Loading examples/factors/README.md +1 −3 Original line number Diff line number Diff line Loading @@ -18,6 +18,4 @@ alternate modes of splitting. Similarly, since the source data came pre-featurized, it is not possible to apply alternative featurizations. In this example, we train various models on the Factors dataset: - In this example, we train various models on the Factors dataset. examples/hiv/README.md +1 −3 Original line number Diff line number Diff line Loading @@ -18,6 +18,4 @@ are used: References: AIDS Antiviral Screen Data. https://wiki.nci.nih.gov/display/NCIDTPdata/AIDS+Antiviral+Screen+Data ## Models Trained In this example we train the following models on the HIV collection. In this example we train models on the HIV collection. examples/kaggle/README.md +1 −1 Original line number Diff line number Diff line Loading @@ -18,4 +18,4 @@ alternate modes of splitting. Similarly, since the source data came pre-featurized, it is not possible to apply alternative featurizations. This folder contains examples training models on the Kaggle dataset: This folder contains examples training models on the Kaggle dataset. examples/model_restore/.gitignore 0 → 100644 +1 −0 Original line number Diff line number Diff line model/ examples/model_restore/chemception_restore.py +3 −5 Original line number Diff line number Diff line Loading @@ -2,15 +2,13 @@ import deepchem as dc import rdkit.Chem as Chem model = dc.models.ChemCeption( img_spec="engd", n_tasks=1, model_dir="./model", mode="regression") img_spec="engd", n_tasks=1, model_dir="./model", mode="regression") model.restore() smiles = "CCCCC" featurizer = dc.feat.SmilesToImage(img_spec="engd", img_size=80, res=0.5) dataset = dc.data.NumpyDataset(featurizer.featurize([Chem.MolFromSmiles(smiles)])) dataset = dc.data.NumpyDataset( featurizer.featurize([Chem.MolFromSmiles(smiles)])) prediction = model.predict(dataset) print("smiles: %s" % smiles) print("prediction: %s" % str(prediction)) examples/model_restore/chemception_model.py +1 −1 File changed.Contains only whitespace changes. Show changes Loading
examples/factors/README.md +1 −3 Original line number Diff line number Diff line Loading @@ -18,6 +18,4 @@ alternate modes of splitting. Similarly, since the source data came pre-featurized, it is not possible to apply alternative featurizations. In this example, we train various models on the Factors dataset: - In this example, we train various models on the Factors dataset.
examples/hiv/README.md +1 −3 Original line number Diff line number Diff line Loading @@ -18,6 +18,4 @@ are used: References: AIDS Antiviral Screen Data. https://wiki.nci.nih.gov/display/NCIDTPdata/AIDS+Antiviral+Screen+Data ## Models Trained In this example we train the following models on the HIV collection. In this example we train models on the HIV collection.
examples/kaggle/README.md +1 −1 Original line number Diff line number Diff line Loading @@ -18,4 +18,4 @@ alternate modes of splitting. Similarly, since the source data came pre-featurized, it is not possible to apply alternative featurizations. This folder contains examples training models on the Kaggle dataset: This folder contains examples training models on the Kaggle dataset.
examples/model_restore/.gitignore 0 → 100644 +1 −0 Original line number Diff line number Diff line model/
examples/model_restore/chemception_restore.py +3 −5 Original line number Diff line number Diff line Loading @@ -2,15 +2,13 @@ import deepchem as dc import rdkit.Chem as Chem model = dc.models.ChemCeption( img_spec="engd", n_tasks=1, model_dir="./model", mode="regression") img_spec="engd", n_tasks=1, model_dir="./model", mode="regression") model.restore() smiles = "CCCCC" featurizer = dc.feat.SmilesToImage(img_spec="engd", img_size=80, res=0.5) dataset = dc.data.NumpyDataset(featurizer.featurize([Chem.MolFromSmiles(smiles)])) dataset = dc.data.NumpyDataset( featurizer.featurize([Chem.MolFromSmiles(smiles)])) prediction = model.predict(dataset) print("smiles: %s" % smiles) print("prediction: %s" % str(prediction))
examples/model_restore/chemception_model.py +1 −1 File changed.Contains only whitespace changes. Show changes
