__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
																__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
																__SCREAMING_SNAKE_CASE		     =       True
																__SCREAMING_SNAKE_CASE		     =       True

						if right_element < a or left_element > b:
											return True
						if left_element >= a and right_element <= b:
											__SCREAMING_SNAKE_CASE		     =       val
											if left_element != right_element:
																__SCREAMING_SNAKE_CASE		     =       val
																__SCREAMING_SNAKE_CASE		     =       val
																__SCREAMING_SNAKE_CASE		     =       True
																__SCREAMING_SNAKE_CASE		     =       True
											return True
						__SCREAMING_SNAKE_CASE		     =       (left_element + right_element) // 2
						self.update(self.left(UpperCAmelCase__     )    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
						self.update(self.right(UpperCAmelCase__     )    ,    mid + 1    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
						__SCREAMING_SNAKE_CASE		     =       max(
						    self.segment_tree[self.left(UpperCAmelCase__     )]    ,    self.segment_tree[self.right(UpperCAmelCase__     )]     )
						return True




	def 						UpperCAmelCase_   (				self    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int     ) ->			int | float:
						if self.flag[idx] is True:
											__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
											__SCREAMING_SNAKE_CASE		     =       False
											if left_element != right_element:
																__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
																__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
																__SCREAMING_SNAKE_CASE		     =       True
																__SCREAMING_SNAKE_CASE		     =       True
						if right_element < a or left_element > b:
											return -math.inf
						if left_element >= a and right_element <= b:
											return self.segment_tree[idx]
						__SCREAMING_SNAKE_CASE		     =       (left_element + right_element) // 2
						__SCREAMING_SNAKE_CASE		     =       self.query(self.left(UpperCAmelCase__     )    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
						__SCREAMING_SNAKE_CASE		     =       self.query(self.right(UpperCAmelCase__     )    ,    mid + 1    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
						return max(UpperCAmelCase__    ,    UpperCAmelCase__     )




	def __str__(				self    :       int     ) ->			str:
						return str([self.query(1    ,    1    ,    self.size    ,    UpperCAmelCase__    ,    UpperCAmelCase__     ) for i in range(1    ,    self.size + 1     )]     )


if __name__ == "__main__":
		a__       :							Tuple        =  [1, 2, -4, 7, 3, -5, 6, 1_1, -2_0, 9, 1_4, 1_5, 5, 2, -8]
		a__       :							Dict        =  1_5
		a__       :							int        =  SegmentTree(size)
		segt.build(1, 1, size, A)
		print(segt.query(1, 1, size, 4, 6))
		print(segt.query(1, 1, size, 7, 1_1))
		print(segt.query(1, 1, size, 7, 1_2))
		segt.update(1, 1, size, 1, 3, 1_1_1)
		print(segt.query(1, 1, size, 1, 1_5))
		segt.update(1, 1, size, 7, 8, 2_3_5)
		print(segt)
