tensorboard_str = 'tensorboard' + '--logdir ' + logs_path
        print('Visualize at Tensorboard using ', tensorboard_str)
    print('Importing and Preprocessing Cloud-of-Point Data')

    dataset = []
    dataset.append(get_data.data_import(file_names_x, data_folder))
    dataset.append(get_data.data_import(file_names_y, data_folder))
    dataset.append(get_data.data_import(file_names_z, data_folder))
    point_index = get_data.load_mapping_index(mapping_index)

    kcc_dataset = get_data.data_import(kcc_files, kcc_folder)
    input_conv_data, kcc_subset_dump, kpi_subset_dump = get_data.data_convert_voxel_mc(
        vrm_system, dataset, point_index, kcc_dataset)

    #Added Function to split KCCs to regression and classification
    kcc_regression, kcc_classification = hy_util.split_kcc(kcc_subset_dump)

    print('Building 3D CNN model')

    output_dimension = assembly_kccs

    dl_model_unet = Encode_Decode_Model(output_dimension)
    model = dl_model_unet.resnet_3d_cnn_hybrid(voxel_dim, voxel_channels,
                                               kcc_classification.shape[1])

    print(model.summary())
    #sys.exit()
    print('Training 3D CNN model')
    model_outputs = [kcc_regression, kcc_classification]

    train_model = TrainModel(batch_size, epocs, split_ratio)
	test_input_conv_data=test_input_conv_data[test_kpi_subset_dump,:,:,:,:]
	#Test output files
	deploy_output=1
	
	if(deploy_output==1):
		
		test_kcc_dataset=get_data.data_import(test_kcc_files,kcc_folder)
		
		if(kcc_sublist!=0):
			print("Sub-setting Process Parameters: ",kcc_sublist)
			test_kcc_dataset=test_kcc_dataset[:,kcc_sublist]
		else:
			print("Using all Process Parameters")
		test_kcc_subset_dump=test_kcc_subset_dump[test_kpi_subset_dump,:]

		kcc_regression_test,kcc_classification_test=hy_util.split_kcc(test_kcc_subset_dump)

		Y_out_test_list=[]
		Y_out_test_list.append(kcc_regression_test)
		Y_out_test_list.append(kcc_classification_test)
		
		y_shape_error_test_list=[]

		for encode_decode_construct in encode_decode_multi_output_construct:
		#importing file names for model output
			print("Importing output data for stage: ",encode_decode_construct)
			
			test_output_file_names_x=encode_decode_construct['output_test_data_files_x']
			test_output_file_names_y=encode_decode_construct['output_test_data_files_y']
			test_output_file_names_z=encode_decode_construct['output_test_data_files_z']
			test_output_dataset=[]