Added RMSProp Optimizer and tests (5bd1a058) · Commits · 钟慕尧 / deepchem

deepchem/models/tensorgraph/optimizers.py

+41 −3

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		@@ -80,6 +80,44 @@ class Adam(Optimizer):
		epsilon=self.epsilon)


		class RMSProp(Optimizer):
		"""RMSProp Optimization algorithm."""

		def __init__(self,
		learning_rate=0.001,
		momentum=0.0,
		decay=0.9,
		epsilon=1e-10):
		"""Construct an RMSProp Optimizer.

		Parameters
		----------
		learning_rate: float or LearningRateSchedule
		the learning_rate used for optimization
		momentum: float, default 0.0
		a parameter of the RMSProp algorithm
		decay: float, default 0.9
		a parameter of the RMSProp algorithm
		epsilon: float, default 1e-10
		a parameter of the RMSProp algorithm
		"""
		self.learning_rate = learning_rate
		self.momentum = momentum
		self.decay = decay
		self.epsilon = epsilon

		def _create_optimizer(self, global_step):
		if isinstance(self.learning_rate, LearningRateSchedule):
		learning_rate = self.learning_rate._create_tensor(global_step)
		else:
		learning_rate = self.learning_rate
		return tf.train.RMSPropOptimizer(
		learning_rate=learning_rate,
		momentum=self.momentum,
		decay=self.decay,
		epsilon=self.epsilon)


		class GradientDescent(Optimizer):
		"""The gradient descent optimization algorithm."""

+8 −0

Original line number	Diff line number	Diff line
		@@ -14,6 +14,14 @@ class TestLayers(test_util.TensorFlowTestCase):
		tfopt = opt._create_optimizer(global_step)
		assert isinstance(tfopt, tf.train.AdamOptimizer)

		def test_rmsprop(self):
		"""Test creating an RMSProp Optimizer."""
		opt = optimizers.RMSProp(learning_rate=0.01)
		with self.session() as sess:
		global_step = tf.Variable(0)
		tfopt = opt._create_optimizer(global_step)
		assert isinstance(tfopt, tf.train.RMSPropOptimizer)

		def test_gradient_descent(self):
		"""Test creating a Gradient Descent optimizer."""
		opt = optimizers.GradientDescent(learning_rate=0.01)