Merge pull request #966 from peastman/multitask (f51c17e6) · Commits · 钟慕尧 / deepchem

deepchem/models/init.py

+3 −3

Original line number	Diff line number	Diff line
		@@ -18,9 +18,9 @@ from deepchem.models.sequential import Sequential
		from deepchem.models.tensorflow_models.fcnet import TensorflowMultiTaskRegressor
		from deepchem.models.tensorflow_models.fcnet import TensorflowMultiTaskClassifier
		from deepchem.models.tensorflow_models.fcnet import TensorflowMultiTaskFitTransformRegressor
		from deepchem.models.tensorflow_models.fcnet import TensorGraphMultiTaskRegressor
		from deepchem.models.tensorflow_models.fcnet import TensorGraphMultiTaskClassifier
		from deepchem.models.tensorflow_models.fcnet import TensorGraphMultiTaskFitTransformRegressor
		from deepchem.models.tensorflow_models.fcnet import MultiTaskRegressor
		from deepchem.models.tensorflow_models.fcnet import MultiTaskClassifier
		from deepchem.models.tensorflow_models.fcnet import MultiTaskFitTransformRegressor
		from deepchem.models.tensorflow_models.robust_multitask import RobustMultitaskRegressor
		from deepchem.models.tensorflow_models.robust_multitask import RobustMultitaskClassifier
		from deepchem.models.tensorflow_models.lr import TensorflowLogisticRegression

deepchem/models/tensorflow_models/fcnet.py

+17 −18

Original line number	Diff line number	Diff line
		@@ -25,7 +25,7 @@ from deepchem.models.tensorgraph.tensor_graph import TensorGraph, TFWrapper
		from deepchem.models.tensorgraph.layers import Feature, Label, Weights, WeightedError, Dense, Dropout, WeightDecay, Reshape, SoftMaxCrossEntropy, L2Loss, ReduceSum


		class TensorGraphMultiTaskClassifier(TensorGraph):
		class MultiTaskClassifier(TensorGraph):

		def __init__(self,
		n_tasks,
		@@ -39,7 +39,7 @@ class TensorGraphMultiTaskClassifier(TensorGraph):
		activation_fns=tf.nn.relu,
		n_classes=2,
		**kwargs):
		"""Create a TensorGraphMultiTaskClassifier.
		"""Create a MultiTaskClassifier.

		In addition to the following arguments, this class also accepts all the keywork arguments
		from TensorGraph.
		@@ -73,7 +73,7 @@ class TensorGraphMultiTaskClassifier(TensorGraph):
		n_classes: int
		the number of classes
		"""
		super(TensorGraphMultiTaskClassifier, self).__init__(**kwargs)
		super(MultiTaskClassifier, self).__init__(**kwargs)
		self.n_tasks = n_tasks
		self.n_features = n_features
		self.n_classes = n_classes
		@@ -152,8 +152,8 @@ class TensorGraphMultiTaskClassifier(TensorGraph):
		yield feed_dict

		def predict_proba(self, dataset, transformers=[], outputs=None):
		return super(TensorGraphMultiTaskClassifier, self).predict(
		dataset, transformers, outputs)
		return super(MultiTaskClassifier, self).predict(dataset, transformers,
		outputs)

		def predict(self, dataset, transformers=[], outputs=None):
		"""
		@@ -176,13 +176,13 @@ class TensorGraphMultiTaskClassifier(TensorGraph):
		y_pred: numpy ndarray or list of numpy ndarrays
		"""
		# Results is of shape (n_samples, n_tasks, n_classes)
		retval = super(TensorGraphMultiTaskClassifier, self).predict(
		dataset, transformers, outputs)
		retval = super(MultiTaskClassifier, self).predict(dataset, transformers,
		outputs)
		# retval is of shape (n_samples, n_tasks)
		return np.argmax(retval, axis=2)


		class TensorGraphMultiTaskRegressor(TensorGraph):
		class MultiTaskRegressor(TensorGraph):

		def __init__(self,
		n_tasks,
		@@ -195,7 +195,7 @@ class TensorGraphMultiTaskRegressor(TensorGraph):
		dropouts=0.5,
		activation_fns=tf.nn.relu,
		**kwargs):
		"""Create a TensorGraphMultiTaskRegressor.
		"""Create a MultiTaskRegressor.

		In addition to the following arguments, this class also accepts all the keywork arguments
		from TensorGraph.
		@@ -228,7 +228,7 @@ class TensorGraphMultiTaskRegressor(TensorGraph):
		len(layer_sizes). Alternatively this may be a single value instead of a list, in which case the
		same value is used for every layer.
		"""
		super(TensorGraphMultiTaskRegressor, self).__init__(**kwargs)
		super(MultiTaskRegressor, self).__init__(**kwargs)
		self.n_tasks = n_tasks
		self.n_features = n_features
		n_layers = len(layer_sizes)
		@@ -309,8 +309,8 @@ class TensorGraphMultiTaskRegressor(TensorGraph):
		yield feed_dict


		class TensorGraphMultiTaskFitTransformRegressor(TensorGraphMultiTaskRegressor):
		"""Implements a TensorGraphMultiTaskRegressor that performs on-the-fly transformation during fit/predict.
		class MultiTaskFitTransformRegressor(MultiTaskRegressor):
		"""Implements a MultiTaskRegressor that performs on-the-fly transformation during fit/predict.

		Example:

		@@ -336,10 +336,10 @@ class TensorGraphMultiTaskFitTransformRegressor(TensorGraphMultiTaskRegressor):
		n_evals=1,
		batch_size=50,
		**kwargs):
		"""Create a TensorGraphMultiTaskFitTransformRegressor.
		"""Create a MultiTaskFitTransformRegressor.

		In addition to the following arguments, this class also accepts all the keywork arguments
		from TensorGraphMultiTaskRegressor.
		from MultiTaskRegressor.

		Parameters
		----------
		@@ -367,7 +367,7 @@ class TensorGraphMultiTaskFitTransformRegressor(TensorGraphMultiTaskRegressor):
		X_b = transformer.X_transform(X_b)
		n_features = X_b.shape[1]
		print("n_features after fit_transform: %d" % int(n_features))
		super(TensorGraphMultiTaskFitTransformRegressor, self).__init__(
		super(MultiTaskFitTransformRegressor, self).__init__(
		n_tasks, n_features, batch_size=batch_size, **kwargs)

		def default_generator(self,
		@@ -405,9 +405,8 @@ class TensorGraphMultiTaskFitTransformRegressor(TensorGraphMultiTaskRegressor):
		feed_dict[self.features[0]] = X_t
		yield feed_dict

		return super(TensorGraphMultiTaskFitTransformRegressor,
		self).predict_on_generator(transform_generator(), transformers,
		outputs)
		return super(MultiTaskFitTransformRegressor, self).predict_on_generator(
		transform_generator(), transformers, outputs)


		class TensorflowMultiTaskClassifier(TensorflowClassifier):

deepchem/models/tensorgraph/layers.py

+1 −0

Original line number	Diff line number	Diff line
		@@ -211,6 +211,7 @@ class Layer(object):
		Instead, the input to the first dense layer will be a different layer
		specified in the replacements map.

		>>> new_input = Feature(shape=(None, 100))
		>>> replacements = {input: new_input}
		>>> dense3_copy = dense3.copy(replacements)

deepchem/models/tensorgraph/models/robust_multitask.py

+1 −1

Original line number	Diff line number	Diff line
		@@ -11,7 +11,7 @@
		# return self.out_tensor
		#
		#
		#def tensorGraphMultitaskClassifier(n_tasks,
		#def MultiTaskClassifier(n_tasks,
		# n_features,
		# layer_sizes=[500],
		# bypass_layer_sizes=[100],

deepchem/models/tests/test_api.py

+1 −1

Original line number	Diff line number	Diff line
		@@ -215,7 +215,7 @@ class TestAPI(unittest.TestCase):
		dc.metrics.Metric(dc.metrics.accuracy_score)
		]

		model = dc.models.TensorGraphMultiTaskClassifier(len(tasks), n_features)
		model = dc.models.MultiTaskClassifier(len(tasks), n_features)

		# Test Parameter getting and setting
		param, value = 'weight_decay_penalty_type', 'l2'

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