add batch_size #37
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add batch_size #37
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@davek44 This looks good and I assume you tested the fix. I had one comment but feel free to merge after |
njbernstein
reviewed
Jun 10, 2020
| valid_pct = params.get('valid_pct', 0.1) | ||
| learning_rate = params.get('learning_rate', 1e-3) | ||
| stopping_params = {'patience': params.get('patience', 10), 'threshold': 0} | ||
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| # protect against single example batch | ||
| while num_cells % batch_size == 1: | ||
| batch_size = int(np.round(1.25*batch_size)) |
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What would be wrong with?:
batch_size = int(np.round(1 + batch_size))
Also wouldn't need to put this in a while loop then.
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Yea that's probably fine. GPUs tend to achieve better efficiency with batches divisible by powers of two, so I tried to come up with a strategy that would tend to maintain that. Either way is fine with me.
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Gotcha. I figured there might be something like that. This is fine with me. Merge away!
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I'm gonna merge this in |
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Solo crashes when there are N cells where N % 128 == 1 due to the following scVI (pytorch?) issue: scverse/scvi-tools#426. They only fixed the problem for training; it still crashes when obtaining latent embeddings from a trained model.
Here, I added batch_size as a parameter, check for a single leftover cell, and change the batch size if it's detected.