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体验新版 GitCode,发现更多精彩内容 >>
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133a914b
编写于
3月 08, 2021
作者:
Q
Qi Li
提交者:
GitHub
3月 08, 2021
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电子邮件补丁
差异文件
[ROCM] fix test_dist_op ci test, test=develop (#31468)
上级
f9377965
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
68 addition
and
12 deletion
+68
-12
paddle/fluid/operators/dist_op.cu
paddle/fluid/operators/dist_op.cu
+9
-0
paddle/fluid/operators/math/math_cuda_utils.h
paddle/fluid/operators/math/math_cuda_utils.h
+10
-4
python/paddle/fluid/tests/unittests/dist_test.sh
python/paddle/fluid/tests/unittests/dist_test.sh
+33
-2
python/paddle/fluid/tests/unittests/test_dist_op.py
python/paddle/fluid/tests/unittests/test_dist_op.py
+16
-6
未找到文件。
paddle/fluid/operators/dist_op.cu
浏览文件 @
133a914b
...
...
@@ -15,9 +15,18 @@
#include "paddle/fluid/operators/dist_op.h"
namespace
ops
=
paddle
::
operators
;
#ifdef PADDLE_WITH_HIP
// Eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorReductionGpu.h:922
// do not support double in HIPCC platform (Eigen3 to be fixed)
REGISTER_OP_CUDA_KERNEL
(
dist
,
ops
::
DistKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
);
REGISTER_OP_CUDA_KERNEL
(
dist_grad
,
ops
::
DistGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
);
#else
REGISTER_OP_CUDA_KERNEL
(
dist
,
ops
::
DistKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
DistKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
REGISTER_OP_CUDA_KERNEL
(
dist_grad
,
ops
::
DistGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
DistGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
#endif
paddle/fluid/operators/math/math_cuda_utils.h
浏览文件 @
133a914b
...
...
@@ -214,7 +214,7 @@ __inline__ __device__ T warpReduceMax(T val, unsigned lane_mask) {
template
<
typename
T
>
__inline__
__device__
T
warpReduceMin
(
T
val
,
unsigned
lane_mask
)
{
for
(
int
mask
=
HALF_WARP
;
mask
>
0
;
mask
>>=
1
)
#if
__CUDA_ARCH__ >= 350 && CUDA_VERSION >= 9000
#if
defined(PADDLE_WITH_CUDA) && (__CUDA_ARCH__ >= 350 && CUDA_VERSION >= 9000)
val
=
min
(
val
,
__shfl_xor_sync
(
lane_mask
,
val
,
mask
,
warpSize
));
#else
val
=
min
(
val
,
__shfl_xor
(
val
,
mask
,
warpSize
));
...
...
@@ -226,7 +226,7 @@ __inline__ __device__ T warpReduceMin(T val, unsigned lane_mask) {
* threads are less than warpSize.*/
template
<
typename
T
>
__inline__
__device__
T
PartialWarpReduceMin
(
T
val
,
unsigned
lane_mask
)
{
#if
__CUDA_ARCH__ >= 350 && CUDA_VERSION >= 9000
#if
defined(PADDLE_WITH_CUDA) && (__CUDA_ARCH__ >= 350 && CUDA_VERSION >= 9000)
T
warp_val
=
__shfl_sync
(
lane_mask
,
val
,
0
,
warpSize
);
#else
T
warp_val
=
__shfl
(
...
...
@@ -235,7 +235,7 @@ __inline__ __device__ T PartialWarpReduceMin(T val, unsigned lane_mask) {
warp_val
=
val
;
for
(
int
offset
=
HALF_WARP
;
offset
>
0
;
offset
>>=
1
)
#if
__CUDA_ARCH__ >= 350 && CUDA_VERSION >= 9000
#if
defined(PADDLE_WITH_CUDA) && (__CUDA_ARCH__ >= 350 && CUDA_VERSION >= 9000)
warp_val
=
min
(
warp_val
,
__shfl_down_sync
(
lane_mask
,
warp_val
,
offset
,
warpSize
));
#else
...
...
@@ -298,9 +298,15 @@ __inline__ __device__ T PartialBlockReduceMin(T val, unsigned mask) {
__syncthreads
();
shared
[
lane
]
=
PartialWarpReduceMin
(
shared
[
lane
],
mask
);
#if defined(PADDLE_WITH_HIP)
// HIP do not support __syncwarp, using __syncthreads() instead is ok,
// although bringing a few performance decrease.
__syncthreads
();
#else
__syncwarp
();
#endif
#if
__CUDA_ARCH__ >= 350 && CUDA_VERSION >= 9000
#if
defined(PADDLE_WITH_CUDA) && (__CUDA_ARCH__ >= 350 && CUDA_VERSION >= 9000)
val
=
__shfl_sync
(
mask
,
shared
[
lane
],
0
,
warpSize
);
#else
val
=
__shfl
(
shared
[
lane
],
0
,
warpSize
);
...
...
python/paddle/fluid/tests/unittests/dist_test.sh
浏览文件 @
133a914b
#!/bin/bash
# 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.
unset
https_proxy http_proxy
export
FLAGS_rpc_disable_reuse_port
=
1
...
...
@@ -50,14 +65,30 @@ do
cat
-n
${
log
}
done
# check CUDA or ROCM env
GPU_SYS_INFO_CMD
=
nvidia-smi
which
${
GPU_SYS_INFO_CMD
}
exit_code
=
$?
if
[[
$exit_code
-ne
0
]]
;
then
GPU_SYS_INFO_CMD
=
rocm-smi
fi
which
${
GPU_SYS_INFO_CMD
}
exit_code
=
$?
if
[[
$exit_code
-ne
0
]]
;
then
echo
"nvidia-smi or rocm-smi faild with
${
exit_code
}
"
exit
${
exit_code
}
fi
#display system context
for
i
in
{
1..2
}
;
do
sleep
3
ps
-aux
netstat
-anlp
if
hash
"
nvidia-smi
"
>
/dev/null
;
then
nvidia-smi
if
hash
"
${
GPU_SYS_INFO_CMD
}
"
>
/dev/null
;
then
${
GPU_SYS_INFO_CMD
}
fi
done
...
...
python/paddle/fluid/tests/unittests/test_dist_op.py
浏览文件 @
133a914b
...
...
@@ -39,9 +39,10 @@ class TestDistOp(OpTest):
self
.
op_type
=
'dist'
self
.
attrs
=
{}
self
.
init_case
()
self
.
init_data_type
()
self
.
inputs
=
{
"X"
:
np
.
random
.
random
(
self
.
x_shape
).
astype
(
"float64"
),
"Y"
:
np
.
random
.
random
(
self
.
y_shape
).
astype
(
"float64"
)
"X"
:
np
.
random
.
random
(
self
.
x_shape
).
astype
(
self
.
data_type
),
"Y"
:
np
.
random
.
random
(
self
.
y_shape
).
astype
(
self
.
data_type
)
}
self
.
attrs
[
"p"
]
=
self
.
p
...
...
@@ -55,6 +56,10 @@ class TestDistOp(OpTest):
self
.
y_shape
=
(
120
)
self
.
p
=
0.
def
init_data_type
(
self
):
self
.
data_type
=
np
.
float32
if
core
.
is_compiled_with_rocm
(
)
else
np
.
float64
def
calc_gradient
(
self
):
x
=
self
.
inputs
[
"X"
]
y
=
self
.
inputs
[
"Y"
]
...
...
@@ -143,15 +148,20 @@ class TestDistOpCase5(TestDistOp):
class
TestDistAPI
(
unittest
.
TestCase
):
def
init_data_type
(
self
):
self
.
data_type
=
'float32'
if
core
.
is_compiled_with_rocm
(
)
else
'float64'
def
test_api
(
self
):
self
.
init_data_type
()
main_program
=
fluid
.
Program
()
startup_program
=
fluid
.
Program
()
with
fluid
.
program_guard
(
main_program
,
startup_program
):
x
=
fluid
.
data
(
name
=
'x'
,
shape
=
[
2
,
3
,
4
,
5
],
dtype
=
'float64'
)
y
=
fluid
.
data
(
name
=
'y'
,
shape
=
[
3
,
1
,
5
],
dtype
=
'float64'
)
x
=
fluid
.
data
(
name
=
'x'
,
shape
=
[
2
,
3
,
4
,
5
],
dtype
=
self
.
data_type
)
y
=
fluid
.
data
(
name
=
'y'
,
shape
=
[
3
,
1
,
5
],
dtype
=
self
.
data_type
)
p
=
2
x_i
=
np
.
random
.
random
((
2
,
3
,
4
,
5
)).
astype
(
"float64"
)
y_i
=
np
.
random
.
random
((
3
,
1
,
5
)).
astype
(
"float64"
)
x_i
=
np
.
random
.
random
((
2
,
3
,
4
,
5
)).
astype
(
self
.
data_type
)
y_i
=
np
.
random
.
random
((
3
,
1
,
5
)).
astype
(
self
.
data_type
)
result
=
paddle
.
dist
(
x
,
y
,
p
)
place
=
fluid
.
CUDAPlace
(
0
)
if
core
.
is_compiled_with_cuda
(
)
else
fluid
.
CPUPlace
()
...
...
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