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Number of ways to split should evenly divide the split dimension #7
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Hey Tomer, I think the problem is that the last training (or validation) batch of your data doesn't actually have 128 samples inside but only 29 (check https://www.tensorflow.org/api_docs/python/tf/data/Dataset, drop_remainder argument). The current implementation assumes that every batch has a number of samples that are divisible by the number of masks. A possible workaround is to create tf dataset with drop_remainder option turned on or just check that number of training (and validation) samples is divisible by 4.
Best, |
Hello,
I'm trying to use the layer, and I'm facing the below error:
My Network looks like this:
My amount of data is 1170 records of train, and 0.1 to the validation.
What should I notice before using this model?
Thanks.
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