提交 3ee87653 编写于 作者: Y yangyaming

Tight the relative error.

上级 09a13f6c
......@@ -14,7 +14,7 @@ def smooth_l1_loss_forward(val, sigma2):
class TestSmoothL1LossOp1(OpTest):
def setUp(self):
self.op_type = "smooth_l1_loss"
dims = (10, 15)
dims = (6, 10)
self.inputs = {
'X': np.random.random(dims).astype("float32"),
'Y': np.random.random(dims).astype("float32")
......@@ -31,21 +31,21 @@ class TestSmoothL1LossOp1(OpTest):
self.check_output()
def test_check_grad_normal(self):
self.check_grad(['X', 'Y'], 'Out', max_relative_error=0.08)
self.check_grad(['X', 'Y'], 'Out', max_relative_error=0.02)
def test_check_grad_ingore_x(self):
self.check_grad(
['Y'], 'Out', max_relative_error=0.08, no_grad_set=set("X"))
['Y'], 'Out', max_relative_error=0.02, no_grad_set=set("X"))
def test_check_grad_ingore_y(self):
self.check_grad(
['X'], 'Out', max_relative_error=0.08, no_grad_set=set('Y'))
['X'], 'Out', max_relative_error=0.02, no_grad_set=set('Y'))
class TestSmoothL1LossOp2(OpTest):
def setUp(self):
self.op_type = "smooth_l1_loss"
dims = (10, 15)
dims = (6, 10)
self.inputs = {
'X': np.random.random(dims).astype("float32"),
'Y': np.random.random(dims).astype("float32"),
......@@ -66,20 +66,20 @@ class TestSmoothL1LossOp2(OpTest):
self.check_output()
def test_check_grad_normal(self):
self.check_grad(['X', 'Y'], 'Out', max_relative_error=0.08)
self.check_grad(['X', 'Y'], 'Out', max_relative_error=0.02)
def test_check_grad_ingore_x(self):
self.check_grad(
['Y'],
'Out',
max_relative_error=0.08,
max_relative_error=0.02,
no_grad_set=set(['X', 'InsideWeight', 'OutsideWeight']))
def test_check_grad_ingore_y(self):
self.check_grad(
['X'],
'Out',
max_relative_error=0.08,
max_relative_error=0.02,
no_grad_set=set(['Y', 'InsideWeight', 'OutsideWeight']))
......
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