Hi, there, I don't find the any code to evident that the parameter is shared. Maybe becanse I don't I understand how to use the "weight shared function" of pytorch? Can u help me? thanks.

class DRRN(nn.Module):
	def __init__(self):
		super(DRRN, self).__init__()
		self.input = nn.Conv2d(in_channels=1, out_channels=128, kernel_size=3, stride=1, padding=1, bias=False)
		self.conv1 = nn.Conv2d(in_channels=128, out_channels=128, kernel_size=3, stride=1, padding=1, bias=False)
		self.conv2 = nn.Conv2d(in_channels=128, out_channels=128, kernel_size=3, stride=1, padding=1, bias=False)
		self.output = nn.Conv2d(in_channels=128, out_channels=1, kernel_size=3, stride=1, padding=1, bias=False)
		self.relu = nn.ReLU(inplace=True)

		# weights initialization
		for m in self.modules():
			if isinstance(m, nn.Conv2d):
				n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels
				m.weight.data.normal_(0, sqrt(2. / n))

	def forward(self, x):
		residual = x
		inputs = self.input(self.relu(x))
		out = inputs
		for _ in range(25):
			out = self.conv2(self.relu(self.conv1(self.relu(out))))
			out = torch.add(out, inputs)

		out = self.output(self.relu(out))
		out = torch.add(out, residual)
return out

I want to be able to test with my own dataset. First, I need to convert the image to. Mat, such as a_ x2.mat ,a_ x4.mat In the project, for example, How is the file baby_ GT_ x2.mat generated?

我希望能用自己的数据集测试，首先需要将图片转换为.mat,如a_x2.mat ,a_x4.mat 请问项目中例如baby_GT_x2.mat的文件是如何生成的？

Hello, after I finished the H5 file on MATLAB, I ran main.py for training, and the TypeError: h5py objects cannot be pickled error appeared. What could be the reason?

感谢大佬开源，我按照你的代码，没有改任何代码，跑50 epoch，发现在第50 epoch得到结果如下： Processing Set5_mat/head_GT_x2.mat Processing Set5_mat/butterfly_GT_x2.mat Processing Set5_mat/baby_GT_x2.mat Processing Set5_mat/woman_GT_x2.mat Scale= 2 Dataset= Set5 PSNR_predicted= 35.98152927120101 PSNR_bicubic= 33.69039381292539 It takes average 5.726621294021607s for processing Processing Set5_mat/woman_GT_x3.mat Processing Set5_mat/bird_GT_x3.mat Processing Set5_mat/baby_GT_x3.mat Processing Set5_mat/head_GT_x3.mat Processing Set5_mat/butterfly_GT_x3.mat Scale= 3 Dataset= Set5 PSNR_predicted= 32.590871083509164 PSNR_bicubic= 30.407692343235453 It takes average 5.687644147872925s for processing Processing Set5_mat/bird_GT_x4.mat Processing Set5_mat/woman_GT_x4.mat Processing Set5_mat/butterfly_GT_x4.mat Processing Set5_mat/head_GT_x4.mat Processing Set5_mat/baby_GT_x4.mat Scale= 4 Dataset= Set5 PSNR_predicted= 30.483599758580993 PSNR_bicubic= 28.41454827257395 It takes average 5.374003458023071s for processing

相反的是我在第20 epoch得到了更好的结果，emmm，如果大佬有时间可以麻烦解答下么： Processing Set5_mat/head_GT_x2.mat Processing Set5_mat/butterfly_GT_x2.mat Processing Set5_mat/baby_GT_x2.mat Processing Set5_mat/woman_GT_x2.mat Scale= 2 Dataset= Set5 PSNR_predicted= 36.17091792433612 PSNR_bicubic= 33.69039381292539 It takes average 5.751824855804443s for processing Processing Set5_mat/woman_GT_x3.mat Processing Set5_mat/bird_GT_x3.mat Processing Set5_mat/baby_GT_x3.mat Processing Set5_mat/head_GT_x3.mat Processing Set5_mat/butterfly_GT_x3.mat Scale= 3 Dataset= Set5 PSNR_predicted= 32.7447910082183 PSNR_bicubic= 30.407692343235453 It takes average 5.653450155258179s for processing Processing Set5_mat/bird_GT_x4.mat Processing Set5_mat/woman_GT_x4.mat Processing Set5_mat/butterfly_GT_x4.mat Processing Set5_mat/head_GT_x4.mat Processing Set5_mat/baby_GT_x4.mat Scale= 4 Dataset= Set5 PSNR_predicted= 30.44373425939143 PSNR_bicubic= 28.41454827257395 It takes average 5.370740699768066s for processing

Thank you for your wonderful work! I want to train a model with my own dataset, but there are something wrong in the process. The error is described as below:

===> Loading datasets ===> Building model /home/luomeilu/anaconda3/envs/py2/lib/python2.7/site-packages/torch/nn/_reduction.py:49: UserWarning: size_average and reduce args will be deprecated, please use reduction='sum' instead. warnings.warn(warning.format(ret)) ===> Setting GPU ===> load model model/model_epoch_28.pth /home/luomeilu/anaconda3/envs/py2/lib/python2.7/site-packages/torch/serialization.py:435: SourceChangeWarning: source code of class 'torch.nn.parallel.data_parallel.DataParallel' has changed. you can retrieve the original source code by accessing the object's source attribute or set torch.nn.Module.dump_patches = True and use the patch tool to revert the changes. warnings.warn(msg, SourceChangeWarning) /home/luomeilu/anaconda3/envs/py2/lib/python2.7/site-packages/torch/serialization.py:435: SourceChangeWarning: source code of class 'torch.nn.modules.conv.Conv2d' has changed. you can retrieve the original source code by accessing the object's source attribute or set torch.nn.Module.dump_patches = True and use the patch tool to revert the changes. warnings.warn(msg, SourceChangeWarning) /home/luomeilu/anaconda3/envs/py2/lib/python2.7/site-packages/torch/serialization.py:435: SourceChangeWarning: source code of class 'torch.nn.modules.activation.ReLU' has changed. you can retrieve the original source code by accessing the object's source attribute or set torch.nn.Module.dump_patches = True and use the patch tool to revert the changes. warnings.warn(msg, SourceChangeWarning) Traceback (most recent call last): File "main.py", line 128, in main() File "main.py", line 69, in main model.load_state_dict(weights['model'].state_dict()) File "/home/luomeilu/anaconda3/envs/py2/lib/python2.7/site-packages/torch/nn/modules/module.py", line 769, in load_state_dict self.class.name, "\n\t".join(error_msgs))) RuntimeError: Error(s) in loading state_dict for DRRN: Missing key(s) in state_dict: "input.weight", "conv1.weight", "conv2.weight", "output.weight". Unexpected key(s) in state_dict: "module.input.weight", "module.conv1.weight", "module.conv2.weight", "module.output.weight".

It seems that the parameters in model are miss? I can't understand the error, hoping you can give me some suggestions. Sincerely appreciate for your reply.