
import json
import os
import unittest

from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class        UpperCAmelCase_			( __lowercase  ,       unittest.TestCase     ):


  '''simple docstring'''







  a__           =		LEDTokenizer
  a__           =		LEDTokenizerFast
  a__           =		True
  def 							_lowercase							( self			: Optional[Any]    )			->	str:







    """simple docstring"""






    super().setUp()
    __magic_name__				     =       [
        """l""",
        """o""",
        """w""",
        """e""",
        """r""",
        """s""",
        """t""",
        """i""",
        """d""",
        """n""",
        """\u0120""",
        """\u0120l""",
        """\u0120n""",
        """\u0120lo""",
        """\u0120low""",
        """er""",
        """\u0120lowest""",
        """\u0120newer""",
        """\u0120wider""",
        """<unk>""",
    ]
    __magic_name__				     =       dict(zip(UpperCAmelCase__			,							range(len(UpperCAmelCase__    )    )    )    )
    __magic_name__				     =       ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
    __magic_name__				     =       {"""unk_token""": """<unk>"""}

    __magic_name__				     =       os.path.join(self.tmpdirname			,							VOCAB_FILES_NAMES["""vocab_file"""]    )
    __magic_name__				     =       os.path.join(self.tmpdirname			,							VOCAB_FILES_NAMES["""merges_file"""]    )
    with open(self.vocab_file			,							"""w"""			,							encoding="""utf-8"""    ) as fp:
      fp.write(json.dumps(UpperCAmelCase__    ) + """\n"""    )
    with open(self.merges_file			,							"""w"""			,							encoding="""utf-8"""    ) as fp:
      fp.write("""\n""".join(UpperCAmelCase__    )    )
  def 							_lowercase							( self			: Dict			,							**UpperCamelCase__			: Optional[Any]    )			->	Dict:







    """simple docstring"""






    kwargs.update(self.special_tokens_map    )
    return self.tokenizer_class.from_pretrained(self.tmpdirname			,							**UpperCAmelCase__    )
  def 							_lowercase							( self			: Optional[int]			,							**UpperCamelCase__			: Optional[int]    )			->	List[str]:







    """simple docstring"""






    kwargs.update(self.special_tokens_map    )
    return self.rust_tokenizer_class.from_pretrained(self.tmpdirname			,							**UpperCAmelCase__    )
  def 							_lowercase							( self			: Any			,							UpperCamelCase__			: Any    )			->	int:







    """simple docstring"""






    return "lower newer", "lower newer"
  @cached_property
  def 							_lowercase							( self			: int    )			->	List[Any]:







    """simple docstring"""






    return LEDTokenizer.from_pretrained("""allenai/led-base-16384"""    )
  @cached_property
  def 							_lowercase							( self			: List[Any]    )			->	Tuple:







    """simple docstring"""






    return LEDTokenizerFast.from_pretrained("""allenai/led-base-16384"""    )
  @require_torch
  def 							_lowercase							( self			: Any    )			->	Any:







    """simple docstring"""






    __magic_name__				     =       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
    __magic_name__				     =       [0, 250, 251, 1_7818, 13, 3_9186, 1938, 4, 2]

    for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
      __magic_name__				     =       tokenizer(UpperCAmelCase__			,							max_length=len(UpperCAmelCase__    )			,							padding=UpperCAmelCase__			,							return_tensors="""pt"""    )
      self.assertIsInstance(UpperCAmelCase__			,							UpperCAmelCase__    )

      self.assertEqual((2, 9)			,							batch.input_ids.shape    )
      self.assertEqual((2, 9)			,							batch.attention_mask.shape    )
      __magic_name__				     =       batch.input_ids.tolist()[0]
      self.assertListEqual(UpperCAmelCase__			,							UpperCAmelCase__    )
  @require_torch
  def 							_lowercase							( self			: List[Any]    )			->	Optional[int]:







    """simple docstring"""






    __magic_name__				     =       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
    for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
      __magic_name__				     =       tokenizer(UpperCAmelCase__			,							padding=UpperCAmelCase__			,							return_tensors="""pt"""    )
      self.assertIn("""input_ids"""			,							UpperCAmelCase__    )
      self.assertIn("""attention_mask"""			,							UpperCAmelCase__    )
      self.assertNotIn("""labels"""			,							UpperCAmelCase__    )
      self.assertNotIn("""decoder_attention_mask"""			,							UpperCAmelCase__    )
  @require_torch
  def 							_lowercase							( self			: Optional[int]    )			->	Optional[int]:







    """simple docstring"""






    __magic_name__				     =       [
        """Summary of the text.""",
        """Another summary.""",
    ]
    for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
      __magic_name__				     =       tokenizer(text_target=UpperCAmelCase__			,							max_length=32			,							padding="""max_length"""			,							return_tensors="""pt"""    )
      self.assertEqual(32			,							targets["""input_ids"""].shape[1]    )
  @require_torch
  def 							_lowercase							( self			: Any    )			->	Any:







    """simple docstring"""






    for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
      __magic_name__				     =       tokenizer(
          ["""I am a small frog""" * 1024, """I am a small frog"""]			,							padding=UpperCAmelCase__			,							truncation=UpperCAmelCase__			,							return_tensors="""pt"""    )
      self.assertIsInstance(UpperCAmelCase__			,							UpperCAmelCase__    )
      self.assertEqual(batch.input_ids.shape			,							(2, 5122)    )
  @require_torch
  def 							_lowercase							( self			: str    )			->	List[Any]:







    """simple docstring"""






    __magic_name__				     =       ["""A long paragraph for summarization."""]
    __magic_name__				     =       [
        """Summary of the text.""",
    ]
    for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
      __magic_name__				     =       tokenizer(UpperCAmelCase__			,							return_tensors="""pt"""    )
      __magic_name__				     =       tokenizer(text_target=UpperCAmelCase__			,							return_tensors="""pt"""    )
      __magic_name__				     =       inputs["""input_ids"""]
      __magic_name__				     =       targets["""input_ids"""]
      self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()    )
      self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()    )
      self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()    )
      self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()    )
  @require_torch
  def 							_lowercase							( self			: Dict    )			->	Optional[int]:







    """simple docstring"""






    for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
      __magic_name__				     =       ["""Summary of the text.""", """Another summary."""]
      __magic_name__				     =       [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

      __magic_name__				     =       tokenizer(UpperCAmelCase__			,							padding=UpperCAmelCase__    )
      __magic_name__				     =       [[0] * len(UpperCAmelCase__    ) for x in encoded_output["""input_ids"""]]
      __magic_name__				     =       tokenizer.pad(UpperCAmelCase__    )
      self.assertSequenceEqual(outputs["""global_attention_mask"""]			,							UpperCAmelCase__    )
  def 							_lowercase							( self			: str    )			->	Optional[int]:







    """simple docstring"""






    pass





  def 							_lowercase							( self			: str    )			->	Tuple:







    """simple docstring"""






    for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
      with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''    ):
        __magic_name__				     =       self.rust_tokenizer_class.from_pretrained(UpperCAmelCase__			,							**UpperCAmelCase__    )
        __magic_name__				     =       self.tokenizer_class.from_pretrained(UpperCAmelCase__			,							**UpperCAmelCase__    )
        __magic_name__				     =       """A, <mask> AllenNLP sentence."""
        __magic_name__				     =       tokenizer_r.encode_plus(UpperCAmelCase__			,							add_special_tokens=UpperCAmelCase__			,							return_token_type_ids=UpperCAmelCase__    )
        __magic_name__				     =       tokenizer_p.encode_plus(UpperCAmelCase__			,							add_special_tokens=UpperCAmelCase__			,							return_token_type_ids=UpperCAmelCase__    )
        self.assertEqual(sum(tokens_r["""token_type_ids"""]    )			,							sum(tokens_p["""token_type_ids"""]    )    )
        self.assertEqual(
            sum(tokens_r["""attention_mask"""]    ) / len(tokens_r["""attention_mask"""]    )			,							sum(tokens_p["""attention_mask"""]    ) / len(tokens_p["""attention_mask"""]    )			,							)

        __magic_name__				     =       tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]    )
        __magic_name__				     =       tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]    )
        self.assertSequenceEqual(tokens_p["""input_ids"""]			,							[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]    )
        self.assertSequenceEqual(tokens_r["""input_ids"""]			,							[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]    )

        self.assertSequenceEqual(
            UpperCAmelCase__			,							["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]    )
        self.assertSequenceEqual(
            UpperCAmelCase__			,							["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]    )





'''simple docstring'''




from __future__ import annotations

from typing import Any

class 		UpperCAmelCase_      :





     def __init__( self       :      Optional[int]    ,      UpperCAmelCase__       :      int    ,      UpperCAmelCase__       :      int    ,      UpperCAmelCase__       :      float = 0    )				->  None:
        lowerCAmelCase     ,  lowerCAmelCase     =			row, column
        lowerCAmelCase     =			[[default_value for c in range(UpperCAmelCase__    )] for r in range(UpperCAmelCase__    )]





     def __str__( self       :      List[str]    )				->  str:
        lowerCAmelCase     =			F'''Matrix consist of {self.row} rows and {self.column} columns\n'''

        # Make string identifier
        lowerCAmelCase     =			0
        for row_vector in self.array:
           for obj in row_vector:
              lowerCAmelCase     =			max(UpperCAmelCase__    ,      len(str(UpperCAmelCase__    )    )    )
        lowerCAmelCase     =			F'''%{max_element_length}s'''

        # Make string and return
        def single_line(UpperCAmelCase__       :      list[float]    ) -> str:
           nonlocal string_format_identifier
           lowerCAmelCase     =			'['
           line += ", ".join(string_format_identifier % (obj,) for obj in row_vector    )
           line += "]"
           return line

        s += "\n".join(single_line(UpperCAmelCase__    ) for row_vector in self.array    )
        return s





     def __repr__( self       :      List[str]    )				->  str:
        return str(self    )





     def 							__UpperCAmelCase      ( self       :      Optional[int]    ,      UpperCAmelCase__       :      tuple[int, int]    )				->  bool:
        if not (isinstance(UpperCAmelCase__    ,      (list, tuple)    ) and len(UpperCAmelCase__    ) == 2):
           return False
        elif not (0 <= loc[0] < self.row and 0 <= loc[1] < self.column):
           return False
        else:
           return True





     def __getitem__( self       :      Any    ,      UpperCAmelCase__       :      tuple[int, int]    )				->  Any:
        assert self.validate_indicies(UpperCAmelCase__    )
        return self.array[loc[0]][loc[1]]





     def __setitem__( self       :      Dict    ,      UpperCAmelCase__       :      tuple[int, int]    ,      UpperCAmelCase__       :      float    )				->  None:
        assert self.validate_indicies(UpperCAmelCase__    )
        lowerCAmelCase     =			value





     def __add__( self       :      Any    ,      UpperCAmelCase__       :      Matrix    )				->  Matrix:
        assert isinstance(UpperCAmelCase__    ,      UpperCAmelCase__    )
        assert self.row == another.row and self.column == another.column

        # Add
        lowerCAmelCase     =			Matrix(self.row    ,      self.column    )
        for r in range(self.row    ):
           for c in range(self.column    ):
              lowerCAmelCase     =			self[r, c] + another[r, c]
        return result





     def __neg__( self       :      int    )				->  Matrix:
        lowerCAmelCase     =			Matrix(self.row    ,      self.column    )
        for r in range(self.row    ):
           for c in range(self.column    ):
              lowerCAmelCase     =			-self[r, c]
        return result





     def __sub__( self       :      str    ,      UpperCAmelCase__       :      Matrix    )				->  Matrix:
        return self + (-another)





     def __mul__( self       :      str    ,      UpperCAmelCase__       :      int | float | Matrix    )				->  Matrix:

        if isinstance(UpperCAmelCase__    ,      (int, float)    ):  # Scalar multiplication
           lowerCAmelCase     =			Matrix(self.row    ,      self.column    )
           for r in range(self.row    ):
              for c in range(self.column    ):
                 lowerCAmelCase     =			self[r, c] * another
           return result
        elif isinstance(UpperCAmelCase__    ,      UpperCAmelCase__    ):  # Matrix multiplication
           assert self.column == another.row
           lowerCAmelCase     =			Matrix(self.row    ,      another.column    )
           for r in range(self.row    ):
              for c in range(another.column    ):
                 for i in range(self.column    ):
                    result[r, c] += self[r, i] * another[i, c]
           return result
        else:
           lowerCAmelCase     =			F'''Unsupported type given for another ({type(UpperCAmelCase__    )})'''
           raise TypeError(UpperCAmelCase__    )





     def 							__UpperCAmelCase      ( self       :      Optional[Any]    )				->  Matrix:
        lowerCAmelCase     =			Matrix(self.column    ,      self.row    )
        for r in range(self.row    ):
           for c in range(self.column    ):
              lowerCAmelCase     =			self[r, c]
        return result





     def 							__UpperCAmelCase      ( self       :      List[str]    ,      UpperCAmelCase__       :      Matrix    ,      UpperCAmelCase__       :      Matrix    )				->  Any:
        assert isinstance(UpperCAmelCase__    ,      UpperCAmelCase__    ) and isinstance(UpperCAmelCase__    ,      UpperCAmelCase__    )
        assert self.row == self.column == u.row == v.row  # u, v should be column vector
        assert u.column == v.column == 1  # u, v should be column vector

        # Calculate
        lowerCAmelCase     =			v.transpose()
        lowerCAmelCase     =			(v_t * self * u)[0, 0] + 1
        if numerator_factor == 0:
           return None  # It's not invertable
        return self - ((self * u) * (v_t * self) * (1.0 / numerator_factor))


# Testing
if __name__ == "__main__":





       def 	a_					( ):
          # a^(-1)
          lowerCAmelCase     =			Matrix(3	, 3	, 0				)
          for i in range(3				):
             lowerCAmelCase     =			1
          print(f'''a^(-1) is {ainv}'''				)
          # u, v
          lowerCAmelCase     =			Matrix(3	, 1	, 0				)
          lowerCAmelCase     ,  lowerCAmelCase     ,  lowerCAmelCase     =			1, 2, -3
          lowerCAmelCase     =			Matrix(3	, 1	, 0				)
          lowerCAmelCase     ,  lowerCAmelCase     ,  lowerCAmelCase     =			4, -2, 5
          print(f'''u is {u}'''				)
          print(f'''v is {v}'''				)
          print(f'''uv^T is {u * v.transpose()}'''				)
          # Sherman Morrison
          print(f'''(a + uv^T)^(-1) is {ainv.sherman_morrison(lowerCamelCase	, lowerCamelCase				)}'''				)





       def 	a_					( ):
          import doctest

          doctest.testmod()




       testa()





