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b43d87c9
编写于
4月 13, 2018
作者:
C
chengduo
提交者:
GitHub
4月 13, 2018
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差异文件
Merge pull request #9825 from chengduoZH/feature/add_gather_and_BCast_op_handle
feature/Add Broadcast and Gather op handle
上级
e4cfe477
384d6ee8
变更
9
隐藏空白更改
内联
并排
Showing
9 changed file
with
769 addition
and
4 deletion
+769
-4
paddle/fluid/framework/details/CMakeLists.txt
paddle/fluid/framework/details/CMakeLists.txt
+9
-1
paddle/fluid/framework/details/broadcast_op_handle.cc
paddle/fluid/framework/details/broadcast_op_handle.cc
+111
-0
paddle/fluid/framework/details/broadcast_op_handle.h
paddle/fluid/framework/details/broadcast_op_handle.h
+48
-0
paddle/fluid/framework/details/broadcast_op_handle_test.cc
paddle/fluid/framework/details/broadcast_op_handle_test.cc
+231
-0
paddle/fluid/framework/details/gather_op_handle.cc
paddle/fluid/framework/details/gather_op_handle.cc
+126
-0
paddle/fluid/framework/details/gather_op_handle.h
paddle/fluid/framework/details/gather_op_handle.h
+48
-0
paddle/fluid/framework/details/gather_op_handle_test.cc
paddle/fluid/framework/details/gather_op_handle_test.cc
+192
-0
paddle/fluid/framework/details/var_handle.h
paddle/fluid/framework/details/var_handle.h
+1
-0
paddle/fluid/framework/tensor_util.cc
paddle/fluid/framework/tensor_util.cc
+3
-3
未找到文件。
paddle/fluid/framework/details/CMakeLists.txt
浏览文件 @
b43d87c9
cc_library
(
var_handle SRCS var_handle.cc DEPS place
)
cc_library
(
var_handle SRCS var_handle.cc DEPS place
)
cc_library
(
op_handle_base SRCS op_handle_base.cc DEPS var_handle device_context
)
cc_library
(
op_handle_base SRCS op_handle_base.cc DEPS var_handle device_context
lod_tensor
)
cc_library
(
scale_loss_grad_op_handle SRCS scale_loss_grad_op_handle.cc DEPS op_handle_base scope lod_tensor ddim memory
)
cc_library
(
scale_loss_grad_op_handle SRCS scale_loss_grad_op_handle.cc DEPS op_handle_base scope lod_tensor ddim memory
)
cc_library
(
fetch_op_handle SRCS fetch_op_handle.cc DEPS op_handle_base scope lod_tensor ddim memory
)
cc_library
(
fetch_op_handle SRCS fetch_op_handle.cc DEPS op_handle_base scope lod_tensor ddim memory
)
nv_library
(
nccl_all_reduce_op_handle SRCS nccl_all_reduce_op_handle.cc DEPS op_handle_base scope lod_tensor ddim memory
nv_library
(
nccl_all_reduce_op_handle SRCS nccl_all_reduce_op_handle.cc DEPS op_handle_base scope lod_tensor ddim memory
...
@@ -20,3 +20,11 @@ cc_library(multi_devices_graph_builder SRCS multi_devices_graph_builder.cc DEPS
...
@@ -20,3 +20,11 @@ cc_library(multi_devices_graph_builder SRCS multi_devices_graph_builder.cc DEPS
cc_library
(
ssa_graph_executor SRCS ssa_graph_executor.cc DEPS ssa_graph framework_proto
)
cc_library
(
ssa_graph_executor SRCS ssa_graph_executor.cc DEPS ssa_graph framework_proto
)
cc_library
(
threaded_ssa_graph_executor SRCS threaded_ssa_graph_executor.cc DEPS fetch_op_handle ssa_graph_executor scope
cc_library
(
threaded_ssa_graph_executor SRCS threaded_ssa_graph_executor.cc DEPS fetch_op_handle ssa_graph_executor scope
simple_threadpool device_context
)
simple_threadpool device_context
)
cc_library
(
broadcast_op_handle SRCS broadcast_op_handle.cc DEPS op_handle_base scope ddim memory
)
cc_library
(
gather_op_handle SRCS gather_op_handle.cc DEPS op_handle_base scope ddim memory
)
cc_test
(
broadcast_op_test SRCS broadcast_op_handle_test.cc DEPS var_handle op_handle_base scope ddim memory
device_context broadcast_op_handle
)
cc_test
(
gather_op_test SRCS gather_op_handle_test.cc DEPS var_handle op_handle_base scope ddim memory
device_context gather_op_handle
)
paddle/fluid/framework/details/broadcast_op_handle.cc
0 → 100644
浏览文件 @
b43d87c9
// 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/framework/details/broadcast_op_handle.h"
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
()
{
// 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
(
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_place
=
in_var_handle
[
0
]
->
place_
;
if
(
in_var_handle
[
0
]
->
generated_op_
)
{
for
(
auto
*
out
:
out_var_handles
)
{
auto
&
out_p
=
out
->
place_
;
in_var_handle
[
0
]
->
generated_op_
->
Wait
(
dev_ctxes_
[
out_p
]);
}
}
//
auto
in_scope_idx
=
in_var_handle
[
0
]
->
scope_idx_
;
auto
in_var
=
local_scopes_
.
at
(
in_scope_idx
)
->
FindVar
(
in_var_handle
[
0
]
->
name_
);
Tensor
*
in_tensor
=
GetTensorFromVar
(
in_var
);
for
(
auto
*
out
:
out_var_handles
)
{
auto
&
out_p
=
out
->
place_
;
auto
out_var
=
local_scopes_
.
at
(
out
->
scope_idx_
)
->
FindVar
(
out
->
name_
);
PADDLE_ENFORCE_EQ
(
out_p
.
which
(),
in_place
.
which
(),
"Places must be all on CPU or all on CUDA."
);
if
(
in_var
->
IsType
<
framework
::
SelectedRows
>
())
{
auto
&
in_sr
=
in_var
->
Get
<
framework
::
SelectedRows
>
();
auto
out_sr
=
out_var
->
GetMutable
<
framework
::
SelectedRows
>
();
if
(
&
in_sr
==
out_sr
)
continue
;
out_sr
->
set_height
(
in_sr
.
height
());
out_sr
->
set_rows
(
in_sr
.
rows
());
out_sr
->
mutable_value
()
->
Resize
(
in_sr
.
value
().
dims
());
out_sr
->
mutable_value
()
->
mutable_data
(
out_p
,
in_sr
.
value
().
type
());
}
else
if
(
in_var
->
IsType
<
framework
::
LoDTensor
>
())
{
auto
in_lod
=
in_var
->
Get
<
framework
::
LoDTensor
>
();
auto
out_lod
=
out_var
->
GetMutable
<
framework
::
LoDTensor
>
();
if
(
&
in_lod
==
out_lod
)
continue
;
out_lod
->
set_lod
(
in_lod
.
lod
());
out_lod
->
Resize
(
in_lod
.
dims
());
out_lod
->
mutable_data
(
out_p
,
in_lod
.
type
());
}
else
{
PADDLE_THROW
(
"Var should be LoDTensor or SelectedRows."
);
}
Tensor
*
out_tensor
=
GetTensorFromVar
(
out_var
);
paddle
::
framework
::
TensorCopy
(
*
in_tensor
,
out_p
,
*
(
dev_ctxes_
[
in_place
]),
out_tensor
);
}
}
std
::
string
BroadcastOpHandle
::
Name
()
const
{
return
"broadcast"
;
}
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/details/broadcast_op_handle.h
0 → 100644
浏览文件 @
b43d87c9
// 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.
#pragma once
#include <map>
#include <string>
#include <vector>
#include "paddle/fluid/framework/details/op_handle_base.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/framework/selected_rows.h"
#include "paddle/fluid/platform/device_context.h"
namespace
paddle
{
namespace
framework
{
namespace
details
{
struct
BroadcastOpHandle
:
public
OpHandleBase
{
const
std
::
vector
<
Scope
*>
&
local_scopes_
;
const
std
::
vector
<
platform
::
Place
>
&
places_
;
BroadcastOpHandle
(
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
std
::
vector
<
platform
::
Place
>
&
places
);
std
::
string
Name
()
const
override
;
bool
IsMultiDeviceTransfer
()
override
{
return
false
;
};
protected:
void
RunImpl
()
override
;
};
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/details/broadcast_op_handle_test.cc
0 → 100644
浏览文件 @
b43d87c9
// 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/framework/details/broadcast_op_handle.h"
#include "gtest/gtest.h"
#include "paddle/fluid/platform/device_context.h"
namespace
paddle
{
namespace
framework
{
namespace
details
{
namespace
f
=
paddle
::
framework
;
namespace
p
=
paddle
::
platform
;
// test data amount
const
f
::
DDim
kDims
=
{
20
,
20
};
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
int
count
=
p
::
GetCUDADeviceCount
();
if
(
count
<=
1
)
{
LOG
(
WARNING
)
<<
"Cannot test multi-gpu Broadcast, because the CUDA "
"device count is "
<<
count
;
exit
(
0
);
}
for
(
int
i
=
0
;
i
<
count
;
++
i
)
{
auto
p
=
p
::
CUDAPlace
(
i
);
gpu_list_
.
push_back
(
p
);
ctxs_
.
emplace_back
(
new
p
::
CUDADeviceContext
(
p
));
}
#else
PADDLE_THROW
(
"CUDA is not support."
);
#endif
}
else
{
int
count
=
8
;
for
(
int
i
=
0
;
i
<
count
;
++
i
)
{
auto
p
=
p
::
CPUPlace
();
gpu_list_
.
push_back
(
p
);
ctxs_
.
emplace_back
(
new
p
::
CPUDeviceContext
(
p
));
}
}
}
void
InitBroadcastOp
(
size_t
input_scope_idx
)
{
for
(
size_t
j
=
0
;
j
<
gpu_list_
.
size
();
++
j
)
{
local_scopes_
.
push_back
(
&
(
g_scope_
.
NewScope
()));
local_scopes_
[
j
]
->
Var
(
"out"
);
}
local_scopes_
[
input_scope_idx
]
->
Var
(
"input"
);
op_handle_
.
reset
(
new
BroadcastOpHandle
(
local_scopes_
,
gpu_list_
));
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
;
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
)
{
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
;
op_handle_
->
AddOutput
(
out_var_handle
);
}
// 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
(
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
(
static_cast
<
size_t
>
(
f
::
product
(
kDims
)));
for
(
size_t
k
=
0
;
k
<
send_vector
.
size
();
++
k
)
{
send_vector
[
k
]
=
k
;
}
f
::
LoD
lod
{{
0
,
10
,
20
}};
paddle
::
framework
::
TensorFromVector
<
float
>
(
send_vector
,
*
(
ctxs_
[
input_scope_idx
]),
in_lod_tensor
);
in_lod_tensor
->
set_lod
(
lod
);
op_handle_
->
Run
(
false
);
WaitAll
();
p
::
CPUPlace
cpu_place
;
for
(
size_t
j
=
0
;
j
<
gpu_list_
.
size
();
++
j
)
{
auto
out_var
=
local_scopes_
[
j
]
->
Var
(
"out"
);
auto
out_tensor
=
out_var
->
Get
<
f
::
LoDTensor
>
();
PADDLE_ENFORCE_EQ
(
out_tensor
.
lod
(),
lod
,
"lod is not equal."
);
f
::
Tensor
result_tensor
;
f
::
TensorCopy
(
out_tensor
,
cpu_place
,
*
(
ctxs_
[
j
]),
&
result_tensor
);
float
*
ct
=
result_tensor
.
mutable_data
<
float
>
(
cpu_place
);
for
(
int64_t
i
=
0
;
i
<
f
::
product
(
kDims
);
++
i
)
{
ASSERT_NEAR
(
ct
[
i
],
send_vector
[
i
],
1e-5
);
}
}
}
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
=
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
(
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
);
op_handle_
->
Run
(
false
);
WaitAll
();
p
::
CPUPlace
cpu_place
;
for
(
size_t
j
=
0
;
j
<
gpu_list_
.
size
();
++
j
)
{
auto
out_var
=
local_scopes_
[
j
]
->
Var
(
"out"
);
auto
&
out_select_rows
=
out_var
->
Get
<
f
::
SelectedRows
>
();
auto
rt
=
out_select_rows
.
value
();
PADDLE_ENFORCE_EQ
(
out_select_rows
.
height
(),
height
,
"height is not equal."
);
for
(
size_t
k
=
0
;
k
<
out_select_rows
.
rows
().
size
();
++
k
)
{
PADDLE_ENFORCE_EQ
(
out_select_rows
.
rows
()[
k
],
rows
[
k
]);
}
f
::
Tensor
result_tensor
;
f
::
TensorCopy
(
rt
,
cpu_place
,
*
(
ctxs_
[
j
]),
&
result_tensor
);
float
*
ct
=
result_tensor
.
data
<
float
>
();
for
(
int64_t
i
=
0
;
i
<
f
::
product
(
kDims
);
++
i
)
{
ASSERT_NEAR
(
ct
[
i
],
send_vector
[
i
],
1e-5
);
}
}
}
};
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
(
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
(
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
(
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
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/details/gather_op_handle.cc
0 → 100644
浏览文件 @
b43d87c9
// 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/framework/details/gather_op_handle.h"
namespace
paddle
{
namespace
framework
{
namespace
details
{
GatherOpHandle
::
GatherOpHandle
(
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
std
::
vector
<
platform
::
Place
>
&
places
)
:
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
(
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
*>
(
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."
);
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
:
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
<
platform
::
Place
>
in_places
;
auto
&
pre_in
=
pre_in_var
->
Get
<
framework
::
SelectedRows
>
();
// gather the inputs
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
);
PADDLE_ENFORCE_EQ
(
in_p
.
which
(),
pre_place
.
which
(),
"Places must be all on CPU or all on CUDA."
);
auto
in_var
=
local_scopes_
.
at
(
in_handle
->
scope_idx_
)
->
FindVar
(
in_handle
->
name_
);
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."
);
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_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
;
}
}
std
::
string
GatherOpHandle
::
Name
()
const
{
return
"gather"
;
}
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/details/gather_op_handle.h
0 → 100644
浏览文件 @
b43d87c9
// 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.
#pragma once
#include <map>
#include <string>
#include <vector>
#include "paddle/fluid/framework/details/op_handle_base.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/framework/selected_rows.h"
#include "paddle/fluid/platform/device_context.h"
namespace
paddle
{
namespace
framework
{
namespace
details
{
struct
GatherOpHandle
:
public
OpHandleBase
{
const
std
::
vector
<
Scope
*>
&
local_scopes_
;
const
std
::
vector
<
platform
::
Place
>
&
places_
;
GatherOpHandle
(
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
std
::
vector
<
platform
::
Place
>
&
places
);
std
::
string
Name
()
const
override
;
bool
IsMultiDeviceTransfer
()
override
{
return
false
;
};
protected:
void
RunImpl
()
override
;
};
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/details/gather_op_handle_test.cc
0 → 100644
浏览文件 @
b43d87c9
// 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/framework/details/gather_op_handle.h"
#include "gtest/gtest.h"
#include "paddle/fluid/platform/device_context.h"
namespace
paddle
{
namespace
framework
{
namespace
details
{
namespace
f
=
paddle
::
framework
;
namespace
p
=
paddle
::
platform
;
// test data amount
const
f
::
DDim
kDims
=
{
20
,
20
};
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 Broadcast, because the CUDA "
"device count is "
<<
count
;
exit
(
0
);
}
for
(
int
i
=
0
;
i
<
count
;
++
i
)
{
auto
p
=
p
::
CUDAPlace
(
i
);
gpu_list_
.
push_back
(
p
);
ctxs_
.
emplace_back
(
new
p
::
CUDADeviceContext
(
p
));
}
#else
PADDLE_THROW
(
"CUDA is not support."
);
#endif
}
else
{
int
count
=
8
;
for
(
int
i
=
0
;
i
<
count
;
++
i
)
{
auto
p
=
p
::
CPUPlace
();
gpu_list_
.
push_back
(
p
);
ctxs_
.
emplace_back
(
new
p
::
CPUDeviceContext
(
p
));
}
}
}
void
InitGatherOp
(
size_t
input_scope_idx
)
{
for
(
size_t
j
=
0
;
j
<
gpu_list_
.
size
();
++
j
)
{
local_scopes_
.
push_back
(
&
(
g_scope_
.
NewScope
()));
local_scopes_
[
j
]
->
Var
(
"out"
);
}
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
)
{
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
;
op_handle_
->
AddInput
(
in_var_handle
);
}
// 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
);
// 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
};
std
::
vector
<
float
>
send_vector
(
f
::
product
(
kDims
));
for
(
size_t
k
=
0
;
k
<
send_vector
.
size
();
++
k
)
{
send_vector
[
k
]
=
k
;
}
for
(
size_t
input_scope_idx
=
0
;
input_scope_idx
<
gpu_list_
.
size
();
++
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
]);
in_selected_rows
->
set_height
(
height
);
in_selected_rows
->
set_rows
(
rows
);
paddle
::
framework
::
TensorFromVector
<
float
>
(
send_vector
,
*
(
ctxs_
[
input_scope_idx
]),
value
);
value
->
Resize
(
kDims
);
}
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_select_rows
=
out_var
->
Get
<
f
::
SelectedRows
>
();
auto
rt
=
out_select_rows
.
value
();
PADDLE_ENFORCE_EQ
(
out_select_rows
.
height
(),
height
,
"height is not equal."
);
for
(
size_t
k
=
0
;
k
<
out_select_rows
.
rows
().
size
();
++
k
)
{
PADDLE_ENFORCE_EQ
(
out_select_rows
.
rows
()[
k
],
rows
[
k
%
rows
.
size
()]);
}
f
::
Tensor
result_tensor
;
f
::
TensorCopy
(
rt
,
cpu_place
,
*
(
ctxs_
[
output_scope_idx
]),
&
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
%
send_vector
.
size
()],
1e-5
);
}
}
};
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
(
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
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/details/var_handle.h
浏览文件 @
b43d87c9
...
@@ -50,6 +50,7 @@ struct VarHandle : public VarHandleBase {
...
@@ -50,6 +50,7 @@ struct VarHandle : public VarHandleBase {
// version field currently is not used, however, just store the version to
// version field currently is not used, however, just store the version to
// debug easily.
// debug easily.
size_t
version_
;
size_t
version_
;
size_t
scope_idx_
;
std
::
string
name_
;
std
::
string
name_
;
platform
::
Place
place_
;
platform
::
Place
place_
;
};
};
...
...
paddle/fluid/framework/tensor_util.cc
浏览文件 @
b43d87c9
...
@@ -11,8 +11,10 @@
...
@@ -11,8 +11,10 @@
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
See the License for the specific language governing permissions and
limitations under the License. */
limitations under the License. */
#include "paddle/fluid/framework/tensor_util.h"
#include "paddle/fluid/framework/tensor_util.h"
#include <algorithm>
#include <limits>
#include <vector>
namespace
paddle
{
namespace
paddle
{
namespace
framework
{
namespace
framework
{
...
@@ -65,8 +67,6 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place,
...
@@ -65,8 +67,6 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place,
auto
dst_gpu_place
=
boost
::
get
<
platform
::
CUDAPlace
>
(
dst_place
);
auto
dst_gpu_place
=
boost
::
get
<
platform
::
CUDAPlace
>
(
dst_place
);
auto
ctx_place
=
ctx
.
GetPlace
();
auto
ctx_place
=
ctx
.
GetPlace
();
PADDLE_ENFORCE
(
platform
::
is_gpu_place
(
ctx_place
));
PADDLE_ENFORCE
(
platform
::
is_gpu_place
(
ctx_place
));
auto
ctx_gpu_place
=
boost
::
get
<
platform
::
CUDAPlace
>
(
ctx_place
);
PADDLE_ENFORCE_EQ
(
src_gpu_place
,
ctx_gpu_place
);
memory
::
Copy
(
memory
::
Copy
(
dst_gpu_place
,
dst_ptr
,
src_gpu_place
,
src_ptr
,
size
,
dst_gpu_place
,
dst_ptr
,
src_gpu_place
,
src_ptr
,
size
,
reinterpret_cast
<
const
platform
::
CUDADeviceContext
&>
(
ctx
).
stream
());
reinterpret_cast
<
const
platform
::
CUDADeviceContext
&>
(
ctx
).
stream
());
...
...
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