code: 
  
  
  
  '''simple docstring'''
  
  import logging
  
  # standard libraries
  import sys
  
  import numpy as np
  import pytest  # type: ignore
  
  # Custom/local libraries
  from matrix import matrix_operation as matop
  
  UpperCamelCase_     			=       [[12, 10], [3, 9]]
  UpperCamelCase_     			=       [[3, 4], [7, 4]]
  UpperCamelCase_     			=       [[3, 0, 2], [2, 0, -2], [0, 1, 1]]
  UpperCamelCase_     			=       [[3, 0, -2], [2, 0, 2], [0, 1, 1]]
  UpperCamelCase_     			=       [[3, 0, 2], [2, 0, -2], [0, 1, 1], [2, 0, -2]]
  UpperCamelCase_     			=       [1]
  UpperCamelCase_     			=       [2]
  
  UpperCamelCase_     			=       logging.getLogger()
  UpperCamelCase_     			=       logging.DEBUG
  UpperCamelCase_     			=       logging.StreamHandler(sys.stdout)
  logger.addHandler(stream_handler)
  
  
  @pytest.mark.mat_ops
  @pytest.mark.parametrize(
      ("""mat1""", """mat2""")  ,      [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]		)
  def 	_UpperCAmelCase				(  _lowerCamelCase						:       Optional[Any]  ,      _lowerCamelCase						:       Any		)    ->						Optional[int]:
  
  
  
  
  
  
  
    if (np.array(_lowerCamelCase		)).shape < (2, 2) or (np.array(_lowerCamelCase		)).shape < (2, 2):
      with pytest.raises(_lowerCamelCase		):
        logger.info(f'\n\t{test_addition.__name__} returned integer'		)
        matop.add(_lowerCamelCase  ,      _lowerCamelCase		)
    elif (np.array(_lowerCamelCase		)).shape == (np.array(_lowerCamelCase		)).shape:
      logger.info(f'\n\t{test_addition.__name__} with same matrix dims'		)
      _lowerCAmelCase       :  List[Any]   				=					(np.array(_lowerCamelCase		) + np.array(_lowerCamelCase		)).tolist()
      _lowerCAmelCase       :  List[Any]   				=					matop.add(_lowerCamelCase  ,      _lowerCamelCase		)
      assert theo == act
    else:
      with pytest.raises(_lowerCamelCase		):
        logger.info(f'\n\t{test_addition.__name__} with different matrix dims'		)
        matop.add(_lowerCamelCase  ,      _lowerCamelCase		)
  
  
  @pytest.mark.mat_ops
  @pytest.mark.parametrize(
      ("""mat1""", """mat2""")  ,      [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]		)
  def 	_UpperCAmelCase				(  _lowerCamelCase						:       List[str]  ,      _lowerCamelCase						:       List[str]		)    ->						Optional[Any]:
  
  
  
  
  
  
  
    if (np.array(_lowerCamelCase		)).shape < (2, 2) or (np.array(_lowerCamelCase		)).shape < (2, 2):
      with pytest.raises(_lowerCamelCase		):
        logger.info(f'\n\t{test_subtraction.__name__} returned integer'		)
        matop.subtract(_lowerCamelCase  ,      _lowerCamelCase		)
    elif (np.array(_lowerCamelCase		)).shape == (np.array(_lowerCamelCase		)).shape:
      logger.info(f'\n\t{test_subtraction.__name__} with same matrix dims'		)
      _lowerCAmelCase       :  Union[str, Any]   				=					(np.array(_lowerCamelCase		) - np.array(_lowerCamelCase		)).tolist()
      _lowerCAmelCase       :  Dict   				=					matop.subtract(_lowerCamelCase  ,      _lowerCamelCase		)
      assert theo == act
    else:
      with pytest.raises(_lowerCamelCase		):
        logger.info(f'\n\t{test_subtraction.__name__} with different matrix dims'		)
        assert matop.subtract(_lowerCamelCase  ,      _lowerCamelCase		)
  
  
  @pytest.mark.mat_ops
  @pytest.mark.parametrize(
      ("""mat1""", """mat2""")  ,      [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]		)
  def 	_UpperCAmelCase				(  _lowerCamelCase						:       Union[str, Any]  ,      _lowerCamelCase						:       List[str]		)    ->						str:
  
  
  
  
  
  
  
    if (np.array(_lowerCamelCase		)).shape < (2, 2) or (np.array(_lowerCamelCase		)).shape < (2, 2):
      logger.info(f'\n\t{test_multiplication.__name__} returned integer'		)
      with pytest.raises(_lowerCamelCase		):
        matop.add(_lowerCamelCase  ,      _lowerCamelCase		)
    elif (np.array(_lowerCamelCase		)).shape == (np.array(_lowerCamelCase		)).shape:
      logger.info(f'\n\t{test_multiplication.__name__} meets dim requirements'		)
      _lowerCAmelCase       :  Union[str, Any]   				=					(np.matmul(_lowerCamelCase  ,      _lowerCamelCase		)).tolist()
      _lowerCAmelCase       :  List[Any]   				=					matop.multiply(_lowerCamelCase  ,      _lowerCamelCase		)
      assert theo == act
    else:
      with pytest.raises(_lowerCamelCase		):
        logger.info(
            f'\n\t{test_multiplication.__name__} does not meet dim requirements'		)
        assert matop.subtract(_lowerCamelCase  ,      _lowerCamelCase		)
  
  
  @pytest.mark.mat_ops
  def 	_UpperCAmelCase				(  )    ->						Any:
    _lowerCAmelCase       :  List[str]   				=					(3.5 * np.array(_lowerCamelCase		)).tolist()
    _lowerCAmelCase       :  str   				=					matop.scalar_multiply(_lowerCamelCase  ,      3.5		)
    assert theo == act
  
  
  @pytest.mark.mat_ops
  def 	_UpperCAmelCase				(  )    ->						Optional[int]:
    _lowerCAmelCase       :  Union[str, Any]   				=					(np.identity(5		)).tolist()
    _lowerCAmelCase       :  Union[str, Any]   				=					matop.identity(5		)
    assert theo == act
  
  
  
  @pytest.mark.mat_ops
  @pytest.mark.parametrize("""mat"""  ,      [mat_a, mat_b, mat_c, mat_d, mat_e, mat_f]		)
  def 	_UpperCAmelCase				(  _lowerCamelCase						:       Union[str, Any]		)    ->						Dict:
  
  
  
  
  
  
  
    if (np.array(_lowerCamelCase		)).shape < (2, 2):
      with pytest.raises(_lowerCamelCase		):
        logger.info(f'\n\t{test_transpose.__name__} returned integer'		)
        matop.transpose(_lowerCamelCase		)
    else:
      _lowerCAmelCase       :  Optional[int]   				=					(np.transpose(_lowerCamelCase		)).tolist()
      _lowerCAmelCase       :  str   				=					matop.transpose(_lowerCamelCase  ,      return_map=_lowerCamelCase		)
      assert theo == act
  
  
  
style_context: 
  '''simple docstring'''
  
  import json
  import os
  import unittest
  
  from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import (
      VOCAB_FILES_NAMES,
      GPTNeoXJapaneseTokenizer,
  )
  from transformers.testing_utils import require_tokenizers, slow
  
  from ...test_tokenization_common import TokenizerTesterMixin
  
  
  @require_tokenizers
  class   a_  (_a							,			unittest.TestCase    ):
         __lowerCAmelCase    :				List[Any]    =      GPTNeoXJapaneseTokenizer
         __lowerCAmelCase    :				Any    =      False
         __lowerCAmelCase    :				List[Any]    =      {"""do_clean_text""": False, """add_prefix_space""": False}
  
  
  
  
         def 							__UpperCamelCase       (     self  ):
           super().setUp()
  
           _lowerCAmelCase       :  Any   				=					[
               """こん""",
               """こんに""",
               """にちは""",
               """ばんは""",
               """世界,㔺界""",
               """、""",
               """。""",
               """<BR>""",
               """<SP>""",
               """<TAB>""",
               """<URL>""",
               """<EMAIL>""",
               """<TEL>""",
               """<DATE>""",
               """<PRICE>""",
               """<BLOCK>""",
               """<KIGOU>""",
               """<U2000U2BFF>""",
               """<|emoji1|>""",
               """<unk>""",
               """<|startoftext|>""",
               """<|endoftext|>""",
           ]
           _lowerCAmelCase       :  Union[str, Any]   				=					{"""emoji""": {"""\ud83d\ude00""": """<|emoji1|>"""}, """emoji_inv""": {"""<|emoji1|>""": """\ud83d\ude00"""}}  # 😀
           _lowerCAmelCase       :  Any   				=					{"""unk_token""": """<unk>"""}
  
           _lowerCAmelCase       :  Optional[int]   				=					os.path.join(self.tmpdirname   ,   VOCAB_FILES_NAMES["""vocab_file"""]  )
           _lowerCAmelCase       :  Any   				=					os.path.join(self.tmpdirname   ,   VOCAB_FILES_NAMES["""emoji_file"""]  )
           with open(self.vocab_file   ,   """w"""   ,   encoding="""utf-8"""  ) as vocab_writer:
             vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]  )  )
           with open(self.emoji_file   ,   """w"""  ) as emoji_writer:
             emoji_writer.write(json.dumps(snake_case_  )  )
  
  
  
  
         def 							__UpperCamelCase       (     self   ,   **snake_case_  ):
           kwargs.update(self.special_tokens_map  )
           return GPTNeoXJapaneseTokenizer.from_pretrained(self.tmpdirname   ,   **snake_case_  )
  
  
  
  
         def 							__UpperCamelCase       (     self   ,   snake_case_  ):
           _lowerCAmelCase       :  Tuple   				=					"""こんにちは、世界。 \nこんばんは、㔺界。😀"""
           _lowerCAmelCase       :  str   				=					"""こんにちは、世界。 \nこんばんは、世界。😀"""
           return input_text, output_text
  
  
  
  
         def 							__UpperCamelCase       (     self   ,   snake_case_  ):
           _lowerCAmelCase				,					_lowerCAmelCase       :  str   				=					self.get_input_output_texts(snake_case_  )
           _lowerCAmelCase       :  Tuple   				=					tokenizer.encode(snake_case_   ,   add_special_tokens=snake_case_  )
           _lowerCAmelCase       :  Optional[Any]   				=					tokenizer.decode(snake_case_   ,   clean_up_tokenization_spaces=snake_case_  )
           return text, ids
  
  
  
  
         def 							__UpperCamelCase       (     self  ):
           pass  # TODO add if relevant
  
  
  
  
         def 							__UpperCamelCase       (     self  ):
           pass  # TODO add if relevant
  
  
  
  
         def 							__UpperCamelCase       (     self  ):
           pass  # TODO add if relevant
  
  
  
  
         def 							__UpperCamelCase       (     self  ):
           _lowerCAmelCase       :  List[Any]   				=					self.get_tokenizer()
  
           # Testing tokenization
           _lowerCAmelCase       :  Tuple   				=					"""こんにちは、世界。　こんばんは、㔺界。"""
           _lowerCAmelCase       :  Optional[Any]   				=					["""こん""", """にちは""", """、""", """世界""", """。""", """<SP>""", """こん""", """ばんは""", """、""", """㔺界""", """。"""]
           _lowerCAmelCase       :  Tuple   				=					tokenizer.tokenize(snake_case_  )
           self.assertListEqual(snake_case_   ,   snake_case_  )
  
           # Testing conversion to ids without special tokens
           _lowerCAmelCase       :  Optional[int]   				=					[0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
           _lowerCAmelCase       :  Optional[int]   				=					tokenizer.convert_tokens_to_ids(snake_case_  )
           self.assertListEqual(snake_case_   ,   snake_case_  )
  
           # Testing conversion to ids with special tokens
           _lowerCAmelCase       :  Optional[Any]   				=					tokens + [tokenizer.unk_token]
           _lowerCAmelCase       :  List[str]   				=					[0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 1_9]
           _lowerCAmelCase       :  Dict   				=					tokenizer.convert_tokens_to_ids(snake_case_  )
           self.assertListEqual(snake_case_   ,   snake_case_  )
  
  
  
  
         @slow
         def 							__UpperCamelCase       (     self  ):
           _lowerCAmelCase       :  int   				=					self.tokenizer_class.from_pretrained("""abeja/gpt-neox-japanese-2.7b"""  )
  
           _lowerCAmelCase       :  List[Any]   				=					tokenizer.encode("""ありがとう。"""   ,   add_special_tokens=snake_case_  )
           _lowerCAmelCase       :  List[str]   				=					tokenizer.encode("""どういたしまして。"""   ,   add_special_tokens=snake_case_  )
  
           _lowerCAmelCase       :  int   				=					tokenizer.build_inputs_with_special_tokens(snake_case_  )
           _lowerCAmelCase       :  Any   				=					tokenizer.build_inputs_with_special_tokens(snake_case_   ,   snake_case_  )
  
           assert encoded_sentence == ids_a
           assert encoded_pair == ids_a + ids_a
  
  
  
  
         def 							__UpperCamelCase       (     self  ):
           # Intentionally convert some words to accommodate character fluctuations unique to Japanese
           pass
  
  
  
  
  
  
  
         def 							__UpperCamelCase       (     self  ):
           # tokenizer has no padding token
           pass
  
  
  