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"""Functional test for learning rate decay."""
import tensorflow.python.platform
from tensorflow.python.framework import test_util
from tensorflow.python.framework import types
from tensorflow.python.ops import state_ops
from tensorflow.python.ops import variables
from tensorflow.python.platform import googletest
from tensorflow.python.training import learning_rate_decay
class LRDecayTest(test_util.TensorFlowTestCase):
def testContinuous(self):
with self.test_session():
step = 5
decayed_lr = learning_rate_decay.exponential_decay(0.05, step, 10, 0.96)
expected = .05 * 0.96 ** (5.0 / 10.0)
self.assertAllClose(decayed_lr.eval(), expected, 1e-6)
def testStaircase(self):
with self.test_session():
step = state_ops.variable_op([], types.int32)
assign_100 = state_ops.assign(step, 100)
assign_1 = state_ops.assign(step, 1)
assign_2 = state_ops.assign(step, 2)
decayed_lr = learning_rate_decay.exponential_decay(.1, step, 3, 0.96,
staircase=True)
# No change to learning rate
assign_1.op.run()
self.assertAllClose(decayed_lr.eval(), .1, 1e-6)
assign_2.op.run()
self.assertAllClose(decayed_lr.eval(), .1, 1e-6)
# Decayed learning rate
assign_100.op.run()
expected = .1 * 0.96 ** (100 / 3)
self.assertAllClose(decayed_lr.eval(), expected, 1e-6)
def testVariables(self):
with self.test_session():
step = variables.Variable(1)
assign_1 = step.assign(1)
assign_2 = step.assign(2)
assign_100 = step.assign(100)
decayed_lr = learning_rate_decay.exponential_decay(.1, step, 3, 0.96,
staircase=True)
variables.initialize_all_variables().run()
# No change to learning rate
assign_1.op.run()
self.assertAllClose(decayed_lr.eval(), .1, 1e-6)
assign_2.op.run()
self.assertAllClose(decayed_lr.eval(), .1, 1e-6)
# Decayed learning rate
assign_100.op.run()
expected = .1 * 0.96 ** (100 / 3)
self.assertAllClose(decayed_lr.eval(), expected, 1e-6)
if __name__ == "__main__":
googletest.main()
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