





'''simple docstring'''

import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available


if is_sentencepiece_available():
    from transformers.models.marian.tokenization_marian import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


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

a   	=    {"target_lang": "fi", "source_lang": "en"}
a   	=    ">>zh<<"
a   	=    "Helsinki-NLP/"

if is_torch_available():
    a   	=    "pt"
elif is_tf_available():
    a   	=    "tf"
else:
    a   	=    "jax"







@require_sentencepiece
class __a			( _snake_case, unittest.TestCase      ):
   __UpperCamelCase :			List[str]						   =						MarianTokenizer
   __UpperCamelCase :			List[str]						   =						False
   __UpperCamelCase :			int						   =						True





   def   UpperCAmelCase__  (       self					:      int     ):

      '''simple docstring'''

      super().setUp()
      __SCREAMING_SNAKE_CASE   				=							["""</s>""", """<unk>""", """▁This""", """▁is""", """▁a""", """▁t""", """est""", """\u0120""", """<pad>"""]
      __SCREAMING_SNAKE_CASE   				=							dict(zip(lowerCamelCase					,range(len(lowerCamelCase     )     )     )     )
      __SCREAMING_SNAKE_CASE   				=							Path(self.tmpdirname     )
      save_json(lowerCamelCase					,save_dir / VOCAB_FILES_NAMES["""vocab"""]     )
      save_json(lowerCamelCase					,save_dir / VOCAB_FILES_NAMES["""tokenizer_config_file"""]     )
      if not (save_dir / VOCAB_FILES_NAMES["source_spm"]).exists():
         copyfile(lowerCamelCase					,save_dir / VOCAB_FILES_NAMES["""source_spm"""]     )
         copyfile(lowerCamelCase					,save_dir / VOCAB_FILES_NAMES["""target_spm"""]     )

      __SCREAMING_SNAKE_CASE   				=							MarianTokenizer.from_pretrained(self.tmpdirname     )
      tokenizer.save_pretrained(self.tmpdirname     )





   def   UpperCAmelCase__  (       self					:      Any					,**lowerCamelCase					:      List[Any]     ):

      '''simple docstring'''

      return MarianTokenizer.from_pretrained(self.tmpdirname					,**lowerCamelCase     )





   def   UpperCAmelCase__  (       self					:      Any					,lowerCamelCase					:      str     ):

      '''simple docstring'''

      return (
          "This is a test",
          "This is a test",
      )





   def   UpperCAmelCase__  (       self					:      Tuple     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							"""</s>"""
      __SCREAMING_SNAKE_CASE   				=							0

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





   def   UpperCAmelCase__  (       self					:      Union[str, Any]     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							list(self.get_tokenizer().get_vocab().keys()     )

      self.assertEqual(vocab_keys[0]					,"""</s>"""     )
      self.assertEqual(vocab_keys[1]					,"""<unk>"""     )
      self.assertEqual(vocab_keys[-1]					,"""<pad>"""     )
      self.assertEqual(len(lowerCamelCase     )					,9     )





   def   UpperCAmelCase__  (       self					:      Union[str, Any]     ):

      '''simple docstring'''

      self.assertEqual(self.get_tokenizer().vocab_size					,9     )





   def   UpperCAmelCase__  (       self					:      Any     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							MarianTokenizer.from_pretrained(f"""{ORG_NAME}opus-mt-en-de"""     )
      __SCREAMING_SNAKE_CASE   				=							en_de_tokenizer(["""I am a small frog"""]					,return_tensors=lowerCamelCase     )
      self.assertIsInstance(lowerCamelCase					,lowerCamelCase     )
      __SCREAMING_SNAKE_CASE   				=							[38, 121, 14, 697, 3_8848, 0]
      self.assertListEqual(lowerCamelCase					,batch.input_ids[0]     )

      __SCREAMING_SNAKE_CASE   				=							tempfile.mkdtemp()
      en_de_tokenizer.save_pretrained(lowerCamelCase     )
      __SCREAMING_SNAKE_CASE   				=							[x.name for x in Path(lowerCamelCase     ).glob("""*"""     )]
      self.assertIn("""source.spm"""					,lowerCamelCase     )
      MarianTokenizer.from_pretrained(lowerCamelCase     )





   def   UpperCAmelCase__  (       self					:      Dict     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							self.get_tokenizer()

      __SCREAMING_SNAKE_CASE   				=							tok(
          ["""I am a small frog""" * 1000, """I am a small frog"""]					,padding=lowerCamelCase					,truncation=lowerCamelCase					,return_tensors=lowerCamelCase     )
      self.assertIsInstance(lowerCamelCase					,lowerCamelCase     )
      self.assertEqual(batch.input_ids.shape					,(2, 512)     )





   def   UpperCAmelCase__  (       self					:      Optional[Any]     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							self.get_tokenizer()
      __SCREAMING_SNAKE_CASE   				=							tok(["""I am a tiny frog""", """I am a small frog"""]					,padding=lowerCamelCase					,return_tensors=lowerCamelCase     )
      self.assertIsInstance(lowerCamelCase					,lowerCamelCase     )
      self.assertEqual(batch_smaller.input_ids.shape					,(2, 10)     )





   @slow
   def   UpperCAmelCase__  (       self					:      str     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							{"""input_ids""": [[4_3495, 462, 20, 4_2164, 1369, 52, 464, 132, 1703, 492, 13, 7491, 3_8999, 6, 8, 464, 132, 1703, 492, 13, 4669, 3_7867, 13, 7525, 27, 1593, 988, 13, 3_3972, 7029, 6, 20, 8251, 383, 2, 270, 5866, 3788, 2, 2353, 8251, 1_2338, 2, 1_3958, 387, 2, 3629, 6953, 188, 2900, 2, 1_3958, 8011, 1_1501, 23, 8460, 4073, 3_4009, 20, 435, 1_1439, 27, 8, 8460, 4073, 6004, 20, 9988, 375, 27, 33, 266, 1945, 1076, 1350, 3_7867, 3288, 5, 577, 1076, 4374, 8, 5082, 5, 2_6453, 257, 556, 403, 2, 242, 132, 383, 316, 492, 8, 1_0767, 6, 316, 304, 4239, 3, 0], [148, 1_5722, 19, 1839, 12, 1350, 13, 2_2327, 5082, 5418, 4_7567, 3_5938, 59, 318, 1_9552, 108, 2183, 54, 1_4976, 4835, 32, 547, 1114, 8, 315, 2417, 5, 92, 1_9088, 3, 0, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100], [36, 6395, 1_2570, 3_9147, 1_1597, 6, 266, 4, 4_5405, 7296, 3, 0, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100, 5_8100]], """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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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=lowerCamelCase					,model_name="""Helsinki-NLP/opus-mt-en-de"""					,revision="""1a8c2263da11e68e50938f97e10cd57820bd504c"""					,decode_kwargs={"""use_source_tokenizer""": True}					,)





   def   UpperCAmelCase__  (       self					:      Tuple     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							MarianTokenizer.from_pretrained("""hf-internal-testing/test-marian-two-vocabs"""     )

      __SCREAMING_SNAKE_CASE   				=							"""Tämä on testi"""
      __SCREAMING_SNAKE_CASE   				=							"""This is a test"""

      __SCREAMING_SNAKE_CASE   				=							[76, 7, 2047, 2]
      __SCREAMING_SNAKE_CASE   				=							[69, 12, 11, 940, 2]

      __SCREAMING_SNAKE_CASE   				=							tokenizer(lowerCamelCase     ).input_ids
      self.assertListEqual(lowerCamelCase					,lowerCamelCase     )

      __SCREAMING_SNAKE_CASE   				=							tokenizer(text_target=lowerCamelCase     ).input_ids
      self.assertListEqual(lowerCamelCase					,lowerCamelCase     )

      __SCREAMING_SNAKE_CASE   				=							tokenizer.decode(lowerCamelCase					,skip_special_tokens=lowerCamelCase     )
      self.assertEqual(lowerCamelCase					,lowerCamelCase     )












'''simple docstring'''

from __future__ import annotations







class __a			:





   def __init__(       self					:      Optional[int]					,lowerCamelCase					:      list[list[int]]     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							TypeError(
          """Matrices must be formed from a list of zero or more lists containing at """
          """least one and the same number of values, each of which must be of type """
          """int or float."""     )
      if len(lowerCamelCase     ) != 0:
         __SCREAMING_SNAKE_CASE   				=							len(rows[0]     )
         if cols == 0:
            raise error
         for row in rows:
            if len(lowerCamelCase     ) != cols:
               raise error
            for value in row:
               if not isinstance(lowerCamelCase					,(int, float)     ):
                  raise error
         __SCREAMING_SNAKE_CASE   				=							rows
      else:
         __SCREAMING_SNAKE_CASE   				=							[]





   def   UpperCAmelCase__  (       self					:      Optional[Any]     ):

      '''simple docstring'''

      return [[row[i] for row in self.rows] for i in range(len(self.rows[0]     )     )]





   @property
   def   UpperCAmelCase__  (       self					:      Any     ):

      '''simple docstring'''

      return len(self.rows     )





   @property
   def   UpperCAmelCase__  (       self					:      Union[str, Any]     ):

      '''simple docstring'''

      return len(self.rows[0]     )





   @property
   def   UpperCAmelCase__  (       self					:      Dict     ):

      '''simple docstring'''

      return (self.num_rows, self.num_columns)





   @property
   def   UpperCAmelCase__  (       self					:      int     ):

      '''simple docstring'''

      return self.order[0] == self.order[1]





   def   UpperCAmelCase__  (       self					:      List[str]     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							[
          [0 if column_num != row_num else 1 for column_num in range(self.num_rows     )]
          for row_num in range(self.num_rows     )
      ]
      return Matrix(lowerCamelCase     )





   def   UpperCAmelCase__  (       self					:      str     ):

      '''simple docstring'''

      if not self.is_square:
         return 0
      if self.order == (0, 0):
         return 1
      if self.order == (1, 1):
         return int(self.rows[0][0]     )
      if self.order == (2, 2):
         return int(
             (self.rows[0][0] * self.rows[1][1])
             - (self.rows[0][1] * self.rows[1][0])     )
      else:
         return sum(
             self.rows[0][column] * self.cofactors().rows[0][column]
             for column in range(self.num_columns     )     )





   def   UpperCAmelCase__  (       self					:      Any     ):

      '''simple docstring'''

      return bool(self.determinant()     )





   def   UpperCAmelCase__  (       self					:      Union[str, Any]					,lowerCamelCase					:      int					,lowerCamelCase					:      int     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							[
          [
              self.rows[other_row][other_column]
              for other_column in range(self.num_columns     )
              if other_column != column
          ]
          for other_row in range(self.num_rows     )
          if other_row != row
      ]
      return Matrix(lowerCamelCase     ).determinant()





   def   UpperCAmelCase__  (       self					:      str					,lowerCamelCase					:      int					,lowerCamelCase					:      int     ):

      '''simple docstring'''

      if (row + column) % 2 == 0:
         return self.get_minor(lowerCamelCase					,lowerCamelCase     )
      return -1 * self.get_minor(lowerCamelCase					,lowerCamelCase     )





   def   UpperCAmelCase__  (       self					:      List[Any]     ):

      '''simple docstring'''

      return Matrix(
          [
              [self.get_minor(lowerCamelCase					,lowerCamelCase     ) for column in range(self.num_columns     )]
              for row in range(self.num_rows     )
          ]     )





   def   UpperCAmelCase__  (       self					:      int     ):

      '''simple docstring'''

      return Matrix(
          [
              [
                  self.minors().rows[row][column]
                  if (row + column) % 2 == 0
                  else self.minors().rows[row][column] * -1
                  for column in range(self.minors().num_columns     )
              ]
              for row in range(self.minors().num_rows     )
          ]     )





   def   UpperCAmelCase__  (       self					:      int     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							[
          [self.cofactors().rows[column][row] for column in range(self.num_columns     )]
          for row in range(self.num_rows     )
      ]
      return Matrix(lowerCamelCase     )





   def   UpperCAmelCase__  (       self					:      Optional[int]     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							self.determinant()
      if not determinant:
         raise TypeError("""Only matrices with a non-zero determinant have an inverse"""     )
      return self.adjugate() * (1 / determinant)





   def __repr__(       self					:      List[Any]     ):

      '''simple docstring'''

      return str(self.rows     )





   def __str__(       self					:      List[str]     ):

      '''simple docstring'''

      if self.num_rows == 0:
         return "[]"
      if self.num_rows == 1:
         return "[[" + ". ".join(str(self.rows[0]     )     ) + "]]"
      return (
          "["
          + "\n ".join(
              [
                  """[""" + """. """.join([str(lowerCamelCase     ) for value in row]     ) + """.]"""
                  for row in self.rows
              ]     )
          + "]"
      )





   def   UpperCAmelCase__  (       self					:      Dict					,lowerCamelCase					:      list[int]					,lowerCamelCase					:      int | None = None     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							TypeError("""Row must be a list containing all ints and/or floats"""     )
      if not isinstance(lowerCamelCase					,lowerCamelCase     ):
         raise type_error
      for value in row:
         if not isinstance(lowerCamelCase					,(int, float)     ):
            raise type_error
      if len(lowerCamelCase     ) != self.num_columns:
         raise ValueError(
             """Row must be equal in length to the other rows in the matrix"""     )
      if position is None:
         self.rows.append(lowerCamelCase     )
      else:
         __SCREAMING_SNAKE_CASE   				=							self.rows[0:position] + [row] + self.rows[position:]





   def   UpperCAmelCase__  (       self					:      Tuple					,lowerCamelCase					:      list[int]					,lowerCamelCase					:      int | None = None     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							TypeError(
          """Column must be a list containing all ints and/or floats"""     )
      if not isinstance(lowerCamelCase					,lowerCamelCase     ):
         raise type_error
      for value in column:
         if not isinstance(lowerCamelCase					,(int, float)     ):
            raise type_error
      if len(lowerCamelCase     ) != self.num_rows:
         raise ValueError(
             """Column must be equal in length to the other columns in the matrix"""     )
      if position is None:
         __SCREAMING_SNAKE_CASE   				=							[self.rows[i] + [column[i]] for i in range(self.num_rows     )]
      else:
         __SCREAMING_SNAKE_CASE   				=							[
             self.rows[i][0:position] + [column[i]] + self.rows[i][position:]
             for i in range(self.num_rows     )
         ]





   def __eq__(       self					:      int					,lowerCamelCase					:      object     ):

      '''simple docstring'''

      if not isinstance(lowerCamelCase					,lowerCamelCase     ):
         return NotImplemented
      return self.rows == other.rows





   def __ne__(       self					:      Any					,lowerCamelCase					:      object     ):

      '''simple docstring'''

      return not self == other





   def __neg__(       self					:      Any     ):

      '''simple docstring'''

      return self * -1





   def __add__(       self					:      List[Any]					,lowerCamelCase					:      Matrix     ):

      '''simple docstring'''

      if self.order != other.order:
         raise ValueError("""Addition requires matrices of the same order"""     )
      return Matrix(
          [
              [self.rows[i][j] + other.rows[i][j] for j in range(self.num_columns     )]
              for i in range(self.num_rows     )
          ]     )





   def __sub__(       self					:      Any					,lowerCamelCase					:      Matrix     ):

      '''simple docstring'''

      if self.order != other.order:
         raise ValueError("""Subtraction requires matrices of the same order"""     )
      return Matrix(
          [
              [self.rows[i][j] - other.rows[i][j] for j in range(self.num_columns     )]
              for i in range(self.num_rows     )
          ]     )





   def __mul__(       self					:      Any					,lowerCamelCase					:      Matrix | int | float     ):

      '''simple docstring'''

      if isinstance(lowerCamelCase					,(int, float)     ):
         return Matrix(
             [[int(element * other     ) for element in row] for row in self.rows]     )
      elif isinstance(lowerCamelCase					,lowerCamelCase     ):
         if self.num_columns != other.num_rows:
            raise ValueError(
                """The number of columns in the first matrix must """
                """be equal to the number of rows in the second"""     )
         return Matrix(
             [
                 [Matrix.dot_product(lowerCamelCase					,lowerCamelCase     ) for column in other.columns()]
                 for row in self.rows
             ]     )
      else:
         raise TypeError(
             """A Matrix can only be multiplied by an int, float, or another matrix"""     )





   def __pow__(       self					:      Optional[int]					,lowerCamelCase					:      int     ):

      '''simple docstring'''

      if not isinstance(lowerCamelCase					,lowerCamelCase     ):
         raise TypeError("""A Matrix can only be raised to the power of an int"""     )
      if not self.is_square:
         raise ValueError("""Only square matrices can be raised to a power"""     )
      if other == 0:
         return self.identity()
      if other < 0:
         if self.is_invertable():
            return self.inverse() ** (-other)
         raise ValueError(
             """Only invertable matrices can be raised to a negative power"""     )
      __SCREAMING_SNAKE_CASE   				=							self
      for _ in range(other - 1     ):
         result *= self
      return result





   @classmethod
   def   UpperCAmelCase__  (       cls					:      str					,lowerCamelCase					:      list[int]					,lowerCamelCase					:      list[int]     ):

      '''simple docstring'''

      return sum(row[i] * column[i] for i in range(len(lowerCamelCase     )     )     )


if __name__ == "__main__":
    import doctest

    doctest.testmod()





