Comments (1)
AlLongley
commented on June 7, 2024
This implementation of CapsNet (If not every other as well) is quite heavy in terms of memory overhead for weights/optimizer gradients.
You're supplying a 128 x 3872 x 196 x16 element batch input, as float32 values would take about 6.2 GB of memory, considering optimizer overhead I could see that being some multiple of that.
Does it run with a batch size of 1? Try 10 and see what difference it makes in memory usage, and work out your highest usable batch size like that
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Related Issues (20)
- ValueError when using cl.layers.conv2d HOT 1
- Reproducing results from "Matrix Capsules with EM Routing" HOT 2
- EM Capsule Dense Layer Routing HOT 4
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- Spelling Error
- CapsLayer Neural Network Example
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- Prediction problem HOT 3
- ModuleNotFoundError: No module named 'capslayer.data.datasets.stanford_drone' HOT 2
- cifar10 dataset "Maximum allowed size exceeded" Error HOT 2
- tensorflow2.0 how to write config.py？ HOT 1
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