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Paddle/python/paddle/v2/framework/tests/test_optimizer.py

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4.5 KiB

import unittest
import paddle.v2.framework.framework as framework
import paddle.v2.framework.optimizer as optimizer
class TestOptimizer(unittest.TestCase):
def test_sgd_optimizer(self):
program = framework.Program()
block = program.global_block()
mul_x = block.create_parameter(
dtype="float32", shape=[5, 10], lod_level=0, name="mul.x")
mul_y = block.create_var(
dtype="float32", shape=[10, 8], lod_level=0, name="mul.y")
mul_out = block.create_var(
dtype="float32", shape=[5, 8], lod_level=0, name="mul.out")
block.append_op(
type="mul",
inputs={"X": mul_x,
"Y": mul_y},
outputs={"Out": mul_out},
attrs={"x_num_col_dims": 1})
sgd_optimizer = optimizer.SGDOptimizer(learning_rate=0.01)
opts = sgd_optimizer.minimize(mul_out)
self.assertEqual(len(opts), 1)
sgd_op = opts[0]
self.assertEqual(sgd_op.type, "sgd")
class TestMomentumOptimizer(unittest.TestCase):
class MockMomentum(optimizer.MomentumOptimizer):
def get_accumulators(self):
return self._accumulators
def get_velocity_str(self):
return self._velocity_acc_str
def test_momentum_optimizer(self):
program = framework.Program()
block = program.global_block()
mul_x = block.create_parameter(
dtype="float32", shape=[5, 10], lod_level=0, name="mul.x")
mul_y = block.create_var(
dtype="float32", shape=[10, 8], lod_level=0, name="mul.y")
mul_out = block.create_var(
dtype="float32", shape=[5, 8], lod_level=0, name="mul.out")
block.append_op(
type="mul",
inputs={"X": mul_x,
"Y": mul_y},
outputs={"Out": mul_out},
attrs={"x_num_col_dims": 1})
momentum_optimizer = self.MockMomentum(learning_rate=0.01, momentum=0.2)
params_grads = momentum_optimizer.create_backward_pass(mul_out)
self.assertEqual(len(params_grads), 1)
self.assertEqual(len(momentum_optimizer.get_accumulators()), 0)
opts = momentum_optimizer.create_optimization_pass(params_grads,
mul_out)
self.assertEqual(len(opts), 1)
sgd_op = opts[0]
self.assertEqual(sgd_op.type, "momentum")
# Check accumulators
accumulators = momentum_optimizer.get_accumulators()
self.assertEqual(len(accumulators), 1)
self.assertTrue(momentum_optimizer.get_velocity_str() in accumulators)
velocity_acc = accumulators[momentum_optimizer.get_velocity_str()]
self.assertEqual(len(velocity_acc), 1)
self.assertTrue(mul_x.name in velocity_acc)
class TestAdagradOptimizer(unittest.TestCase):
class MockAdagrad(optimizer.AdagradOptimizer):
def get_accumulators(self):
return self._accumulators
def get_moment_str(self):
return self._moment_acc_str
def test_adagrad_optimizer(self):
program = framework.Program()
block = program.global_block()
mul_x = block.create_parameter(
dtype="float32", shape=[5, 10], lod_level=0, name="mul.x")
mul_y = block.create_var(
dtype="float32", shape=[10, 8], lod_level=0, name="mul.y")
mul_out = block.create_var(
dtype="float32", shape=[5, 8], lod_level=0, name="mul.out")
block.append_op(
type="mul",
inputs={"X": mul_x,
"Y": mul_y},
outputs={"Out": mul_out},
attrs={"x_num_col_dims": 1})
adagrad_optimizer = self.MockAdagrad(learning_rate=0.01, epsilon=1.0e-6)
params_grads = adagrad_optimizer.create_backward_pass(mul_out)
self.assertEqual(len(params_grads), 1)
self.assertEqual(len(adagrad_optimizer.get_accumulators()), 0)
opts = adagrad_optimizer.create_optimization_pass(params_grads, mul_out)
self.assertEqual(len(opts), 1)
adagrad_op = opts[0]
self.assertEqual(adagrad_op.type, "adagrad")
# check accumulators
accumulators = adagrad_optimizer.get_accumulators()
self.assertEqual(len(accumulators), 1)
self.assertTrue(adagrad_optimizer.get_moment_str() in accumulators)
moment_acc = accumulators[adagrad_optimizer.get_moment_str()]
self.assertEqual(len(moment_acc), 1)
self.assertTrue(mul_x.name in moment_acc)
if __name__ == '__main__':
unittest.main()