Loading deepchem/models/tests/test_cgcnn.py +1 −1 Original line number Diff line number Diff line Loading @@ -45,7 +45,7 @@ def test_cgcnn(): # check overfit regression_metric = Metric(mae_score, n_tasks=n_tasks) scores = model.evaluate(train, [regression_metric], transformers) assert scores[regression_metric.name] < 0.5 assert scores[regression_metric.name] < 0.6 # classification test tasks, datasets, transformers = load_mp_metallicity(**config) Loading deepchem/models/torch_models/cgcnn.py +4 −1 Original line number Diff line number Diff line Loading @@ -200,7 +200,10 @@ class CGCNN(nn.Module): Returns ------- out: torch.Tensor The output value, the shape is `(batch_size, n_tasks)`. The output values of this model. If mode == 'regression', the shape is `(batch_size, n_tasks)`. If mode == 'classification', the shape is `(batch_size, n_tasks, n_classes)` (n_tasks > 1) or `(batch_size, n_classes)` (n_tasks == 1) and the output values are probabilities of each class label. """ try: import dgl Loading deepchem/molnet/load_function/material_datasets/load_bandgap.py +1 −1 Original line number Diff line number Diff line Loading @@ -68,7 +68,7 @@ def load_bandgap( Parameters ---------- featurizer : MaterialCompositionFeaturizer, default ElementPropertyFingerprint featurizer : MaterialCompositionFeaturizer (default ElementPropertyFingerprint) A featurizer that inherits from deepchem.feat.Featurizer. transformers : List[Transformer] A transformer that inherits from deepchem.trans.Transformer. Loading deepchem/molnet/load_function/material_datasets/load_mp_formation_energy.py +1 −1 Original line number Diff line number Diff line Loading @@ -69,7 +69,7 @@ def load_mp_formation_energy( Parameters ---------- featurizer : MaterialStructureFeaturizer, default SineCoulombMatrix featurizer : MaterialStructureFeaturizer (default SineCoulombMatrix) A featurizer that inherits from deepchem.feat.Featurizer. transformers : List[Transformer] A transformer that inherits from deepchem.trans.Transformer. Loading deepchem/molnet/load_function/material_datasets/load_mp_metallicity.py +2 −2 Original line number Diff line number Diff line Loading @@ -69,9 +69,9 @@ def load_mp_metallicity( Parameters ---------- featurizer : MaterialStructureFeaturizer, default SineCoulombMatrix featurizer : MaterialStructureFeaturizer (default SineCoulombMatrix) A featurizer that inherits from deepchem.feat.Featurizer. transformers : List[Transformer], , default NormalizationTransformer transformers : List[Transformer] A transformer that inherits from deepchem.trans.Transformer. splitter : Splitter (default RandomSplitter) A splitter that inherits from deepchem.splits.splitters.Splitter. Loading Loading
deepchem/models/tests/test_cgcnn.py +1 −1 Original line number Diff line number Diff line Loading @@ -45,7 +45,7 @@ def test_cgcnn(): # check overfit regression_metric = Metric(mae_score, n_tasks=n_tasks) scores = model.evaluate(train, [regression_metric], transformers) assert scores[regression_metric.name] < 0.5 assert scores[regression_metric.name] < 0.6 # classification test tasks, datasets, transformers = load_mp_metallicity(**config) Loading
deepchem/models/torch_models/cgcnn.py +4 −1 Original line number Diff line number Diff line Loading @@ -200,7 +200,10 @@ class CGCNN(nn.Module): Returns ------- out: torch.Tensor The output value, the shape is `(batch_size, n_tasks)`. The output values of this model. If mode == 'regression', the shape is `(batch_size, n_tasks)`. If mode == 'classification', the shape is `(batch_size, n_tasks, n_classes)` (n_tasks > 1) or `(batch_size, n_classes)` (n_tasks == 1) and the output values are probabilities of each class label. """ try: import dgl Loading
deepchem/molnet/load_function/material_datasets/load_bandgap.py +1 −1 Original line number Diff line number Diff line Loading @@ -68,7 +68,7 @@ def load_bandgap( Parameters ---------- featurizer : MaterialCompositionFeaturizer, default ElementPropertyFingerprint featurizer : MaterialCompositionFeaturizer (default ElementPropertyFingerprint) A featurizer that inherits from deepchem.feat.Featurizer. transformers : List[Transformer] A transformer that inherits from deepchem.trans.Transformer. Loading
deepchem/molnet/load_function/material_datasets/load_mp_formation_energy.py +1 −1 Original line number Diff line number Diff line Loading @@ -69,7 +69,7 @@ def load_mp_formation_energy( Parameters ---------- featurizer : MaterialStructureFeaturizer, default SineCoulombMatrix featurizer : MaterialStructureFeaturizer (default SineCoulombMatrix) A featurizer that inherits from deepchem.feat.Featurizer. transformers : List[Transformer] A transformer that inherits from deepchem.trans.Transformer. Loading
deepchem/molnet/load_function/material_datasets/load_mp_metallicity.py +2 −2 Original line number Diff line number Diff line Loading @@ -69,9 +69,9 @@ def load_mp_metallicity( Parameters ---------- featurizer : MaterialStructureFeaturizer, default SineCoulombMatrix featurizer : MaterialStructureFeaturizer (default SineCoulombMatrix) A featurizer that inherits from deepchem.feat.Featurizer. transformers : List[Transformer], , default NormalizationTransformer transformers : List[Transformer] A transformer that inherits from deepchem.trans.Transformer. splitter : Splitter (default RandomSplitter) A splitter that inherits from deepchem.splits.splitters.Splitter. Loading
