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前往新版Gitcode,体验更适合开发者的 AI 搜索 >>
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81dec05a
编写于
7月 26, 2021
作者:
J
jakpiase
提交者:
GitHub
7月 26, 2021
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差异文件
Fix for failing CI(test_activation_mkldnn_op.py) (#34329)
* fixed CI failing * removed unnecessary imports
上级
577fdde5
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
106 addition
and
84 deletion
+106
-84
python/paddle/fluid/tests/unittests/mkldnn/test_activation_bf16_mkldnn_op.py
.../tests/unittests/mkldnn/test_activation_bf16_mkldnn_op.py
+106
-0
python/paddle/fluid/tests/unittests/mkldnn/test_activation_mkldnn_op.py
...fluid/tests/unittests/mkldnn/test_activation_mkldnn_op.py
+0
-84
未找到文件。
python/paddle/fluid/tests/unittests/mkldnn/test_activation_bf16_mkldnn_op.py
0 → 100644
浏览文件 @
81dec05a
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from
__future__
import
print_function
import
unittest
import
numpy
as
np
from
scipy.special
import
expit
,
erf
import
paddle.fluid.core
as
core
from
paddle.fluid.tests.unittests.op_test
import
OpTest
,
OpTestTool
,
convert_float_to_uint16
from
paddle.fluid.tests.unittests.test_activation_op
import
TestActivation
from
paddle.fluid.tests.unittests.test_gelu_op
import
gelu
@
OpTestTool
.
skip_if_not_cpu_bf16
()
class
TestMKLDNNSigmoidBF16Op
(
TestActivation
):
def
config
(
self
):
self
.
op_type
=
"sigmoid"
def
op_forward
(
self
,
x
):
return
1
/
(
1
+
np
.
exp
(
-
x
))
def
op_grad
(
self
,
dout
,
x
):
return
dout
*
self
.
op_forward
(
x
)
*
(
1
-
self
.
op_forward
(
x
))
def
set_attrs
(
self
):
self
.
attrs
=
{
"use_mkldnn"
:
True
}
def
init_data
(
self
):
self
.
x
=
np
.
random
.
uniform
(
-
1
,
1
,
[
2
,
4
,
3
,
5
]).
astype
(
np
.
float32
)
def
setUp
(
self
):
self
.
dtype
=
np
.
uint16
self
.
init_data
()
self
.
config
()
self
.
out
=
self
.
op_forward
(
self
.
x
)
self
.
inputs
=
{
'X'
:
convert_float_to_uint16
(
self
.
x
)}
self
.
outputs
=
{
'Out'
:
self
.
out
}
self
.
set_attrs
()
def
calculate_grads
(
self
):
self
.
dx
=
self
.
op_grad
(
self
.
out
,
self
.
x
)
def
test_check_output
(
self
):
self
.
check_output_with_place
(
core
.
CPUPlace
())
def
test_check_grad
(
self
):
self
.
calculate_grads
()
self
.
check_grad_with_place
(
core
.
CPUPlace
(),
[
"X"
],
"Out"
,
user_defined_grads
=
[
self
.
dx
],
user_defined_grad_outputs
=
[
convert_float_to_uint16
(
self
.
out
)])
class
TestMKLDNNGeluErfBF16Op
(
TestMKLDNNSigmoidBF16Op
):
def
config
(
self
):
self
.
op_type
=
"gelu"
def
op_forward
(
self
,
x
):
return
gelu
(
x
,
False
)
def
op_grad
(
self
,
dout
,
x
):
return
(
dout
*
(
0.5
+
0.5
*
erf
(
x
/
np
.
sqrt
(
2
))
+
(
x
/
np
.
sqrt
(
2
*
np
.
pi
)
*
np
.
exp
(
-
0.5
*
np
.
power
(
x
,
2
)))))
class
TestMKLDNNGeluErfDim2BF16Op
(
TestMKLDNNGeluErfBF16Op
):
def
init_data
(
self
):
self
.
x
=
np
.
random
.
uniform
(
-
1
,
1
,
[
11
,
17
]).
astype
(
np
.
float32
)
class
TestMKLDNNGeluTanhBF16Op
(
TestMKLDNNSigmoidBF16Op
):
def
config
(
self
):
self
.
op_type
=
"gelu"
def
op_forward
(
self
,
x
):
return
gelu
(
x
,
True
)
def
op_grad
(
self
,
dout
,
x
):
grad_part
=
np
.
tanh
(
np
.
sqrt
(
2
/
np
.
pi
)
*
(
x
+
0.044715
*
np
.
power
(
x
,
3
)))
return
dout
*
0.5
*
(
1
+
grad_part
)
*
(
1
+
np
.
sqrt
(
2
/
np
.
pi
)
*
(
x
+
0.134145
*
np
.
power
(
x
,
3
))
*
(
1
-
grad_part
))
def
set_attrs
(
self
):
self
.
attrs
=
{
"use_mkldnn"
:
True
,
"approximate"
:
True
}
class
TestMKLDNNGeluTanhDim2BF16Op
(
TestMKLDNNGeluTanhBF16Op
):
def
init_data
(
self
):
self
.
x
=
np
.
random
.
uniform
(
-
1
,
1
,
[
11
,
17
]).
astype
(
np
.
float32
)
python/paddle/fluid/tests/unittests/mkldnn/test_activation_mkldnn_op.py
浏览文件 @
81dec05a
...
...
@@ -79,90 +79,6 @@ class TestMKLDNNGeluDim2Approx(TestActivation):
self
.
attrs
=
{
"use_mkldnn"
:
True
,
"approximate"
:
True
}
#Use it as a base class for BF16 activation tests, just override necessary functions
class
TestMKLDNNSigmoidBF16Op
(
TestActivation
):
@
OpTestTool
.
skip_if_not_cpu_bf16
()
def
config
(
self
):
self
.
op_type
=
"sigmoid"
def
op_forward
(
self
,
x
):
return
1
/
(
1
+
np
.
exp
(
-
x
))
def
op_grad
(
self
,
dout
,
x
):
return
dout
*
self
.
op_forward
(
x
)
*
(
1
-
self
.
op_forward
(
x
))
def
set_attrs
(
self
):
self
.
attrs
=
{
"use_mkldnn"
:
True
}
def
init_data
(
self
):
self
.
x
=
np
.
random
.
uniform
(
-
1
,
1
,
[
2
,
4
,
3
,
5
]).
astype
(
np
.
float32
)
def
setUp
(
self
):
self
.
dtype
=
np
.
uint16
self
.
init_data
()
self
.
config
()
self
.
out
=
self
.
op_forward
(
self
.
x
)
self
.
inputs
=
{
'X'
:
convert_float_to_uint16
(
self
.
x
)}
self
.
outputs
=
{
'Out'
:
self
.
out
}
self
.
set_attrs
()
def
calculate_grads
(
self
):
self
.
dx
=
self
.
op_grad
(
self
.
out
,
self
.
x
)
def
test_check_output
(
self
):
self
.
check_output_with_place
(
core
.
CPUPlace
())
def
test_check_grad
(
self
):
self
.
calculate_grads
()
self
.
check_grad_with_place
(
core
.
CPUPlace
(),
[
"X"
],
"Out"
,
user_defined_grads
=
[
self
.
dx
],
user_defined_grad_outputs
=
[
convert_float_to_uint16
(
self
.
out
)])
class
TestMKLDNNGeluErfBF16Op
(
TestMKLDNNSigmoidBF16Op
):
def
config
(
self
):
self
.
op_type
=
"gelu"
def
op_forward
(
self
,
x
):
return
gelu
(
x
,
False
)
def
op_grad
(
self
,
dout
,
x
):
return
(
dout
*
(
0.5
+
0.5
*
erf
(
x
/
np
.
sqrt
(
2
))
+
(
x
/
np
.
sqrt
(
2
*
np
.
pi
)
*
np
.
exp
(
-
0.5
*
np
.
power
(
x
,
2
)))))
class
TestMKLDNNGeluErfDim2BF16Op
(
TestMKLDNNGeluErfBF16Op
):
def
init_data
(
self
):
self
.
x
=
np
.
random
.
uniform
(
-
1
,
1
,
[
11
,
17
]).
astype
(
np
.
float32
)
class
TestMKLDNNGeluTanhBF16Op
(
TestMKLDNNSigmoidBF16Op
):
def
config
(
self
):
self
.
op_type
=
"gelu"
def
op_forward
(
self
,
x
):
return
gelu
(
x
,
True
)
def
op_grad
(
self
,
dout
,
x
):
grad_part
=
np
.
tanh
(
np
.
sqrt
(
2
/
np
.
pi
)
*
(
x
+
0.044715
*
np
.
power
(
x
,
3
)))
return
dout
*
0.5
*
(
1
+
grad_part
)
*
(
1
+
np
.
sqrt
(
2
/
np
.
pi
)
*
(
x
+
0.134145
*
np
.
power
(
x
,
3
))
*
(
1
-
grad_part
))
def
set_attrs
(
self
):
self
.
attrs
=
{
"use_mkldnn"
:
True
,
"approximate"
:
True
}
class
TestMKLDNNGeluTanhDim2BF16Op
(
TestMKLDNNGeluTanhBF16Op
):
def
init_data
(
self
):
self
.
x
=
np
.
random
.
uniform
(
-
1
,
1
,
[
11
,
17
]).
astype
(
np
.
float32
)
class
TestMKLDNNTanhDim2
(
TestTanh
):
def
setUp
(
self
):
super
(
TestMKLDNNTanhDim2
,
self
).
setUp
()
...
...
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