NeuralNetVisualizer calls nonexistent function safe_squeeze() about m-loop HOT 2 CLOSED

def safe_cast_to_array(in_array):
    '''
    Attempts to safely cast the input to an array. Takes care of border cases
    
    Args:
        in_array (array or equivalent): The array (or otherwise) to be converted to a list.
    
    Returns:
        array : array that has been squeezed and 0-D cases change to 1-D cases
    
    '''
    
    out_array = np.squeeze(np.array(in_array))
    
    if out_array.shape == ():
        out_array = np.array([out_array[()]]) 
    
    return out_array

def safe_squeeze(in_array, set_dtype = float):
    '''
    Attempts to squeeze an array, but has a different behavior for arrays with only a single value. 
    
    Args:
        in_array (array): The array to be squeezed
    
    Returns:
        array: Array.
    '''
    
    out_array = np.squeeze(np.array(in_array, dtype=set_dtype))
    if out_array.shape == ():
        out_array = np.array([out_array[()]])
    
    return out_array

import mloop.visualizations as mlv

# Monkey patch safe_cast_to_array() in place of safe_squeeze() in neural net visualizer code.
mlv.mlu.safe_squeeze = mlv.mlu.safe_cast_to_array

# Make the plots.
mlv.configure_plots()
mlv.create_controller_visualizations(controller_archive, file_type=file_type)
mlv.create_neural_net_learner_visualizations(learner_archive, file_type=file_type)