Leftover changes (1f34ec68) · Commits · 钟慕尧 / deepchem

deepchem/hyperparameters/tests/test_hyperparam_opt.py

+1 −1

Original line number	Diff line number	Diff line
		@@ -60,7 +60,7 @@ class TestHyperparamOptAPI(TestAPI):
		smiles_field=self.smiles_field,
		featurizer=featurizer,
		verbosity="low")
		dataset = featurizer.featurize(input_file, self.data_dir)
		dataset = loader.featurize(input_file, self.data_dir)

		splitter = ScaffoldSplitter()
		train_dataset, valid_dataset, test_dataset = splitter.train_valid_test_split(

deepchem/models/tests/test_api.py

+8 −8

Original line number	Diff line number	Diff line
		@@ -51,7 +51,7 @@ class TestModelAPI(TestAPI):
		smiles_field=self.smiles_field,
		featurizer=featurizer,
		verbosity="low")
		dataset = featurizer.featurize(input_file, self.data_dir)
		dataset = loader.featurize(input_file, self.data_dir)

		splitter = ScaffoldSplitter()
		train_dataset, test_dataset = splitter.train_test_split(
		@@ -95,7 +95,7 @@ class TestModelAPI(TestAPI):
		smiles_field=self.smiles_field,
		featurizer=featurizer,
		verbosity="low")
		dataset = featurizer.featurize(input_file, self.data_dir, debug=True)
		dataset = loader.featurize(input_file, self.data_dir, debug=True)

		splitter = SpecifiedSplitter(input_file, "split")
		train_dataset, test_dataset = splitter.train_test_split(
		@@ -193,7 +193,7 @@ class TestModelAPI(TestAPI):
		smiles_field=self.smiles_field,
		featurizer=featurizer,
		verbosity="low")
		dataset = featurizer.featurize(input_file, self.data_dir)
		dataset = loader.featurize(input_file, self.data_dir)

		splitter = ScaffoldSplitter()
		train_dataset, test_dataset = splitter.train_test_split(
		@@ -249,11 +249,11 @@ class TestModelAPI(TestAPI):
		# "nb_layers": 1, "batchnorm": False}

		# input_file = os.path.join(self.current_dir, "gbd3k.pkl.gz")
		# featurizer = DataLoader(tasks=tasks,
		# loader = DataLoader(tasks=tasks,
		# smiles_field=self.smiles_field,
		# featurizer=featurizer,
		# verbosity="low")
		# dataset = featurizer.featurize(input_file, self.data_dir)
		# dataset = loader.featurize(input_file, self.data_dir)

		# splitter = ScaffoldSplitter()
		# train_dataset, test_dataset = splitter.train_test_split(

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