Split forward functions in DXSM models #74
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matsen
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Oct 27, 2024
netam/models.py
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| representation: A tensor of shape (B, L, E) representing the | ||
| embedded parent sequences. | ||
| Returns: | ||
| A tensor of shape (B, L, 1) representing the log level of selection |
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netam/models.py
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| mask: A tensor of shape (B, L) representing the mask of valid amino acid sites. | ||
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| Returns: | ||
| A tensor of shape (B, L, 20) representing the log level of selection |
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I think rather than 20 it should be out_features which is a kwd arg. It's set to 1 for classic DSNM.
Speaking of which, in the definition of the hyperparameters we have
"output_dim": self.linear.out_features,
We should decide on one or the other of dim or features. What do you prefer?
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Intuitively I'd say dim, but maybe features is a more torch-y way of saying it?
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Beh. Let's honor your intuition.
Makefile
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| @@ -21,6 +21,9 @@ lint: | |||
| # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide | |||
| flake8 . --count --max-complexity=30 --max-line-length=127 --statistics --exclude=_ignore | |||
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| lintless: | |||
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feel free to make this the default lint if you'd like.
willdumm
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Splits forward functions into
representandpredictmethods, whererepresentdoes everything except applying the final linear layer, in preparation for https://github.com/matsengrp/dnsm-experiments-1/issues/28Will close #72.
Will need to be rebased on #73 when that's done/merged.