Comments (1)
Thank you @pawopawo !
Running this current version with multi-gpu will be very slow, see post here.
People start using Apex for parallel, maybe you could have a try.
from fasterseg.
Related Issues (20)
- I reported an error on my own data set while I was infering HOT 3
- Test Issue HOT 1
- Training with custom data with different resolution to cityscapes dataset HOT 1
- TranA and TrainB is overlapped according to your implementation HOT 5
- NaN values in loss function during Step 2.2 HOT 2
- BaseDataset.__getitem__ always returns random item if file_length is set HOT 1
- CUDA out of memory: GeForce GTX 1650. HOT 1
- Which Nvidia GPU card do you use for training? HOT 2
- What's the idea of `betas2path ` ? HOT 3
- CUDA out of memory HOT 2
- How to estimate the runtime of the four steps depending on epochs and iterations?
- RuntimeError: transform: failed to synchronize: cudaErrorAssert: device-side assert triggered
- error during run_latency.py HOT 3
- Whether the architectures are different after each searching?
- Custom Data Resolution for Training HOT 10
- RuntimeError:CUDA error:API call is not supported in the installed CUDA driver HOT 1
- Setting up on Windows
- Model mismatch occurs when training student network with own data set HOT 2
- A train_fine_val.txt file
- Pretrained model
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from fasterseg.