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289677e2
编写于
3月 22, 2023
作者:
B
Bo Zhang
提交者:
GitHub
3月 22, 2023
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差异文件
【AMP OP&Test】unit test for test_logit_op (#51051)
* test_logit_op * add cudaKernel to replace eigen impl * bf16 unit test CI
上级
de2166c0
变更
5
显示空白变更内容
内联
并排
Showing
5 changed file
with
138 addition
and
21 deletion
+138
-21
paddle/phi/kernels/funcs/activation_functor.h
paddle/phi/kernels/funcs/activation_functor.h
+52
-0
paddle/phi/kernels/gpu/activation_grad_kernel.cu
paddle/phi/kernels/gpu/activation_grad_kernel.cu
+4
-9
paddle/phi/kernels/gpu/activation_kernel.cu
paddle/phi/kernels/gpu/activation_kernel.cu
+3
-8
python/paddle/fluid/tests/unittests/test_logit_op.py
python/paddle/fluid/tests/unittests/test_logit_op.py
+78
-4
python/paddle/fluid/tests/unittests/white_list/op_accuracy_white_list.py
...luid/tests/unittests/white_list/op_accuracy_white_list.py
+1
-0
未找到文件。
paddle/phi/kernels/funcs/activation_functor.h
浏览文件 @
289677e2
...
...
@@ -2472,6 +2472,58 @@ struct SquareGradGradFunctor : public BaseActivationFunctor<T> {
};
#if defined(__NVCC__) || defined(__HIPCC__) || defined(__xpu__)
template
<
typename
T
>
struct
CudaLogitFunctor
:
public
BaseActivationFunctor
<
T
>
{
using
MT
=
typename
phi
::
dtype
::
MPTypeTrait
<
T
>::
Type
;
MT
zero
=
static_cast
<
MT
>
(
0.0
f
);
MT
one
=
static_cast
<
MT
>
(
1.0
f
);
float
eps
;
typename
BaseActivationFunctor
<
T
>::
AttrPair
GetAttrs
()
{
return
{{
"eps"
,
&
eps
}};
}
// logit(x) = ln(x/(1-x))
__device__
__forceinline__
T
operator
()(
const
T
arg_x
)
const
{
MT
x
=
static_cast
<
MT
>
(
arg_x
);
MT
y
=
min
(
x
,
(
one
-
static_cast
<
MT
>
(
eps
)));
y
=
max
(
y
,
static_cast
<
MT
>
(
eps
));
if
(
!
eps
)
{
y
=
x
<
zero
||
x
>
one
?
static_cast
<
T
>
(
NAN
)
:
log
(
y
/
(
one
-
y
));
}
else
{
y
=
log
(
y
/
(
one
-
y
));
}
return
static_cast
<
T
>
(
y
);
}
};
template
<
typename
T
>
struct
CudaLogitGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
using
MT
=
typename
phi
::
dtype
::
MPTypeTrait
<
T
>::
Type
;
float
eps
;
MT
zero
=
static_cast
<
MT
>
(
0.0
f
);
MT
one
=
static_cast
<
MT
>
(
1.0
f
);
typename
BaseActivationFunctor
<
T
>::
AttrPair
GetAttrs
()
{
return
{{
"eps"
,
&
eps
}};
}
// logit(x)' = 1/(x*(1-x))
__device__
__forceinline__
T
operator
()(
const
T
dout
,
const
T
arg_x
)
const
{
MT
x
=
static_cast
<
MT
>
(
arg_x
);
MT
dx
=
(
x
<
static_cast
<
MT
>
(
eps
)
||
x
>
one
-
static_cast
<
MT
>
(
eps
))
?
zero
:
(
static_cast
<
MT
>
(
dout
)
/
(
x
*
(
one
-
x
)));
return
static_cast
<
T
>
(
dx
);
}
static
constexpr
ActBwdOpFwdDeps
FwdDeps
()
{
return
ActBwdOpFwdDeps
::
kDepOut
;
}
};
template
<
typename
T
>
struct
CudaReluFunctor
:
public
BaseActivationFunctor
<
T
>
{
T
zero
=
static_cast
<
T
>
(
0.0
f
);
...
...
paddle/phi/kernels/gpu/activation_grad_kernel.cu
浏览文件 @
289677e2
...
...
@@ -228,6 +228,9 @@ DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(Celu,
DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPOUT
(
Relu6
,
CudaRelu6GradFunctor
,
threshold
);
DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPOUT
(
LogitCUDA
,
CudaLogitGradFunctor
,
eps
);
DEFINE_GPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPX
(
HardTanh
,
CudaHardTanhGradFunctor
,
...
...
@@ -382,6 +385,7 @@ PD_REGISTER_ACTIVATION_GRAD_KERNEL(tanh_shrink_grad, TanhShrinkGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL
(
silu_grad
,
SiluGradKernel
)
PD_REGISTER_ACTIVATION_GRAD_KERNEL
(
elu_grad
,
EluGradKernel
)
PD_REGISTER_ACTIVATION_GRAD_KERNEL
(
elu_double_grad
,
EluDoubleGradKernel
)
PD_REGISTER_ACTIVATION_GRAD_KERNEL
(
logit_grad
,
LogitCUDAGradKernel
)
PD_REGISTER_KERNEL
(
expm1_grad
,
GPU
,
...
...
@@ -392,15 +396,6 @@ PD_REGISTER_KERNEL(expm1_grad,
phi
::
dtype
::
float16
,
phi
::
dtype
::
bfloat16
)
{}
PD_REGISTER_KERNEL
(
logit_grad
,
GPU
,
ALL_LAYOUT
,
phi
::
LogitGradKernel
,
float
,
double
,
phi
::
dtype
::
float16
,
phi
::
dtype
::
bfloat16
)
{}
PD_REGISTER_KERNEL
(
square_grad
,
GPU
,
ALL_LAYOUT
,
...
...
paddle/phi/kernels/gpu/activation_kernel.cu
浏览文件 @
289677e2
...
...
@@ -109,6 +109,7 @@ DEFINE_GPU_ACTIVATION_KERNEL(Floor, CudaFloorFunctor)
DEFINE_GPU_ACTIVATION_KERNEL
(
Ceil
,
CudaCeilFunctor
)
DEFINE_GPU_ACT_KERNEL_WITH_ONE_ATTRS
(
LeakyRelu
,
CudaLeakyReluFunctor
,
alpha
)
DEFINE_GPU_ACT_KERNEL_WITH_ONE_ATTRS
(
LogitCUDA
,
CudaLogitFunctor
,
eps
)
DEFINE_GPU_ACT_KERNEL_WITH_ONE_ATTRS
(
ThresholdedRelu
,
CudaThresholdedReluFunctor
,
threshold
)
...
...
@@ -225,14 +226,6 @@ PD_REGISTER_KERNEL(expm1,
double
,
phi
::
dtype
::
float16
,
phi
::
dtype
::
bfloat16
)
{}
PD_REGISTER_KERNEL
(
logit
,
GPU
,
ALL_LAYOUT
,
phi
::
LogitKernel
,
float
,
double
,
phi
::
dtype
::
float16
,
phi
::
dtype
::
bfloat16
)
{}
PD_REGISTER_KERNEL
(
square
,
GPU
,
ALL_LAYOUT
,
...
...
@@ -263,6 +256,8 @@ PD_REGISTER_ACTIVATION_KERNEL(round, RoundKernel)
PD_REGISTER_ACTIVATION_KERNEL
(
floor
,
FloorKernel
)
PD_REGISTER_ACTIVATION_KERNEL
(
ceil
,
CeilKernel
)
PD_REGISTER_ACTIVATION_KERNEL
(
celu
,
CeluKernel
)
PD_REGISTER_ACTIVATION_KERNEL
(
logit
,
LogitCUDAKernel
)
PD_REGISTER_KERNEL
(
pow
,
GPU
,
ALL_LAYOUT
,
...
...
python/paddle/fluid/tests/unittests/test_logit_op.py
浏览文件 @
289677e2
...
...
@@ -18,6 +18,8 @@ import numpy as np
from
op_test
import
OpTest
import
paddle
from
paddle.fluid
import
core
from
paddle.fluid.tests.unittests.op_test
import
convert_float_to_uint16
np
.
random
.
seed
(
10
)
...
...
@@ -43,9 +45,6 @@ class TestLogitOp(OpTest):
def
setUp
(
self
):
self
.
op_type
=
'logit'
self
.
python_api
=
paddle
.
logit
self
.
dtype
=
np
.
float64
self
.
shape
=
[
120
]
self
.
eps
=
1e-8
self
.
set_attrs
()
x
=
np
.
random
.
uniform
(
-
1.0
,
1.0
,
self
.
shape
).
astype
(
self
.
dtype
)
out
=
logit
(
x
,
self
.
eps
)
...
...
@@ -55,7 +54,9 @@ class TestLogitOp(OpTest):
self
.
attrs
=
{
'eps'
:
self
.
eps
}
def
set_attrs
(
self
):
pass
self
.
dtype
=
np
.
float64
self
.
shape
=
[
120
]
self
.
eps
=
1e-8
def
test_check_output
(
self
):
self
.
check_output
(
check_eager
=
True
)
...
...
@@ -66,13 +67,86 @@ class TestLogitOp(OpTest):
)
class
TestLogitOpFp32
(
TestLogitOp
):
def
set_attrs
(
self
):
self
.
dtype
=
np
.
float32
self
.
shape
=
[
120
]
self
.
eps
=
1e-8
def
test_check_output
(
self
):
self
.
check_output
(
check_eager
=
True
)
def
test_check_grad
(
self
):
self
.
check_grad
(
[
'X'
],
[
'Out'
],
user_defined_grads
=
[
self
.
x_grad
],
check_eager
=
True
)
class
TestLogitOpFp16
(
TestLogitOp
):
def
set_attrs
(
self
):
self
.
dtype
=
np
.
float16
self
.
shape
=
[
120
]
self
.
eps
=
1e-8
def
test_check_output
(
self
):
self
.
check_output
(
check_eager
=
True
)
def
test_check_grad
(
self
):
self
.
check_grad
(
[
'X'
],
[
'Out'
],
user_defined_grads
=
[
self
.
x_grad
],
check_eager
=
True
)
@
unittest
.
skipIf
(
not
core
.
is_compiled_with_cuda
()
or
not
core
.
is_bfloat16_supported
(
core
.
CUDAPlace
(
0
)),
"core is not compiled with CUDA and not support the bfloat16"
,
)
class
TestLogitOpBf16
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
'logit'
self
.
python_api
=
paddle
.
logit
self
.
set_attrs
()
x
=
np
.
random
.
uniform
(
-
0.5
,
0.5
,
self
.
shape
).
astype
(
np
.
float32
)
out
=
logit
(
x
,
self
.
eps
)
self
.
x_grad
=
logit_grad
(
x
,
self
.
eps
)
self
.
inputs
=
{
'X'
:
convert_float_to_uint16
(
x
)}
self
.
outputs
=
{
'Out'
:
convert_float_to_uint16
(
out
)}
self
.
attrs
=
{
'eps'
:
self
.
eps
}
def
set_attrs
(
self
):
self
.
dtype
=
np
.
uint16
self
.
shape
=
[
120
]
self
.
eps
=
1e-8
def
test_check_output
(
self
):
if
core
.
is_compiled_with_cuda
():
place
=
core
.
CUDAPlace
(
0
)
self
.
check_output_with_place
(
place
,
check_eager
=
True
)
def
test_check_grad
(
self
):
if
core
.
is_compiled_with_cuda
():
place
=
core
.
CUDAPlace
(
0
)
self
.
check_grad_with_place
(
place
,
[
'X'
],
[
'Out'
],
user_defined_grads
=
[
self
.
x_grad
],
check_eager
=
True
,
)
class
TestLogitShape
(
TestLogitOp
):
def
set_attrs
(
self
):
self
.
dtype
=
np
.
float64
self
.
shape
=
[
2
,
60
]
self
.
eps
=
1e-8
class
TestLogitEps
(
TestLogitOp
):
def
set_attrs
(
self
):
self
.
dtype
=
np
.
float32
self
.
shape
=
[
120
]
self
.
eps
=
1e-8
...
...
python/paddle/fluid/tests/unittests/white_list/op_accuracy_white_list.py
浏览文件 @
289677e2
...
...
@@ -38,6 +38,7 @@ NO_FP64_CHECK_GRAD_OP_LIST = [
'increment'
,
'l1_norm'
,
'log_loss'
,
'logit'
,
'lrn'
,
'margin_rank_loss'
,
'match_matrix_tensor'
,
...
...
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