21758dd81de16d2bfdcf1a0d5d6d98f25a2e5868,autosklearn/metrics/util.py,,normalize_array,#Any#Any#,30

Before Change

    
    // Binarize solution
    sol = np.ravel(solution)  // convert to 1-d array
    maxi = np.nanmax((filter(lambda x: x != float("inf"), sol))
                     )  // Max except NaN and Inf
    mini = np.nanmin((filter(lambda x: x != float("-inf"), sol))
                     )  // Mini except NaN and Inf
    if maxi == mini:

After Change

    //                 )  // Max except NaN and Inf
    //mini = np.nanmin((filter(lambda x: x != float("-inf"), sol))
    //                 )  // Mini except NaN and Inf
    maxi = np.nanmax(sol[np.isfinite(sol)])
    mini = np.nanmin(sol[np.isfinite(sol)])
    if maxi == mini:
        print("Warning, cannot normalize")
        return [solution, prediction]

Instances