






'''simple docstring'''

import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, 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


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


if is_torch_available():
      from transformers.models.plbart.modeling_plbart import shift_tokens_right

UpperCamelCase      					=5_0003
UpperCamelCase      					=5_0002




@require_sentencepiece
@require_tokenizers
class      A     (   SCREAMING_SNAKE_CASE__, unittest.TestCase    ):






 """simple docstring"""





 __a      :    List[str]			  =    PLBartTokenizer
 __a      :    List[str]			  =    None
 __a      :    Optional[int]			  =    False
 def 	_UpperCAmelCase							(				self			):
       super().setUp()

       # We have a SentencePiece fixture for testing
       UpperCamelCase_					: List[str]            =				PLBartTokenizer(__lowerCAmelCase      ,  language_codes="""base"""      ,  keep_accents=__lowerCAmelCase			)
       tokenizer.save_pretrained(self.tmpdirname			)
 def 	_UpperCAmelCase							(				self			):
       UpperCamelCase_					: Optional[int]            =				PLBartTokenizer(__lowerCAmelCase      ,  language_codes="""base"""      ,  keep_accents=__lowerCAmelCase			)

       UpperCamelCase_					: Dict            =				tokenizer.tokenize("""This is a test"""			)
       self.assertListEqual(__lowerCAmelCase      ,  ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]			)

       self.assertListEqual(
           tokenizer.convert_tokens_to_ids(__lowerCAmelCase			)      ,  [value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]      ,  )

       UpperCamelCase_					: Dict            =				tokenizer.tokenize("""I was born in 92000, and this is falsé."""			)
       self.assertListEqual(
           __lowerCAmelCase      ,  [
               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""",
               """.""",
           ]      ,  )
       UpperCamelCase_					: List[str]            =				tokenizer.convert_tokens_to_ids(__lowerCAmelCase			)
       self.assertListEqual(
           __lowerCAmelCase      ,  [
               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]
           ]      ,  )

       UpperCamelCase_					: str            =				tokenizer.convert_ids_to_tokens(__lowerCAmelCase			)
       self.assertListEqual(
           __lowerCAmelCase      ,  [
               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>""",
               """.""",
           ]      ,  )

       UpperCamelCase_					: List[str]            =				tokenizer.vocab_size
       UpperCamelCase_					: Optional[int]            =				[tokenizer.convert_ids_to_tokens(__lowerCAmelCase			) for x in range(end - 4      ,  __lowerCAmelCase			)]

       self.assertListEqual(__lowerCAmelCase      ,  ["""__java__""", """__python__""", """__en_XX__""", """<mask>"""]			)

       UpperCamelCase_					: List[str]            =				"""java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"""
       UpperCamelCase_					: Dict            =				tokenizer(__lowerCAmelCase			).input_ids
       self.assertEqual(
           tokenizer.decode(__lowerCAmelCase      ,  skip_special_tokens=__lowerCAmelCase      ,  clean_up_tokenization_spaces=__lowerCAmelCase			)      ,  __lowerCAmelCase      ,  )





 def 	_UpperCAmelCase							(				self			):
       UpperCamelCase_					: Tuple            =				PLBartTokenizer(__lowerCAmelCase      ,  language_codes="""multi"""      ,  keep_accents=__lowerCAmelCase			)

       UpperCamelCase_					: Tuple            =				tokenizer.tokenize("""This is a test"""			)
       self.assertListEqual(__lowerCAmelCase      ,  ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]			)

       self.assertListEqual(
           tokenizer.convert_tokens_to_ids(__lowerCAmelCase			)      ,  [value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]      ,  )

       UpperCamelCase_					: Union[str, Any]            =				tokenizer.tokenize("""I was born in 92000, and this is falsé."""			)
       self.assertListEqual(
           __lowerCAmelCase      ,  [
               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""",
               """.""",
           ]      ,  )
       UpperCamelCase_					: Union[str, Any]            =				tokenizer.convert_tokens_to_ids(__lowerCAmelCase			)
       self.assertListEqual(
           __lowerCAmelCase      ,  [
               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]
           ]      ,  )

       UpperCamelCase_					: List[str]            =				tokenizer.convert_ids_to_tokens(__lowerCAmelCase			)
       self.assertListEqual(
           __lowerCAmelCase      ,  [
               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>""",
               """.""",
           ]      ,  )
       UpperCamelCase_					: Optional[Any]            =				tokenizer.vocab_size
       UpperCamelCase_					: str            =				[tokenizer.convert_ids_to_tokens(__lowerCAmelCase			) for x in range(end - 7      ,  __lowerCAmelCase			)]

       self.assertListEqual(
           __lowerCAmelCase      ,  ["""__java__""", """__python__""", """__en_XX__""", """__javascript__""", """__php__""", """__ruby__""", """__go__"""]			)
       UpperCamelCase_					: Optional[Any]            =				"""java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"""
       UpperCamelCase_					: Optional[int]            =				tokenizer(__lowerCAmelCase			).input_ids
       self.assertEqual(
           tokenizer.decode(__lowerCAmelCase      ,  skip_special_tokens=__lowerCAmelCase      ,  clean_up_tokenization_spaces=__lowerCAmelCase			)      ,  __lowerCAmelCase      ,  )






@require_torch
@require_sentencepiece
@require_tokenizers
class      A     (   unittest.TestCase    ):






 """simple docstring"""





 __a      :    Any			  =    '''uclanlp/plbart-python-en_XX'''
 __a      :    Tuple			  =    [
     '''def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])''',
     '''def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])''',
 ]
 __a      :    str			  =    [
     '''Returns the maximum value of a b c.''',
     '''Sums the values of a b c.''',
 ]
 __a      :    Any			  =    [
     134,
     5452,
     3_3460,
     3_3441,
     3_3463,
     3_3465,
     3_3463,
     3_3449,
     988,
     20,
     3_3456,
     19,
     3_3456,
     771,
     39,
     4258,
     889,
     3318,
     3_3441,
     3_3463,
     3_3465,
     3_3463,
     3_3449,
     2471,
     2,
     PYTHON_CODE,
 ]
 @classmethod
 def 	_UpperCAmelCase							(				cls			):
       UpperCamelCase_					: PLBartTokenizer            =				PLBartTokenizer.from_pretrained(
           cls.checkpoint_name      ,  language_codes="""base"""      ,  src_lang="""python"""      ,  tgt_lang="""en_XX"""			)
       UpperCamelCase_					: Union[str, Any]            =				1
       return cls
 def 	_UpperCAmelCase							(				self			):
       self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__java__"""]      ,  5_00_01			)
       self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__python__"""]      ,  5_00_02			)
       self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""__en_XX__"""]      ,  5_00_03			)
 def 	_UpperCAmelCase							(				self			):
       UpperCamelCase_					: List[str]            =				self.tokenizer.batch_encode_plus(self.src_text			).input_ids[0]
       self.assertListEqual(self.expected_src_tokens      ,  __lowerCAmelCase			)
 def 	_UpperCAmelCase							(				self			):
       self.assertIn(__lowerCAmelCase      ,  self.tokenizer.all_special_ids			)
       UpperCamelCase_					: List[str]            =				[EN_CODE, 90_37, 3_34_42, 57, 7_52, 1_53, 14, 56, 18, 9, 2]
       UpperCamelCase_					: Any            =				self.tokenizer.decode(__lowerCAmelCase      ,  skip_special_tokens=__lowerCAmelCase			)
       UpperCamelCase_					: Tuple            =				self.tokenizer.decode(generated_ids[1:]      ,  skip_special_tokens=__lowerCAmelCase			)
       self.assertEqual(__lowerCAmelCase      ,  __lowerCAmelCase			)
       self.assertNotIn(self.tokenizer.eos_token      ,  __lowerCAmelCase			)
 def 	_UpperCAmelCase							(				self			):
       UpperCamelCase_					: List[str]            =				["""def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])""" * 20]
       self.assertIsInstance(src_text[0]      ,  __lowerCAmelCase			)
       UpperCamelCase_					: List[str]            =				10
       UpperCamelCase_					: Optional[int]            =				self.tokenizer(__lowerCAmelCase      ,  max_length=__lowerCAmelCase      ,  truncation=__lowerCAmelCase			).input_ids[0]
       self.assertEqual(ids[-2]      ,  2			)
       self.assertEqual(ids[-1]      ,  __lowerCAmelCase			)
       self.assertEqual(len(__lowerCAmelCase			)      ,  __lowerCAmelCase			)
 def 	_UpperCAmelCase							(				self			):
       self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """__java__"""]			)      ,  [5_00_04, 5_00_01]			)
 def 	_UpperCAmelCase							(				self			):
       UpperCamelCase_					: List[str]            =				tempfile.mkdtemp()
       UpperCamelCase_					: Dict            =				self.tokenizer.fairseq_tokens_to_ids
       self.tokenizer.save_pretrained(__lowerCAmelCase			)
       UpperCamelCase_					: List[Any]            =				PLBartTokenizer.from_pretrained(__lowerCAmelCase			)
       self.assertDictEqual(new_tok.fairseq_tokens_to_ids      ,  __lowerCAmelCase			)
 @require_torch
 def 	_UpperCAmelCase							(				self			):
       UpperCamelCase_					: Optional[int]            =				self.tokenizer(self.src_text      ,  text_target=self.tgt_text      ,  padding=__lowerCAmelCase      ,  return_tensors="""pt"""			)
       UpperCamelCase_					: Union[str, Any]            =				shift_tokens_right(batch["""labels"""]      ,  self.tokenizer.pad_token_id			)

       # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
       self.assertEqual(batch.input_ids[1][-2:].tolist()      ,  [2, PYTHON_CODE]			)
       self.assertEqual(batch.decoder_input_ids[1][0]      ,  __lowerCAmelCase			)
       self.assertEqual(batch.decoder_input_ids[1][-1]      ,  2			)
       self.assertEqual(batch.labels[1][-2:].tolist()      ,  [2, EN_CODE]			)
 @require_torch
 def 	_UpperCAmelCase							(				self			):
       UpperCamelCase_					: Tuple            =				self.tokenizer(
           self.src_text      ,  text_target=self.tgt_text      ,  padding=__lowerCAmelCase      ,  truncation=__lowerCAmelCase      ,  max_length=len(self.expected_src_tokens			)      ,  return_tensors="""pt"""      ,  )
       UpperCamelCase_					: List[str]            =				shift_tokens_right(batch["""labels"""]      ,  self.tokenizer.pad_token_id			)

       self.assertIsInstance(__lowerCAmelCase      ,  __lowerCAmelCase			)

       self.assertEqual((2, 26)      ,  batch.input_ids.shape			)
       self.assertEqual((2, 26)      ,  batch.attention_mask.shape			)
       UpperCamelCase_					: Tuple            =				batch.input_ids.tolist()[0]
       self.assertListEqual(self.expected_src_tokens      ,  __lowerCAmelCase			)
       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, PYTHON_CODE]			)
 def 	_UpperCAmelCase							(				self			):
       UpperCamelCase_					: Dict            =				self.tokenizer(self.src_text      ,  padding=__lowerCAmelCase      ,  truncation=__lowerCAmelCase      ,  max_length=3      ,  return_tensors="""pt"""			)
       UpperCamelCase_					: Union[str, Any]            =				self.tokenizer(
           text_target=self.tgt_text      ,  padding=__lowerCAmelCase      ,  truncation=__lowerCAmelCase      ,  max_length=10      ,  return_tensors="""pt"""			)
       UpperCamelCase_					: List[str]            =				targets["""input_ids"""]
       UpperCamelCase_					: Dict            =				shift_tokens_right(__lowerCAmelCase      ,  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			):
       UpperCamelCase_					: Tuple            =				self.tokenizer._build_translation_inputs(
           """A test"""      ,  return_tensors="""pt"""      ,  src_lang="""en_XX"""      ,  tgt_lang="""java"""			)

       self.assertEqual(
           nested_simplify(__lowerCAmelCase			)      ,  {
               # A, test, EOS, en_XX
               """input_ids""": [[1_50, 2_42, 2, 5_00_03]],
               """attention_mask""": [[1, 1, 1, 1]],
               # java
               """forced_bos_token_id""": 5_00_01,
           }      ,  )














'''simple docstring'''

from __future__ import annotations



def 				snake_case       (  a_				:			list[int]     , a_				:			list[int]     , a_				:			list[int]     , a_				:			list[list[str]]     , a_				:			int     , )							->					None:





      """simple docstring"""

      UpperCamelCase_					: List[Any]            =				len(a_						)

      # 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(a_						):
            # 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]     , a_     , a_     , )



def 				snake_case       (  a_				:			int						)							->					None:





      """simple docstring"""

      UpperCamelCase_					: list[list[str]]            =				[]
      depth_first_search([]     , []     , []     , a_     , a_						)

      # Print all the boards
      for board in boards:
            for column in board:
                  print(a_						)
            print(""""""						)

      print(len(a_						)     , """solutions were found."""						)


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      n_queens_solution(4)






