Attempt at tensorflow (785ac0b6) · Commits · 钟慕尧 / deepchem

deepchem/hyperparameters/tests/test_hyperparam_opt.py

+15 −1

Original line number	Diff line number	Diff line
		@@ -30,6 +30,10 @@ from deepchem.models.keras_models.fcnet import MultiTaskDNN
		from deepchem.models.tensorflow_models import TensorflowModel
		from deepchem.models.tensorflow_models.fcnet import TensorflowMultiTaskClassifier
		from deepchem.splits import ScaffoldSplitter
		############################################################# DEBUG
		import tensorflow as tf
		from keras import backend as K
		############################################################# DEBUG

		def rf_model_builder(tasks, task_types, params_dict, model_dir, verbosity=None):
		"""Builds random forests given hyperparameters.
		@@ -173,6 +177,16 @@ class TestHyperparamOptAPI(TestAPI):
		"batchnorm": [False],
		"data_shape": [train_dataset.get_data_shape()]}

		def model_builder(tasks, task_types, model_params, task_model_dir,
		verbosity=None):
		############################################################# DEBUG
		g = tf.Graph()
		sess = tf.Session(graph=g)
		K.set_session(sess)
		with g.as_default():
		############################################################# DEBUG
		return MultiTaskDNN(tasks, task_types, model_params, task_model_dir,
		model_instance=LogisticRegression())
		optimizer = HyperparamOpt(MultiTaskDNN, tasks, task_types,
		verbosity="low")
		best_model, best_hyperparams, all_results = optimizer.hyperparam_search(

deepchem/models/tests/test_api.py

+11 −1

Original line number	Diff line number	Diff line
		@@ -33,6 +33,11 @@ from deepchem.models.tensorflow_models import TensorflowModel
		from deepchem.models.tensorflow_models.fcnet import TensorflowMultiTaskClassifier
		from deepchem.splits import ScaffoldSplitter
		from deepchem.splits import SpecifiedSplitter
		############################################################# DEBUG
		from deepchem.models.keras_models.fcnet import MultiTaskDNN
		import tensorflow as tf
		from keras import backend as K
		############################################################# DEBUG

		class TestModelAPI(TestAPI):
		"""
		@@ -294,7 +299,12 @@ class TestModelAPI(TestAPI):

		def test_multitask_keras_mlp_ECFP_classification_API(self):
		"""Straightforward test of Keras multitask deepchem classification API."""
		from deepchem.models.keras_models.fcnet import MultiTaskDNN
		############################################################# DEBUG
		g = tf.Graph()
		#sess = tf.Session(graph=g)
		sess = tf.Session()
		K.set_session(sess)
		############################################################# DEBUG
		task_type = "classification"
		# TODO(rbharath): There should be some automatic check to ensure that all
		# required model_params are specified.

deepchem/models/tests/test_overfit.py

+261 −227

Original line number	Diff line number	Diff line
		@@ -26,6 +26,10 @@ from deepchem.models.tensorflow_models import TensorflowModel
		from deepchem.models.tensorflow_models.fcnet import TensorflowMultiTaskRegressor
		from deepchem.models.tensorflow_models.fcnet import TensorflowMultiTaskClassifier
		from deepchem.models.multitask import SingletaskToMultitask
		############################################################# DEBUG
		import tensorflow as tf
		from keras import backend as K
		############################################################# DEBUG

		class TestOverfitAPI(TestAPI):
		"""
		@@ -152,6 +156,12 @@ class TestOverfitAPI(TestAPI):

		def test_keras_regression_overfit(self):
		"""Test that keras models can overfit simple regression datasets."""
		############################################################# DEBUG
		g = tf.Graph()
		sess = tf.Session(graph=g)
		K.set_session(sess)
		with g.as_default():
		############################################################# DEBUG
		tasks = ["task0"]
		task_types = {task: "regression" for task in tasks}
		n_samples = 10
		@@ -252,6 +262,12 @@ class TestOverfitAPI(TestAPI):

		def test_keras_classification_overfit(self):
		"""Test that keras models can overfit simple classification datasets."""
		############################################################# DEBUG
		g = tf.Graph()
		sess = tf.Session(graph=g)
		K.set_session(sess)
		with g.as_default():
		############################################################# DEBUG
		tasks = ["task0"]
		task_types = {task: "classification" for task in tasks}
		n_samples = 10
		@@ -301,6 +317,12 @@ class TestOverfitAPI(TestAPI):

		def test_keras_skewed_classification_overfit(self):
		"""Test keras models can overfit 0/1 datasets with few actives."""
		############################################################# DEBUG
		g = tf.Graph()
		sess = tf.Session(graph=g)
		K.set_session(sess)
		with g.as_default():
		############################################################# DEBUG
		tasks = ["task0"]
		task_types = {task: "classification" for task in tasks}
		n_samples = 100
		@@ -577,6 +599,12 @@ class TestOverfitAPI(TestAPI):

		def test_keras_multitask_classification_overfit(self):
		"""Test keras multitask overfits tiny data."""
		############################################################# DEBUG
		g = tf.Graph()
		sess = tf.Session(graph=g)
		K.set_session(sess)
		with g.as_default():
		############################################################# DEBUG
		n_tasks = 10
		tasks = ["task%d" % task for task in range(n_tasks)]
		task_types = {task: "classification" for task in tasks}
		@@ -723,6 +751,12 @@ class TestOverfitAPI(TestAPI):

		def test_keras_multitask_regression_overfit(self):
		"""Test keras multitask overfits tiny data."""
		############################################################# DEBUG
		g = tf.Graph()
		sess = tf.Session(graph=g)
		K.set_session(sess)
		with g.as_default():
		############################################################# DEBUG
		n_tasks = 10
		tasks = ["task%d" % task for task in range(n_tasks)]
		task_types = {task: "regression" for task in tasks}

deepchem/models/tests/test_reload.py

+61 −51

Original line number	Diff line number	Diff line
		@@ -20,6 +20,10 @@ from deepchem.models.sklearn_models import SklearnModel
		from deepchem.models.keras_models.fcnet import MultiTaskDNN
		from deepchem.models.tensorflow_models import TensorflowModel
		from deepchem.models.tensorflow_models.fcnet import TensorflowMultiTaskClassifier
		############################################################# DEBUG
		import tensorflow as tf
		from keras import backend as K
		############################################################# DEBUG

		class TestModelReload(TestAPI):

		@@ -69,6 +73,12 @@ class TestModelReload(TestAPI):

		def test_keras_reload(self):
		"""Test that trained keras models can be reloaded correctly."""
		############################################################# DEBUG
		g = tf.Graph()
		sess = tf.Session(graph=g)
		K.set_session(sess)
		with g.as_default():
		############################################################# DEBUG
		tasks = ["task0"]
		task_types = {task: "classification" for task in tasks}
		n_samples = 10

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