utils.py

from matplotlib import pyplot as plt
import numpy as np
import torch.nn as nn
import torchvision.utils as vutils

# 初始化权重
def weights_init(m):
    classname = m.__class__.__name__
    if classname.find('Conv') != -1:
        nn.init.normal_(m.weight.data, 0.0, 0.02)
    elif classname.find('BatchNorm') != -1:
        nn.init.normal_(m.weight.data, 1.0, 0.02)
        nn.init.constant_(m.bias.data, 0)

def save_image(real_cpu, img_list, sample_path, device):
    # 显示生成的图像
    plt.figure(figsize=(15,15))
    plt.subplot(1,2,1)
    plt.axis("off")
    plt.title("Real Images")
    plt.imshow(np.transpose(vutils.make_grid(real_cpu.to(device)[:64], padding=5, normalize=True).cpu(),(1,2,0)))

    plt.subplot(1,2,2)
    plt.axis("off")
    plt.title("Fake Images")
    plt.imshow(np.transpose(img_list[-1],(1,2,0)))
    # plt.show()
    plt.savefig(sample_path + f'/showcase.png')