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adding pfam samples sweeps and images for pfam and gfp experiments #7
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dmrd
suggested changes
Jul 2, 2020
contextual_lenses/pfam_family_classification/analyze_pfam_sweeps.py
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contextual_lenses/pfam_family_classification/pfam_nearest_neighbors.py
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contextual_lenses/pfam_family_classification/pfam_nearest_neighbors_sample_sweep.py
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contextual_lenses/pfam_family_classification/pfam_nearest_neighbors_sample_sweep.py
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dmrd
suggested changes
Jul 13, 2020
| from protein_lm import data, models | ||
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| def load_transformer_model(ckpt_dir, model_cls, domain=None): |
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this function should definitely have test coverage. The easiest way to do this would be to make a new small model, compute the output on some dummy inputs, save the model to disk, make a new model by loading from file, and check that the output on the dummy inputs is the same.
contextual_lenses/pfam_family_classification/analyze_pfam_sweeps.py
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contextual_lenses/pfam_family_classification/pfam_nearest_neighbors_sample_sweep.py
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contextual_lenses/pfam_family_classification/pfam_nearest_neighbors_sample_sweep.py
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contextual_lenses/pfam_family_classification/pfam_nearest_neighbors_sample_sweep.py
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| optimizer_def = optim.Adam(learning_rate=learning_rate, weight_decay=weight_decay) | ||
| optimizer = optimizer_def.create(model) | ||
| def create_optimizer(model, learning_rate, weight_decay, layers=None): |
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Lots of flax details here. make sure ddohan signs off on this entire file. Also need to have some loading/saving tests.
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