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提交 63ab12c8 编写于 作者: Q qiaolongfei
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update test_optimizer

上级 4fdd114d
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Showing with 63 addition and 27 deletion
python/paddle/fluid/tests/unittests/test_optimizer.py
浏览文件 @ 63ab12c8
...@@ -21,31 +21,43 @@ from paddle.fluid.backward import append_backward ...@@ -21,31 +21,43 @@ from paddle.fluid.backward import append_backward
class TestOptimizer(unittest.TestCase): class TestOptimizer(unittest.TestCase):
def test_sgd_optimizer(self): def test_sgd_optimizer(self):
init_program = framework.Program() def check_sgd_optimizer(optimizer_attr):
program = framework.Program() init_program = framework.Program()
block = program.global_block() program = framework.Program()
mul_x = block.create_parameter( block = program.global_block()
dtype="float32", shape=[5, 10], lod_level=0, name="mul.x") mul_x = block.create_parameter(
mul_y = block.create_var( dtype="float32",
dtype="float32", shape=[10, 8], lod_level=0, name="mul.y") shape=[5, 10],
mul_out = block.create_var( lod_level=0,
dtype="float32", shape=[5, 8], lod_level=0, name="mul.out") name="mul.x",
mean_out = block.create_var( optimize_attr=optimizer_attr)
dtype="float32", shape=[1], lod_level=0, name="mean.out") mul_y = block.create_var(
block.append_op( dtype="float32", shape=[10, 8], lod_level=0, name="mul.y")
type="mul", mul_out = block.create_var(
inputs={"X": mul_x, dtype="float32", shape=[5, 8], lod_level=0, name="mul.out")
"Y": mul_y}, mean_out = block.create_var(
outputs={"Out": mul_out}, dtype="float32", shape=[1], lod_level=0, name="mean.out")
attrs={"x_num_col_dims": 1}) block.append_op(
block.append_op( type="mul",
type="mean", inputs={"X": mul_out}, outputs={"Out": mean_out}) inputs={"X": mul_x,
sgd_optimizer = optimizer.SGDOptimizer(learning_rate=0.01) "Y": mul_y},
opts, _ = sgd_optimizer.minimize(mean_out, init_program) outputs={"Out": mul_out},
attrs={"x_num_col_dims": 1})
block.append_op(
type="mean", inputs={"X": mul_out}, outputs={"Out": mean_out})
sgd_optimizer = optimizer.SGDOptimizer(learning_rate=0.01)
opts, _ = sgd_optimizer.minimize(mean_out, init_program)
return opts
opts = check_sgd_optimizer({'learning_rate': 1.1})
self.assertEqual(len(opts), 3) self.assertEqual(len(opts), 3)
self.assertEqual([op.type for op in opts], self.assertEqual([op.type for op in opts],
["fill_constant", "elementwise_mul", "sgd"]) ["fill_constant", "elementwise_mul", "sgd"])
opts = check_sgd_optimizer({'learning_rate': 1.0})
self.assertEqual(len(opts), 1)
self.assertEqual([op.type for op in opts], ["sgd"])
class TestMomentumOptimizer(unittest.TestCase): class TestMomentumOptimizer(unittest.TestCase):
class MockMomentum(optimizer.MomentumOptimizer): class MockMomentum(optimizer.MomentumOptimizer):
...@@ -60,7 +72,11 @@ class TestMomentumOptimizer(unittest.TestCase): ...@@ -60,7 +72,11 @@ class TestMomentumOptimizer(unittest.TestCase):
program = framework.Program() program = framework.Program()
block = program.global_block() block = program.global_block()
mul_x = block.create_parameter( mul_x = block.create_parameter(
dtype="float32", shape=[5, 10], lod_level=0, name="mul.x") dtype="float32",
shape=[5, 10],
lod_level=0,
name="mul.x",
optimize_attr={'learning_rate': 1.1})
mul_y = block.create_var( mul_y = block.create_var(
dtype="float32", shape=[10, 8], lod_level=0, name="mul.y") dtype="float32", shape=[10, 8], lod_level=0, name="mul.y")
mul_out = block.create_var( mul_out = block.create_var(
...@@ -110,7 +126,11 @@ class TestMomentumOptimizer(unittest.TestCase): ...@@ -110,7 +126,11 @@ class TestMomentumOptimizer(unittest.TestCase):
program = framework.Program() program = framework.Program()
block = program.global_block() block = program.global_block()
mul_x = block.create_parameter( mul_x = block.create_parameter(
dtype="float32", shape=[5, 10], lod_level=0, name="mul.x") dtype="float32",
shape=[5, 10],
lod_level=0,
name="mul.x",
optimize_attr={'learning_rate': 1.1})
mul_y = block.create_var( mul_y = block.create_var(
dtype="float32", shape=[10, 8], lod_level=0, name="mul.y") dtype="float32", shape=[10, 8], lod_level=0, name="mul.y")
mul_out = block.create_var( mul_out = block.create_var(
...@@ -169,7 +189,11 @@ class TestAdagradOptimizer(unittest.TestCase): ...@@ -169,7 +189,11 @@ class TestAdagradOptimizer(unittest.TestCase):
program = framework.Program() program = framework.Program()
block = program.global_block() block = program.global_block()
mul_x = block.create_parameter( mul_x = block.create_parameter(
dtype="float32", shape=[5, 10], lod_level=0, name="mul.x") dtype="float32",
shape=[5, 10],
lod_level=0,
name="mul.x",
optimize_attr={'learning_rate': 1.1})
mul_y = block.create_var( mul_y = block.create_var(
dtype="float32", shape=[10, 8], lod_level=0, name="mul.y") dtype="float32", shape=[10, 8], lod_level=0, name="mul.y")
mul_out = block.create_var( mul_out = block.create_var(
...@@ -229,7 +253,11 @@ class TestAdamOptimizer(unittest.TestCase): ...@@ -229,7 +253,11 @@ class TestAdamOptimizer(unittest.TestCase):
program = framework.Program() program = framework.Program()
block = program.global_block() block = program.global_block()
mul_x = block.create_parameter( mul_x = block.create_parameter(
dtype="float32", shape=[5, 10], lod_level=0, name="mul.x") dtype="float32",
shape=[5, 10],
lod_level=0,
name="mul.x",
optimize_attr={'learning_rate': 1.1})
mul_y = block.create_var( mul_y = block.create_var(
dtype="float32", shape=[10, 8], lod_level=0, name="mul.y") dtype="float32", shape=[10, 8], lod_level=0, name="mul.y")
mul_out = block.create_var( mul_out = block.create_var(
...@@ -292,7 +320,11 @@ class TestAdamaxOptimizer(unittest.TestCase): ...@@ -292,7 +320,11 @@ class TestAdamaxOptimizer(unittest.TestCase):
program = framework.Program() program = framework.Program()
block = program.global_block() block = program.global_block()
mul_x = block.create_parameter( mul_x = block.create_parameter(
dtype="float32", shape=[5, 10], lod_level=0, name="mul.x") dtype="float32",
shape=[5, 10],
lod_level=0,
name="mul.x",
optimize_attr={'learning_rate': 1.1})
mul_y = block.create_var( mul_y = block.create_var(
dtype="float32", shape=[10, 8], lod_level=0, name="mul.y") dtype="float32", shape=[10, 8], lod_level=0, name="mul.y")
mul_out = block.create_var( mul_out = block.create_var(
...@@ -352,7 +384,11 @@ class TestDecayedAdagradOptimizer(unittest.TestCase): ...@@ -352,7 +384,11 @@ class TestDecayedAdagradOptimizer(unittest.TestCase):
program = framework.Program() program = framework.Program()
block = program.global_block() block = program.global_block()
mul_x = block.create_parameter( mul_x = block.create_parameter(
dtype="float32", shape=[5, 10], lod_level=0, name="mul.x") dtype="float32",
shape=[5, 10],
lod_level=0,
name="mul.x",
optimize_attr={'learning_rate': 1.1})
mul_y = block.create_var( mul_y = block.create_var(
dtype="float32", shape=[10, 8], lod_level=0, name="mul.y") dtype="float32", shape=[10, 8], lod_level=0, name="mul.y")
mul_out = block.create_var( mul_out = block.create_var(
......
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