'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Optional

import pandas as pd
import pyarrow as pa

import datasets
from datasets.table import table_cast







@dataclass
class lowerCamelCase							(	datasets.BuilderConfig					):




  '''simple docstring'''



  lowerCAmelCase__										=	None







class lowerCamelCase							(	datasets.ArrowBasedBuilder					):




  '''simple docstring'''



  lowerCAmelCase__										=	PandasConfig






  def  lowerCAmelCase__ (      self			:       Tuple  )				->str:
        return datasets.DatasetInfo(features=self.config.features  )






  def  lowerCAmelCase__ (      self			:       List[str]  ,							UpperCAmelCase__			:       List[str]  )				->Union[str, Any]:
        if not self.config.data_files:
              raise ValueError(f"""At least one data file must be specified, but got data_files={self.config.data_files}"""  )
        UpperCAmelCase_            =  dl_manager.download_and_extract(self.config.data_files  )
        if isinstance(UpperCAmelCase__  ,							(str, list, tuple)  ):
              UpperCAmelCase_            =  data_files
              if isinstance(UpperCAmelCase__  ,							UpperCAmelCase__  ):
                    UpperCAmelCase_            =  [files]
              # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
              UpperCAmelCase_            =  [dl_manager.iter_files(UpperCAmelCase__  ) for file in files]
              return [datasets.SplitGenerator(name=datasets.Split.TRAIN  ,							gen_kwargs={'''files''': files}  )]
        UpperCAmelCase_            =  []
        for split_name, files in data_files.items():
              if isinstance(UpperCAmelCase__  ,							UpperCAmelCase__  ):
                    UpperCAmelCase_            =  [files]
              # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
              UpperCAmelCase_            =  [dl_manager.iter_files(UpperCAmelCase__  ) for file in files]
              splits.append(datasets.SplitGenerator(name=UpperCAmelCase__  ,							gen_kwargs={'''files''': files}  )  )
        return splits






  def  lowerCAmelCase__ (      self			:       Tuple  ,							UpperCAmelCase__			:       pa.Table  )				->pa.Table:
        if self.config.features is not None:
              # more expensive cast to support nested features with keys in a different order
              # allows str <-> int/float or str to Audio for example
              UpperCAmelCase_            =  table_cast(UpperCAmelCase__  ,							self.config.features.arrow_schema  )
        return pa_table






  def  lowerCAmelCase__ (      self			:       List[Any]  ,							UpperCAmelCase__			:       Optional[Any]  )				->List[Any]:
        for i, file in enumerate(itertools.chain.from_iterable(UpperCAmelCase__  )  ):
              with open(UpperCAmelCase__  ,							'''rb'''  ) as f:
                    UpperCAmelCase_            =  pa.Table.from_pandas(pd.read_pickle(UpperCAmelCase__  )  )
                    yield i, self._cast_table(UpperCAmelCase__  )






'''simple docstring'''
from datetime import datetime

import matplotlib.pyplot as plt
import torch



def  __lowerCamelCase       (      _UpperCamelCase  :  Union[str, Any]					):


      '''simple docstring'''


      for param in module.parameters():
            UpperCAmelCase_            =  False



def  __lowerCamelCase       (      ):


      '''simple docstring'''


      UpperCAmelCase_            =  '''cuda''' if torch.cuda.is_available() else '''cpu'''
      if torch.backends.mps.is_available() and torch.backends.mps.is_built():
            UpperCAmelCase_            =  '''mps'''
      if device == "mps":
            print(
                '''WARNING: MPS currently doesn\'t seem to work, and messes up backpropagation without any visible torch'''
                ''' errors. I recommend using CUDA on a colab notebook or CPU instead if you\'re facing inexplicable issues'''
                ''' with generations.'''					)
      return device



def  __lowerCamelCase       (      _UpperCamelCase  :  Union[str, Any]					):


      '''simple docstring'''


      UpperCAmelCase_            =  plt.imshow(_UpperCamelCase					)
      fig.axes.get_xaxis().set_visible(_UpperCamelCase					)
      fig.axes.get_yaxis().set_visible(_UpperCamelCase					)
      plt.show()





def  __lowerCamelCase       (      ):


      '''simple docstring'''


      UpperCAmelCase_            =  datetime.now()
      UpperCAmelCase_            =  current_time.strftime('''%H:%M:%S'''					)
      return timestamp





