
"""simple docstring"""




import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union


A__      :	Union[str, Any]   		=    re.compile(R"""^(?P<major>\d+)""" R"""\.(?P<minor>\d+)""" R"""\.(?P<patch>\d+)$""")







@total_ordering
@dataclass
class   _lowercase						:


     '''simple docstring'''





     _A								=							42
     _A								=							None
     _A								=							None
     _A								=							None
     _A								=							None



     def  lowerCAmelCase__       (      self  )->					Optional[int]:
          UpperCAmelCase__							: List[str] 							=						_str_to_version_tuple(self.version_str  )



     def __repr__(      self  )->					str:
          return F"{self.tuple[0]}.{self.tuple[1]}.{self.tuple[2]}"



     @property
     def  lowerCAmelCase__       (      self  )->					Dict:
          return self.major, self.minor, self.patch



     def  lowerCAmelCase__       (      self ,			__UpperCamelCase  )->					List[str]:
          if isinstance(__UpperCamelCase ,			__UpperCamelCase  ):
               return Version(__UpperCamelCase  )
          elif isinstance(__UpperCamelCase ,			__UpperCamelCase  ):
               return other
          raise TypeError(F"{other} (type {type(__UpperCamelCase  )}) cannot be compared to version."  )



     def __eq__(      self ,			__UpperCamelCase  )->					Optional[int]:
          try:
               UpperCAmelCase__							: Any 							=						self._validate_operand(__UpperCamelCase  )
          except (TypeError, ValueError):
               return False
          else:
               return self.tuple == other.tuple



     def __lt__(      self ,			__UpperCamelCase  )->					List[str]:
          UpperCAmelCase__							: Any 							=						self._validate_operand(__UpperCamelCase  )
          return self.tuple < other.tuple



     def __hash__(      self  )->					Optional[Any]:
          return hash(_version_tuple_to_str(self.tuple  )  )



     @classmethod
     def  lowerCAmelCase__       (      cls ,			__UpperCamelCase  )->					Dict:
          UpperCAmelCase__							: str 							=						{f.name for f in dataclasses.fields(cls  )}
          return cls(**{k: v for k, v in dic.items() if k in field_names}  )



     def  lowerCAmelCase__       (      self  )->					str:
          return self.version_str





def 							a__ (				lowerCAmelCase	:       int		):






     '''simple docstring'''
     UpperCAmelCase__							: Dict 							=						_VERSION_REG.match(lowerCAmelCase		)
     if not res:
          raise ValueError(F"Invalid version '{version_str}'. Format should be x.y.z with {{x,y,z}} being digits."		)
     return tuple(int(lowerCAmelCase		) for v in [res.group("major"		), res.group("minor"		), res.group("patch"		)]		)



def 							a__ (				lowerCAmelCase	:       Union[str, Any]		):






     '''simple docstring'''
     return ".".join(str(lowerCAmelCase		) for v in version_tuple		)





"""simple docstring"""




import timeit

import numpy as np

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD



def 							a__ (				lowerCAmelCase	:       List[str]		):






     '''simple docstring'''
     def wrapper(*lowerCAmelCase	:       Any       ,    **lowerCAmelCase	:       Tuple		):
          UpperCAmelCase__							: Optional[int] 							=						timeit.default_timer()
          UpperCAmelCase__							: int 							=						func(*lowerCAmelCase       ,    **lowerCAmelCase		)
          UpperCAmelCase__							: List[Any] 							=						timeit.default_timer() - starttime
          return delta

     UpperCAmelCase__							: int 							=						func.__name__

     return wrapper



def 							a__ (				lowerCAmelCase	:       dict       ,    lowerCAmelCase	:       Optional[int]=100       ,    lowerCAmelCase	:       List[str]=None		):






     '''simple docstring'''
     UpperCAmelCase__							: str 							=						[]
     UpperCAmelCase__							: Optional[Any] 							=						seq_shapes or {}
     for i in range(lowerCAmelCase		):
          UpperCAmelCase__							: int 							=						{}
          for col_id, (k, v) in enumerate(features.items()		):
               if isinstance(lowerCAmelCase       ,    _ArrayXD		):
                    UpperCAmelCase__							: List[str] 							=						np.random.rand(*v.shape		).astype(v.dtype		)
               elif isinstance(lowerCAmelCase       ,    datasets.Value		):
                    if v.dtype == "string":
                         UpperCAmelCase__							: Dict 							=						"The small grey turtle was surprisingly fast when challenged."
                    else:
                         UpperCAmelCase__							: str 							=						np.random.randint(10       ,    size=1		).astype(v.dtype		).item()
               elif isinstance(lowerCAmelCase       ,    datasets.Sequence		):
                    while isinstance(lowerCAmelCase       ,    datasets.Sequence		):
                         UpperCAmelCase__							: List[str] 							=						v.feature
                    UpperCAmelCase__							: Optional[int] 							=						seq_shapes[k]
                    UpperCAmelCase__							: Optional[int] 							=						np.random.rand(*lowerCAmelCase		).astype(v.dtype		)
               UpperCAmelCase__							: Union[str, Any] 							=						data

          dummy_data.append((i, example)		)

     return dummy_data



def 							a__ (				lowerCAmelCase	:       List[str]       ,    lowerCAmelCase	:       Tuple       ,    lowerCAmelCase	:       List[str]=100       ,    lowerCAmelCase	:       Optional[int]=None		):






     '''simple docstring'''
     UpperCAmelCase__							: int 							=						generate_examples(lowerCAmelCase       ,    num_examples=lowerCAmelCase       ,    seq_shapes=lowerCAmelCase		)

     with ArrowWriter(features=lowerCAmelCase       ,    path=lowerCAmelCase		) as writer:
          for key, record in dummy_data:
               UpperCAmelCase__							: List[Any] 							=						features.encode_example(lowerCAmelCase		)
               writer.write(lowerCAmelCase		)

          UpperCAmelCase__							,	UpperCAmelCase__							: Optional[Any] 							=						writer.finalize()

     if not num_final_examples == num_examples:
          raise ValueError(
              F"Error writing the dataset, wrote {num_final_examples} examples but should have written {num_examples}."		)

     UpperCAmelCase__							: Optional[int] 							=						datasets.Dataset.from_file(filename=lowerCAmelCase       ,    info=datasets.DatasetInfo(features=lowerCAmelCase		)		)

     return dataset



