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Methods of Reducing Vram Required?

Currently training a CNN on images that are 1024 x 768, these are scaled down to an input shape of 256, 192

Struggling to get the model accurate with real world predictions but can’t add much more complexity to the model without getting insufficient memory errors.

Tried using tf.keras.experimental.set_memory_growth to True without much improvement.

Does anyone have any tips to reduce the amount of Vram required or do I need to get a GPU with more Vram?

GPU: RTX 3070 8GB

Tensorflow: 2.5

CUDA: 11.2

submitted by /u/Cooperrrrr
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