Comments (6)
@HsinYingLee and @milankolkata I think the code is now working properly in pytorch 0.4 now.
We spent sometime in the past few days playing with this summer2winter_yosemite256
. We found that when enabling explicit cycle consistency loss, the model converges faster and better. The new config file can be found in configs/summer2winter_yosemite256_folder.yaml
.
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@HsinYingLee I also have the similar problem, how many images do you have in your training set(trainA and trainB)?
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@milankolkata According to the the recent commit, the degraded issue is due to setting <track_running_stats=True>
for instance normalization. I haven't tried the updated code yet but I believe the problem should be fixed.
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@HsinYingLee Thanks for mentioning it. I am trying the new code. How many images did you use when training the model?
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@milankolkata In the commit 972e42, the custom layernorm only supports one image per batch. With the new commit 4c21350, it supports multiple images per batch. However, the time required for each iteration would increase about 4 times when you use a batch size greater than 1. (This is due to the change of the way pytorch implements view
function in 0.4. For training with batch size greater than 1, please roll back to pytorch 0.3 and use munit_pytorch0.3.
BTW, I am still confirming if the performance is the same for pytorch 0.3 and 0.4.
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@mingyuliutw Thanks! I will try munit_pytorch0.3 and hope it could speed the training up. Also, expect the code supports the multi-GPUs in the future.
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Related Issues (20)
- How to implement MUNIT with K Fold Cross Validation?
- Question about Multi-GPU training on single machine HOT 4
- Can you use non-standardised dataset for training?
- Checkpoint images examples?
- Can i do train grayscale-imageset?
- Pytorch version >=1.0 How to load VGG16 pretrain in VGG16.T7? HOT 1
- Experiment of using Instance Normalization vs Layer Normalization on Decoder HOT 8
- AdaptiveInstanceNorm2d and the LayerNorm misunderstand
- May I ask if everyone will prompt "Warning: NaN or Inf found in input tensor." during runtime? HOT 1
- Questions about batch_size and GPU memory usage
- loss Nan
- When are you planning to make it public?
- After F(x)+x, the ResBlock seems not follow by a non-linearity activation HOT 1
- Ideas to speed up training phase
- Missing max pooling layer in the Vgg16 network structure
- outputs = (outputs + 1) / 2. in test code HOT 1
- inception checkpoint? HOT 3
- Ŕ
- summer2winter_yosemite checkpoint?
- Pretrained Inception Network HOT 1
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