Loading .travis.yml +7 −1 Original line number Diff line number Diff line Loading @@ -19,9 +19,15 @@ install: - pip install coveralls - python setup.py install script: - nosetests --with-flaky -a '!slow' --with-timer --with-coverage --cover-package=deepchem -v deepchem --nologcapture - nosetests --with-flaky -a '!slow' --with-timer --with-coverage --cover-package=deepchem -v deepchem --nologcapture - find ./deepchem | grep .py$ |xargs python -m doctest -v - bash devtools/travis-ci/test_format_code.sh after_success: - echo $TRAVIS_SECURE_ENV_VARS - coveralls deploy: provider: pypi user: "lilleswing" password: secure: 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 MANIFEST.in 0 → 100644 +2 −0 Original line number Diff line number Diff line prune datasets prune examples README.md +3 −0 Original line number Diff line number Diff line # DeepChem [](https://travis-ci.org/deepchem/deepchem) [](https://coveralls.io/github/deepchem/deepchem?branch=master) [](https://anaconda.org/deepchem/deepchem) [](https://badge.fury.io/py/deepchem) DeepChem aims to provide a high quality open-source toolchain that democratizes the use of deep-learning in drug discovery, materials science, quantum chemistry, and biology. Loading deepchem/data/datasets.py +10 −8 Original line number Diff line number Diff line Loading @@ -624,7 +624,8 @@ class DiskDataset(Dataset): if not len(self.metadata_df): raise ValueError("No data in dataset.") sample_X = load_from_disk( os.path.join(self.data_dir, next(self.metadata_df.iterrows())[1]['X'])) os.path.join(self.data_dir, next(self.metadata_df.iterrows())[1]['X'])) return np.shape(sample_X)[1:] def get_shard_size(self): Loading @@ -632,7 +633,8 @@ class DiskDataset(Dataset): if not len(self.metadata_df): raise ValueError("No data in dataset.") sample_y = load_from_disk( os.path.join(self.data_dir, next(self.metadata_df.iterrows())[1]['y'])) os.path.join(self.data_dir, next(self.metadata_df.iterrows())[1]['y'])) return len(sample_y) def _get_metadata_filename(self): Loading deepchem/models/tensorgraph/models/test_graph_models.py +20 −0 Original line number Diff line number Diff line Loading @@ -7,6 +7,7 @@ from deepchem.data import NumpyDataset from deepchem.models import GraphConvTensorGraph from deepchem.models import TensorGraph from deepchem.molnet.load_function.delaney_datasets import load_delaney from deepchem.models.tensorgraph.layers import ReduceSum, L2Loss class TestGraphModels(unittest.TestCase): Loading Loading @@ -79,3 +80,22 @@ class TestGraphModels(unittest.TestCase): dataset, transformers, untransform=True, n_passes=24) assert mu.shape == (len(dataset), len(tasks)) assert sigma.shape == (len(dataset), len(tasks)) def test_change_loss_function(self): tasks, dataset, transformers, metric = self.get_dataset( 'regression', 'GraphConv', num_tasks=1) batch_size = 50 model = GraphConvTensorGraph( len(tasks), batch_size=batch_size, mode='regression') model.fit(dataset, nb_epoch=1) model.save() model2 = TensorGraph.load_from_dir(model.model_dir, restore=False) dummy_label = model2.labels[-1] dummy_ouput = model2.outputs[-1] loss = ReduceSum(L2Loss(in_layers=[dummy_label, dummy_ouput])) module = model2.create_submodel(loss=loss) model2.restore() model2.fit(dataset, nb_epoch=1, submodel=module) Loading
.travis.yml +7 −1 Original line number Diff line number Diff line Loading @@ -19,9 +19,15 @@ install: - pip install coveralls - python setup.py install script: - nosetests --with-flaky -a '!slow' --with-timer --with-coverage --cover-package=deepchem -v deepchem --nologcapture - nosetests --with-flaky -a '!slow' --with-timer --with-coverage --cover-package=deepchem -v deepchem --nologcapture - find ./deepchem | grep .py$ |xargs python -m doctest -v - bash devtools/travis-ci/test_format_code.sh after_success: - echo $TRAVIS_SECURE_ENV_VARS - coveralls deploy: provider: pypi user: "lilleswing" password: secure: 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
MANIFEST.in 0 → 100644 +2 −0 Original line number Diff line number Diff line prune datasets prune examples
README.md +3 −0 Original line number Diff line number Diff line # DeepChem [](https://travis-ci.org/deepchem/deepchem) [](https://coveralls.io/github/deepchem/deepchem?branch=master) [](https://anaconda.org/deepchem/deepchem) [](https://badge.fury.io/py/deepchem) DeepChem aims to provide a high quality open-source toolchain that democratizes the use of deep-learning in drug discovery, materials science, quantum chemistry, and biology. Loading
deepchem/data/datasets.py +10 −8 Original line number Diff line number Diff line Loading @@ -624,7 +624,8 @@ class DiskDataset(Dataset): if not len(self.metadata_df): raise ValueError("No data in dataset.") sample_X = load_from_disk( os.path.join(self.data_dir, next(self.metadata_df.iterrows())[1]['X'])) os.path.join(self.data_dir, next(self.metadata_df.iterrows())[1]['X'])) return np.shape(sample_X)[1:] def get_shard_size(self): Loading @@ -632,7 +633,8 @@ class DiskDataset(Dataset): if not len(self.metadata_df): raise ValueError("No data in dataset.") sample_y = load_from_disk( os.path.join(self.data_dir, next(self.metadata_df.iterrows())[1]['y'])) os.path.join(self.data_dir, next(self.metadata_df.iterrows())[1]['y'])) return len(sample_y) def _get_metadata_filename(self): Loading
deepchem/models/tensorgraph/models/test_graph_models.py +20 −0 Original line number Diff line number Diff line Loading @@ -7,6 +7,7 @@ from deepchem.data import NumpyDataset from deepchem.models import GraphConvTensorGraph from deepchem.models import TensorGraph from deepchem.molnet.load_function.delaney_datasets import load_delaney from deepchem.models.tensorgraph.layers import ReduceSum, L2Loss class TestGraphModels(unittest.TestCase): Loading Loading @@ -79,3 +80,22 @@ class TestGraphModels(unittest.TestCase): dataset, transformers, untransform=True, n_passes=24) assert mu.shape == (len(dataset), len(tasks)) assert sigma.shape == (len(dataset), len(tasks)) def test_change_loss_function(self): tasks, dataset, transformers, metric = self.get_dataset( 'regression', 'GraphConv', num_tasks=1) batch_size = 50 model = GraphConvTensorGraph( len(tasks), batch_size=batch_size, mode='regression') model.fit(dataset, nb_epoch=1) model.save() model2 = TensorGraph.load_from_dir(model.model_dir, restore=False) dummy_label = model2.labels[-1] dummy_ouput = model2.outputs[-1] loss = ReduceSum(L2Loss(in_layers=[dummy_label, dummy_ouput])) module = model2.create_submodel(loss=loss) model2.restore() model2.fit(dataset, nb_epoch=1, submodel=module)
