

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


a		=get_tests_dir("""fixtures/test_sentencepiece.model""")


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

a		=250004
a		=250020






@require_sentencepiece
@require_tokenizers
class 	A_		(	SCREAMING_SNAKE_CASE      ,							unittest.TestCase    ):
							_UpperCAmelCase   :  Tuple										=				MBartTokenizer
							_UpperCAmelCase   :  Optional[int]										=				MBartTokenizerFast
							_UpperCAmelCase   :  Union[str, Any]										=				True
							_UpperCAmelCase   :  Union[str, Any]										=				True
							def    lowerCAmelCase					(		self		:      Union[str, Any]):
								super().setUp()

								# We have a SentencePiece fixture for testing
								__lowerCamelCase    :    Optional[int] 	=			MBartTokenizer(SCREAMING_SNAKE_CASE__       ,keep_accents=SCREAMING_SNAKE_CASE__)
								tokenizer.save_pretrained(self.tmpdirname)
							def    lowerCAmelCase					(		self		:      Dict):
								__lowerCamelCase    :    Optional[int] 	=			MBartTokenizer(SCREAMING_SNAKE_CASE__       ,keep_accents=SCREAMING_SNAKE_CASE__)

								__lowerCamelCase    :    Any 	=			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]]       ,)

								__lowerCamelCase    :    Optional[Any] 	=			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',
								        '.',
								    ]       ,)
								__lowerCamelCase    :    Tuple 	=			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]
								        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
								    ]       ,)

								__lowerCamelCase    :    Optional[int] 	=			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>',
								        '.',
								    ]       ,)


							def    lowerCAmelCase					(		self		:      List[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

								__lowerCamelCase    :    Optional[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})"):
										__lowerCamelCase    :    str 	=			self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE__       ,**SCREAMING_SNAKE_CASE__)
										__lowerCamelCase    :    Dict 	=			self.tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE__       ,**SCREAMING_SNAKE_CASE__)

										__lowerCamelCase    :    List[Any] 	=			tempfile.mkdtemp()

										__lowerCamelCase    :    Any 	=			tokenizer_r.save_pretrained(SCREAMING_SNAKE_CASE__)
										__lowerCamelCase    :    str 	=			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))
										__lowerCamelCase    :    str 	=			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
										__lowerCamelCase    :    Tuple 	=			tokenizer_r.from_pretrained(SCREAMING_SNAKE_CASE__)
										__lowerCamelCase    :    Dict 	=			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
										__lowerCamelCase    :    Tuple 	=			tempfile.mkdtemp()

										__lowerCamelCase    :    Optional[Any] 	=			tokenizer_r.save_pretrained(SCREAMING_SNAKE_CASE__       ,legacy_format=SCREAMING_SNAKE_CASE__)
										__lowerCamelCase    :    Union[str, Any] 	=			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
										__lowerCamelCase    :    int 	=			tokenizer_r.from_pretrained(SCREAMING_SNAKE_CASE__)
										__lowerCamelCase    :    Optional[int] 	=			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
										__lowerCamelCase    :    str 	=			tempfile.mkdtemp()

										__lowerCamelCase    :    int 	=			tokenizer_r.save_pretrained(SCREAMING_SNAKE_CASE__       ,legacy_format=SCREAMING_SNAKE_CASE__)
										__lowerCamelCase    :    Optional[Any] 	=			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
										__lowerCamelCase    :    Optional[int] 	=			tokenizer_r.from_pretrained(SCREAMING_SNAKE_CASE__)
										__lowerCamelCase    :    Union[str, Any] 	=			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    ):
							_UpperCAmelCase   :  Any										=				'''facebook/mbart-large-en-ro'''
							_UpperCAmelCase   :  List[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.''',
							]
							_UpperCAmelCase   :  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.''',
							]
							_UpperCAmelCase   :  int										=				[8_274, 127_873, 25_916, 7, 8_622, 2_071, 438, 67_485, 53, 187_895, 23, 51_712, 2, EN_CODE]
							@classmethod
							def    lowerCAmelCase					(		cls		:      Dict):
								__lowerCamelCase    :    MBartTokenizer 	=			MBartTokenizer.from_pretrained(
								    cls.checkpoint_name       ,src_lang='en_XX'       ,tgt_lang='ro_RO')
								__lowerCamelCase    :    Any 	=			1
								return cls
							def    lowerCAmelCase					(		self		:      int):
								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)
							def    lowerCAmelCase					(		self		:      Dict):
								__lowerCamelCase    :    List[str] 	=			self.tokenizer.batch_encode_plus(self.src_text).input_ids[0]
								self.assertListEqual(self.expected_src_tokens       ,SCREAMING_SNAKE_CASE__)
							def    lowerCAmelCase					(		self		:      Tuple):
								self.assertIn(SCREAMING_SNAKE_CASE__       ,self.tokenizer.all_special_ids)
								__lowerCamelCase    :    Optional[Any] 	=			[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]
								__lowerCamelCase    :    str 	=			self.tokenizer.decode(SCREAMING_SNAKE_CASE__       ,skip_special_tokens=SCREAMING_SNAKE_CASE__)
								__lowerCamelCase    :    Union[str, Any] 	=			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    lowerCAmelCase					(		self		:      List[Any]):
								__lowerCamelCase    :    int 	=			['this is gunna be a long sentence ' * 2_0]
								assert isinstance(src_text[0]       ,SCREAMING_SNAKE_CASE__)
								__lowerCamelCase    :    Dict 	=			1_0
								__lowerCamelCase    :    List[Any] 	=			self.tokenizer(SCREAMING_SNAKE_CASE__       ,max_length=SCREAMING_SNAKE_CASE__       ,truncation=SCREAMING_SNAKE_CASE__).input_ids[0]
								self.assertEqual(ids[-2]       ,2)
								self.assertEqual(ids[-1]       ,SCREAMING_SNAKE_CASE__)
								self.assertEqual(len(SCREAMING_SNAKE_CASE__)       ,SCREAMING_SNAKE_CASE__)
							def    lowerCAmelCase					(		self		:      Union[str, Any]):
								self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR'])       ,[2_5_0_0_2_6, 2_5_0_0_0_1])
							def    lowerCAmelCase					(		self		:      Dict):
								__lowerCamelCase    :    str 	=			tempfile.mkdtemp()
								__lowerCamelCase    :    List[Any] 	=			self.tokenizer.fairseq_tokens_to_ids
								self.tokenizer.save_pretrained(SCREAMING_SNAKE_CASE__)
								__lowerCamelCase    :    Tuple 	=			MBartTokenizer.from_pretrained(SCREAMING_SNAKE_CASE__)
								self.assertDictEqual(new_tok.fairseq_tokens_to_ids       ,SCREAMING_SNAKE_CASE__)
							@require_torch
							def    lowerCAmelCase					(		self		:      Union[str, Any]):
								__lowerCamelCase    :    Optional[Any] 	=			self.tokenizer(self.src_text       ,text_target=self.tgt_text       ,padding=SCREAMING_SNAKE_CASE__       ,return_tensors='pt')
								__lowerCamelCase    :    Optional[Any] 	=			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    lowerCAmelCase					(		self		:      List[str]):
								__lowerCamelCase    :    Union[str, Any] 	=			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'       ,)

								__lowerCamelCase    :    List[Any] 	=			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)
								__lowerCamelCase    :    Any 	=			batch.input_ids.tolist()[0]
								self.assertListEqual(self.expected_src_tokens       ,SCREAMING_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    lowerCAmelCase					(		self		:      List[Any]):
								__lowerCamelCase    :    Optional[int] 	=			self.tokenizer(self.src_text       ,padding=SCREAMING_SNAKE_CASE__       ,truncation=SCREAMING_SNAKE_CASE__       ,max_length=3       ,return_tensors='pt')
								__lowerCamelCase    :    Any 	=			self.tokenizer(
								    text_target=self.tgt_text       ,padding=SCREAMING_SNAKE_CASE__       ,truncation=SCREAMING_SNAKE_CASE__       ,max_length=1_0       ,return_tensors='pt')
								__lowerCamelCase    :    Tuple 	=			targets['input_ids']
								__lowerCamelCase    :    int 	=			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    lowerCAmelCase					(		self		:      Optional[int]):
								__lowerCamelCase    :    Tuple 	=			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__)       ,{
								        # A, test, EOS, en_XX
								        'input_ids': [[6_2, 3_0_3_4, 2, 2_5_0_0_0_4]],
								        'attention_mask': [[1, 1, 1, 1]],
								        # ar_AR
								        'forced_bos_token_id': 2_5_0_0_0_1,
								    }       ,)







from __future__ import annotations






def        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__     ,			lowerCamelCase__     ,			lowerCamelCase__     ,			lowerCamelCase__     ,			lowerCamelCase__     ,			)  ->					None:
	__lowerCamelCase    :    int 	=			len(lowerCamelCase__      )

	# If row is equal to the size of the board it means there are a queen in each row in
	# the current board (possible_board)
	if row == n:
		# We convert the variable possible_board that looks like this: [1, 3, 0, 2] to
		# this: ['. Q . . ', '. . . Q ', 'Q . . . ', '. . Q . ']
		boards.append(['. ' * i + 'Q ' + '. ' * (n - 1 - i) for i in possible_board]      )
		return

	# We iterate each column in the row to find all possible results in each row
	for col in range(lowerCamelCase__      ):
		# We apply that we learned previously. First we check that in the current board
		# (possible_board) there are not other same value because if there is it means
		# that there are a collision in vertical. Then we apply the two formulas we
		# learned before:
		#
		# 45º: y - x = b or 45: row - col = b
		# 135º: y + x = b or row + col = b.
		#
		# And we verify if the results of this two formulas not exist in their variables
		# respectively.  (diagonal_right_collisions, diagonal_left_collisions)
		#
		# If any or these are True it means there is a collision so we continue to the
		# next value in the for loop.
		if (
		    col in possible_board
		    or row - col in diagonal_right_collisions
		    or row + col in diagonal_left_collisions
		):
			continue

		# If it is False we call dfs function again and we update the inputs
		depth_first_search(
		    [*possible_board, col]     ,			[*diagonal_right_collisions, row - col]     ,			[*diagonal_left_collisions, row + col]     ,			lowerCamelCase__     ,			lowerCamelCase__     ,			)






def        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__      )  ->					None:
	__lowerCamelCase    :    list[list[str]] 	=			[]
	depth_first_search([]     ,			[]     ,			[]     ,			lowerCamelCase__     ,			lowerCamelCase__      )

	# Print all the boards
	for board in boards:
		for column in board:
			print(lowerCamelCase__      )
		print(''      )

	print(len(lowerCamelCase__      )     ,			'solutions were found.'      )


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					n_queens_solution(4)




