parameters: (self, estimator,
                         val_batch,
                         batch_axis=0)
return_statement: return data, label, pred, loss
docstring: Evaluate the estimator model on a batch of validation data.
  
          Parameters
          ----------
          estimator : Estimator
              Reference to the estimator
          val_batch : tuple
              Data and label of a batch from the validation data loader.
          batch_axis : int, default 0
              Batch axis to split the validation data into devices.
docstring_summary: Evaluate the estimator model on a batch of validation data.
docstring_tokens: Evaluate the estimator model on a batch of validation data .
function: def evaluate_batch(self, estimator,
                         val_batch,
                         batch_axis=0):
          """Evaluate the estimator model on a batch of validation data.
  
          Parameters
          ----------
          estimator : Estimator
              Reference to the estimator
          val_batch : tuple
              Data and label of a batch from the validation data loader.
          batch_axis : int, default 0
              Batch axis to split the validation data into devices.
          """
          data, label = self._get_data_and_label(val_batch, estimator.device, batch_axis)
          pred = [estimator.val_net(x) for x in data]
          loss = [estimator.val_loss(y_hat, y) for y_hat, y in zip(pred, label)]
  
          return data, label, pred, loss
function_tokens: def evaluate_batch ( self , estimator , val_batch , batch_axis = 0 ) : data , label = self . _get_data_and_label ( val_batch , estimator . device , batch_axis ) pred = [ estimator . val_net ( x ) for x in data ] loss = [ estimator . val_loss ( y_hat , y ) for y_hat , y in zip ( pred , label ) ] return data , label , pred , loss