AUTO_VI                 AUTO_VI class environment
AUTO_VI$..init..        Initialization method
AUTO_VI$..str..         String representation of the object
AUTO_VI$auxiliary       Compute auxiliary variables for the keras model
AUTO_VI$boot_method     Get bootstrapped residuals from a fitted model
AUTO_VI$boot_vss        Predict visual signal strength for bootstrapped
                        residual plots
AUTO_VI$check           Conduct a auto visual inference check with a
                        computer vision model
AUTO_VI$check_result    List of diagnostic results
AUTO_VI$feature_pca     Conduct principal component analysis for
                        features extracted from keras model
AUTO_VI$feature_pca_plot
                        Draw a summary Plot for principal component
                        analysis conducted on extracted features
AUTO_VI$get_data        Get data out of a model object
AUTO_VI$get_fitted_and_resid
                        Get fitted values and residuals out of a model
                        object
AUTO_VI$likelihood_ratio
                        Compute the likelihood ratio using the
                        simulated result
AUTO_VI$lineup_check    Conduct a auto visual inference lineup check
                        with a computer vision model
AUTO_VI$null_method     Get null residuals from a fitted model
AUTO_VI$null_vss        Simulate null plots and predict the visual
                        signal strength
AUTO_VI$p_value         Compute the p-value based on the check result
AUTO_VI$plot_lineup     Draw a lineup of standard residual plots
AUTO_VI$plot_pair       Draw a pair of standard residual plots
AUTO_VI$plot_resid      Draw a standard residual plot
AUTO_VI$rotate_resid    Get rotated residuals from a fitted linear
                        model
AUTO_VI$save_plot       Save plot(s)
AUTO_VI$summary         Summary of the object
AUTO_VI$summary_density_plot
                        Draw a summary density plot for the result
AUTO_VI$summary_plot    Draw a summary plot for the result
AUTO_VI$summary_rank_plot
                        Draw a summary rank plot for the result
AUTO_VI$vss             Predict the visual signal strength
KERAS_WRAPPER           KERAS_WRAPPER class environment
KERAS_WRAPPER$..init..
                        Initialization method
KERAS_WRAPPER$..str..   String representation of the object
KERAS_WRAPPER$get_input_height
                        Get keras model input image height
KERAS_WRAPPER$get_input_width
                        Get keras model input image width
KERAS_WRAPPER$image_to_array
                        Load an image as numpy array
KERAS_WRAPPER$list_layer_name
                        List all layer names
KERAS_WRAPPER$predict   Predict visual signal strength
check_python_library_available
                        Check python library availability
get_keras_model         Download and load the keras model
list_keras_model        List all available pre-trained computer vision
                        models
remove_plot             Remove a plot
save_plot               Save plot(s)
