import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


__lowerCamelCase			: Tuple							   =		pytest.mark.integration



@pytest.mark.parametrize("""path""" ,     ["""paws""", """csv"""]	)
def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       List[Any] ,     __UpperCamelCase    :       Tuple	)							->					Union[str, Any]:







  """simple docstring"""





  inspect_dataset(__UpperCamelCase ,     __UpperCamelCase	)
  SCREAMING_SNAKE_CASE__										=      path + """.py"""
  assert script_name in os.listdir(__UpperCamelCase	)
  assert "__pycache__" not in os.listdir(__UpperCamelCase	)



@pytest.mark.filterwarnings("""ignore:inspect_metric is deprecated:FutureWarning"""	)
@pytest.mark.filterwarnings("""ignore:metric_module_factory is deprecated:FutureWarning"""	)
@pytest.mark.parametrize("""path""" ,     ["""accuracy"""]	)
def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       Tuple ,     __UpperCamelCase    :       List[str]	)							->					Union[str, Any]:







  """simple docstring"""





  inspect_metric(__UpperCamelCase ,     __UpperCamelCase	)
  SCREAMING_SNAKE_CASE__										=      path + """.py"""
  assert script_name in os.listdir(__UpperCamelCase	)
  assert "__pycache__" not in os.listdir(__UpperCamelCase	)



@pytest.mark.parametrize(
    """path, config_name, expected_splits""" ,     [
        ("""squad""", """plain_text""", ["""train""", """validation"""]),
        ("""dalle-mini/wit""", """dalle-mini--wit""", ["""train"""]),
        ("""paws""", """labeled_final""", ["""train""", """test""", """validation"""]),
    ] ,     )
def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       Optional[int] ,     __UpperCamelCase    :       List[Any] ,     __UpperCamelCase    :       Dict	)							->					Tuple:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__										=      get_dataset_config_info(__UpperCamelCase ,     config_name=__UpperCamelCase	)
  assert info.config_name == config_name
  assert list(info.splits.keys()	) == expected_splits



@pytest.mark.parametrize(
    """path, config_name, expected_exception""" ,     [
        ("""paws""", None, ValueError),
    ] ,     )
def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       int ,     __UpperCamelCase    :       str ,     __UpperCamelCase    :       Optional[Any]	)							->					int:







  """simple docstring"""





  with pytest.raises(__UpperCamelCase	):
    get_dataset_config_info(__UpperCamelCase ,     config_name=__UpperCamelCase	)



@pytest.mark.parametrize(
    """path, expected""" ,     [
        ("""squad""", """plain_text"""),
        ("""acronym_identification""", """default"""),
        ("""lhoestq/squad""", """plain_text"""),
        ("""lhoestq/test""", """default"""),
        ("""lhoestq/demo1""", """lhoestq--demo1"""),
        ("""dalle-mini/wit""", """dalle-mini--wit"""),
    ] ,     )
def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       Dict ,     __UpperCamelCase    :       Tuple	)							->					str:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__										=      get_dataset_config_names(__UpperCamelCase	)
  assert expected in config_names



@pytest.mark.parametrize(
    """path, expected_configs, expected_splits_in_first_config""" ,     [
        ("""squad""", ["""plain_text"""], ["""train""", """validation"""]),
        ("""dalle-mini/wit""", ["""dalle-mini--wit"""], ["""train"""]),
        ("""paws""", ["""labeled_final""", """labeled_swap""", """unlabeled_final"""], ["""train""", """test""", """validation"""]),
    ] ,     )
def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       List[Any] ,     __UpperCamelCase    :       Optional[int] ,     __UpperCamelCase    :       Any	)							->					str:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__										=      get_dataset_infos(__UpperCamelCase	)
  assert list(infos.keys()	) == expected_configs
  SCREAMING_SNAKE_CASE__										=      expected_configs[0]
  assert expected_config in infos
  SCREAMING_SNAKE_CASE__										=      infos[expected_config]
  assert info.config_name == expected_config
  assert list(info.splits.keys()	) == expected_splits_in_first_config



@pytest.mark.parametrize(
    """path, expected_config, expected_splits""" ,     [
        ("""squad""", """plain_text""", ["""train""", """validation"""]),
        ("""dalle-mini/wit""", """dalle-mini--wit""", ["""train"""]),
        ("""paws""", """labeled_final""", ["""train""", """test""", """validation"""]),
    ] ,     )
def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       Tuple ,     __UpperCamelCase    :       Optional[int] ,     __UpperCamelCase    :       Dict	)							->					List[str]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__										=      get_dataset_infos(__UpperCamelCase	)
  assert expected_config in infos
  SCREAMING_SNAKE_CASE__										=      infos[expected_config]
  assert info.config_name == expected_config
  assert list(info.splits.keys()	) == expected_splits






@pytest.mark.parametrize(
    """path, config_name, expected_exception""" ,     [
        ("""paws""", None, ValueError),
    ] ,     )
def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       Dict ,     __UpperCamelCase    :       Dict ,     __UpperCamelCase    :       Union[str, Any]	)							->					int:







  """simple docstring"""





  with pytest.raises(__UpperCamelCase	):
    get_dataset_split_names(__UpperCamelCase ,     config_name=__UpperCamelCase	)

import doctest
from collections import deque

import numpy as np







class __snake_case				:




   def __init__(    self			:				Dict      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      [2, 1, 2, -1]
     SCREAMING_SNAKE_CASE__										=      [1, 2, 3, 4]




   def 	__a						(    self			:				int      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      len(self.first_signal      )
     SCREAMING_SNAKE_CASE__										=      len(self.second_signal      )

     SCREAMING_SNAKE_CASE__										=      max(_lowercase       ,	_lowercase      )

     # create a zero matrix of max_length x max_length
     SCREAMING_SNAKE_CASE__										=      [[0] * max_length for i in range(_lowercase      )]

     # fills the smaller signal with zeros to make both signals of same length
     if length_first_signal < length_second_signal:
       self.first_signal += [0] * (max_length - length_first_signal)
     elif length_first_signal > length_second_signal:
       self.second_signal += [0] * (max_length - length_second_signal)
     for i in range(_lowercase      ):
       SCREAMING_SNAKE_CASE__										=      deque(self.second_signal      )
       rotated_signal.rotate(_lowercase      )
       for j, item in enumerate(_lowercase      ):
         matrix[i][j] += item

        # multiply the matrix with the first signal
     SCREAMING_SNAKE_CASE__										=      np.matmul(np.transpose(_lowercase      )       ,	np.transpose(self.first_signal      )      )

     # rounding-off to two decimal places
     return [round(_lowercase       ,	2      ) for i in final_signal]


if __name__ == "__main__":
   doctest.testmod()
