未验证 提交 56882ce4 编写于 作者: L lijianshe02 提交者: GitHub

change input data type and decrease max_relative_error value in...

change input data type and decrease max_relative_error value in test_check_grad for grop_nom_op test test=develop (#21608)
上级 84b72671
......@@ -44,7 +44,7 @@ class TestGroupNormOp(OpTest):
def setUp(self):
self.op_type = "group_norm"
self.data_format = "NCHW"
self.dtype = np.float32
self.dtype = np.float64
self.shape = (2, 4, 3, 3)
self.attrs = {'epsilon': 1e-5, 'groups': 2, 'data_layout': "NCHW"}
self.compare_between_place = False
......@@ -113,7 +113,7 @@ class TestGroupNormOp(OpTest):
place,
set(['X', 'Scale', 'Bias']),
'Y',
max_relative_error=0.01)
max_relative_error=0.005)
def init_test_case(self):
pass
......@@ -193,19 +193,19 @@ class TestGroupNormOpLargeData_With_NHWC(TestGroupNormOp):
self.compare_between_place = True
class TestGroupNormAPI_With_NHWC(OpTest):
class TestGroupNormAPI_With_NHWC(unittest.TestCase):
def test_case1(self):
data1 = fluid.data(name='data1', shape=[None, 3, 3, 4], dtype='float32')
data1 = fluid.data(name='data1', shape=[None, 3, 3, 4], dtype='float64')
out1 = fluid.layers.group_norm(
input=data1, groups=2, data_layout="NHWC")
data2 = fluid.data(name='data2', shape=[None, 4, 3, 3], dtype='float32')
data2 = fluid.data(name='data2', shape=[None, 4, 3, 3], dtype='float64')
out2 = fluid.layers.group_norm(
input=data2, groups=2, data_layout="NCHW")
data1_np = np.random.random((2, 3, 3, 4)).astype("float32")
data2_np = np.random.random((2, 4, 3, 3)).astype("float32")
scale = np.array([1]).astype("float32")
bias = np.array([0]).astype("float32")
data1_np = np.random.random((2, 3, 3, 4)).astype("float64")
data2_np = np.random.random((2, 4, 3, 3)).astype("float64")
scale = np.array([1]).astype("float64")
bias = np.array([0]).astype("float64")
place = core.CPUPlace()
exe = fluid.Executor(place)
......@@ -225,7 +225,7 @@ class TestGroupNormAPI_With_NHWC(OpTest):
class TestGroupNormException(unittest.TestCase):
# data_layout is not NHWC or NCHW
def test_exception(self):
data = fluid.data(name='data', shape=[None, 3, 3, 4], dtype="float32")
data = fluid.data(name='data', shape=[None, 3, 3, 4], dtype="float64")
def attr_data_format():
out = fluid.layers.group_norm(
......
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