Comments (6)
I'm having the same issue with the current status of "master" branch. Commit "https://github.com/Janspiry/Palette-Image-to-Image-Diffusion-Models/tree/d1b9b010edeee177aaa15850002766e370a8307b" is working fine for me. A bug was probably introduced in commit "ed29b1ce9ff2ae41791d52642004385886f0680f"
from palette-image-to-image-diffusion-models.
Feel free to reopen the issue if there is any question.
from palette-image-to-image-diffusion-models.
#5 talks about the same error Model [Palette() form models.model] not recognized
from palette-image-to-image-diffusion-models.
train.log
22-06-09 22:55:24.592 - INFO: Create the log file in directory experiments/debug_inpainting_celebahq_220609_225523.
22-06-09 22:55:24.684 - INFO: Dataset [InpaintDataset() form data.dataset] is created.
22-06-09 22:55:24.684 - INFO: Dataset for train have 48 samples.
22-06-09 22:55:24.685 - INFO: Dataset for val have 2 samples.
22-06-09 22:55:25.194 - INFO: Network [Network() form models.network] is created.
22-06-09 22:55:25.195 - INFO: Network [Network] weights initialize using [kaiming] method.
22-06-09 22:55:25.692 - WARNING: Config is a str, converts to a dict {'name': 'mae'}
22-06-09 22:55:26.060 - INFO: Metric [mae() form models.metric] is created.
22-06-09 22:55:26.060 - WARNING: Config is a str, converts to a dict {'name': 'mse_loss'}
22-06-09 22:55:26.068 - INFO: Loss [mse_loss() form models.loss] is created.
22-06-09 22:55:26.257 - INFO: Beign loading pretrained model [Network] ...
22-06-09 22:55:26.257 - WARNING: Pretrained model in [experiments/train_inpainting_celebahq_220426_233652/checkpoint/190_Network.pth] is not existed, Skip it
22-06-09 22:55:26.257 - INFO: Beign loading pretrained model [Network_ema] ...
22-06-09 22:55:26.258 - WARNING: Pretrained model in [experiments/train_inpainting_celebahq_220426_233652/checkpoint/190_Network_ema.pth] is not existed, Skip it
22-06-09 22:55:26.281 - INFO: Beign loading training states
22-06-09 22:55:26.282 - WARNING: Training state in [experiments/train_inpainting_celebahq_220426_233652/checkpoint/190.state] is not existed, Skip it
from palette-image-to-image-diffusion-models.
I'm having the same issue with the current status of "master" branch. Commit "https://github.com/Janspiry/Palette-Image-to-Image-Diffusion-Models/tree/d1b9b010edeee177aaa15850002766e370a8307b" is working fine for me. A bug was probably introduced in commit "ed29b1ce9ff2ae41791d52642004385886f0680f"
Hi, could you show me the log and configure file?
Since the lastest code have changed the configure file structure.
from palette-image-to-image-diffusion-models.
I have the same problem when I train from scratch on my own dataset, but I don't know how to solve it. Here is my log:
23-04-22 20:28:58.357 - INFO: Create the log file in directory experiments/debug_colorization_mirflickr25k_230422_202856.
23-04-22 20:28:58.409 - INFO: Dataset [ColorizationDataset() form data.dataset] is created.
23-04-22 20:28:58.409 - INFO: Dataset for train have 48 samples.
23-04-22 20:28:58.409 - INFO: Dataset for val have 2 samples.
23-04-22 20:28:58.910 - INFO: Network [Network() form models.network] is created.
23-04-22 20:28:58.910 - INFO: Network [Network] weights initialize using [kaiming] method.
23-04-22 20:28:59.314 - INFO: Config is a str, converts to a dict {'name': 'mae'}
23-04-22 20:28:59.865 - INFO: Metric [mae() form models.metric] is created.
23-04-22 20:28:59.865 - INFO: Config is a str, converts to a dict {'name': 'mse_loss'}
23-04-22 20:28:59.897 - INFO: Loss [mse_loss() form models.loss] is created.
23-04-22 20:28:59.900 - INFO: Optimizer [Adam() form default file] is created.
23-04-22 20:28:59.900 - INFO: Scheduler [LinearLR() form default file] is created.
from palette-image-to-image-diffusion-models.
Related Issues (20)
- use specific mask HOT 3
- what's the valid mask HOT 5
- Question about encode the gama rather than t HOT 2
- pth2onnx,How should I use βtorch.onnx.export()β HOT 1
- Image-to-image translation with mostly black images HOT 3
- How can I add classifier guidance while doing the uncropping task?
- Broken pipeline error while training on multiple gpu
- use this project for image restoration
- How can I adapt the colorization model to work with different image resolutions?
- Training loss growing up
- why p_mean_variance use noise_level instead of sample_gammas like in training for time conditon of denoise function. HOT 3
- There was no result at the time of the test
- segmentation fault HOT 1
- Some of the results are full of noise. HOT 2
- test noise schedule and train noise schedule are different?
- Whether to use a lr scheduler when training from the scratch? HOT 1
- I'm fused by the output and target noise.
- [Uncropping]How to generate panoramas like Firgure 2?
- Error During Colorization Training
- How to implement JPEG restoration task based on this paper?
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