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Speed up Dino with DALI #5431
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Hi @jpfeil, Thank you for reaching out. |
Thank you, @JanuszL! I've implemented the pipeline with your suggestions, but now I'm having issues with the iterator.
This works and I can get augmented images out of it. The only issue is that I'm used to the pytorch representation using floats whereas in DALI it usually represents the image as uint8, but hopefully that doesn't influence training that much. The problem I have now is passing the pipeline to the iterator:
This will run for a little while and then it throws this error:
This seems to be related to the global and local crops being different sizes. Is there a way to support this kind of data in DALI? Thanks! |
Hi @jpfeil,
You can use the
Yes, the iterator expects that the batch of samples can be represented as the tensor where one of the dimensions is the batch size. In this case, you can either pad samples to have them uniform or try out PyTorch DALIRaggedIterator. |
Describe the question.
Hello,
I'm trying to speed up the image augmentations in DINO with DALI. I'm trying to start with a naive solution which is just calling the augmentations from DALI. I'll optimize it once I get this running, but I can't get this to build. I'm getting this error:
Can you please help me find the issue with this code?
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