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the github repository of GDSR
Hi there, I am currently trying to reproduce your project and have faced some issues that I cannot resolve, I was wondering if you could help me?
I am currently running pretrain for DualSR using python train.py -opt options/train/DualSR_pretrain.json
, the JSON configs are as follows:
{
"name": "12_21_01_Dual_RRDB_128_GAN_x4_DIV2K",
"use_tb_logger": true,
"model": "DualSR_pretrain",
"scale": 4,
"gpu_ids": [0, 1, 2, 3],
"datasets": {
"train": {
"name": "DIV2K",
"mode": "LRHR",
"dataroot_HR": "/media/e621/RAID5/e621/downloads/.tmp/DIV2K_train_HR_sub.lmdb",
"dataroot_LR": "/media/e621/RAID5/e621/downloads/.tmp/DIV2K_train_LR_x4_sub.lmdb",
"subset_file": null,
"use_shuffle": true,
"n_workers": 8,
"batch_size": 28
,
"HR_size": 128
,
"use_flip": true,
"use_rot": true
},
"val": {
"name": "val_set5_part",
"mode": "LRHR",
"dataroot_HR": "/home/e517herb/Desktop/GDSR/Set5/original",
"dataroot_LR": "/home/e517herb/Desktop/GDSR/Set5/LRbicx4"
}
},
"path": {
"root": "/home/e517herb/Desktop/LCC_BasicSR-master"
},
"network_G": {
"which_model_G": "DualSR_RRDB"
,
"norm_type": null,
"mode": "CNA",
"nf": 64,
"nb_l_1": 10,
"nb_l_2": 5,
"nb_h_1": 5,
"nb_h_2": 10,
"nb_e": 2,
"nb_m": 5,
"in_nc": 3,
"out_nc": 3,
"gc": 32,
"group": 1
},
"network_D": {
"which_model_D": "discriminator_vgg_128"
, "norm_type": "batch"
, "act_type": "leakyrelu"
, "mode": "CNA"
, "nf": 64
, "in_nc": 3
},
"train": {
"lr_G": 5e-5,
"lr_scheme": "MultiStepLR",
"lr_steps": [
200000,
400000,
600000,
800000
],
"lr_gamma": 0.5,
"pixel_criterion": "l1",
"pixel_weight": 1.0,
"val_freq": 1e3,
"manual_seed": 0,
"niter": 1e6,
"feature_weight": 1
},
"logger": {
"print_freq": 200,
"save_checkpoint_freq": 1e3
}
}
the output shows a mismatch between input channel size
20-11-10 00:57:08.525 - INFO: Model [DualSR_pretrain] is created.
20-11-10 00:57:08.525 - INFO: Start training from epoch: 0, iter: 0
Traceback (most recent call last):
File "train.py", line 182, in <module>
main()
File "train.py", line 112, in main
model.optimize_parameters(current_step)
File "/home/e517herb/Desktop/GDSR/codes/models/DualSR_pretrain.py", line 68, in optimize_parameters
self.fake_Low, self.fake_high, self.fake_mask = self.netG(self.var_L)
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/nn/modules/module.py", line 541, in __call__
result = self.forward(*input, **kwargs)
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/nn/parallel/data_parallel.py", line 152, in forward
outputs = self.parallel_apply(replicas, inputs, kwargs)
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/nn/parallel/data_parallel.py", line 162, in parallel_apply
return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)])
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/nn/parallel/parallel_apply.py", line 85, in parallel_apply
output.reraise()
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/_utils.py", line 385, in reraise
raise self.exc_type(msg)
RuntimeError: Caught RuntimeError in replica 0 on device 0.
Original Traceback (most recent call last):
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/nn/parallel/parallel_apply.py", line 60, in _worker
output = module(*input, **kwargs)
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/nn/modules/module.py", line 541, in __call__
result = self.forward(*input, **kwargs)
File "/home/e517herb/Desktop/GDSR/codes/models/modules/DualSR_RRDB.py", line 89, in forward
x = self.body_ex(x) # shared module做2次RRDB後
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/nn/modules/module.py", line 541, in __call__
result = self.forward(*input, **kwargs)
File "/home/e517herb/Desktop/GDSR/codes/models/modules/block.py", line 94, in forward
output = x + self.sub(x)
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/nn/modules/module.py", line 541, in __call__
result = self.forward(*input, **kwargs)
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/nn/modules/container.py", line 92, in forward
input = module(input)
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/nn/modules/module.py", line 541, in __call__
result = self.forward(*input, **kwargs)
File "/home/e517herb/Desktop/GDSR/codes/models/modules/block.py", line 240, in forward
out = self.RDB1(x)
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/nn/modules/module.py", line 541, in __call__
result = self.forward(*input, **kwargs)
File "/home/e517herb/Desktop/GDSR/codes/models/modules/block.py", line 215, in forward
x1 = self.conv1(x)
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/nn/modules/module.py", line 541, in __call__
result = self.forward(*input, **kwargs)
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/nn/modules/container.py", line 92, in forward
input = module(input)
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/nn/modules/module.py", line 541, in __call__
result = self.forward(*input, **kwargs)
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/nn/modules/conv.py", line 345, in forward
return self.conv2d_forward(input, self.weight)
File "/home/e517herb/anaconda3/envs/GDSR/lib/python3.6/site-packages/torch/nn/modules/conv.py", line 342, in conv2d_forward
self.padding, self.dilation, self.groups)
RuntimeError: Given groups=1, weight of size 32 64 3 3, expected input[7, 3, 32, 32] to have 64 channels, but got 3 channels instead
Is there something I did wrong? Thanks in advance!
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