


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				:       Tuple      =  get_tests_dir('fixtures/test_sentencepiece.model')

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

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






@require_sentencepiece
@require_tokenizers
class      UpperCamelCase(	_a  ,				unittest.TestCase ):
					snake_case_		:					List[str]    					=						MBartaaTokenizer
					snake_case_		:					int    					=						MBartaaTokenizerFast
					snake_case_		:					Any    					=						True
					snake_case_		:					Any    					=						True


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




											'''simple docstring'''

											super().setUp()

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


					def 				SCREAMING_SNAKE_CASE_	(    self						:		Tuple    )      ->						Tuple:




											'''simple docstring'''

											__snake_case				=		"<s>"
											__snake_case				=		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 				SCREAMING_SNAKE_CASE_	(    self						:		int    )      ->						Tuple:




											'''simple docstring'''

											__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(SCREAMING_SNAKE_CASE    )  ,     1_0_5_4    )


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




											'''simple docstring'''

											self.assertEqual(self.get_tokenizer().vocab_size  ,     1_0_5_4    )


					def 				SCREAMING_SNAKE_CASE_	(    self						:		str    )      ->						int:




											'''simple docstring'''

											__snake_case				=		MBartaaTokenizer(SCREAMING_SNAKE_CASE  ,     src_lang="en_XX"  ,     tgt_lang="ro_RO"  ,     keep_accents=SCREAMING_SNAKE_CASE    )

											__snake_case				=		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 [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]  ,     )

											__snake_case				=		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", "."]  ,     )
											__snake_case				=		tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE    )
											self.assertListEqual(
											    SCREAMING_SNAKE_CASE  ,     [
											        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]
											    ]  ,     )

											__snake_case				=		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 				SCREAMING_SNAKE_CASE_	(    self						:		Tuple    )      ->						Dict:




											'''simple docstring'''

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






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




											'''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

											__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})'''    ):
																							__snake_case				=		self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE  ,     **SCREAMING_SNAKE_CASE    )
																							__snake_case				=		self.tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE  ,     **SCREAMING_SNAKE_CASE    )

																							__snake_case				=		tempfile.mkdtemp()

																							__snake_case				=		tokenizer_r.save_pretrained(SCREAMING_SNAKE_CASE    )
																							__snake_case				=		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    )    )
																							__snake_case				=		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
																							__snake_case				=		tokenizer_r.from_pretrained(SCREAMING_SNAKE_CASE    )
																							__snake_case				=		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
																							__snake_case				=		tempfile.mkdtemp()

																							__snake_case				=		tokenizer_r.save_pretrained(SCREAMING_SNAKE_CASE  ,     legacy_format=SCREAMING_SNAKE_CASE    )
																							__snake_case				=		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
																							__snake_case				=		tokenizer_r.from_pretrained(SCREAMING_SNAKE_CASE    )
																							__snake_case				=		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
																							__snake_case				=		tempfile.mkdtemp()

																							__snake_case				=		tokenizer_r.save_pretrained(SCREAMING_SNAKE_CASE  ,     legacy_format=SCREAMING_SNAKE_CASE    )
																							__snake_case				=		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
																							__snake_case				=		tokenizer_r.from_pretrained(SCREAMING_SNAKE_CASE    )
																							__snake_case				=		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      UpperCamelCase(	unittest.TestCase ):
					snake_case_		:					str    					=						"""facebook/mbart-large-50-one-to-many-mmt"""
					snake_case_		:					int    					=						[
					    """ UN Chief Says There Is No Military Solution in Syria""",
					    """ Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.""",
					]
					snake_case_		:					Tuple    					=						[
					    """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_		:					List[Any]    					=						[EN_CODE, 8274, 12_7873, 2_5916, 7, 8622, 2071, 438, 6_7485, 53, 18_7895, 23, 5_1712, 2]


					@classmethod
					def 				SCREAMING_SNAKE_CASE_	(    cls						:		Any    )      ->						Union[str, Any]:




											'''simple docstring'''

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


					def 				SCREAMING_SNAKE_CASE_	(    self						:		str    )      ->						Optional[int]:




											'''simple docstring'''

											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 				SCREAMING_SNAKE_CASE_	(    self						:		Dict    )      ->						List[Any]:




											'''simple docstring'''

											__snake_case				=		self.tokenizer.batch_encode_plus(self.src_text    ).input_ids[0]
											self.assertListEqual(self.expected_src_tokens  ,     SCREAMING_SNAKE_CASE    )


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




											'''simple docstring'''

											self.assertIn(SCREAMING_SNAKE_CASE  ,     self.tokenizer.all_special_ids    )
											__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]
											__snake_case				=		self.tokenizer.decode(SCREAMING_SNAKE_CASE  ,     skip_special_tokens=SCREAMING_SNAKE_CASE    )
											__snake_case				=		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 				SCREAMING_SNAKE_CASE_	(    self						:		Union[str, Any]    )      ->						List[Any]:




											'''simple docstring'''

											__snake_case				=		["this is gunna be a long sentence " * 2_0]
											assert isinstance(src_text[0]  ,     SCREAMING_SNAKE_CASE    )
											__snake_case				=		1_0
											__snake_case				=		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 				SCREAMING_SNAKE_CASE_	(    self						:		str    )      ->						Optional[Any]:




											'''simple docstring'''

											self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"]    )  ,     [2_5_0_0_5_3, 2_5_0_0_0_1]    )


					def 				SCREAMING_SNAKE_CASE_	(    self						:		Tuple    )      ->						str:




											'''simple docstring'''

											__snake_case				=		tempfile.mkdtemp()
											__snake_case				=		self.tokenizer.fairseq_tokens_to_ids
											self.tokenizer.save_pretrained(SCREAMING_SNAKE_CASE    )
											__snake_case				=		MBartaaTokenizer.from_pretrained(SCREAMING_SNAKE_CASE    )
											self.assertDictEqual(new_tok.fairseq_tokens_to_ids  ,     SCREAMING_SNAKE_CASE    )


					@require_torch
					def 				SCREAMING_SNAKE_CASE_	(    self						:		Any    )      ->						Union[str, Any]:




											'''simple docstring'''

											__snake_case				=		self.tokenizer(self.src_text  ,     text_target=self.tgt_text  ,     padding=SCREAMING_SNAKE_CASE  ,     return_tensors="pt"    )
											__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 				SCREAMING_SNAKE_CASE_	(    self						:		Union[str, Any]    )      ->						List[Any]:




											'''simple docstring'''

											__snake_case				=		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"  ,     )
											__snake_case				=		shift_tokens_right(batch["labels"]  ,     self.tokenizer.pad_token_id    )

											self.assertIsInstance(SCREAMING_SNAKE_CASE  ,     SCREAMING_SNAKE_CASE    )

											self.assertEqual((2, 1_4)  ,     batch.input_ids.shape    )
											self.assertEqual((2, 1_4)  ,     batch.attention_mask.shape    )
											__snake_case				=		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 				SCREAMING_SNAKE_CASE_	(    self						:		Any    )      ->						int:




											'''simple docstring'''

											__snake_case				=		self.tokenizer(self.src_text  ,     padding=SCREAMING_SNAKE_CASE  ,     truncation=SCREAMING_SNAKE_CASE  ,     max_length=3  ,     return_tensors="pt"    )
											__snake_case				=		self.tokenizer(
											    text_target=self.tgt_text  ,     padding=SCREAMING_SNAKE_CASE  ,     truncation=SCREAMING_SNAKE_CASE  ,     max_length=1_0  ,     return_tensors="pt"    )
											__snake_case				=		targets["input_ids"]
											__snake_case				=		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]  ,     1_0    )






					@require_torch
					def 				SCREAMING_SNAKE_CASE_	(    self						:		Any    )      ->						int:




											'''simple docstring'''

											__snake_case				=		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": [[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,
											    }  ,     )









def 						_lowerCAmelCase							(     _lowerCAmelCase = 1000			)    ->						int:


						'''simple docstring'''






						__snake_case				=		2**power
						__snake_case				=		str(_lowerCAmelCase			)
						__snake_case				=		list(_lowerCAmelCase			)
						__snake_case				=		0

						for i in list_num:
												sum_of_num += int(_lowerCAmelCase			)

						return sum_of_num


if __name__ == "__main__":
	A				:       Optional[Any]      =  int(input('Enter the power of 2: ').strip())
	print('2 ^ ', power, ' = ', 2**power)
	A				:       List[Any]      =  solution(power)
	print('Sum of the digits is: ', result)





