Porting DTNN Class #3513
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Porting DTNN Class #3513
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tonydavis629
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Aug 6, 2023
deepchem/models/torch_models/dtnn.py
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| >>> from deepchem.models.torch_models import dtnn | ||
| >>> from deepchem.data import SDFLoader | ||
| >>> from deepchem.feat import CoulombMatrix | ||
| >>> from deepchem.models.torch_models import dtnn |
deepchem/models/torch_models/dtnn.py
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| Computed Features | ||
| ----------------- |
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should be Returns, and the doc should explain that features is a list of these np arrays, not separate values
shaipranesh2
approved these changes
Aug 6, 2023
tonydavis629
approved these changes
Aug 6, 2023
rbharath
reviewed
Aug 9, 2023
rbharath
reviewed
Aug 9, 2023
deepchem/models/torch_models/dtnn.py
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| return output | ||
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| def _compute_features_on_batch(X_b: np.ndarray, |
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Let's make this a public function and add an explicit unit test since it's quite complicated
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This should document it's designed to work with CoulombMatrix outputs
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For now, let's make a new file in utils for batching and add this there and document it
rbharath
reviewed
Aug 9, 2023
rbharath
reviewed
Aug 18, 2023
| from deepchem.models.torch_models import layers | ||
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| class DTNN(nn.Module): |
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This should be listed in docs/. Let's just add it to layers.rst.
rbharath
reviewed
Aug 18, 2023
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Description
Fix #(issue)
Type of change
Please check the option that is related to your PR.
Checklist
yapf -i <modified file>and check no errors (yapf version must be 0.32.0)mypy -p deepchemand check no errorsflake8 <modified file> --countand check no errorspython -m doctest <modified file>and check no errors