



'''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




'''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


