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体验新版 GitCode,发现更多精彩内容 >>
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32d5a160
编写于
2月 22, 2019
作者:
X
Xin Pan
浏览文件
操作
浏览文件
下载
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差异文件
resolve conflicts
test=develop
上级
26e32e09
变更
9
显示空白变更内容
内联
并排
Showing
9 changed file
with
47 addition
and
164 deletion
+47
-164
paddle/fluid/framework/details/build_strategy.cc
paddle/fluid/framework/details/build_strategy.cc
+1
-2
paddle/fluid/framework/details/parallel_ssa_graph_executor.cc
...le/fluid/framework/details/parallel_ssa_graph_executor.cc
+3
-4
paddle/fluid/framework/details/parallel_ssa_graph_executor.h
paddle/fluid/framework/details/parallel_ssa_graph_executor.h
+2
-3
paddle/fluid/framework/ir/graph.h
paddle/fluid/framework/ir/graph.h
+0
-10
paddle/fluid/framework/parallel_executor.cc
paddle/fluid/framework/parallel_executor.cc
+27
-113
paddle/fluid/framework/parallel_executor.h
paddle/fluid/framework/parallel_executor.h
+5
-6
paddle/fluid/pybind/pybind.cc
paddle/fluid/pybind/pybind.cc
+2
-5
python/paddle/fluid/compiler.py
python/paddle/fluid/compiler.py
+4
-18
python/paddle/fluid/parallel_executor.py
python/paddle/fluid/parallel_executor.py
+3
-3
未找到文件。
paddle/fluid/framework/details/build_strategy.cc
浏览文件 @
32d5a160
...
...
@@ -206,8 +206,7 @@ std::unique_ptr<ir::Graph> BuildStrategy::Apply(
graph
->
Erase
(
kAllOpDescs
);
}
graph
->
SetNotOwned
<
const
std
::
vector
<
OpDesc
*>>
(
kAllOpDescs
,
&
all_ops
);
// take ownership
graph
->
SetNotOwned
<
const
std
::
vector
<
OpDesc
*>>
(
kAllOpDescs
,
&
all_ops
);
pass
->
Erase
(
kAllOpDescs
);
pass
->
SetNotOwned
<
const
std
::
vector
<
OpDesc
*>>
(
kAllOpDescs
,
&
all_ops
);
...
...
paddle/fluid/framework/details/parallel_ssa_graph_executor.cc
浏览文件 @
32d5a160
...
...
@@ -20,7 +20,7 @@ namespace framework {
namespace
details
{
std
::
vector
<
std
::
unique_ptr
<
ir
::
Graph
>>
ParallelSSAGraphExecutor
::
SeparateMultiDevicesGraph
(
ir
::
Graph
*
graph
)
{
ParallelSSAGraphExecutor
::
SeparateMultiDevicesGraph
(
ir
::
Graph
*
graph
)
{
std
::
vector
<
std
::
unique_ptr
<
ir
::
Graph
>>
graphs
;
graphs
.
reserve
(
places_
.
size
());
for
(
size_t
i
=
0
;
i
<
places_
.
size
();
++
i
)
{
...
...
@@ -76,13 +76,12 @@ ParallelSSAGraphExecutor::SeparateMultiDevicesGraph(ir::Graph* graph) {
ParallelSSAGraphExecutor
::
ParallelSSAGraphExecutor
(
const
ExecutionStrategy
&
strategy
,
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
std
::
vector
<
platform
::
Place
>
&
places
,
const
framework
::
ProgramDesc
&
main_prog
,
ir
::
Graph
*
graph
)
const
std
::
vector
<
platform
::
Place
>
&
places
,
ir
::
Graph
*
graph
)
:
strategy_
(
std
::
move
(
strategy
)),
local_scopes_
(
std
::
move
(
local_scopes
)),
pool_
(
places
.
size
()
>=
2
?
new
::
ThreadPool
(
places
.
size
())
:
nullptr
),
places_
(
std
::
move
(
places
)),
main_prog_
(
main_prog
),
main_prog_
(
graph
->
OriginProgram
()
),
// TODO(Yancey1989): Copying graphs is not safely since it deleted the
// attrs.
graphs_
(
SeparateMultiDevicesGraph
(
graph
))
{
...
...
paddle/fluid/framework/details/parallel_ssa_graph_executor.h
浏览文件 @
32d5a160
...
...
@@ -31,8 +31,7 @@ class ParallelSSAGraphExecutor : public SSAGraphExecutor {
ParallelSSAGraphExecutor
(
const
ExecutionStrategy
&
strategy
,
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
std
::
vector
<
platform
::
Place
>
&
places
,
const
framework
::
ProgramDesc
&
main_prog
,
ir
::
Graph
*
graph
);
ir
::
Graph
*
graph
);
~
ParallelSSAGraphExecutor
()
final
=
default
;
const
ir
::
Graph
&
Graph
()
const
override
{
return
*
graphs_
[
0
];
}
...
...
@@ -41,7 +40,7 @@ class ParallelSSAGraphExecutor : public SSAGraphExecutor {
private:
std
::
vector
<
std
::
unique_ptr
<
ir
::
Graph
>>
SeparateMultiDevicesGraph
(
ir
::
Graph
*
graph
);
ir
::
Graph
*
graph
);
ExecutionStrategy
strategy_
;
std
::
vector
<
Scope
*>
local_scopes_
;
...
...
paddle/fluid/framework/ir/graph.h
浏览文件 @
32d5a160
...
...
@@ -195,22 +195,12 @@ class Graph {
return
nullptr
;
}
<<<<<<<
HEAD
=======
// Returns reference to the original program.
// WARN: After a series of passes, the current graph can be quite
// different from OriginProgram. Caller shouldn't assume much from
// the returned OriginProgram.
const
ProgramDesc
&
OriginProgram
()
const
{
return
program_
;
}
void
ResolveHazard
(
const
std
::
map
<
std
::
string
,
std
::
vector
<
ir
::
Node
*>>
&
var_nodes
);
private:
std
::
map
<
std
::
string
,
std
::
vector
<
ir
::
Node
*>>
InitFromProgram
(
const
ProgramDesc
&
program
);
>>>>>>>
polish
// This method takes ownership of `node`.
ir
::
Node
*
AddNode
(
ir
::
Node
*
node
)
{
PADDLE_ENFORCE
(
node_set_
.
find
(
node
)
==
node_set_
.
end
());
...
...
paddle/fluid/framework/parallel_executor.cc
浏览文件 @
32d5a160
...
...
@@ -184,9 +184,10 @@ std::vector<Scope *> &ParallelExecutor::GetLocalScopes() {
ParallelExecutor
::
ParallelExecutor
(
const
std
::
vector
<
platform
::
Place
>
&
places
,
const
std
::
unordered_set
<
std
::
string
>
&
bcast_vars
,
const
std
::
vector
<
ir
::
Graph
*>
&
graphs
,
const
std
::
string
&
loss_var_name
,
Scope
*
scope
,
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
ExecutionStrategy
&
exec_strategy
,
const
BuildStrategy
&
build_strategy
)
const
std
::
string
&
loss_var_name
,
Scope
*
scope
,
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
ExecutionStrategy
&
exec_strategy
,
const
BuildStrategy
&
build_strategy
,
ir
::
Graph
*
graph
)
:
member_
(
new
ParallelExecutorPrivate
(
places
))
{
member_
->
global_scope_
=
scope
;
member_
->
use_cuda_
=
exec_strategy
.
use_cuda_
;
...
...
@@ -216,34 +217,17 @@ ParallelExecutor::ParallelExecutor(
}
}
<<<<<<<
HEAD
std
::
unique_ptr
<
ir
::
Graph
>
temp_owned_graph
(
graph
);
// FIXME(Yancey1989): parallel graph mode get better performance
// in GPU allreduce distributed training. Need an elegant way to
// choice the execution strategy.
build_strategy
.
enable_parallel_graph_
=
EnableParallelGraphExecution
(
*
temp_owned_graph
,
exec_strategy
,
build_strategy
);
build_strategy
.
enable_parallel_graph_
=
EnableParallelGraphExecution
(
*
temp_owned_graph
,
exec_strategy
,
build_strategy
);
if
(
build_strategy
.
enable_parallel_graph_
)
VLOG
(
0
)
<<
"The Executor would execute the graph by ParallelGraph "
"Execution which can get better performance,"
<<
"you can force it off by env FLAGS_enable_parallel_graph=0"
;
=======
// TODO(panyx0718): Update pass interface so we don't need this here.
std
::
vector
<
std
::
unique_ptr
<
ir
::
Graph
>>
temp_owned_graphs
;
for
(
ir
::
Graph
*
g
:
graphs
)
{
temp_owned_graphs
.
emplace_back
(
g
);
}
<<<<<<<
HEAD
>>>>>>>
fix
parallel
graph
mode
program
=======
bool
parallel_graphs
=
(
temp_owned_graphs
.
size
()
>
1
);
if
(
parallel_graphs
)
{
PADDLE_ENFORCE_EQ
(
temp_owned_graphs
.
size
(),
places
.
size
());
}
VLOG
(
1
)
<<
"Enable ParallelGraph Execution: "
<<
parallel_graphs
;
>>>>>>>
polish
if
(
member_
->
use_cuda_
)
{
// Bcast Parameters to all GPUs
...
...
@@ -255,7 +239,7 @@ ParallelExecutor::ParallelExecutor(
if
(
nccl_id_var
!=
nullptr
)
{
nccl_id
=
nccl_id_var
->
GetMutable
<
ncclUniqueId
>
();
}
if
(
parallel_graphs
&&
member_
->
nranks_
>
1UL
)
{
if
(
build_strategy
.
enable_parallel_graph_
&&
member_
->
nranks_
>
1UL
)
{
if
(
nccl_id
==
nullptr
)
{
local_nccl_id_
.
reset
(
new
ncclUniqueId
());
platform
::
dynload
::
ncclGetUniqueId
(
local_nccl_id_
.
get
());
...
...
@@ -273,105 +257,54 @@ ParallelExecutor::ParallelExecutor(
if
(
member_
->
local_scopes_
.
size
()
!=
1
&&
local_scopes
.
empty
())
{
BCastParamsToDevices
(
bcast_vars
);
}
// Startup Program has been run. All local scopes has correct parameters.
// Startup Program has been run. All local scopes has correct parameters.
// Step 2. Convert main_program to SSA form and dependency graph. Also, insert
// ncclOp
<<<<<<<
HEAD
std
::
unique_ptr
<
ir
::
Graph
>
graph
;
// Step 2. Convert main_program to SSA form and dependency graph. Also, insert
// ncclOp
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
temp_owned_graph
=
build_strategy
.
Apply
(
std
::
move
(
temp_owned_graph
),
member_
->
places_
,
loss_var_name
,
member_
->
local_scopes_
,
member_
->
nranks_
,
member_
->
use_cuda_
,
member_
->
nccl_ctxs_
.
get
());
#else
temp_owned_graph
=
build_strategy
.
Apply
(
std
::
move
(
temp_owned_graph
),
member_
->
places_
,
loss_var_name
,
member_
->
local_scopes_
,
member_
->
nranks_
,
member_
->
use_cuda_
);
=======
std
::
vector
<
ir
::
Graph
*>
compiled_graphs
;
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
if
(
parallel_graphs
)
{
for
(
size_t
i
=
0
;
i
<
member_
->
places_
.
size
();
++
i
)
{
auto
temp_owned_graph
=
build_strategy
.
Apply
(
std
::
move
(
temp_owned_graphs
[
i
]),
{
member_
->
places_
[
i
]},
loss_var_name
,
{
member_
->
local_scopes_
[
i
]},
member_
->
nranks_
,
member_
->
use_cuda_
,
member_
->
nccl_ctxs_
.
get
());
compiled_graphs
.
push_back
(
temp_owned_graph
.
release
());
}
}
else
{
auto
temp_owned_graph
=
build_strategy
.
Apply
(
std
::
move
(
temp_owned_graphs
[
0
]),
member_
->
places_
,
loss_var_name
,
temp_owned_graph
=
build_strategy
.
Apply
(
std
::
move
(
temp_owned_graph
),
member_
->
places_
,
loss_var_name
,
member_
->
local_scopes_
,
member_
->
nranks_
,
member_
->
use_cuda_
,
member_
->
nccl_ctxs_
.
get
());
compiled_graphs
.
push_back
(
temp_owned_graph
.
release
());
}
#else
auto
temp_owned_graph
=
build_strategy
.
Apply
(
std
::
move
(
temp_owned_graph
s
[
0
]
),
member_
->
places_
,
loss_var_name
,
temp_owned_graph
=
build_strategy
.
Apply
(
std
::
move
(
temp_owned_graph
),
member_
->
places_
,
loss_var_name
,
member_
->
local_scopes_
,
member_
->
nranks_
,
member_
->
use_cuda_
);
compiled_graphs
.
push_back
(
temp_owned_graph
.
release
());
>>>>>>>
fix
parallel
graph
mode
program
#endif
auto
max_memory_size
=
GetEagerDeletionThreshold
();
VLOG
(
10
)
<<
"Eager Deletion Threshold "
<<
static_cast
<
float
>
(
max_memory_size
)
/
(
1
<<
30
);
if
(
max_memory_size
>=
0
)
{
<<<<<<<
HEAD
graph
=
member_
->
PrepareGCAndRefCnts
(
std
::
move
(
graph
),
static_cast
<
size_t
>
(
max_memory_size
)).
release
();
=======
for
(
size_t
i
=
0
;
i
<
graphs
.
size
();
++
i
)
{
compiled_graphs
[
i
]
=
member_
->
PrepareGCAndRefCnts
(
std
::
unique_ptr
<
ir
::
Graph
>
(
compiled_graphs
[
i
]),
graph
=
member_
->
PrepareGCAndRefCnts
(
std
::
move
(
temp_owned_graph
),
static_cast
<
size_t
>
(
max_memory_size
))
.
release
();
}
>>>>>>>
fix
parallel
graph
mode
program
}
else
{
graph
=
temp_owned_graph
.
release
();
}
// Step 3. Create vars in each scope. Passes may also create new vars.
// skip control vars and empty vars
std
::
vector
<
details
::
VariableInfo
>
var_infos
;
<<<<<<<
HEAD
for
(
auto
&
node
:
graph
->
Nodes
())
{
if
(
node
->
IsVar
()
&&
!
node
->
IsCtrlVar
()
&&
node
->
Var
())
{
var_infos
.
emplace_back
();
var_infos
.
back
().
name_
=
node
->
Var
()
->
Name
();
var_infos
.
back
().
type_
=
node
->
Var
()
->
GetType
();
var_infos
.
back
().
persistable_
=
node
->
Var
()
->
Persistable
();
=======
for
(
auto
&
graph
:
compiled_graphs
)
{
for
(
auto
&
node
:
graph
->
Nodes
())
{
if
(
node
->
IsVar
()
&&
!
node
->
IsCtrlVar
()
&&
node
->
Var
())
{
var_infos
.
emplace_back
();
var_infos
.
back
().
name_
=
node
->
Var
()
->
Name
();
var_infos
.
back
().
type_
=
node
->
Var
()
->
GetType
();
var_infos
.
back
().
persistable_
=
node
->
Var
()
->
Persistable
();
}
>>>>>>>
fix
parallel
graph
mode
program
}
}
// If the loss_var_name is given, the number of graph should be only one.
if
(
loss_var_name
.
size
())
{
<<<<<<<
HEAD
size_t
graph_num
=
ir
::
GraphNum
(
*
graph
);
=======
size_t
graph_num
=
ir
::
GraphNum
(
*
compiled_graphs
[
0
]);
>>>>>>>
fix
parallel
graph
mode
program
if
(
graph_num
>
1
)
{
LOG
(
WARNING
)
<<
"The number of graph should be only one, "
"but the current graph has "
<<<<<<<
HEAD
<<
ir
::
GraphNum
(
*
graph
)
=======
<<
ir
::
GraphNum
(
*
compiled_graphs
[
0
])
>>>>>>>
fix
parallel
graph
mode
program
<<
" sub_graphs. If you want to see the nodes of the "
"sub_graphs, you should use 'FLAGS_print_sub_graph_dir' "
"to specify the output dir. NOTES: if you not do training, "
...
...
@@ -379,18 +312,12 @@ ParallelExecutor::ParallelExecutor(
}
}
<<<<<<<
HEAD
if
(
build_strategy
.
enable_parallel_graph_
)
{
#ifdef PADDLE_WITH_CUDA
// TODO(Yancey1989): Remove passing in the main_program when
// allreduce_seq_pass doesn't need it as the attr.
=======
if
(
parallel_graphs
)
{
>>>>>>>
polish
member_
->
executor_
.
reset
(
new
details
::
ParallelSSAGraphExecutor
(
<<<<<<<
HEAD
exec_strategy
,
member_
->
local_scopes_
,
member_
->
places_
,
main_program
,
graph
));
exec_strategy
,
member_
->
local_scopes_
,
member_
->
places_
,
graph
));
#else
PADDLE_THROW
(
"Paddle should be compiled with CUDA for ParallelGraph Execution."
);
...
...
@@ -402,19 +329,6 @@ ParallelExecutor::ParallelExecutor(
}
else
{
member_
->
executor_
.
reset
(
new
details
::
FastThreadedSSAGraphExecutor
(
exec_strategy
,
member_
->
local_scopes_
,
member_
->
places_
,
graph
));
=======
exec_strategy
,
member_
->
local_scopes_
,
member_
->
places_
,
compiled_graphs
));
}
else
{
if
(
exec_strategy
.
type_
==
ExecutionStrategy
::
kDefault
)
{
member_
->
executor_
.
reset
(
new
details
::
ThreadedSSAGraphExecutor
(
exec_strategy
,
member_
->
local_scopes_
,
member_
->
places_
,
compiled_graphs
[
0
]));
}
else
{
member_
->
executor_
.
reset
(
new
details
::
FastThreadedSSAGraphExecutor
(
exec_strategy
,
member_
->
local_scopes_
,
member_
->
places_
,
compiled_graphs
[
0
]));
>>>>>>>
fix
parallel
graph
mode
program
}
}
...
...
@@ -551,9 +465,9 @@ ParallelExecutor::~ParallelExecutor() {
delete
member_
;
}
bool
EnableParallelGraphExecution
(
const
ir
::
Graph
&
graph
,
const
ExecutionStrategy
&
exec_strategy
,
const
BuildStrategy
&
build_strategy
)
{
bool
ParallelExecutor
::
EnableParallelGraphExecution
(
const
ir
::
Graph
&
graph
,
const
ExecutionStrategy
&
exec_strategy
,
const
BuildStrategy
&
build_strategy
)
const
{
if
(
!
FLAGS_enable_parallel_graph
)
return
false
;
bool
enable_parallel_graph
=
true
;
...
...
paddle/fluid/framework/parallel_executor.h
浏览文件 @
32d5a160
...
...
@@ -46,11 +46,11 @@ class ParallelExecutor {
public:
explicit
ParallelExecutor
(
const
std
::
vector
<
platform
::
Place
>
&
places
,
const
std
::
unordered_set
<
std
::
string
>
&
bcast_vars
,
const
std
::
vector
<
ir
::
Graph
*>
&
graphs
,
const
std
::
string
&
loss_var_name
,
Scope
*
scope
,
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
ExecutionStrategy
&
exec_strategy
,
const
BuildStrategy
&
build_strategy
);
const
BuildStrategy
&
build_strategy
,
ir
::
Graph
*
graph
);
~
ParallelExecutor
();
...
...
@@ -71,6 +71,9 @@ class ParallelExecutor {
private:
void
BCastParamsToDevices
(
const
std
::
unordered_set
<
std
::
string
>
&
vars
)
const
;
bool
EnableParallelGraphExecution
(
const
ir
::
Graph
&
graph
,
const
ExecutionStrategy
&
exec_strategy
,
const
BuildStrategy
&
build_strategy
)
const
;
ParallelExecutorPrivate
*
member_
;
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
...
...
@@ -78,9 +81,5 @@ class ParallelExecutor {
#endif
};
bool
EnableParallelGraphExecution
(
const
ir
::
Graph
&
graph
,
const
ExecutionStrategy
&
exec_strategy
,
const
BuildStrategy
&
build_strategy
);
}
// namespace framework
}
// namespace paddle
paddle/fluid/pybind/pybind.cc
浏览文件 @
32d5a160
...
...
@@ -976,8 +976,6 @@ All parameter, weight, gradient are variables in Paddle.
[](
ir
::
PassBuilder
&
self
,
size_t
idx
)
{
self
.
RemovePass
(
idx
);
});
// -- python binds for parallel executor.
m
.
def
(
"_enable_parallel_graph_execution"
,
framework
::
EnableParallelGraphExecution
);
py
::
class_
<
ParallelExecutor
>
pe
(
m
,
"ParallelExecutor"
);
py
::
class_
<
ExecutionStrategy
>
exec_strategy
(
pe
,
"ExecutionStrategy"
,
R"DOC(
...
...
@@ -1216,10 +1214,9 @@ All parameter, weight, gradient are variables in Paddle.
cannot be updated after being finalized.)DOC"
);
pe
.
def
(
py
::
init
<
const
std
::
vector
<
platform
::
Place
>
&
,
const
std
::
unordered_set
<
std
::
string
>
&
,
const
std
::
vector
<
ir
::
Graph
*>
&
,
const
std
::
string
&
,
const
std
::
unordered_set
<
std
::
string
>
&
,
const
std
::
string
&
,
Scope
*
,
std
::
vector
<
Scope
*>
&
,
const
ExecutionStrategy
&
,
const
BuildStrategy
&>
())
const
BuildStrategy
&
,
ir
::
Graph
*
>
())
// NOTE: even we return a vec<Scope*>* to Python use reference policy.
// We still cannot get local_scope from this vector, since the element
// of vec<Scope*> will be freed by Python GC. We can only return Scope*
...
...
python/paddle/fluid/compiler.py
浏览文件 @
32d5a160
...
...
@@ -198,7 +198,6 @@ class CompiledProgram(object):
if
self
.
_build_strategy
.
enable_inplace
is
None
:
self
.
_build_strategy
.
enable_inplace
=
False
if
self
.
_program
and
self
.
_program
.
_is_mem_optimized
else
True
# TODO(wuyi): trainer endpoings should be passed in through
# build_strategy, not program.xxx.
if
self
.
_program
and
self
.
_build_strategy
.
num_trainers
>
1
and
\
...
...
@@ -219,26 +218,13 @@ class CompiledProgram(object):
places
=
list
(
map
(
_place_obj
,
self
.
_places
))
# FIXME(Yancey1989): parallel graph mode get better performance
# in GPU allreduce distributed training. Need an elegant way to
# choice the execution strategy.
enable_parallel_graph
=
\
core
.
_enable_parallel_graph_execution
(
self
.
_graph
,
self
.
_exec_strategy
,
self
.
_build_strategy
)
and
\
self
.
_program
# only supported if compile program not graph.
self
.
_pe_graphs
=
[
self
.
_graph
]
if
enable_parallel_graph
:
for
_
in
range
(
len
(
places
)
-
1
):
self
.
_pe_graphs
.
append
(
core
.
Graph
(
self
.
_program_desc
))
return
core
.
ParallelExecutor
(
pe
=
core
.
ParallelExecutor
(
places
,
set
(
self
.
_persistable_vars
),
self
.
_pe_graphs
,
set
(
self
.
_persistable_vars
),
cpt
.
to_text
(
self
.
_loss_name
)
if
self
.
_loss_name
else
six
.
u
(
''
),
self
.
_scope
,
self
.
_local_scopes
,
self
.
_exec_strategy
,
self
.
_build_strategy
)
self
.
_exec_strategy
,
self
.
_build_strategy
,
self
.
_graph
)
return
pe
def
_compile_inference
(
self
):
return
core
.
create_paddle_predictor
(
self
.
_infer_config
)
...
...
python/paddle/fluid/parallel_executor.py
浏览文件 @
32d5a160
...
...
@@ -186,12 +186,12 @@ class ParallelExecutor(object):
# step7: init ParallelExecutor
# ParallelExecutor API will be deprecated, don't support parallel graph.
self
.
_graph
s
=
[
core
.
Graph
(
main
.
desc
)]
self
.
_graph
=
core
.
Graph
(
main
.
desc
)
self
.
executor
=
core
.
ParallelExecutor
(
places
,
persistable_vars
,
self
.
_graphs
,
places
,
persistable_vars
,
cpt
.
to_text
(
loss_name
)
if
loss_name
else
six
.
u
(
''
),
scope
,
local_scopes
,
exec_strategy
,
build_strategy
)
local_scopes
,
exec_strategy
,
build_strategy
,
self
.
_graph
)
self
.
scope
=
scope
...
...
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