original_docstring:  Check values of all parameters and raise `ValueError` if incorrect values are found.
  
          :param kwargs: dictionary containing names and values of all parameters.
  
          
docstring: Check values of all parameters and raise `ValueError` if incorrect values are found.
docstring_tokens: Check values of all parameters and raise ` ValueError ` if incorrect values are found .
code: def check_params(**kwargs):
          """ Check values of all parameters and raise `ValueError` if incorrect values are found.
  
          :param kwargs: dictionary containing names and values of all parameters.
  
          """
          if 'batch_size' not in kwargs:
              raise ValueError('`batch_size` is not found!')
          if not isinstance(kwargs['batch_size'], int):
              raise ValueError(f'`batch_size` must be `{type(10)}`, not `{type(kwargs["batch_size"])}`.')
          if kwargs['batch_size'] < 1:
              raise ValueError(f'`batch_size` must be a positive number! {kwargs["batch_size"]} is not positive.')
          if 'epochs' not in kwargs:
              raise ValueError('`epochs` is not found!')
          if not isinstance(kwargs['epochs'], int):
              raise ValueError(f'`epochs` must be `{type(10)}`, not `{type(kwargs["epochs"])}`.')
          if kwargs['epochs'] < 1:
              raise ValueError(f'`epochs` must be a positive number! {kwargs["epochs"]} is not positive.')
          if 'latent_dim' not in kwargs:
              raise ValueError('`latent_dim` is not found!')
          if not isinstance(kwargs['latent_dim'], int):
              raise ValueError(f'`latent_dim` must be `{type(10)}`, not `{type(kwargs["latent_dim"])}`.')
          if kwargs['latent_dim'] < 1:
              raise ValueError(f'`latent_dim` must be a positive number! {kwargs["latent_dim"]} is not positive.')
          if 'lowercase' not in kwargs:
              raise ValueError('`lowercase` is not found!')
          if (not isinstance(kwargs['lowercase'], int)) and (not isinstance(kwargs['lowercase'], bool)):
              raise ValueError(f'`lowercase` must be `{type(10)}` or `{type(True)}`, not `{type(kwargs["lowercase"])}`.')
          if 'verbose' not in kwargs:
              raise ValueError('`verbose` is not found!')
          if (not isinstance(kwargs['verbose'], int)) and (not isinstance(kwargs['verbose'], bool)):
              raise ValueError(f'`verbose` must be `{type(10)}` or `{type(True)}`, not `{type(kwargs["verbose"])}`.')
          if 'validation_split' not in kwargs:
              raise ValueError('`validation_split` is not found!')
          if kwargs['validation_split'] is not None:
              if not isinstance(kwargs['validation_split'], float):
                  raise ValueError(f'`validation_split` must be `{type(1.5)}`, not `{type(kwargs["validation_split"])}`.')
              if (kwargs['validation_split'] <= 0.0) or (kwargs['validation_split'] >= 1.0):
                  raise ValueError('`validation_split` must be in interval (0.0, 1.0)!')
          if 'lr' not in kwargs:
              raise ValueError('`lr` is not found!')
          if not isinstance(kwargs['lr'], float):
              raise ValueError(f'`lr` must be `{type(1.5)}`, not `{type(kwargs["lr"])}`.')
          if kwargs['lr'] <= 0.0:
              raise ValueError('`lr` must be a positive floating-point value!')
          if 'grad_clipping' not in kwargs:
              raise ValueError('`grad_clipping` is not found!')
          if kwargs['grad_clipping'] is not None:
              if not isinstance(kwargs['grad_clipping'], float):
                  raise ValueError(f'`grad_clipping` must be `{type(1.5)}`, not `{type(kwargs["grad_clipping"])}`.')
              if kwargs['grad_clipping'] <= 0.0:
                  raise ValueError('`grad_clipping` must be a positive floating-point value!')
          if 'weight_decay' not in kwargs:
              raise ValueError('`weight_decay` is not found!')
          if not isinstance(kwargs['weight_decay'], float):
              raise ValueError(f'`weight_decay` must be `{type(1.5)}`, not `{type(kwargs["weight_decay"])}`.')
          if kwargs['weight_decay'] < 0.0:
              raise ValueError('`weight_decay` must be a non-negative floating-point value!')
          if 'random_state' not in kwargs:
              raise ValueError('`random_state` is not found!')
          if kwargs['random_state'] is not None:
              if not isinstance(kwargs['random_state'], int):
                  raise ValueError(f'`random_state` must be `{type(10)}`, not `{type(kwargs["random_state"])}`.')
code_tokens: def check_params ( ** kwargs ) : if 'batch_size' not in kwargs : raise ValueError ( '`batch_size` is not found!' ) if not isinstance ( kwargs [ 'batch_size' ] , int ) : raise ValueError ( f'`batch_size` must be `{type(10)}`, not `{type(kwargs["batch_size"])}`.' ) if kwargs [ 'batch_size' ] < 1 : raise ValueError ( f'`batch_size` must be a positive number! {kwargs["batch_size"]} is not positive.' ) if 'epochs' not in kwargs : raise ValueError ( '`epochs` is not found!' ) if not isinstance ( kwargs [ 'epochs' ] , int ) : raise ValueError ( f'`epochs` must be `{type(10)}`, not `{type(kwargs["epochs"])}`.' ) if kwargs [ 'epochs' ] < 1 : raise ValueError ( f'`epochs` must be a positive number! {kwargs["epochs"]} is not positive.' ) if 'latent_dim' not in kwargs : raise ValueError ( '`latent_dim` is not found!' ) if not isinstance ( kwargs [ 'latent_dim' ] , int ) : raise ValueError ( f'`latent_dim` must be `{type(10)}`, not `{type(kwargs["latent_dim"])}`.' ) if kwargs [ 'latent_dim' ] < 1 : raise ValueError ( f'`latent_dim` must be a positive number! {kwargs["latent_dim"]} is not positive.' ) if 'lowercase' not in kwargs : raise ValueError ( '`lowercase` is not found!' ) if ( not isinstance ( kwargs [ 'lowercase' ] , int ) ) and ( not isinstance ( kwargs [ 'lowercase' ] , bool ) ) : raise ValueError ( f'`lowercase` must be `{type(10)}` or `{type(True)}`, not `{type(kwargs["lowercase"])}`.' ) if 'verbose' not in kwargs : raise ValueError ( '`verbose` is not found!' ) if ( not isinstance ( kwargs [ 'verbose' ] , int ) ) and ( not isinstance ( kwargs [ 'verbose' ] , bool ) ) : raise ValueError ( f'`verbose` must be `{type(10)}` or `{type(True)}`, not `{type(kwargs["verbose"])}`.' ) if 'validation_split' not in kwargs : raise ValueError ( '`validation_split` is not found!' ) if kwargs [ 'validation_split' ] is not None : if not isinstance ( kwargs [ 'validation_split' ] , float ) : raise ValueError ( f'`validation_split` must be `{type(1.5)}`, not `{type(kwargs["validation_split"])}`.' ) if ( kwargs [ 'validation_split' ] <= 0.0 ) or ( kwargs [ 'validation_split' ] >= 1.0 ) : raise ValueError ( '`validation_split` must be in interval (0.0, 1.0)!' ) if 'lr' not in kwargs : raise ValueError ( '`lr` is not found!' ) if not isinstance ( kwargs [ 'lr' ] , float ) : raise ValueError ( f'`lr` must be `{type(1.5)}`, not `{type(kwargs["lr"])}`.' ) if kwargs [ 'lr' ] <= 0.0 : raise ValueError ( '`lr` must be a positive floating-point value!' ) if 'grad_clipping' not in kwargs : raise ValueError ( '`grad_clipping` is not found!' ) if kwargs [ 'grad_clipping' ] is not None : if not isinstance ( kwargs [ 'grad_clipping' ] , float ) : raise ValueError ( f'`grad_clipping` must be `{type(1.5)}`, not `{type(kwargs["grad_clipping"])}`.' ) if kwargs [ 'grad_clipping' ] <= 0.0 : raise ValueError ( '`grad_clipping` must be a positive floating-point value!' ) if 'weight_decay' not in kwargs : raise ValueError ( '`weight_decay` is not found!' ) if not isinstance ( kwargs [ 'weight_decay' ] , float ) : raise ValueError ( f'`weight_decay` must be `{type(1.5)}`, not `{type(kwargs["weight_decay"])}`.' ) if kwargs [ 'weight_decay' ] < 0.0 : raise ValueError ( '`weight_decay` must be a non-negative floating-point value!' ) if 'random_state' not in kwargs : raise ValueError ( '`random_state` is not found!' ) if kwargs [ 'random_state' ] is not None : if not isinstance ( kwargs [ 'random_state' ] , int ) : raise ValueError ( f'`random_state` must be `{type(10)}`, not `{type(kwargs["random_state"])}`.' )
short_docstring: Check values of all parameters and raise `ValueError` if incorrect values are found.
short_docstring_tokens: Check values of all parameters and raise ` ValueError ` if incorrect values are found .
comment: """ Check values of all parameters and raise `ValueError` if incorrect values are found.
  
          :param kwargs: dictionary containing names and values of all parameters.
  
          """