【日常出错】使用开源项目KAIR训练EDSR超分辨率模型

Question

我使用GITHUB开源项目KAIR源码框架训练EDSR超分辨率模型，模型能够跑的通但是为什么最后超分辨率输出的图像会是这个样子

这两张图是两次不同迭代代数的效果

并且输出的训练日志中PSNR的数值波动的十分诡异，下面这些是我截图的训练日志
明显看到PSNR从10dB掉到1dB，又再次回到10dB

使用的是自制的数据集，低分辨率图像尺寸是6464 高分辨率是128128，模型是在GoogleColab环境下训练的
这是EDSR模型的源码

from models import common

import torch.nn as nn

url = {
    'r16f64x2': 'https://cv.snu.ac.kr/research/EDSR/models/edsr_baseline_x2-1bc95232.pt',
    'r16f64x3': 'https://cv.snu.ac.kr/research/EDSR/models/edsr_baseline_x3-abf2a44e.pt',
    'r16f64x4': 'https://cv.snu.ac.kr/research/EDSR/models/edsr_baseline_x4-6b446fab.pt',
    'r32f256x2': 'https://cv.snu.ac.kr/research/EDSR/models/edsr_x2-0edfb8a3.pt',
    'r32f256x3': 'https://cv.snu.ac.kr/research/EDSR/models/edsr_x3-ea3ef2c6.pt',
    'r32f256x4': 'https://cv.snu.ac.kr/research/EDSR/models/edsr_x4-4f62e9ef.pt'
}

def make_model(args, parent=False):
    return EDSR(args)

class EDSR(nn.Module):
    def __init__(self, args, conv=common.default_conv):
        super(EDSR, self).__init__()

        n_resblocks = args['n_resblocks']
        n_feats = args['n_feats']
        kernel_size = 3 
        scale = args['scale']
        act = nn.ReLU(True)
        url_name = 'r{}f{}x{}'.format(n_resblocks, n_feats, scale)
        if url_name in url:
            self.url = url[url_name]
        else:
            self.url = None
        self.sub_mean = common.MeanShift(args['rgb_range'])
        self.add_mean = common.MeanShift(args['rgb_range'], sign=1)

        # define head module
        m_head = [conv(args['n_colors'], n_feats, kernel_size)]

        # define body module
        m_body = [
            common.ResBlock(
                conv, n_feats, kernel_size, act=act, res_scale=args['res_scale']
            ) for _ in range(n_resblocks)
        ]
        m_body.append(conv(n_feats, n_feats, kernel_size))

        # define tail module
        m_tail = [
            common.Upsampler(conv, scale, n_feats, act=False),
            conv(n_feats, args['n_colors'], kernel_size)
        ]

        self.head = nn.Sequential(*m_head)
        self.body = nn.Sequential(*m_body)
        self.tail = nn.Sequential(*m_tail)

    def forward(self, x):
        x = self.sub_mean(x)
        x = self.head(x)

        res = self.body(x)
        res += x

        x = self.tail(res)
        x = self.add_mean(x)

        return x 

    def load_state_dict(self, state_dict, strict=True):
        own_state = self.state_dict()
        for name, param in state_dict.items():
            if name in own_state:
                if isinstance(param, nn.Parameter):
                    param = param.data
                try:
                    own_state[name].copy_(param)
                except Exception:
                    if name.find('tail') == -1:
                        raise RuntimeError('While copying the parameter named {}, '
                                           'whose dimensions in the model are {} and '
                                           'whose dimensions in the checkpoint are {}.'
                                           .format(name, own_state[name].size(), param.size()))
            elif strict:
                if name.find('tail') == -1:
                    raise KeyError('unexpected key "{}" in state_dict'
                                   .format(name))

这其中的arg是来自于json文件中的配置参数,我是按照KAIR中的框架结构自己添加的模型，也就是说本身KAIR是没有EDSR这个模型的