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a05fce65
编写于
10月 25, 2018
作者:
T
tensor-tang
浏览文件
操作
浏览文件
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差异文件
Merge remote-tracking branch 'ups/develop' into fix/jit/avx
test=develop
上级
d24d282a
d0fdcb2f
变更
6
显示空白变更内容
内联
并排
Showing
6 changed file
with
174 addition
and
27 deletion
+174
-27
paddle/fluid/operators/math/CMakeLists.txt
paddle/fluid/operators/math/CMakeLists.txt
+1
-0
paddle/fluid/operators/math/sequence_pooling.cc
paddle/fluid/operators/math/sequence_pooling.cc
+32
-7
paddle/fluid/operators/math/sequence_pooling_test.cc
paddle/fluid/operators/math/sequence_pooling_test.cc
+126
-0
python/paddle/fluid/tests/unittests/CMakeLists.txt
python/paddle/fluid/tests/unittests/CMakeLists.txt
+3
-3
python/paddle/fluid/tests/unittests/dist_transformer.py
python/paddle/fluid/tests/unittests/dist_transformer.py
+8
-15
python/paddle/fluid/tests/unittests/test_dist_transformer.py
python/paddle/fluid/tests/unittests/test_dist_transformer.py
+4
-2
未找到文件。
paddle/fluid/operators/math/CMakeLists.txt
浏览文件 @
a05fce65
...
...
@@ -68,6 +68,7 @@ cc_test(selected_rows_functor_test SRCS selected_rows_functor_test.cc DEPS selec
cc_test
(
im2col_test SRCS im2col_test.cc DEPS im2col
)
cc_test
(
vol2col_test SRCS vol2col_test.cc DEPS vol2col
)
cc_test
(
sequence_padding_test SRCS sequence_padding_test.cc DEPS sequence_padding
)
cc_test
(
sequence_pooling_test SRCS sequence_pooling_test.cc DEPS sequence_pooling
)
if
(
WITH_GPU
)
nv_test
(
math_function_gpu_test SRCS math_function_test.cu DEPS math_function
)
nv_test
(
selected_rows_functor_gpu_test SRCS selected_rows_functor_test.cu DEPS selected_rows_functor math_function
)
...
...
paddle/fluid/operators/math/sequence_pooling.cc
浏览文件 @
a05fce65
...
...
@@ -157,6 +157,31 @@ class FirstSeqPoolFunctor {
}
};
template
<
typename
T
>
class
SumSeqPoolGradFunctor
{
public:
void
operator
()(
const
platform
::
CPUDeviceContext
&
context
,
const
framework
::
Tensor
&
out_grad
,
framework
::
LoDTensor
*
in_grad
)
{
auto
lod
=
in_grad
->
lod
()[
0
];
int64_t
out_w
=
out_grad
.
numel
()
/
out_grad
.
dims
()[
0
];
int64_t
in_w
=
in_grad
->
numel
()
/
in_grad
->
dims
()[
0
];
PADDLE_ENFORCE
(
in_w
==
out_w
);
const
T
*
out_g_data
=
out_grad
.
data
<
T
>
();
T
*
in_g_data
=
in_grad
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
blas
=
math
::
GetBlas
<
platform
::
CPUDeviceContext
,
T
>
(
context
);
for
(
int
i
=
0
;
i
<
static_cast
<
int
>
(
lod
.
size
())
-
1
;
++
i
)
{
int64_t
h
=
static_cast
<
int64_t
>
(
lod
[
i
+
1
]
-
lod
[
i
]);
int64_t
in_offset
=
lod
[
i
]
*
in_w
;
const
T
*
out_pos
=
out_g_data
+
i
*
out_w
;
T
*
in_pos
=
in_g_data
+
in_offset
;
for
(
int
r
=
0
;
r
!=
h
;
++
r
)
{
blas
.
VCOPY
(
in_w
,
out_pos
,
in_pos
+
r
*
in_w
);
}
}
}
};
template
<
typename
T
>
class
SequencePoolFunctor
<
platform
::
CPUDeviceContext
,
T
>
{
public:
...
...
@@ -231,9 +256,15 @@ class SequencePoolGradFunctor<platform::CPUDeviceContext, T> {
math
::
SetConstant
<
platform
::
CPUDeviceContext
,
T
>
functor
;
functor
(
context
,
in_grad
,
0
);
}
if
(
pooltype
==
"SUM"
)
{
math
::
SumSeqPoolGradFunctor
<
T
>
sum_pool_grad
;
sum_pool_grad
(
context
,
out_grad
,
in_grad
);
return
;
}
auto
lod
=
in_grad
->
lod
()[
0
];
auto
&
place
=
*
context
.
eigen_device
();
auto
blas
=
math
::
GetBlas
<
platform
::
CPUDeviceContext
,
T
>
(
context
);
for
(
int
i
=
0
;
i
<
static_cast
<
int
>
(
lod
.
size
())
-
1
;
++
i
)
{
auto
in_g_t
=
in_grad
->
Slice
(
static_cast
<
int
>
(
lod
[
i
]),
static_cast
<
int
>
(
lod
[
i
+
1
]));
...
...
@@ -247,12 +278,6 @@ class SequencePoolGradFunctor<platform::CPUDeviceContext, T> {
if
(
pooltype
==
"AVERAGE"
)
{
in_g_e
.
device
(
place
)
=
(
out_g_e
/
static_cast
<
T
>
(
h
)).
broadcast
(
bcast
);
}
else
if
(
pooltype
==
"SUM"
)
{
const
T
*
out_g_data
=
out_g_t
.
data
<
T
>
();
T
*
in_g_data
=
in_g_t
.
mutable_data
<
T
>
(
context
.
GetPlace
());
for
(
int
r
=
0
;
r
!=
h
;
++
r
)
{
blas
.
VCOPY
(
w
,
out_g_data
,
in_g_data
+
r
*
w
);
}
}
else
if
(
pooltype
==
"SQRT"
)
{
in_g_e
.
device
(
place
)
=
(
out_g_e
/
std
::
sqrt
(
static_cast
<
T
>
(
h
))).
broadcast
(
bcast
);
...
...
paddle/fluid/operators/math/sequence_pooling_test.cc
0 → 100644
浏览文件 @
a05fce65
/* Copyright (c) 2018 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. */
#include "paddle/fluid/operators/math/sequence_pooling.h"
#include <gtest/gtest.h>
#include <vector>
template
<
typename
DeviceContext
,
typename
Place
,
typename
T
>
void
TestSequencePoolingSum
(
const
paddle
::
framework
::
LoD
&
lod
)
{
paddle
::
framework
::
LoDTensor
cpu_out_grad
;
paddle
::
framework
::
LoDTensor
cpu_in_grad
;
paddle
::
framework
::
LoDTensor
out_grad
;
paddle
::
framework
::
LoDTensor
in_grad
;
const
size_t
second_dim
=
128u
;
// construct out_grad's tensor in cpu
const
size_t
out_first_dim
=
lod
[
0
].
size
()
-
1
;
auto
out_dims
=
paddle
::
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
out_first_dim
),
static_cast
<
int64_t
>
(
second_dim
)});
cpu_out_grad
.
mutable_data
<
T
>
(
out_dims
,
paddle
::
platform
::
CPUPlace
());
for
(
int64_t
i
=
0
;
i
<
cpu_out_grad
.
numel
();
++
i
)
{
cpu_out_grad
.
data
<
T
>
()[
i
]
=
static_cast
<
T
>
(
i
);
}
// copy to dst out_grad
auto
*
place
=
new
Place
();
DeviceContext
*
context
=
new
DeviceContext
(
*
place
);
if
(
paddle
::
platform
::
is_cpu_place
(
*
place
))
{
out_grad
=
cpu_out_grad
;
}
else
{
TensorCopySync
(
cpu_out_grad
,
*
place
,
&
out_grad
);
}
// construct in_grad
in_grad
.
set_lod
(
lod
);
auto
in_dims
=
paddle
::
framework
::
make_ddim
(
{
static_cast
<
int64_t
>
(
lod
[
0
].
back
()),
static_cast
<
int64_t
>
(
second_dim
)});
in_grad
.
mutable_data
<
T
>
(
in_dims
,
context
->
GetPlace
());
// check tensor contruction result
PADDLE_ENFORCE_EQ
(
in_grad
.
dims
().
size
(),
out_grad
.
dims
().
size
());
for
(
int64_t
i
=
1
;
i
<
out_grad
.
dims
().
size
();
++
i
)
{
PADDLE_ENFORCE_EQ
(
in_grad
.
dims
()[
i
],
out_grad
.
dims
()[
i
]);
}
// call functor
paddle
::
operators
::
math
::
SequencePoolGradFunctor
<
DeviceContext
,
T
>
()(
*
context
,
"SUM"
,
out_grad
,
&
in_grad
);
if
(
paddle
::
platform
::
is_cpu_place
(
*
place
))
{
cpu_in_grad
=
in_grad
;
}
else
{
TensorCopySync
(
in_grad
,
paddle
::
platform
::
CPUPlace
(),
&
cpu_in_grad
);
cpu_in_grad
.
set_lod
(
in_grad
.
lod
());
}
EXPECT_EQ
(
in_grad
.
numel
(),
lod
[
0
].
back
()
*
second_dim
);
EXPECT_EQ
(
in_grad
.
lod
(),
lod
);
if
(
paddle
::
platform
::
is_cpu_place
(
*
place
))
{
for
(
int64_t
i
=
0
;
i
<
in_grad
.
lod
()[
0
].
size
()
-
1
;
++
i
)
{
int64_t
begin
=
in_grad
.
lod
()[
0
][
i
];
int64_t
end
=
in_grad
.
lod
()[
0
][
i
+
1
];
paddle
::
framework
::
Tensor
tmp
=
in_grad
.
Slice
(
begin
,
end
);
for
(
int64_t
j
=
0
;
j
!=
tmp
.
numel
()
/
second_dim
;
++
j
)
{
for
(
int64_t
m
=
0
;
m
!=
second_dim
;
++
m
)
{
EXPECT_EQ
(
tmp
.
data
<
T
>
()[
m
+
j
*
second_dim
],
out_grad
.
data
<
T
>
()[
m
+
i
*
second_dim
]);
}
}
}
}
else
{
for
(
int64_t
i
=
0
;
i
<
cpu_in_grad
.
lod
()[
0
].
size
()
-
1
;
++
i
)
{
int64_t
begin
=
cpu_in_grad
.
lod
()[
0
][
i
];
int64_t
end
=
cpu_in_grad
.
lod
()[
0
][
i
+
1
];
paddle
::
framework
::
Tensor
tmp
=
cpu_in_grad
.
Slice
(
begin
,
end
);
for
(
int64_t
j
=
0
;
j
!=
tmp
.
numel
()
/
second_dim
;
++
j
)
{
for
(
int64_t
m
=
0
;
m
!=
second_dim
;
++
m
)
{
EXPECT_EQ
(
tmp
.
data
<
T
>
()[
m
+
j
*
second_dim
],
cpu_out_grad
.
data
<
T
>
()[
m
+
i
*
second_dim
]);
}
}
}
}
delete
place
;
delete
context
;
}
TEST
(
SequencePoolingGrad
,
CPU_SUM
)
{
paddle
::
framework
::
LoD
lod1
;
lod1
.
push_back
(
std
::
vector
<
size_t
>
{
0
,
10
});
TestSequencePoolingSum
<
paddle
::
platform
::
CPUDeviceContext
,
paddle
::
platform
::
CPUPlace
,
float
>
(
lod1
);
paddle
::
framework
::
LoD
lod2
;
lod2
.
push_back
(
std
::
vector
<
size_t
>
{
0
,
2
,
7
,
10
});
TestSequencePoolingSum
<
paddle
::
platform
::
CPUDeviceContext
,
paddle
::
platform
::
CPUPlace
,
float
>
(
lod2
);
}
#ifdef PADDLE_WITH_CUDA
TEST
(
SequencePoolingGrad
,
CUDA_SUM
)
{
paddle
::
framework
::
LoD
lod1
;
lod1
.
push_back
(
std
::
vector
<
size_t
>
{
0
,
10
});
TestSequencePoolingSum
<
paddle
::
platform
::
CUDADeviceContext
,
paddle
::
platform
::
CUDAPlace
,
float
>
(
lod1
);
paddle
::
framework
::
LoD
lod2
;
lod2
.
push_back
(
std
::
vector
<
size_t
>
{
0
,
2
,
7
,
10
});
TestSequencePoolingSum
<
paddle
::
platform
::
CUDADeviceContext
,
paddle
::
platform
::
CUDAPlace
,
float
>
(
lod2
);
}
#endif
python/paddle/fluid/tests/unittests/CMakeLists.txt
浏览文件 @
a05fce65
...
...
@@ -78,9 +78,9 @@ if(WITH_DISTRIBUTE)
set_tests_properties
(
test_dist_word2vec PROPERTIES TIMEOUT 200
)
py_test_modules
(
test_dist_se_resnext MODULES test_dist_se_resnext
)
set_tests_properties
(
test_dist_se_resnext PROPERTIES TIMEOUT 1000
)
# TODO: fix this test
#
py_test_modules(test_dist_transformer MODULES test_dist_transformer)
#
set_tests_properties(test_dist_transformer PROPERTIES TIMEOUT 1000)
py_test_modules
(
test_dist_transformer MODULES test_dist_transformer
)
set_tests_properties
(
test_dist_transformer PROPERTIES TIMEOUT 1000
)
endif
(
NOT APPLE
)
py_test_modules
(
test_dist_transpiler MODULES test_dist_transpiler
)
endif
()
...
...
python/paddle/fluid/tests/unittests/dist_transformer.py
浏览文件 @
a05fce65
...
...
@@ -35,7 +35,7 @@ import paddle
import
paddle.fluid
as
fluid
import
paddle.fluid.layers
as
layers
from
paddle.fluid
import
core
from
test_dist_base
import
TestDistRunnerBase
,
runtime_main
from
test_dist_base
import
TestDistRunnerBase
,
runtime_main
,
RUN_STEP
import
paddle.compat
as
cpt
from
paddle.compat
import
long_type
...
...
@@ -562,18 +562,12 @@ def train_loop(exe, train_progm, dev_count, sum_cost, avg_cost, lr_scheduler,
for
pass_id
in
six
.
moves
.
xrange
(
TrainTaskConfig
.
pass_num
):
pass_start_time
=
time
.
time
()
for
batch_id
,
data
in
enumerate
(
train_data
()):
if
batch_id
>=
5
:
if
batch_id
>=
RUN_STEP
:
break
feed_list
=
[]
total_num_token
=
0
#if TrainTaskConfig.local:
# lr_rate = lr_scheduler.update_learning_rate()
#for place_id, data_buffer in enumerate(
# split_data(
# data, num_part=dev_count)):
if
TrainTaskConfig
.
local
:
lr_rate
=
lr_scheduler
.
update_learning_rate
()
...
...
@@ -619,7 +613,6 @@ def train_loop(exe, train_progm, dev_count, sum_cost, avg_cost, lr_scheduler,
init
=
True
# Validate and save the model for inference.
if
batch_id
==
0
or
batch_id
==
4
:
if
TrainTaskConfig
.
val_file_pattern
is
not
None
:
val_avg_cost
,
val_ppl
=
test
()
print
(
"[%f]"
%
val_avg_cost
)
...
...
@@ -1701,7 +1694,7 @@ class DistTransformer2x2(TestDistRunnerBase):
def
run_trainer
(
self
,
args
):
TrainTaskConfig
.
use_gpu
=
args
.
use_cuda
sum_cost
,
avg_cost
,
predict
,
token_num
,
local_lr_scheduler
=
get_model
(
sum_cost
,
avg_cost
,
predict
,
token_num
,
local_lr_scheduler
,
test_program
=
get_model
(
args
.
is_dist
,
not
args
.
sync_mode
)
if
args
.
is_dist
:
...
...
python/paddle/fluid/tests/unittests/test_dist_transformer.py
浏览文件 @
a05fce65
...
...
@@ -61,7 +61,8 @@ class TestDistTransformer2x2Sync(TestDistBase):
def
test_dist_train
(
self
):
download_files
()
self
.
check_with_place
(
"dist_transformer.py"
,
delta
=
1e-5
)
self
.
check_with_place
(
"dist_transformer.py"
,
delta
=
1e-5
,
check_error_log
=
False
)
class
TestDistTransformer2x2Async
(
TestDistBase
):
...
...
@@ -70,7 +71,8 @@ class TestDistTransformer2x2Async(TestDistBase):
def
test_dist_train
(
self
):
download_files
()
self
.
check_with_place
(
"dist_transformer.py"
,
delta
=
1.0
)
self
.
check_with_place
(
"dist_transformer.py"
,
delta
=
1.0
,
check_error_log
=
False
)
if
__name__
==
"__main__"
:
...
...
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