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

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

SCREAMING_SNAKE_CASE							:str							 =				25_0004
SCREAMING_SNAKE_CASE							:Dict							 =				25_0020





@require_sentencepiece
@require_tokenizers
class 							UpperCAmelCase      (  A_			,			unittest.TestCase  ):




	'''simple docstring'''





	snake_case_					    =     MBartaaTokenizer
	snake_case_					    =     MBartaaTokenizerFast
	snake_case_					    =     True
	snake_case_					    =     True






	def 				UpperCamelCase_  (       self					: int ):
					super().setUp()

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






	def 				UpperCamelCase_  (       self					: List[str] ):
					__A   			= "<s>"
					__A   			= 0

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






	def 				UpperCamelCase_  (       self					: str ):
					__A   			= 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(snake_case__ )							,10_54 )






	def 				UpperCamelCase_  (       self					: int ):
					self.assertEqual(self.get_tokenizer().vocab_size							,10_54 )






	def 				UpperCamelCase_  (       self					: Any ):
					__A   			= MBartaaTokenizer(snake_case__							,src_lang="en_XX"							,tgt_lang="ro_RO"							,keep_accents=snake_case__ )

					__A   			= 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 [2_85, 46, 10, 1_70, 3_82]]							,)

					__A   			= 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", "."]							,)
					__A   			= 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, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
					    ]							,)

					__A   			= 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>", "."]							,)






	@slow
	def 				UpperCamelCase_  (       self					: Union[str, Any] ):
					__A   			= {"input_ids": [[25_00_04, 1_10_62, 8_27_72, 7, 15, 8_27_72, 5_38, 5_15_29, 2_37, 1_71_98, 12_90, 2_06, 9, 21_51_75, 13_14, 1_36, 1_71_98, 12_90, 2_06, 9, 5_63_59, 42, 12_20_09, 9, 1_64_66, 16, 8_73_44, 45_37, 9, 47_17, 7_83_81, 6, 15_99_58, 7, 15, 2_44_80, 6_18, 4, 5_27, 2_26_93, 54_28, 4, 27_77, 2_44_80, 98_74, 4, 4_35_23, 5_94, 4, 8_03, 1_83_92, 3_31_89, 18, 4, 4_35_23, 2_44_47, 1_23_99, 1_00, 2_49_55, 8_36_58, 96_26, 14_40_57, 15, 8_39, 2_23_35, 16, 1_36, 2_49_55, 8_36_58, 8_34_79, 15, 3_91_02, 7_24, 16, 6_78, 6_45, 27_89, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 8_05, 13_28, 4_68_76, 7, 1_36, 5_38_94, 19_40, 4_22_27, 4_11_59, 1_77_21, 8_23, 4_25, 4, 2_75_12, 9_87_22, 2_06, 1_36, 55_31, 49_70, 9_19, 1_73_36, 5, 2], [25_00_04, 2_00_80, 6_18, 83, 8_27_75, 47, 4_79, 9, 15_17, 73, 5_38_94, 3_33, 8_05_81, 11_01_17, 1_88_11, 52_56, 12_95, 51, 15_25_26, 2_97, 79_86, 3_90, 12_44_16, 5_38, 3_54_31, 2_14, 98, 1_50_44, 2_57_37, 1_36, 71_08, 4_37_01, 23, 7_56, 13_53_55, 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], [25_00_04, 5_81, 6_37_73, 11_94_55, 6, 14_77_97, 8_82_03, 7, 6_45, 70, 21, 32_85, 1_02_69, 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=snake_case__							,model_name="facebook/mbart-large-50"							,revision="d3913889c59cd5c9e456b269c376325eabad57e2"							,)







	def 				UpperCamelCase_  (       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

					__A   			= (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})''' ):
													__A   			= self.rust_tokenizer_class.from_pretrained(snake_case__							,**snake_case__ )
													__A   			= self.tokenizer_class.from_pretrained(snake_case__							,**snake_case__ )

													__A   			= tempfile.mkdtemp()

													__A   			= tokenizer_r.save_pretrained(snake_case__ )
													__A   			= 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 ) )
													__A   			= 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
													__A   			= tokenizer_r.from_pretrained(snake_case__ )
													__A   			= 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
													__A   			= tempfile.mkdtemp()

													__A   			= tokenizer_r.save_pretrained(snake_case__							,legacy_format=snake_case__ )
													__A   			= 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
													__A   			= tokenizer_r.from_pretrained(snake_case__ )
													__A   			= 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
													__A   			= tempfile.mkdtemp()

													__A   			= tokenizer_r.save_pretrained(snake_case__							,legacy_format=snake_case__ )
													__A   			= 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
													__A   			= tokenizer_r.from_pretrained(snake_case__ )
													__A   			= 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 							UpperCAmelCase      (  unittest.TestCase  ):




	'''simple docstring'''





	snake_case_					    =     "facebook/mbart-large-50-one-to-many-mmt"
	snake_case_					    =     [
	    " 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_					    =     [
	    "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_					    =     [EN_CODE, 8274, 127873, 25916, 7, 8622, 2071, 438, 67485, 53, 187895, 23, 51712, 2]






	@classmethod
	def 				UpperCamelCase_  (       cls					: Optional[int] ):
					__A   			= MBartaaTokenizer.from_pretrained(
					    cls.checkpoint_name							,src_lang="en_XX"							,tgt_lang="ro_RO" )
					__A   			= 1
					return cls






	def 				UpperCamelCase_  (       self					: int ):
					self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ar_AR"]							,25_00_01 )
					self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["en_EN"]							,25_00_04 )
					self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ro_RO"]							,25_00_20 )
					self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["mr_IN"]							,25_00_38 )






	def 				UpperCamelCase_  (       self					: int ):
					__A   			= self.tokenizer.batch_encode_plus(self.src_text ).input_ids[0]
					self.assertListEqual(self.expected_src_tokens							,snake_case__ )






	def 				UpperCamelCase_  (       self					: List[str] ):
					self.assertIn(snake_case__							,self.tokenizer.all_special_ids )
					__A   			= [RO_CODE, 8_84, 90_19, 96, 9, 9_16, 8_67_92, 36, 1_87_43, 1_55_96, 5, 2]
					__A   			= self.tokenizer.decode(snake_case__							,skip_special_tokens=snake_case__ )
					__A   			= 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 				UpperCamelCase_  (       self					: Optional[Any] ):
					__A   			= ["this is gunna be a long sentence " * 20]
					assert isinstance(src_text[0]							,snake_case__ )
					__A   			= 10
					__A   			= self.tokenizer(snake_case__							,max_length=snake_case__							,truncation=snake_case__ ).input_ids[0]
					self.assertEqual(ids[0]							,snake_case__ )
					self.assertEqual(ids[-1]							,2 )
					self.assertEqual(len(snake_case__ )							,snake_case__ )






	def 				UpperCamelCase_  (       self					: str ):
					self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"] )							,[25_00_53, 25_00_01] )






	def 				UpperCamelCase_  (       self					: Optional[Any] ):
					__A   			= tempfile.mkdtemp()
					__A   			= self.tokenizer.fairseq_tokens_to_ids
					self.tokenizer.save_pretrained(snake_case__ )
					__A   			= MBartaaTokenizer.from_pretrained(snake_case__ )
					self.assertDictEqual(new_tok.fairseq_tokens_to_ids							,snake_case__ )






	@require_torch
	def 				UpperCamelCase_  (       self					: Optional[int] ):
					__A   			= self.tokenizer(self.src_text							,text_target=self.tgt_text							,padding=snake_case__							,return_tensors="pt" )
					__A   			= 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					: Union[str, Any] ):
					__A   			= 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"							,)
					__A   			= 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 )
					__A   			= batch.input_ids.tolist()[0]
					self.assertListEqual(self.expected_src_tokens							,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 				UpperCamelCase_  (       self					: List[Any] ):
					__A   			= self.tokenizer(self.src_text							,padding=snake_case__							,truncation=snake_case__							,max_length=3							,return_tensors="pt" )
					__A   			= self.tokenizer(
					    text_target=self.tgt_text							,padding=snake_case__							,truncation=snake_case__							,max_length=10							,return_tensors="pt" )
					__A   			= targets["input_ids"]
					__A   			= 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 				UpperCamelCase_  (       self					: Optional[Any] ):
					__A   			= self.tokenizer._build_translation_inputs(
					    "A test"							,return_tensors="pt"							,src_lang="en_XX"							,tgt_lang="ar_AR" )

					self.assertEqual(
					    nested_simplify(snake_case__ )							,{
					        # en_XX, A, test, EOS
					        "input_ids": [[25_00_04, 62, 30_34, 2]],
					        "attention_mask": [[1, 1, 1, 1]],
					        # ar_AR
					        "forced_bos_token_id": 25_00_01,
					    }							,)


from __future__ import annotations

__lowerCamelCase							=       list[list[int]]

# assigning initial values to the grid
__lowerCamelCase							=       [
    [3, 0, 6, 5, 0, 8, 4, 0, 0],
    [5, 2, 0, 0, 0, 0, 0, 0, 0],
    [0, 8, 7, 0, 0, 0, 0, 3, 1],
    [0, 0, 3, 0, 1, 0, 0, 8, 0],
    [9, 0, 0, 8, 6, 3, 0, 0, 5],
    [0, 5, 0, 0, 9, 0, 6, 0, 0],
    [1, 3, 0, 0, 0, 0, 2, 5, 0],
    [0, 0, 0, 0, 0, 0, 0, 7, 4],
    [0, 0, 5, 2, 0, 6, 3, 0, 0],
]

# a grid with no solution
__lowerCamelCase							=       [
    [5, 0, 6, 5, 0, 8, 4, 0, 3],
    [5, 2, 0, 0, 0, 0, 0, 0, 2],
    [1, 8, 7, 0, 0, 0, 0, 3, 1],
    [0, 0, 3, 0, 1, 0, 0, 8, 0],
    [9, 0, 0, 8, 6, 3, 0, 0, 5],
    [0, 5, 0, 0, 9, 0, 6, 0, 0],
    [1, 3, 0, 0, 0, 0, 2, 5, 0],
    [0, 0, 0, 0, 0, 0, 0, 7, 4],
    [0, 0, 5, 2, 0, 6, 3, 0, 0],
]


def 			UpperCamelCase					(    __lowerCamelCase     : Matrix				,					__lowerCamelCase     : int				,					__lowerCamelCase     : int				,					__lowerCamelCase     : int    ):
       for i in range(9    ):
              if grid[row][i] == n or grid[i][column] == n:
                     return False

       for i in range(3    ):
              for j in range(3    ):
                     if grid[(row - row % 3) + i][(column - column % 3) + j] == n:
                            return False

       return True


def 			UpperCamelCase					(    __lowerCamelCase     : Matrix    ):
       for i in range(9    ):
              for j in range(9    ):
                     if grid[i][j] == 0:
                            return i, j
       return None


def 			UpperCamelCase					(    __lowerCamelCase     : Matrix    ):
       if location := find_empty_location(__lowerCamelCase    ):
              snake_case				,					snake_case       :   Union[str, Any]							=      location
       else:
              # If the location is ``None``, then the grid is solved.
              return grid

       for digit in range(1				,					10    ):
              if is_safe(__lowerCamelCase				,					__lowerCamelCase				,					__lowerCamelCase				,					__lowerCamelCase    ):
                     snake_case       :   List[Any]							=      digit

                     if sudoku(__lowerCamelCase    ) is not None:
                            return grid

                     snake_case       :   Union[str, Any]							=      0

       return None


def 			UpperCamelCase					(    __lowerCamelCase     : Matrix    ):
       for row in grid:
              for cell in row:
                     print(__lowerCamelCase				,					end=" "    )
              print()


if __name__ == "__main__":
   # make a copy of grid so that you can compare with the unmodified grid
   for example_grid in (initial_grid, no_solution):
      print("""\nExample grid:\n""" + """=""" * 20)
      print_solution(example_grid)
      print("""\nExample grid solution:""")
      __lowerCamelCase							=       sudoku(example_grid)
      if solution is not None:
         print_solution(solution)
      else:
         print("""Cannot find a solution.""")





