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02842cfc
编写于
4月 13, 2018
作者:
C
chengduoZH
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
enhance broadcast_op_handle and gather_op_handle
上级
b0267ac9
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
266 addition
and
239 deletion
+266
-239
paddle/fluid/framework/details/broadcast_op_handle.cc
paddle/fluid/framework/details/broadcast_op_handle.cc
+50
-21
paddle/fluid/framework/details/broadcast_op_handle_test.cc
paddle/fluid/framework/details/broadcast_op_handle_test.cc
+78
-73
paddle/fluid/framework/details/gather_op_handle.cc
paddle/fluid/framework/details/gather_op_handle.cc
+68
-63
paddle/fluid/framework/details/gather_op_handle_test.cc
paddle/fluid/framework/details/gather_op_handle_test.cc
+70
-59
paddle/fluid/framework/details/op_handle_base.cc
paddle/fluid/framework/details/op_handle_base.cc
+0
-15
paddle/fluid/framework/details/op_handle_base.h
paddle/fluid/framework/details/op_handle_base.h
+0
-8
未找到文件。
paddle/fluid/framework/details/broadcast_op_handle.cc
浏览文件 @
02842cfc
...
...
@@ -18,45 +18,74 @@ namespace paddle {
namespace
framework
{
namespace
details
{
Tensor
*
GetTensorFromVar
(
Variable
*
in_var
)
{
if
(
in_var
->
IsType
<
LoDTensor
>
())
{
return
in_var
->
GetMutable
<
LoDTensor
>
();
}
else
if
(
in_var
->
IsType
<
SelectedRows
>
())
{
return
in_var
->
GetMutable
<
SelectedRows
>
()
->
mutable_value
();
}
else
{
PADDLE_THROW
(
"Var should be LoDTensor or SelectedRows"
);
}
return
nullptr
;
}
BroadcastOpHandle
::
BroadcastOpHandle
(
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
std
::
vector
<
platform
::
Place
>
&
places
)
:
local_scopes_
(
local_scopes
),
places_
(
places
)
{}
void
BroadcastOpHandle
::
RunImpl
()
{
PADDLE_ENFORCE_EQ
(
this
->
inputs_
.
size
(),
1
,
// the input may have dummy var.
std
::
vector
<
VarHandle
*>
in_var_handle
;
for
(
auto
*
in
:
inputs_
)
{
auto
*
out_handle
=
dynamic_cast
<
VarHandle
*>
(
in
);
if
(
out_handle
)
{
in_var_handle
.
push_back
(
out_handle
);
}
}
PADDLE_ENFORCE_EQ
(
in_var_handle
.
size
(),
1
,
"The number of input should be one."
);
// the output may have dummy var.
std
::
vector
<
VarHandle
*>
out_var_handles
;
for
(
auto
*
out
:
outputs_
)
{
auto
*
out_handle
=
dynamic_cast
<
VarHandle
*>
(
out
);
if
(
out_handle
)
{
out_var_handles
.
push_back
(
out_handle
);
}
}
PADDLE_ENFORCE_EQ
(
this
->
outputs_
.
size
(),
places_
.
size
(),
out_var_handles
.
size
(),
places_
.
size
(),
"The number of output should equal to the number of places."
);
// Wait input done, this Wait is asynchronous operation
auto
in_var_handle
=
static_cast
<
VarHandle
*>
(
this
->
inputs_
[
0
]);
auto
&
in_place
=
in_var_handle
->
place_
;
if
(
inputs_
[
0
]
->
generated_op_
)
{
inputs_
[
0
]
->
generated_op_
->
Wait
(
dev_ctxes_
[
in_place
]);
for
(
auto
*
out
:
outputs_
)
{
auto
out_handle
=
static_cast
<
VarHandle
*>
(
out
);
auto
&
out_p
=
out_handle
->
place_
;
inputs_
[
0
]
->
generated_op_
->
Wait
(
dev_ctxes_
[
out_p
]);
auto
&
in_place
=
in_var_handle
[
0
]
->
place_
;
if
(
in_var_handle
[
0
]
->
generated_op_
)
{
in_var_handle
[
0
]
->
generated_op_
->
Wait
(
dev_ctxes_
[
in_place
]);
for
(
auto
*
out
:
out_var_handles
)
{
auto
&
out_p
=
out
->
place_
;
if
(
platform
::
is_same_place
(
in_place
,
out_p
))
continue
;
in_var_handle
[
0
]
->
generated_op_
->
Wait
(
dev_ctxes_
[
out_p
]);
}
}
auto
in_scope_idx
=
in_var_handle
->
scope_idx_
;
//
auto
in_scope_idx
=
in_var_handle
[
0
]
->
scope_idx_
;
PADDLE_ENFORCE_LT
(
in_scope_idx
,
local_scopes_
.
size
(),
"The input(%s) is not in the local_scopes."
,
in_var_handle
->
name_
);
auto
in_var
=
local_scopes_
[
in_scope_idx
]
->
FindVar
(
in_var_handle
->
name_
);
in_var_handle
[
0
]
->
name_
);
auto
in_var
=
local_scopes_
[
in_scope_idx
]
->
FindVar
(
in_var_handle
[
0
]
->
name_
);
Tensor
*
in_tensor
=
GetTensorFromVar
(
in_var
);
for
(
auto
*
out
:
outputs_
)
{
auto
out_handle
=
static_cast
<
VarHandle
*>
(
out
);
auto
&
out_p
=
out_handle
->
place_
;
auto
out_scope_idx
=
out_handle
->
scope_idx_
;
for
(
auto
*
out
:
out_var_handles
)
{
auto
&
out_p
=
out
->
place_
;
auto
out_scope_idx
=
out
->
scope_idx_
;
PADDLE_ENFORCE_LT
(
out_scope_idx
,
local_scopes_
.
size
(),
"%s is not in the local_scopes "
,
out_handle
->
name_
);
"%s is not in the local_scopes "
,
out
->
name_
);
auto
*
s
=
local_scopes_
[
out_scope_idx
];
auto
out_var
=
s
->
FindVar
(
out
_handle
->
name_
);
auto
out_var
=
s
->
FindVar
(
out
->
name_
);
PADDLE_ENFORCE_EQ
(
out_p
.
which
(),
in_place
.
which
(),
"The place of input and output should be the same."
);
...
...
@@ -89,7 +118,7 @@ void BroadcastOpHandle::RunImpl() {
auto
dst_gpu_place
=
boost
::
get
<
platform
::
CUDAPlace
>
(
out_p
);
void
*
dst_ptr
=
out_tensor
->
mutable_data
(
out_p
);
void
*
src_ptr
=
in_tensor
->
data
<
void
>
();
int64_t
size
=
in_tensor
->
numel
();
int64_t
size
=
in_tensor
->
numel
()
*
SizeOfType
(
in_tensor
->
type
())
;
memory
::
Copy
(
dst_gpu_place
,
dst_ptr
,
src_gpu_place
,
src_ptr
,
size
,
reinterpret_cast
<
platform
::
CUDADeviceContext
*>
(
dev_ctxes_
[
out_p
])
...
...
paddle/fluid/framework/details/broadcast_op_handle_test.cc
浏览文件 @
02842cfc
...
...
@@ -27,8 +27,20 @@ namespace p = paddle::platform;
// test data amount
const
f
::
DDim
kDims
=
{
20
,
20
};
class
BroadcastTester
:
public
::
testing
::
Test
{
public:
struct
TestBroadcastOpHandle
{
std
::
vector
<
std
::
unique_ptr
<
p
::
DeviceContext
>>
ctxs_
;
std
::
vector
<
Scope
*>
local_scopes_
;
Scope
g_scope_
;
std
::
unique_ptr
<
OpHandleBase
>
op_handle_
;
std
::
vector
<
std
::
unique_ptr
<
VarHandleBase
>>
vars_
;
std
::
vector
<
p
::
Place
>
gpu_list_
;
void
WaitAll
()
{
for
(
size_t
j
=
0
;
j
<
ctxs_
.
size
();
++
j
)
{
ctxs_
[
j
]
->
Wait
();
}
}
void
InitCtxOnGpu
(
bool
use_gpu
)
{
if
(
use_gpu
)
{
#ifdef PADDLE_WITH_CUDA
...
...
@@ -57,61 +69,56 @@ class BroadcastTester : public ::testing::Test {
}
}
void
BroadcastInitOp
(
in
t
input_scope_idx
)
{
void
InitBroadcastOp
(
size_
t
input_scope_idx
)
{
for
(
size_t
j
=
0
;
j
<
gpu_list_
.
size
();
++
j
)
{
local_scope
_
.
push_back
(
&
g_scope_
.
NewScope
(
));
local_scope_
[
j
]
->
Var
(
"out"
);
local_scope
s_
.
push_back
(
&
(
g_scope_
.
NewScope
()
));
local_scope
s
_
[
j
]
->
Var
(
"out"
);
}
local_scope_
[
input_scope_idx
]
->
Var
(
"input"
);
local_scope
s
_
[
input_scope_idx
]
->
Var
(
"input"
);
bc_op_handle_
=
new
f
::
details
::
BroadcastOpHandle
(
local_scope_
,
gpu_list_
);
op_handle_
.
reset
(
new
BroadcastOpHandle
(
local_scopes_
,
gpu_list_
)
);
f
::
details
::
VarHandle
*
in_var_handle
=
new
f
::
details
::
VarHandle
();
vars_
.
emplace_back
(
new
VarHandle
());
VarHandle
*
in_var_handle
=
static_cast
<
VarHandle
*>
(
vars_
.
back
().
get
());
in_var_handle
->
place_
=
gpu_list_
[
input_scope_idx
];
in_var_handle
->
name_
=
"input"
;
in_var_handle
->
version_
=
1
;
in_var_handle
->
scope_idx_
=
input_scope_idx
;
in_var_handle
->
generated_op_
=
nullptr
;
bc_op_handle_
->
AddInput
(
in_var_handle
);
op_handle_
->
AddInput
(
in_var_handle
);
// add dummy var
vars_
.
emplace_back
(
new
DummyVarHandle
());
DummyVarHandle
*
dummy_var_handle
=
static_cast
<
DummyVarHandle
*>
(
vars_
.
back
().
get
());
dummy_var_handle
->
generated_op_
=
nullptr
;
op_handle_
->
AddInput
(
dummy_var_handle
);
for
(
size_t
j
=
0
;
j
<
gpu_list_
.
size
();
++
j
)
{
bc_op_handle_
->
dev_ctxes_
[
gpu_list_
[
j
]]
=
ctxs_
[
j
];
f
::
details
::
VarHandle
*
out_var_handle
=
new
f
::
details
::
VarHandle
();
op_handle_
->
dev_ctxes_
[
gpu_list_
[
j
]]
=
ctxs_
[
j
].
get
();
vars_
.
emplace_back
(
new
VarHandle
());
VarHandle
*
out_var_handle
=
static_cast
<
VarHandle
*>
(
vars_
.
back
().
get
());
out_var_handle
->
place_
=
gpu_list_
[
j
];
out_var_handle
->
name_
=
"out"
;
out_var_handle
->
version_
=
2
;
out_var_handle
->
scope_idx_
=
j
;
bc_op_handle_
->
AddOutput
(
out_var_handle
);
}
}
void
BroadcastOpDestroy
()
{
for
(
auto
in
:
bc_op_handle_
->
inputs_
)
{
delete
in
;
}
for
(
auto
out
:
bc_op_handle_
->
outputs_
)
{
delete
out
;
op_handle_
->
AddOutput
(
out_var_handle
);
}
delete
bc_op_handle_
;
for
(
size_t
j
=
0
;
j
<
ctxs_
.
size
();
++
j
)
{
delete
ctxs_
[
j
];
}
}
void
WaitAll
()
{
for
(
size_t
j
=
0
;
j
<
ctxs_
.
size
();
++
j
)
{
ctxs_
[
j
]
->
Wait
();
}
// add dummy var
vars_
.
emplace_back
(
new
DummyVarHandle
());
DummyVarHandle
*
out_dummy_var_handle
=
static_cast
<
DummyVarHandle
*>
(
vars_
.
back
().
get
());
out_dummy_var_handle
->
generated_op_
=
nullptr
;
op_handle_
->
AddOutput
(
out_dummy_var_handle
);
}
void
TestBroadcastLodTensor
()
{
int
input_scope_idx
=
0
;
BroadcastInitOp
(
input_scope_idx
);
auto
in_var
=
local_scope_
[
input_scope_idx
]
->
Var
(
"input"
);
void
TestBroadcastLodTensor
(
size_t
input_scope_idx
)
{
auto
in_var
=
local_scopes_
[
input_scope_idx
]
->
Var
(
"input"
);
auto
in_lod_tensor
=
in_var
->
GetMutable
<
f
::
LoDTensor
>
();
in_lod_tensor
->
mutable_data
<
float
>
(
kDims
,
gpu_list_
[
input_scope_idx
]);
std
::
vector
<
float
>
send_vector
(
f
::
product
(
kDims
),
input_scope_idx
+
12
);
std
::
vector
<
float
>
send_vector
(
static_cast
<
size_t
>
(
f
::
product
(
kDims
))
);
for
(
size_t
k
=
0
;
k
<
send_vector
.
size
();
++
k
)
{
send_vector
[
k
]
=
k
;
}
...
...
@@ -120,13 +127,13 @@ class BroadcastTester : public ::testing::Test {
send_vector
,
*
(
ctxs_
[
input_scope_idx
]),
in_lod_tensor
);
in_lod_tensor
->
set_lod
(
lod
);
bc_
op_handle_
->
Run
(
false
);
op_handle_
->
Run
(
false
);
WaitAll
();
p
::
CPUPlace
cpu_place
;
for
(
size_t
j
=
0
;
j
<
gpu_list_
.
size
();
++
j
)
{
auto
out_var
=
local_scope_
[
j
]
->
Var
(
"out"
);
auto
out_var
=
local_scope
s
_
[
j
]
->
Var
(
"out"
);
auto
out_tensor
=
out_var
->
Get
<
f
::
LoDTensor
>
();
PADDLE_ENFORCE_EQ
(
out_tensor
.
lod
(),
lod
,
"lod is not equal."
);
...
...
@@ -134,42 +141,37 @@ class BroadcastTester : public ::testing::Test {
f
::
TensorCopy
(
out_tensor
,
cpu_place
,
*
(
ctxs_
[
j
]),
&
result_tensor
);
float
*
ct
=
result_tensor
.
mutable_data
<
float
>
(
cpu_place
);
for
(
int64_t
j
=
0
;
j
<
f
::
product
(
kDims
);
++
j
)
{
ASSERT_NEAR
(
ct
[
j
],
send_vector
[
j
],
1e-5
);
for
(
int64_t
i
=
0
;
i
<
f
::
product
(
kDims
);
++
i
)
{
ASSERT_NEAR
(
ct
[
i
],
send_vector
[
i
],
1e-5
);
}
}
BroadcastOpDestroy
();
}
void
TestBroadcastSelectedRows
()
{
int
input_scope_idx
=
0
;
BroadcastInitOp
(
input_scope_idx
);
auto
in_var
=
local_scope_
[
input_scope_idx
]
->
Var
(
"input"
);
void
TestBroadcastSelectedRows
(
size_t
input_scope_idx
)
{
auto
in_var
=
local_scopes_
[
input_scope_idx
]
->
Var
(
"input"
);
auto
in_selected_rows
=
in_var
->
GetMutable
<
f
::
SelectedRows
>
();
auto
value
=
in_selected_rows
->
mutable_value
();
value
->
mutable_data
<
float
>
(
kDims
,
gpu_list_
[
input_scope_idx
]);
int
height
=
kDims
[
0
]
*
2
;
int
height
=
static_cast
<
int
>
(
kDims
[
0
])
*
2
;
std
::
vector
<
int64_t
>
rows
{
0
,
1
,
2
,
3
,
3
,
0
,
14
,
7
,
3
,
1
,
2
,
4
,
6
,
3
,
1
,
1
,
1
,
1
,
3
,
7
};
in_selected_rows
->
set_height
(
height
);
in_selected_rows
->
set_rows
(
rows
);
std
::
vector
<
float
>
send_vector
(
f
::
product
(
kDims
));
std
::
vector
<
float
>
send_vector
(
static_cast
<
size_t
>
(
f
::
product
(
kDims
)
));
for
(
size_t
k
=
0
;
k
<
send_vector
.
size
();
++
k
)
{
send_vector
[
k
]
=
k
;
}
paddle
::
framework
::
TensorFromVector
<
float
>
(
send_vector
,
*
(
ctxs_
[
input_scope_idx
]),
value
);
bc_
op_handle_
->
Run
(
false
);
op_handle_
->
Run
(
false
);
WaitAll
();
p
::
CPUPlace
cpu_place
;
for
(
size_t
j
=
0
;
j
<
gpu_list_
.
size
();
++
j
)
{
auto
out_var
=
local_scope_
[
j
]
->
Var
(
"out"
);
auto
out_var
=
local_scope
s
_
[
j
]
->
Var
(
"out"
);
auto
&
out_select_rows
=
out_var
->
Get
<
f
::
SelectedRows
>
();
auto
rt
=
out_select_rows
.
value
();
...
...
@@ -183,41 +185,44 @@ class BroadcastTester : public ::testing::Test {
f
::
TensorCopy
(
rt
,
cpu_place
,
*
(
ctxs_
[
j
]),
&
result_tensor
);
float
*
ct
=
result_tensor
.
data
<
float
>
();
for
(
int64_t
j
=
0
;
j
<
f
::
product
(
kDims
);
++
j
)
{
ASSERT_NEAR
(
ct
[
j
],
send_vector
[
j
],
1e-5
);
for
(
int64_t
i
=
0
;
i
<
f
::
product
(
kDims
);
++
i
)
{
ASSERT_NEAR
(
ct
[
i
],
send_vector
[
i
],
1e-5
);
}
}
BroadcastOpDestroy
();
}
public:
f
::
Scope
g_scope_
;
std
::
vector
<
p
::
DeviceContext
*>
ctxs_
;
std
::
vector
<
f
::
Scope
*>
local_scope_
;
std
::
vector
<
p
::
Place
>
gpu_list_
;
f
::
details
::
BroadcastOpHandle
*
bc_op_handle_
;
};
TEST_F
(
BroadcastTester
,
TestCPUBroadcastTestLodTensor
)
{
InitCtxOnGpu
(
false
);
TestBroadcastLodTensor
();
TEST
(
BroadcastTester
,
TestCPUBroadcastTestLodTensor
)
{
TestBroadcastOpHandle
test_op
;
size_t
input_scope_idx
=
0
;
test_op
.
InitCtxOnGpu
(
false
);
test_op
.
InitBroadcastOp
(
input_scope_idx
);
test_op
.
TestBroadcastLodTensor
(
input_scope_idx
);
}
TEST_F
(
BroadcastTester
,
TestCPUBroadcastTestSelectedRows
)
{
InitCtxOnGpu
(
false
);
TestBroadcastSelectedRows
();
TEST
(
BroadcastTester
,
TestCPUBroadcastTestSelectedRows
)
{
TestBroadcastOpHandle
test_op
;
size_t
input_scope_idx
=
0
;
test_op
.
InitCtxOnGpu
(
false
);
test_op
.
InitBroadcastOp
(
input_scope_idx
);
test_op
.
TestBroadcastSelectedRows
(
input_scope_idx
);
}
#ifdef PADDLE_WITH_CUDA
TEST_F
(
BroadcastTester
,
TestGPUBroadcastTestLodTensor
)
{
InitCtxOnGpu
(
true
);
TestBroadcastLodTensor
();
TEST
(
BroadcastTester
,
TestGPUBroadcastTestLodTensor
)
{
TestBroadcastOpHandle
test_op
;
size_t
input_scope_idx
=
0
;
test_op
.
InitCtxOnGpu
(
true
);
test_op
.
InitBroadcastOp
(
input_scope_idx
);
test_op
.
TestBroadcastLodTensor
(
input_scope_idx
);
}
TEST_F
(
BroadcastTester
,
TestGPUBroadcastTestSelectedRows
)
{
InitCtxOnGpu
(
true
);
TestBroadcastSelectedRows
();
TEST
(
BroadcastTester
,
TestGPUBroadcastTestSelectedRows
)
{
TestBroadcastOpHandle
test_op
;
size_t
input_scope_idx
=
0
;
test_op
.
InitCtxOnGpu
(
true
);
test_op
.
InitBroadcastOp
(
input_scope_idx
);
test_op
.
TestBroadcastSelectedRows
(
input_scope_idx
);
}
#endif
...
...
paddle/fluid/framework/details/gather_op_handle.cc
浏览文件 @
02842cfc
...
...
@@ -23,32 +23,54 @@ GatherOpHandle::GatherOpHandle(const std::vector<Scope *> &local_scopes,
:
local_scopes_
(
local_scopes
),
places_
(
places
)
{}
void
GatherOpHandle
::
RunImpl
()
{
// the input may have dummy var.
std
::
vector
<
VarHandle
*>
in_var_handles
;
for
(
auto
*
in
:
inputs_
)
{
auto
*
in_handle
=
dynamic_cast
<
VarHandle
*>
(
in
);
if
(
in_handle
)
{
in_var_handles
.
push_back
(
in_handle
);
}
}
PADDLE_ENFORCE_EQ
(
this
->
inputs_
.
size
(),
places_
.
size
(),
"The number of inputs should be equal to the number of place."
);
PADDLE_ENFORCE_EQ
(
this
->
outputs_
.
size
(),
1
,
in_var_handles
.
size
(),
places_
.
size
(),
"The number of output should equal to the number of places."
);
// the output may have dummy var.
std
::
vector
<
VarHandle
*>
out_var_handles
;
for
(
auto
*
out
:
outputs_
)
{
auto
*
out_handle
=
dynamic_cast
<
VarHandle
*>
(
out
);
if
(
out_handle
)
{
out_var_handles
.
push_back
(
out_handle
);
}
}
PADDLE_ENFORCE_EQ
(
out_var_handles
.
size
(),
1
,
"The number of output should be one."
);
auto
in_0_handle
=
static_cast
<
VarHandle
*>
(
inputs_
[
0
]);
auto
in_0_handle
=
static_cast
<
VarHandle
*>
(
in_var_handles
[
0
]);
auto
pre_in_var
=
local_scopes_
[
in_0_handle
->
scope_idx_
]
->
FindVar
(
in_0_handle
->
name_
);
auto
pre_place
=
in_0_handle
->
place_
;
PADDLE_ENFORCE
(
pre_in_var
->
IsType
<
framework
::
SelectedRows
>
(),
"Currently, gather_op only can gather SelectedRows."
);
auto
pre_place
=
in_0_handle
->
place_
;
PADDLE_ENFORCE_EQ
(
out_var_handles
[
0
]
->
place_
.
which
(),
pre_place
.
which
(),
"The place of input and output should be the same."
);
// Wait input done, this Wait is asynchronous operation
for
(
auto
*
in
:
inputs_
)
{
if
(
inputs_
[
0
]
->
generated_op_
)
{
auto
&
p
=
static_cast
<
VarHandle
*>
(
in
)
->
place_
;
in
->
generated_op_
->
Wait
(
dev_ctxes_
[
p
]);
for
(
auto
*
in
:
in_var_handles
)
{
if
(
in
->
generated_op_
)
{
in
->
generated_op_
->
Wait
(
dev_ctxes_
[
in
->
place_
]);
}
}
std
::
vector
<
int64_t
>
out_rows
;
std
::
vector
<
Tensor
*
>
in_tensors
;
std
::
vector
<
Tensor
>
in_tensors
;
std
::
vector
<
platform
::
Place
>
in_places
;
auto
&
pre_in
=
pre_in_var
->
Get
<
framework
::
SelectedRows
>
();
// gather the inputs
for
(
auto
*
in
:
in
puts_
)
{
for
(
auto
*
in
:
in
_var_handles
)
{
auto
in_handle
=
static_cast
<
VarHandle
*>
(
in
);
auto
in_p
=
in_handle
->
place_
;
in_places
.
push_back
(
in_p
);
...
...
@@ -58,63 +80,46 @@ void GatherOpHandle::RunImpl() {
"The place of input should be the same."
);
auto
*
s
=
local_scopes_
[
in_handle
->
scope_idx_
];
auto
in_var
=
s
->
FindVar
(
in_handle
->
name_
);
PADDLE_ENFORCE_EQ
(
in_var
->
Type
(),
pre_in_var
->
Type
(),
auto
&
in_sr
=
in_var
->
Get
<
framework
::
SelectedRows
>
();
PADDLE_ENFORCE_EQ
(
in_sr
.
value
().
type
(),
pre_in
.
value
().
type
(),
"The type of input is not consistent."
);
PADDLE_ENFORCE_EQ
(
pre_in
.
height
(),
in_sr
.
height
(),
"The height of inputs is not consistent."
);
PADDLE_ENFORCE_EQ
(
pre_in
.
GetCompleteDims
(),
in_sr
.
GetCompleteDims
(),
,
"The dims of inputs is not consistent."
);
if
(
in_var
->
IsType
<
framework
::
SelectedRows
>
())
{
auto
&
pre_in
=
pre_in_var
->
Get
<
framework
::
SelectedRows
>
();
auto
&
in_sr
=
in_var
->
Get
<
framework
::
SelectedRows
>
();
auto
in_sr_rows
=
in_sr
.
rows
();
out_rows
.
insert
(
out_rows
.
begin
(),
in_sr_rows
.
begin
(),
in_sr_rows
.
end
());
PADDLE_ENFORCE_EQ
(
pre_in
.
height
(),
in_sr
.
height
(),
"The height of inputs is not consistent."
);
PADDLE_ENFORCE_EQ
(
pre_in
.
GetCompleteDims
(),
in_sr
.
GetCompleteDims
(),
,
"The dims of inputs is not consistent."
);
}
else
if
(
in_var
->
IsType
<
framework
::
LoDTensor
>
())
{
auto
&
pre_in
=
pre_in_var
->
Get
<
framework
::
LoDTensor
>
();
auto
&
in_lodtensor
=
in_var
->
Get
<
framework
::
LoDTensor
>
();
PADDLE_ENFORCE_EQ
(
in_lodtensor
.
lod
(),
pre_in
.
lod
(),
"The lod of inputs is not consistent."
);
PADDLE_ENFORCE_EQ
(
in_lodtensor
.
dims
(),
pre_in
.
dims
(),
"The dims of inputs is not consistent."
);
}
else
{
PADDLE_THROW
(
"Var should be LoDTensor or SelectedRows."
);
}
in_tensors
.
push_back
(
GetTensorFromVar
(
in_var
));
pre_in_var
=
in_var
;
auto
in_sr_rows
=
in_sr
.
rows
();
out_rows
.
insert
(
out_rows
.
end
(),
in_sr_rows
.
begin
(),
in_sr_rows
.
end
());
in_tensors
.
emplace_back
(
in_sr
.
value
());
}
// write the output
auto
out_handle
=
static_cast
<
VarHandle
*>
(
this
->
outputs_
[
0
]);
auto
&
out_place
=
out_handle
->
place_
;
auto
out_scope_idx
=
out_handle
->
scope_idx_
;
auto
out_var
=
local_scopes_
[
out_scope_idx
]
->
FindVar
(
out_handle
->
name_
);
PADDLE_ENFORCE_EQ
(
out_place
.
which
(),
pre_place
.
which
(),
"The place of input and output should be the same."
);
if
(
pre_in_var
->
IsType
<
framework
::
SelectedRows
>
())
{
auto
&
pre_in
=
pre_in_var
->
Get
<
framework
::
SelectedRows
>
();
auto
out
=
out_var
->
GetMutable
<
framework
::
SelectedRows
>
();
out
->
set_height
(
pre_in
.
height
());
out
->
set_rows
(
out_rows
);
size_t
rows
=
out_rows
.
size
();
DDim
out_dim
=
pre_in
.
GetCompleteDims
();
out_dim
[
0
]
=
static_cast
<
int64_t
>
(
rows
);
out
->
mutable_value
()
->
Resize
(
out_dim
);
out
->
mutable_value
()
->
mutable_data
(
out_place
,
pre_in
.
value
().
type
());
auto
out_tensor
=
out
->
mutable_value
();
// copy
int
s
=
0
,
e
=
0
;
for
(
size_t
j
=
0
;
j
<
in_tensors
.
size
();
++
j
)
{
e
+=
in_tensors
[
j
]
->
dims
()[
0
];
auto
sub_out
=
out_tensor
->
Slice
(
s
,
e
);
paddle
::
framework
::
TensorCopy
(
*
(
in_tensors
[
j
]),
out_place
,
*
(
dev_ctxes_
[
in_places
[
j
]]),
&
sub_out
);
s
=
e
;
}
}
else
if
(
pre_in_var
->
IsType
<
framework
::
LoDTensor
>
())
{
PADDLE_THROW
(
"Currently, Var only can be SelectedRows."
);
}
else
{
PADDLE_THROW
(
"Var should be SelectedRows."
);
auto
&
out_place
=
out_var_handles
[
0
]
->
place_
;
auto
out_scope_idx
=
out_var_handles
[
0
]
->
scope_idx_
;
auto
out_var
=
local_scopes_
[
out_scope_idx
]
->
FindVar
(
out_var_handles
[
0
]
->
name_
);
auto
out
=
out_var
->
GetMutable
<
framework
::
SelectedRows
>
();
out
->
set_height
(
pre_in
.
height
());
out
->
set_rows
(
out_rows
);
size_t
rows
=
out_rows
.
size
();
DDim
out_dim
=
pre_in
.
GetCompleteDims
();
out_dim
[
0
]
=
static_cast
<
int64_t
>
(
rows
);
out
->
mutable_value
()
->
Resize
(
out_dim
);
out
->
mutable_value
()
->
mutable_data
(
out_place
,
pre_in
.
value
().
type
());
Tensor
*
out_tensor
=
out
->
mutable_value
();
// copy
int
s
=
0
,
e
=
0
;
for
(
size_t
j
=
0
;
j
<
in_tensors
.
size
();
++
j
)
{
e
+=
in_tensors
[
j
].
dims
()[
0
];
auto
sub_out
=
out_tensor
->
Slice
(
s
,
e
);
paddle
::
framework
::
TensorCopy
(
in_tensors
[
j
],
out_place
,
*
(
dev_ctxes_
[
in_places
[
j
]]),
&
sub_out
);
s
=
e
;
}
}
...
...
paddle/fluid/framework/details/gather_op_handle_test.cc
浏览文件 @
02842cfc
...
...
@@ -26,14 +26,26 @@ namespace p = paddle::platform;
// test data amount
const
f
::
DDim
kDims
=
{
20
,
20
};
class
GatherTester
:
public
::
testing
::
Test
{
public:
struct
TestGatherOpHandle
{
std
::
vector
<
std
::
unique_ptr
<
p
::
DeviceContext
>>
ctxs_
;
std
::
vector
<
Scope
*>
local_scopes_
;
Scope
g_scope_
;
std
::
unique_ptr
<
OpHandleBase
>
op_handle_
;
std
::
vector
<
std
::
unique_ptr
<
VarHandleBase
>>
vars_
;
std
::
vector
<
p
::
Place
>
gpu_list_
;
void
WaitAll
()
{
for
(
size_t
j
=
0
;
j
<
ctxs_
.
size
();
++
j
)
{
ctxs_
[
j
]
->
Wait
();
}
}
void
InitCtxOnGpu
(
bool
use_gpu
)
{
if
(
use_gpu
)
{
#ifdef PADDLE_WITH_CUDA
int
count
=
p
::
GetCUDADeviceCount
();
if
(
count
<=
1
)
{
LOG
(
WARNING
)
<<
"Cannot test multi-gpu
Gather
, because the CUDA "
LOG
(
WARNING
)
<<
"Cannot test multi-gpu
Broadcast
, because the CUDA "
"device count is "
<<
count
;
exit
(
0
);
...
...
@@ -56,57 +68,51 @@ class GatherTester : public ::testing::Test {
}
}
void
InitGatherOp
(
in
t
input_scope_idx
)
{
void
InitGatherOp
(
size_
t
input_scope_idx
)
{
for
(
size_t
j
=
0
;
j
<
gpu_list_
.
size
();
++
j
)
{
local_scope
_
.
push_back
(
&
g_scope_
.
NewScope
(
));
local_scope
_
[
j
]
->
Var
(
"inp
ut"
);
local_scope
s_
.
push_back
(
&
(
g_scope_
.
NewScope
()
));
local_scope
s_
[
j
]
->
Var
(
"o
ut"
);
}
local_scope_
[
input_scope_idx
]
->
Var
(
"out"
);
gather_op_handle_
=
new
f
::
details
::
GatherOpHandle
(
local_scope_
,
gpu_list_
);
f
::
details
::
VarHandle
*
out_var_handle
=
new
f
::
details
::
VarHandle
();
out_var_handle
->
place_
=
gpu_list_
[
input_scope_idx
];
out_var_handle
->
name_
=
"out"
;
out_var_handle
->
version_
=
2
;
out_var_handle
->
scope_idx_
=
input_scope_idx
;
out_var_handle
->
generated_op_
=
gather_op_handle_
;
gather_op_handle_
->
AddOutput
(
out_var_handle
);
local_scopes_
[
input_scope_idx
]
->
Var
(
"input"
);
op_handle_
.
reset
(
new
GatherOpHandle
(
local_scopes_
,
gpu_list_
));
// add input
for
(
size_t
j
=
0
;
j
<
gpu_list_
.
size
();
++
j
)
{
gather_op_handle_
->
dev_ctxes_
[
gpu_list_
[
j
]]
=
ctxs_
[
j
];
f
::
details
::
VarHandle
*
in_var_handle
=
new
f
::
details
::
VarHandle
();
op_handle_
->
dev_ctxes_
[
gpu_list_
[
j
]]
=
ctxs_
[
j
].
get
();
vars_
.
emplace_back
(
new
VarHandle
());
VarHandle
*
in_var_handle
=
static_cast
<
VarHandle
*>
(
vars_
.
back
().
get
());
in_var_handle
->
place_
=
gpu_list_
[
j
];
in_var_handle
->
name_
=
"input"
;
in_var_handle
->
version_
=
1
;
in_var_handle
->
scope_idx_
=
j
;
in_var_handle
->
generated_op_
=
nullptr
;
gather_op_handle_
->
AddInput
(
in_var_handle
);
}
}
void
GatherOpDestroy
()
{
for
(
auto
in
:
gather_op_handle_
->
inputs_
)
{
delete
in
;
}
for
(
auto
out
:
gather_op_handle_
->
outputs_
)
{
delete
out
;
}
delete
gather_op_handle_
;
for
(
size_t
j
=
0
;
j
<
ctxs_
.
size
();
++
j
)
{
delete
ctxs_
[
j
];
op_handle_
->
AddInput
(
in_var_handle
);
}
}
void
WaitAll
()
{
for
(
size_t
j
=
0
;
j
<
ctxs_
.
size
();
++
j
)
{
ctxs_
[
j
]
->
Wait
();
}
}
// add dummy var
vars_
.
emplace_back
(
new
DummyVarHandle
());
DummyVarHandle
*
in_dummy_var_handle
=
static_cast
<
DummyVarHandle
*>
(
vars_
.
back
().
get
());
in_dummy_var_handle
->
generated_op_
=
nullptr
;
op_handle_
->
AddInput
(
in_dummy_var_handle
);
// add output
vars_
.
emplace_back
(
new
VarHandle
());
VarHandle
*
out_var_handle
=
static_cast
<
VarHandle
*>
(
vars_
.
back
().
get
());
out_var_handle
->
place_
=
gpu_list_
[
input_scope_idx
];
out_var_handle
->
name_
=
"out"
;
out_var_handle
->
version_
=
2
;
out_var_handle
->
scope_idx_
=
input_scope_idx
;
op_handle_
->
AddOutput
(
out_var_handle
);
void
TestGatherSelectedRows
()
{
int
output_scope_idx
=
0
;
InitGatherOp
(
output_scope_idx
);
// add dummy var
vars_
.
emplace_back
(
new
DummyVarHandle
());
DummyVarHandle
*
dummy_var_handle
=
static_cast
<
DummyVarHandle
*>
(
vars_
.
back
().
get
());
op_handle_
->
AddOutput
(
dummy_var_handle
);
}
void
TestGatherSelectedRows
(
size_t
output_scope_idx
)
{
int
height
=
kDims
[
0
]
*
2
;
std
::
vector
<
int64_t
>
rows
{
0
,
1
,
2
,
3
,
3
,
0
,
14
,
7
,
3
,
1
,
2
,
4
,
6
,
3
,
1
,
1
,
1
,
1
,
3
,
7
};
...
...
@@ -117,7 +123,7 @@ class GatherTester : public ::testing::Test {
for
(
size_t
input_scope_idx
=
0
;
input_scope_idx
<
gpu_list_
.
size
();
++
input_scope_idx
)
{
auto
in_var
=
local_scope_
[
input_scope_idx
]
->
Var
(
"input"
);
auto
in_var
=
local_scope
s
_
[
input_scope_idx
]
->
Var
(
"input"
);
auto
in_selected_rows
=
in_var
->
GetMutable
<
f
::
SelectedRows
>
();
auto
value
=
in_selected_rows
->
mutable_value
();
value
->
mutable_data
<
float
>
(
kDims
,
gpu_list_
[
input_scope_idx
]);
...
...
@@ -130,13 +136,21 @@ class GatherTester : public ::testing::Test {
value
->
Resize
(
kDims
);
}
gather_op_handle_
->
Run
(
false
);
auto
out_var
=
local_scopes_
[
output_scope_idx
]
->
Var
(
"out"
);
auto
out_selected_rows
=
out_var
->
GetMutable
<
f
::
SelectedRows
>
();
auto
in_var
=
local_scopes_
[
output_scope_idx
]
->
Var
(
"input"
);
auto
in_selected_rows
=
in_var
->
GetMutable
<
f
::
SelectedRows
>
();
out_selected_rows
->
mutable_value
()
->
ShareDataWith
(
in_selected_rows
->
value
());
op_handle_
->
Run
(
false
);
WaitAll
();
p
::
CPUPlace
cpu_place
;
auto
out_var
=
local_scope_
[
output_scope_idx
]
->
Var
(
"out"
);
auto
&
out_select_rows
=
out_var
->
Get
<
f
::
SelectedRows
>
();
auto
rt
=
out_select_rows
.
value
();
...
...
@@ -152,28 +166,25 @@ class GatherTester : public ::testing::Test {
for
(
int64_t
j
=
0
;
j
<
f
::
product
(
kDims
);
++
j
)
{
ASSERT_NEAR
(
ct
[
j
],
send_vector
[
j
%
send_vector
.
size
()],
1e-5
);
}
GatherOpDestroy
();
}
public:
f
::
Scope
g_scope_
;
std
::
vector
<
p
::
DeviceContext
*>
ctxs_
;
std
::
vector
<
f
::
Scope
*>
local_scope_
;
std
::
vector
<
p
::
Place
>
gpu_list_
;
f
::
details
::
GatherOpHandle
*
gather_op_handle_
;
};
TEST_F
(
GatherTester
,
TestCPUGatherTestSelectedRows
)
{
InitCtxOnGpu
(
false
);
TestGatherSelectedRows
();
TEST
(
GatherTester
,
TestCPUGatherTestSelectedRows
)
{
TestGatherOpHandle
test_op
;
size_t
input_scope_idx
=
0
;
test_op
.
InitCtxOnGpu
(
false
);
test_op
.
InitGatherOp
(
input_scope_idx
);
test_op
.
TestGatherSelectedRows
(
input_scope_idx
);
}
#ifdef PADDLE_WITH_CUDA
TEST_F
(
GatherTester
,
TestGPUGatherTestSelectedRows
)
{
InitCtxOnGpu
(
true
);
TestGatherSelectedRows
();
TEST
(
GatherTester
,
TestGPUGatherTestSelectedRows
)
{
TestGatherOpHandle
test_op
;
size_t
input_scope_idx
=
0
;
test_op
.
InitCtxOnGpu
(
false
);
test_op
.
InitGatherOp
(
input_scope_idx
);
test_op
.
TestGatherSelectedRows
(
input_scope_idx
);
}
#endif
}
// namespace details
...
...
paddle/fluid/framework/details/op_handle_base.cc
浏览文件 @
02842cfc
...
...
@@ -17,21 +17,6 @@
namespace
paddle
{
namespace
framework
{
namespace
details
{
// GetTensorFromVar is used in broadcast_op handle and gather_op handle, so it
// should be placed in a commonplace. I don't find an appropriate place, so I
// temporarily place it in op_handle_base.
Tensor
*
GetTensorFromVar
(
Variable
*
in_var
)
{
if
(
in_var
->
IsType
<
LoDTensor
>
())
{
return
in_var
->
GetMutable
<
LoDTensor
>
();
}
else
if
(
in_var
->
IsType
<
SelectedRows
>
())
{
return
in_var
->
GetMutable
<
SelectedRows
>
()
->
mutable_value
();
}
else
{
PADDLE_THROW
(
"Var should be LoDTensor or SelectedRows"
);
}
return
nullptr
;
}
std
::
string
OpHandleBase
::
DebugString
()
const
{
std
::
stringstream
ss
;
ss
<<
"("
;
...
...
paddle/fluid/framework/details/op_handle_base.h
浏览文件 @
02842cfc
...
...
@@ -17,9 +17,6 @@
#include <vector>
#include "paddle/fluid/framework/details/var_handle.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/selected_rows.h"
#include "paddle/fluid/framework/variable.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/macros.h"
...
...
@@ -27,11 +24,6 @@ namespace paddle {
namespace
framework
{
namespace
details
{
// GetTensorFromVar is used in broadcast_op handle and gather_op handle, so it
// should be placed in a commonplace. I don't find an appropriate place, so I
// temporarily place it in op_handle.
Tensor
*
GetTensorFromVar
(
Variable
*
in_var
);
constexpr
char
kLocalExecScopeName
[]
=
"@LCOAL_SCOPE@"
;
class
OpHandleBase
{
...
...
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