import numpy as np
import matplotlib.pyplot as plt

def normalization(data):
    rang=np.max(data)-np.min(data)
    return (data-np.min(data))/rang


def save_1_feature_map(feature_map):
    # [1, H, W] -> [H, W]
    im = np.squeeze(feature_map.detach().cpu().numpy())

    # normalization
    im=normalization(-im)

    # plt.figure()
    plt.axis('off')
    plt.imshow(im, cmap='jet')
    plt.savefig('feature_map{}.png'.format(1))