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体验新版 GitCode,发现更多精彩内容 >>
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7722baa8
编写于
5月 04, 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
follow comments and clean code
上级
c8911895
变更
8
隐藏空白更改
内联
并排
Showing
8 changed file
with
160 addition
and
107 deletion
+160
-107
paddle/fluid/framework/details/broadcast_op_handle.cc
paddle/fluid/framework/details/broadcast_op_handle.cc
+46
-41
paddle/fluid/framework/details/gather_op_handle.cc
paddle/fluid/framework/details/gather_op_handle.cc
+14
-20
paddle/fluid/framework/details/multi_devices_graph_builder.cc
...le/fluid/framework/details/multi_devices_graph_builder.cc
+19
-16
paddle/fluid/framework/details/reduce_op_handle.cc
paddle/fluid/framework/details/reduce_op_handle.cc
+22
-19
paddle/fluid/framework/details/ssa_graph_builder.cc
paddle/fluid/framework/details/ssa_graph_builder.cc
+0
-11
paddle/fluid/framework/details/var_handle.h
paddle/fluid/framework/details/var_handle.h
+10
-0
paddle/fluid/framework/details/variable_visitor.cc
paddle/fluid/framework/details/variable_visitor.cc
+46
-0
paddle/fluid/framework/details/variable_visitor.h
paddle/fluid/framework/details/variable_visitor.h
+3
-0
未找到文件。
paddle/fluid/framework/details/broadcast_op_handle.cc
浏览文件 @
7722baa8
...
...
@@ -22,9 +22,9 @@ namespace details {
void
BroadcastOpHandle
::
RunImpl
()
{
if
(
places_
.
size
()
==
1
)
return
;
// the input and output may have dummy var.
VarHandle
*
in_var_handle
;
// The input and output may have dummy vars.
VarHandle
*
in_var_handle
;
{
auto
in_var_handles
=
DynamicCast
<
VarHandle
>
(
inputs_
);
PADDLE_ENFORCE_EQ
(
in_var_handles
.
size
(),
1
,
...
...
@@ -53,23 +53,39 @@ void BroadcastOpHandle::RunImpl() {
Tensor
&
in_tensor
=
VariableVisitor
::
GetMutableTensor
(
in_var
);
// NOTE(zcd): the Place of input can be get from in_tensor and in_var_handle ,
// maybe they are different, because the Place that getting from in_tensor is
// determined at runtime, the other is determined at building SSA graph stage.
// If they are different, DataTransform should be applied. Currently, it has
// not been done yet.
for
(
auto
*
out_var_handle
:
out_var_handles
)
{
if
(
*
out_var_handle
==
*
in_var_handle
)
{
continue
;
}
auto
&
out_p
=
out_var_handle
->
place_
;
auto
*
out_var
=
var_scopes
.
at
(
out_var_handle
->
scope_idx_
)
->
FindVar
(
out_var_handle
->
name_
);
PADDLE_ENFORCE_NOT_NULL
(
out_var
);
PADDLE_ENFORCE_EQ
(
out_p
.
which
(),
in_tensor
.
place
().
which
(),
"Currently, Places of input and output must be all on CPU "
"or all on GPU."
);
VariableVisitor
::
ShareDimsAndLoD
(
*
in_var
,
out_var
);
VariableVisitor
::
GetMutableTensor
(
out_var
).
mutable_data
(
out_p
,
in_tensor
.
type
());
}
if
(
platform
::
is_cpu_place
(
in_tensor
.
place
()))
{
for
(
auto
*
out
:
out_var_handles
)
{
if
(
*
out
==
*
in_var_handle
)
{
for
(
auto
*
out
_var_handle
:
out_var_handles
)
{
if
(
*
out
_var_handle
==
*
in_var_handle
)
{
continue
;
}
auto
&
out_p
=
out
->
place_
;
auto
*
out_var
=
var_scopes
.
at
(
out
->
scope_idx_
)
->
FindVar
(
out
->
name_
);
PADDLE_ENFORCE_NOT_NULL
(
out_var
);
PADDLE_ENFORCE_EQ
(
out_p
.
which
(),
in_tensor
.
place
().
which
(),
"Places must be all on CPU or all on CUDA."
);
VariableVisitor
::
ShareDimsAndLoD
(
*
in_var
,
out_var
);
VariableVisitor
::
GetMutableTensor
(
out_var
).
mutable_data
(
out_p
,
in_tensor
.
type
());
auto
&
out_p
=
out_var_handle
->
place_
;
auto
dev_ctx
=
dev_ctxes_
.
at
(
out_p
);
auto
*
out_var
=
var_scopes
.
at
(
out_var_handle
->
scope_idx_
)
->
FindVar
(
out_var_handle
->
name_
);
RunAndRecordEvent
(
out_p
,
[
in_tensor
,
out_var
,
dev_ctx
,
out_p
]
{
paddle
::
framework
::
TensorCopy
(
in_tensor
,
out_p
,
*
dev_ctx
,
...
...
@@ -78,35 +94,21 @@ void BroadcastOpHandle::RunImpl() {
}
}
else
{
#ifdef PADDLE_WITH_CUDA
PADDLE_ENFORCE
(
platform
::
is_gpu_place
(
in_tensor
.
place
()));
VarHandle
*
out_handle
;
int
root
=
boost
::
get
<
platform
::
CUDAPlace
>
(
in_tensor
.
place
()).
device
;
VarHandle
*
out_handle
=
nullptr
;
int
root_id
=
boost
::
get
<
platform
::
CUDAPlace
>
(
in_tensor
.
place
()).
device
;
std
::
vector
<
std
::
function
<
void
()
>>
broadcast_calls
;
for
(
size_t
j
=
0
;
j
<
out_var_handles
.
size
();
++
j
)
{
VarHandle
*
out_var_handle
=
out_var_handles
[
j
];
for
(
auto
out_var_handle
:
out_var_handles
)
{
Variable
*
out_var
=
var_scopes
.
at
(
out_var_handle
->
scope_idx_
)
->
FindVar
(
out_var_handle
->
name_
);
if
(
*
out_var_handle
!=
*
in_var_handle
)
{
PADDLE_ENFORCE_NOT_NULL
(
out_var
);
PADDLE_ENFORCE_EQ
(
out_var_handle
->
place_
.
which
(),
in_tensor
.
place
().
which
(),
"Places must be all on CPU or all on CUDA."
);
VariableVisitor
::
ShareDimsAndLoD
(
*
in_var
,
out_var
);
VariableVisitor
::
GetMutableTensor
(
out_var
).
mutable_data
(
out_var_handle
->
place_
,
in_tensor
.
type
());
}
int
dst_id
=
boost
::
get
<
platform
::
CUDAPlace
>
(
out_var_handle
->
place_
).
device
;
auto
out_p
=
out_var_handle
->
place_
;
int
dev_id
=
boost
::
get
<
platform
::
CUDAPlace
>
(
out_p
).
device
;
auto
&
nccl_ctx
=
nccl_ctxs_
->
at
(
dev_id
);
auto
stream
=
nccl_ctx
.
stream
();
auto
comm
=
nccl_ctx
.
comm_
;
auto
&
nccl_ctx
=
nccl_ctxs_
->
at
(
dst_id
);
void
*
send_recv_buffer
=
nullptr
;
if
(
root
==
dev
_id
)
{
if
(
root
_id
==
dst
_id
)
{
send_recv_buffer
=
const_cast
<
void
*>
(
in_tensor
.
data
<
void
>
());
out_handle
=
out_var_handle
;
}
else
{
...
...
@@ -116,11 +118,13 @@ void BroadcastOpHandle::RunImpl() {
}
int
type
=
platform
::
ToNCCLDataType
(
in_tensor
.
type
());
broadcast_calls
.
emplace_back
([
=
]
{
PADDLE_ENFORCE
(
platform
::
dynload
::
ncclBcast
(
send_recv_buffer
,
in_tensor
.
numel
(),
static_cast
<
ncclDataType_t
>
(
type
),
root
,
comm
,
stream
));
});
size_t
numel
=
static_cast
<
size_t
>
(
in_tensor
.
numel
());
broadcast_calls
.
emplace_back
(
[
send_recv_buffer
,
numel
,
type
,
root_id
,
&
nccl_ctx
]
{
PADDLE_ENFORCE
(
platform
::
dynload
::
ncclBcast
(
send_recv_buffer
,
numel
,
static_cast
<
ncclDataType_t
>
(
type
),
root_id
,
nccl_ctx
.
comm_
,
nccl_ctx
.
stream
()));
});
}
this
->
RunAndRecordEvent
([
&
]
{
...
...
@@ -130,6 +134,7 @@ void BroadcastOpHandle::RunImpl() {
call
();
}
}
// TODO(zcd): Maybe the unequal operator is not appropriate here.
if
(
*
out_handle
!=
*
in_var_handle
)
{
auto
out_var
=
var_scopes
.
at
(
in_var_handle
->
scope_idx_
)
->
FindVar
(
out_var_handles
[
0
]
->
name_
);
...
...
@@ -140,7 +145,7 @@ void BroadcastOpHandle::RunImpl() {
}
});
#else
PADDLE_THROW
(
"CUDA is not
support
."
);
PADDLE_THROW
(
"CUDA is not
enabled
."
);
#endif
}
}
...
...
paddle/fluid/framework/details/gather_op_handle.cc
浏览文件 @
7722baa8
...
...
@@ -36,7 +36,6 @@ void GatherOpHandle::RunImpl() {
VarHandle
*
out_var_handle
;
{
auto
out_var_handles
=
DynamicCast
<
VarHandle
>
(
outputs_
);
PADDLE_ENFORCE_EQ
(
out_var_handles
.
size
(),
1
,
"The number of output should be one."
);
out_var_handle
=
out_var_handles
.
front
();
...
...
@@ -51,43 +50,39 @@ void GatherOpHandle::RunImpl() {
auto
pre_in_var
=
var_scopes
.
at
(
in_0_handle
->
scope_idx_
)
->
FindVar
(
in_0_handle
->
name_
);
PADDLE_ENFORCE_NOT_NULL
(
pre_in_var
);
PADDLE_ENFORCE
(
pre_in_var
->
IsType
<
framework
::
SelectedRows
>
(),
"Currently, gather_op only can gather SelectedRows."
);
// Wait input done, this Wait is asynchronous operation
WaitInputVarGenerated
(
in_var_handles
);
auto
&
pre_in_value
=
pre_in_var
->
Get
<
framework
::
SelectedRows
>
();
std
::
vector
<
int64_t
>
out_rows
;
std
::
vector
<
Tensor
>
in_tensors
;
auto
&
pre_in_value
=
pre_in_var
->
Get
<
framework
::
SelectedRows
>
();
// gather the inputs
// Gather the inputs
for
(
auto
*
in_handle
:
in_var_handles
)
{
auto
*
in_var
=
var_scopes
.
at
(
in_handle
->
scope_idx_
)
->
FindVar
(
in_handle
->
name_
);
PADDLE_ENFORCE_NOT_NULL
(
in_var
);
VariableVisitor
::
EnforceShapeAndDTypeEQ
(
*
in_var
,
*
pre_in_var
);
auto
&
in_sr_value
=
in_var
->
Get
<
framework
::
SelectedRows
>
();
PADDLE_ENFORCE_EQ
(
in_sr_value
.
place
().
which
(),
pre_in_value
.
place
().
which
(),
"Places must be all on CPU or all on GPU."
);
PADDLE_ENFORCE_EQ
(
in_sr_value
.
value
().
type
(),
pre_in_value
.
value
().
type
(),
"The type of input is not consistent."
);
PADDLE_ENFORCE_EQ
(
in_sr_value
.
height
(),
pre_in_value
.
height
(),
"The height of inputs is not consistent."
);
PADDLE_ENFORCE_EQ
(
in_sr_value
.
GetCompleteDims
(),
pre_in_value
.
GetCompleteDims
(),
"The dims of inputs is not consistent."
);
auto
&
in_sr_rows
=
in_sr_value
.
rows
();
out_rows
.
insert
(
out_rows
.
end
(),
in_sr_rows
.
begin
(),
in_sr_rows
.
end
());
in_tensors
.
emplace_back
(
in_sr_value
.
value
());
}
// write the output
// TODO(zcd): The Place of var_handle is determined at building SSA graph
// stage, while the Place of var is determined at runtime. If they are
// different, DataTransform should be applied. Currently, it has not been done
// yet.
auto
&
out_place
=
out_var_handle
->
place_
;
PADDLE_ENFORCE_EQ
(
out_place
.
which
(),
pre_in_value
.
place
().
which
(),
"Places must be all on CPU or all on GPU."
);
"Currently, Places of input and output must be all on CPU "
"or all on GPU."
);
auto
out_var
=
var_scopes
.
at
(
out_var_handle
->
scope_idx_
)
->
FindVar
(
out_var_handle
->
name_
);
PADDLE_ENFORCE_NOT_NULL
(
out_var
);
...
...
@@ -97,19 +92,18 @@ void GatherOpHandle::RunImpl() {
size_t
rows
=
out_rows
.
size
();
DDim
out_dim
=
pre_in_value
.
GetCompleteDims
();
out_dim
[
0
]
=
static_cast
<
int64_t
>
(
rows
);
out_value
->
mutable_value
()
->
Resize
(
out_dim
);
out_value
->
mutable_value
()
->
mutable_data
(
out_place
,
pre_in_value
.
value
().
type
());
out_value
->
mutable_value
()
->
Resize
(
out_dim
).
mutable_data
(
out_place
,
pre_in_value
.
value
().
type
());
Tensor
*
out_tensor
=
out_value
->
mutable_value
();
// copy
auto
dev_ctx
=
dev_ctxes_
[
out_place
];
RunAndRecordEvent
(
out_place
,
[
in_tensors
,
out_tensor
,
dev_ctx
,
out_place
]
{
RunAndRecordEvent
(
out_place
,
[
in_tensors
,
out_tensor
,
&
dev_ctx
,
out_place
]
{
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_ctx
)
,
paddle
::
framework
::
TensorCopy
(
in_tensors
[
j
],
out_place
,
*
dev_ctx
,
&
sub_out
);
s
=
e
;
}
...
...
paddle/fluid/framework/details/multi_devices_graph_builder.cc
浏览文件 @
7722baa8
...
...
@@ -116,13 +116,12 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
std
::
unordered_map
<
std
::
string
,
std
::
vector
<
std
::
unique_ptr
<
VarHandle
>>>>
(
places_
.
size
());
// size_t cur_device_id = 0;
size_t
update_sparse_gp_device_id
=
0
;
std
::
vector
<
std
::
unordered_set
<
std
::
string
>>
var_name_on_devices
;
std
::
vector
<
std
::
unordered_set
<
std
::
string
>>
bcast_var_name_set
;
size_t
cur_update_sparse_gp_dev_id
=
0
;
std
::
vector
<
std
::
unordered_set
<
std
::
string
>>
sparse_var_name_on_devices
;
std
::
vector
<
std
::
unordered_set
<
std
::
string
>>
bcast_sparse_var_name_set
;
var_name_on_devices
.
resize
(
places_
.
size
());
bcast_var_name_set
.
resize
(
places_
.
size
());
sparse_
var_name_on_devices
.
resize
(
places_
.
size
());
bcast_
sparse_
var_name_set
.
resize
(
places_
.
size
());
// Find "send" op first for split is in front of send.
OpDesc
*
send_op
=
GetSendOpDesc
(
program
);
...
...
@@ -142,13 +141,13 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
}
is_forwarding
=
false
;
}
else
{
int
op_dev_id
=
GetOpDeviceID
(
var_name_on_devices
,
*
op
);
int
op_dev_id
=
GetOpDeviceID
(
sparse_
var_name_on_devices
,
*
op
);
if
(
op_dev_id
==
-
1
)
{
// var on all device
CreateComputationalOps
(
&
result
,
*
op
,
places_
.
size
());
}
else
{
CreateComputationalOp
(
&
result
,
*
op
,
op_dev_id
);
for
(
auto
&
var_name
:
op
->
OutputArgumentNames
())
{
var_name_on_devices
[
op_dev_id
].
emplace
(
var_name
);
sparse_
var_name_on_devices
[
op_dev_id
].
emplace
(
var_name
);
}
}
...
...
@@ -158,10 +157,13 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
for
(
auto
&
og
:
op
->
OutputArgumentNames
())
{
if
(
IsParameterGradientOnce
(
og
,
&
og_has_been_broadcast
))
{
if
(
IsSparseGradient
(
og
))
{
CreateReduceOp
(
&
result
,
update_sparse_gp_device_id
,
og
);
var_name_on_devices
[
update_sparse_gp_device_id
].
emplace
(
og
);
bcast_var_name_set
[
update_sparse_gp_device_id
].
emplace
(
CreateReduceOp
(
&
result
,
cur_update_sparse_gp_dev_id
,
og
);
sparse_var_name_on_devices
[
cur_update_sparse_gp_dev_id
].
emplace
(
og
);
bcast_sparse_var_name_set
[
cur_update_sparse_gp_dev_id
].
emplace
(
og
.
substr
(
0
,
og
.
size
()
-
strlen
(
kGradVarSuffix
)));
cur_update_sparse_gp_dev_id
=
(
cur_update_sparse_gp_dev_id
+
1
)
%
places_
.
size
();
}
else
{
InsertNCCLAllReduceOp
(
&
result
,
og
);
}
...
...
@@ -172,8 +174,8 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
}
// Insert BCast Ops
for
(
size_t
dev_id
=
0
;
dev_id
<
bcast_var_name_set
.
size
();
++
dev_id
)
{
auto
&
to_bcast_set
=
bcast_var_name_set
[
dev_id
];
for
(
size_t
dev_id
=
0
;
dev_id
<
bcast_
sparse_
var_name_set
.
size
();
++
dev_id
)
{
auto
&
to_bcast_set
=
bcast_
sparse_
var_name_set
[
dev_id
];
for
(
auto
&
bcast_name
:
to_bcast_set
)
{
CreateBroadcastOp
(
&
result
,
bcast_name
,
dev_id
);
}
...
...
@@ -206,13 +208,14 @@ bool MultiDevSSAGraphBuilder::IsSparseGradient(const std::string &og) const {
}
int
MultiDevSSAGraphBuilder
::
GetOpDeviceID
(
const
std
::
vector
<
std
::
unordered_set
<
std
::
string
>>
&
var_name_on_devices
,
const
std
::
vector
<
std
::
unordered_set
<
std
::
string
>>
&
sparse_var_name_on_devices
,
const
OpDesc
&
op
)
const
{
int
var_dev_id
=
-
1
;
for
(
auto
&
var_name
:
op
.
InputArgumentNames
())
{
if
(
var_dev_id
!=
-
1
)
break
;
for
(
size_t
i
=
0
;
i
<
var_name_on_devices
.
size
();
++
i
)
{
if
(
var_name_on_devices
[
i
].
count
(
var_name
))
{
for
(
size_t
i
=
0
;
i
<
sparse_
var_name_on_devices
.
size
();
++
i
)
{
if
(
sparse_
var_name_on_devices
[
i
].
count
(
var_name
))
{
var_dev_id
=
static_cast
<
int
>
(
i
);
break
;
}
...
...
paddle/fluid/framework/details/reduce_op_handle.cc
浏览文件 @
7722baa8
...
...
@@ -52,27 +52,30 @@ void ReduceOpHandle::RunImpl() {
// Wait input done, this Wait is asynchronous operation
WaitInputVarGenerated
(
in_var_handles
);
auto
pre_place
=
in_0_handle
->
place_
;
std
::
vector
<
platform
::
Place
>
in_places
;
// used to get dev_ctx
auto
pre_in_tensor
=
VariableVisitor
::
GetMutableTensor
(
pre_in_var
);
for
(
auto
*
in_handle
:
in_var_handles
)
{
in_places
.
emplace_back
(
in_handle
->
place_
);
auto
in_var
=
var_scopes
.
at
(
in_handle
->
scope_idx_
)
->
FindVar
(
in_handle
->
name_
);
PADDLE_ENFORCE_NOT_NULL
(
in_var
);
auto
in_tensor
=
VariableVisitor
::
GetMutableTensor
(
in_var
);
PADDLE_ENFORCE_EQ
(
pre_in_tensor
.
place
().
which
(),
in_tensor
.
place
().
which
(),
"Places must be all on CPU or all on GPU."
);
PADDLE_ENFORCE_EQ
(
in_tensor
.
type
(),
pre_in_tensor
.
type
(),
"The type of input is not consistent."
);
VariableVisitor
::
EnforceShapeAndDTypeEQ
(
*
pre_in_var
,
*
in_var
);
}
auto
out_var
=
var_scopes
.
at
(
out_var_handle
->
scope_idx_
)
->
FindVar
(
out_var_handle
->
name_
);
PADDLE_ENFORCE_NOT_NULL
(
out_var
);
// TODO(zcd): The Place of var_handle is determined at building SSA graph
// stage, while the Place of var is determined at runtime. If they are
// different, DataTransform should be applied. Currently, it has not been done
// yet.
PADDLE_ENFORCE_EQ
(
VariableVisitor
::
GetMutableTensor
(
pre_in_var
).
place
().
which
(),
out_var_handle
->
place_
.
which
(),
"Currently, Places of input and output must be all on CPU or all on "
"GPU."
);
if
(
pre_in_var
->
IsType
<
framework
::
SelectedRows
>
())
{
std
::
vector
<
const
SelectedRows
*>
in_selected_rows
=
GetInputValues
<
SelectedRows
>
(
in_var_handles
,
var_scopes
);
...
...
@@ -96,7 +99,7 @@ void ReduceOpHandle::RunImpl() {
out_var_handle
->
place_
,
pre_in
.
type
());
auto
out_p
=
out_var_handle
->
place_
;
int
root
=
boost
::
get
<
platform
::
CUDAPlace
>
(
out_p
).
device
;
int
root
_id
=
boost
::
get
<
platform
::
CUDAPlace
>
(
out_p
).
device
;
std
::
vector
<
std
::
function
<
void
()
>>
all_reduce_calls
;
for
(
size_t
i
=
0
;
i
<
var_scopes
.
size
();
++
i
)
{
auto
&
p
=
in_places
[
i
];
...
...
@@ -104,23 +107,23 @@ void ReduceOpHandle::RunImpl() {
int
dev_id
=
boost
::
get
<
platform
::
CUDAPlace
>
(
p
).
device
;
auto
&
nccl_ctx
=
nccl_ctxs_
->
at
(
dev_id
);
auto
stream
=
nccl_ctx
.
stream
();
auto
comm
=
nccl_ctx
.
comm_
;
void
*
buffer
=
const_cast
<
void
*>
(
lod_tensor
.
data
<
void
>
());
void
*
recvbuffer
=
nullptr
;
if
(
root
==
dev_id
)
{
if
(
root
_id
==
dev_id
)
{
recvbuffer
=
out_var
->
GetMutable
<
framework
::
LoDTensor
>
()
->
mutable_data
(
out_var_handle
->
place_
);
}
int
type
=
platform
::
ToNCCLDataType
(
lod_tensor
.
type
());
all_reduce_calls
.
emplace_back
([
=
]
{
PADDLE_ENFORCE
(
platform
::
dynload
::
ncclReduce
(
buffer
,
recvbuffer
,
static_cast
<
size_t
>
(
lod_tensor
.
numel
()),
static_cast
<
ncclDataType_t
>
(
type
),
ncclSum
,
root
,
comm
,
stream
));
});
size_t
numel
=
static_cast
<
size_t
>
(
lod_tensor
.
numel
());
all_reduce_calls
.
emplace_back
(
[
buffer
,
recvbuffer
,
type
,
numel
,
root_id
,
&
nccl_ctx
]
{
PADDLE_ENFORCE
(
platform
::
dynload
::
ncclReduce
(
buffer
,
recvbuffer
,
numel
,
static_cast
<
ncclDataType_t
>
(
type
),
ncclSum
,
root_id
,
nccl_ctx
.
comm_
,
nccl_ctx
.
stream
()));
});
}
this
->
RunAndRecordEvent
([
&
]
{
...
...
@@ -130,7 +133,7 @@ void ReduceOpHandle::RunImpl() {
}
});
#else
PADDLE_THROW
(
"CUDA is not
support
."
);
PADDLE_THROW
(
"CUDA is not
enabled
."
);
#endif
}
else
{
PADDLE_THROW
(
"Place should be CPUPlace or CUDAPlace."
);
...
...
paddle/fluid/framework/details/ssa_graph_builder.cc
浏览文件 @
7722baa8
...
...
@@ -47,17 +47,6 @@ void SSAGraphBuilder::PolishGraphToSupportDataHazards(SSAGraph *graph) {
}
}
VarHandle
*
SSAGraphBuilder
::
GetLatestVarHandle
(
SSAGraph
*
graph
,
const
std
::
string
&
each_var_name
,
size_t
place_offset
)
{
auto
&
var_holders
=
graph
->
vars_
[
place_offset
];
auto
&
var_holder
=
var_holders
[
each_var_name
];
if
(
var_holder
.
empty
())
{
return
nullptr
;
}
return
var_holder
.
rbegin
()
->
get
();
}
VarHandle
*
SSAGraphBuilder
::
CreateOrGetLatestVarHandle
(
SSAGraph
*
graph
,
const
std
::
string
&
each_var_name
,
const
platform
::
Place
&
place
,
size_t
place_offset
)
{
...
...
paddle/fluid/framework/details/var_handle.h
浏览文件 @
7722baa8
...
...
@@ -62,6 +62,16 @@ struct VarHandle : public VarHandleBase {
std
::
string
name_
;
platform
::
Place
place_
;
// NOTE(zcd): Strictly speaking, if the two var_handle is equal, the four
// member
// variables(version_, scope_id_, name_, place_) must be equal. But sometimes
// judging whether the two var_handle is equal is actually to determine
// whether
// the two Variables that represented by var_handle is the same. And the same
// Variable may have many different var_handles, the version_ of these
// var_handles
// is different. So I don't take care of version_ temporarily when overloading
// equal.
bool
operator
==
(
const
VarHandle
&
o
)
const
{
return
o
.
generated_op_
==
generated_op_
&&
o
.
name_
==
name_
&&
o
.
scope_idx_
==
scope_idx_
;
...
...
paddle/fluid/framework/details/variable_visitor.cc
浏览文件 @
7722baa8
...
...
@@ -88,6 +88,52 @@ void VariableVisitor::ShareDimsAndLoD(const Variable& src, Variable* trg) {
VisitVariable
(
src
,
&
visitor
);
}
struct
EnforceEqualShapeAndDTypeVisitor
{
const
Variable
*
trg_
;
void
operator
()(
const
LoDTensor
&
src
)
{
auto
&
tensor
=
trg_
->
Get
<
LoDTensor
>
();
PADDLE_ENFORCE_EQ
(
src
.
place
().
which
(),
tensor
.
place
().
which
(),
"The Places of the two Variable must be all on CPU or all on GPU."
);
PADDLE_ENFORCE_EQ
(
src
.
type
(),
tensor
.
type
(),
"The dtype of the two Variable is not equal."
);
PADDLE_ENFORCE_EQ
(
src
.
dims
(),
tensor
.
dims
(),
"The dims of the two Variable is not equal."
);
PADDLE_ENFORCE_EQ
(
src
.
lod
(),
tensor
.
lod
(),
"The lod of the two Variable is not equal."
);
PADDLE_ENFORCE_EQ
(
src
.
layout
(),
tensor
.
layout
(),
"The layout of the two Variable's tensor is not equal."
);
}
void
operator
()(
const
SelectedRows
&
src
)
{
auto
&
selected_rows
=
trg_
->
Get
<
SelectedRows
>
();
PADDLE_ENFORCE_EQ
(
src
.
place
().
which
(),
selected_rows
.
place
().
which
(),
"The Places of the two Variable must be all on CPU or all on GPU."
);
PADDLE_ENFORCE_EQ
(
src
.
value
().
type
(),
selected_rows
.
value
().
type
(),
"The dtype of the two Variable is not equal."
);
PADDLE_ENFORCE_EQ
(
src
.
value
().
layout
(),
selected_rows
.
value
().
layout
(),
"The layout of the two Variable's tensor is not equal."
);
PADDLE_ENFORCE_EQ
(
src
.
height
(),
selected_rows
.
height
(),
"The height of the two Variable is not equal."
);
PADDLE_ENFORCE_EQ
(
src
.
GetCompleteDims
(),
selected_rows
.
GetCompleteDims
(),
"The dims of the two Variable is not equal."
);
}
template
<
typename
T
>
void
operator
()(
const
T
&
)
{
PADDLE_ENFORCE
(
"EnforceShapeAndDTypeEQ is not supported by type %s"
,
typeid
(
T
).
name
());
}
};
void
VariableVisitor
::
EnforceShapeAndDTypeEQ
(
const
Variable
&
var1
,
const
Variable
&
var2
)
{
EnforceEqualShapeAndDTypeVisitor
visitor
{
&
var1
};
VisitVariable
(
var2
,
&
visitor
);
}
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/details/variable_visitor.h
浏览文件 @
7722baa8
...
...
@@ -26,6 +26,9 @@ class VariableVisitor {
static
Tensor
&
GetMutableTensor
(
Variable
*
var
);
static
void
ShareDimsAndLoD
(
const
Variable
&
src
,
Variable
*
trg
);
static
void
EnforceShapeAndDTypeEQ
(
const
Variable
&
var1
,
const
Variable
&
var2
);
};
}
// namespace details
...
...
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