Loading deepchem/models/tensorgraph/optimizers.py +35 −0 Original line number Diff line number Diff line Loading @@ -191,3 +191,38 @@ class PolynomialDecay(LearningRateSchedule): global_step=global_step, decay_steps=self.decay_steps, power=self.power) class LinearCosineDecay(LearningRateSchedule): """Applies linear cosine decay to the learning rate""" def __init__(self, initial_rate, decay_steps, alpha=0.0, beta=0.001, num_periods=0.5): """ Parameters ---------- learning_rate : float initial learning rate decay_steps : int number of steps to decay over num_periods : number of periods in the cosine part of the decay """ self.initial_rate = initial_rate self.decay_steps = decay_steps self.alpha = alpha self.beta = beta self.num_periods = num_periods def _create_tensor(self, global_step): return tf.train.linear_cosine_decay( learning_rate=self.initial_rate, global_step=global_step, decay_steps=self.decay_steps, alpha=self.alpha, beta=self.beta, num_periods=self.num_periods) deepchem/models/tensorgraph/tests/test_optimizers.py +8 −0 Original line number Diff line number Diff line Loading @@ -47,3 +47,11 @@ class TestLayers(test_util.TensorFlowTestCase): with self.test_session() as sess: global_step = tf.Variable(0) tfopt = opt._create_optimizer(global_step) def test_linearCosine_decay(self): """test creating an optimizer with a linear cosine decay to the learning rate""" rate = optimizers.LinearCosineDecay(initial_rate=0.1, decay_steps=10000) opt = optimizers.Adam(learning_rate=rate) with self.test_session() as sess: global_step = tf.Variable(0) tfopt = opt._create_optimizer(global_step) Loading
deepchem/models/tensorgraph/optimizers.py +35 −0 Original line number Diff line number Diff line Loading @@ -191,3 +191,38 @@ class PolynomialDecay(LearningRateSchedule): global_step=global_step, decay_steps=self.decay_steps, power=self.power) class LinearCosineDecay(LearningRateSchedule): """Applies linear cosine decay to the learning rate""" def __init__(self, initial_rate, decay_steps, alpha=0.0, beta=0.001, num_periods=0.5): """ Parameters ---------- learning_rate : float initial learning rate decay_steps : int number of steps to decay over num_periods : number of periods in the cosine part of the decay """ self.initial_rate = initial_rate self.decay_steps = decay_steps self.alpha = alpha self.beta = beta self.num_periods = num_periods def _create_tensor(self, global_step): return tf.train.linear_cosine_decay( learning_rate=self.initial_rate, global_step=global_step, decay_steps=self.decay_steps, alpha=self.alpha, beta=self.beta, num_periods=self.num_periods)
deepchem/models/tensorgraph/tests/test_optimizers.py +8 −0 Original line number Diff line number Diff line Loading @@ -47,3 +47,11 @@ class TestLayers(test_util.TensorFlowTestCase): with self.test_session() as sess: global_step = tf.Variable(0) tfopt = opt._create_optimizer(global_step) def test_linearCosine_decay(self): """test creating an optimizer with a linear cosine decay to the learning rate""" rate = optimizers.LinearCosineDecay(initial_rate=0.1, decay_steps=10000) opt = optimizers.Adam(learning_rate=rate) with self.test_session() as sess: global_step = tf.Variable(0) tfopt = opt._create_optimizer(global_step)
