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enable check_dygraph for mkldnn activation tests (#25779)

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* enable check_dygraph for mkldnn activation tests

* TestMKLDNNSwishDim4 float32->self.dtype
revert-24895-update_cub
Sylwester Fraczek 5 years ago committed by GitHub
parent 5258d53d65
commit 4c9ddb3db4
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GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 21 additions and 121 deletions
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142
python/paddle/fluid/tests/unittests/mkldnn/test_activation_mkldnn_op.py
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@ -30,16 +30,8 @@ class TestMKLDNNReluDim2(TestRelu):
self.attrs = {"use_mkldnn": True}
def test_check_output(self):
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_output(check_dygraph=False)
def test_check_grad(self):
if self.dtype == np.float16:
return
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_grad(
['X'], 'Out', max_relative_error=0.007, check_dygraph=False)
def init_dtype(self):
self.dtype = np.float32
class TestMKLDNNLeakyReluDim2(TestLeakyRelu):
@ -48,16 +40,8 @@ class TestMKLDNNLeakyReluDim2(TestLeakyRelu):
self.attrs = {"use_mkldnn": True}
def test_check_output(self):
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_output(check_dygraph=False)
def test_check_grad(self):
if self.dtype == np.float16:
return
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_grad(
['X'], 'Out', max_relative_error=0.007, check_dygraph=False)
def init_dtype(self):
self.dtype = np.float32
class TestMKLDNNGeluDim2(TestActivation):
@ -92,16 +76,8 @@ class TestMKLDNNTanhDim2(TestTanh):
self.attrs = {"use_mkldnn": True}
def test_check_output(self):
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_output(check_dygraph=False)
def test_check_grad(self):
if self.dtype == np.float16:
return
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_grad(
['X'], 'Out', max_relative_error=0.007, check_dygraph=False)
def init_dtype(self):
self.dtype = np.float32
class TestMKLDNNSqrtDim2(TestSqrt):
@ -110,16 +86,8 @@ class TestMKLDNNSqrtDim2(TestSqrt):
self.attrs = {"use_mkldnn": True}
def test_check_output(self):
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_output(check_dygraph=False)
def test_check_grad(self):
if self.dtype == np.float16:
return
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_grad(
['X'], 'Out', max_relative_error=0.007, check_dygraph=False)
def init_dtype(self):
self.dtype = np.float32
class TestMKLDNNAbsDim2(TestAbs):
@ -127,16 +95,8 @@ class TestMKLDNNAbsDim2(TestAbs):
super(TestMKLDNNAbsDim2, self).setUp()
self.attrs = {"use_mkldnn": True}
def test_check_output(self):
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_output(check_dygraph=False)
def test_check_grad(self):
if self.dtype == np.float16:
return
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_grad(
['X'], 'Out', max_relative_error=0.007, check_dygraph=False)
def init_dtype(self):
self.dtype = np.float32
class TestMKLDNNSwishDim2(TestSwish):
@ -151,15 +111,8 @@ class TestMKLDNNSwishDim2(TestSwish):
self.outputs = {'Out': out}
self.attrs = {"use_mkldnn": True, "beta": beta}
def test_check_output(self):
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_output()
def test_check_grad(self):
if self.dtype == np.float16:
return
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_grad(['X'], 'Out')
def init_dtype(self):
self.dtype = np.float32
class TestMKLDNNSigmoidDim2(TestSigmoid):
@ -181,16 +134,8 @@ class TestMKLDNNReluDim4(TestRelu):
self.outputs = {'Out': out}
self.attrs = {"use_mkldnn": True}
def test_check_output(self):
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_output(check_dygraph=False)
def test_check_grad(self):
if self.dtype == np.float16:
return
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_grad(
['X'], 'Out', max_relative_error=0.007, check_dygraph=False)
def init_dtype(self):
self.dtype = np.float32
class TestMKLDNNLeakyReluDim4(TestLeakyRelu):
@ -206,16 +151,8 @@ class TestMKLDNNLeakyReluDim4(TestLeakyRelu):
self.outputs = {'Out': out}
self.attrs = {"use_mkldnn": True}
def test_check_output(self):
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_output(check_dygraph=False)
def test_check_grad(self):
if self.dtype == np.float16:
return
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_grad(
['X'], 'Out', max_relative_error=0.007, check_dygraph=False)
def init_dtype(self):
self.dtype = np.float32
class TestMKLDNNGeluDim4(TestActivation):
@ -254,17 +191,6 @@ class TestMKLDNNTanhDim4(TestTanh):
self.outputs = {'Out': np.tanh(self.inputs['X'])}
self.attrs = {"use_mkldnn": True}
def test_check_output(self):
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_output(check_dygraph=False)
def test_check_grad(self):
if self.dtype == np.float16:
return
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_grad(
['X'], 'Out', max_relative_error=0.007, check_dygraph=False)
class TestMKLDNNSqrtDim4(TestSqrt):
def setUp(self):
@ -276,17 +202,6 @@ class TestMKLDNNSqrtDim4(TestSqrt):
self.outputs = {'Out': np.sqrt(self.inputs['X'])}
self.attrs = {"use_mkldnn": True}
def test_check_output(self):
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_output(check_dygraph=False)
def test_check_grad(self):
if self.dtype == np.float16:
return
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_grad(
['X'], 'Out', max_relative_error=0.007, check_dygraph=False)
class TestMKLDNNAbsDim4(TestAbs):
def setUp(self):
@ -299,23 +214,15 @@ class TestMKLDNNAbsDim4(TestAbs):
self.outputs = {'Out': np.abs(self.inputs['X'])}
self.attrs = {"use_mkldnn": True}
def test_check_output(self):
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_output(check_dygraph=False)
def test_check_grad(self):
if self.dtype == np.float16:
return
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_grad(
['X'], 'Out', max_relative_error=0.007, check_dygraph=False)
def init_dtype(self):
self.dtype = np.float32
class TestMKLDNNSwishDim4(TestSwish):
def setUp(self):
super(TestMKLDNNSwishDim4, self).setUp()
x = np.random.uniform(0.1, 1, [2, 4, 3, 5]).astype("float32")
x = np.random.uniform(0.1, 1, [2, 4, 3, 5]).astype(self.dtype)
beta = 2.3
out = x * expit(beta * x)
@ -323,15 +230,8 @@ class TestMKLDNNSwishDim4(TestSwish):
self.outputs = {'Out': out}
self.attrs = {"use_mkldnn": True, "beta": beta}
def test_check_output(self):
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_output()
def test_check_grad(self):
if self.dtype == np.float16:
return
# TODO(wangzhongpu): support mkldnn op in dygraph mode
self.check_grad(['X'], 'Out')
def init_dtype(self):
self.dtype = np.float32
class TestMKLDNNSigmoidDim4(TestSigmoid):

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