def reset_val_batches(self): self.val_batches = int( np.floor(self.val_input_data.shape[0] / self.batch_size)) if self.val_batches > 0: self.val_input_batches = self.val_input_data self.val_output_batches = self.val_output_data self.val_input_batches = self.val_input_batches[:self.batch_size * self.val_batches] self.val_output_batches = self.val_output_batches[:self. batch_size * self.val_batches] else: self.val_input_batches = np.zeros( (self.batch_size, self.val_input_data.shape)) self.val_output_batches = np.zeros( (self.batch_size, self.val_output_data.shape)) self.val_input_batches = data.reshape_1D_input( self.val_input_batches) self.val_input_batches[:self.val_input_data. shape[0]] = self.val_input_data self.val_output_batches[:self.val_output_data. shape[0]] = self.val_output_data if self.frame_work == 'Tensorflow': self.val_input_batches, self.val_output_batches = data.convert_to_tensorflow_minbatch( self.val_input_batches, self.val_output_batches, self.batch_size)
def reshape_1D_input(self): self.all_input_data = data.reshape_1D_input(self.all_input_data)