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3efac174
编写于
8月 17, 2018
作者:
T
tangwei12
浏览文件
操作
浏览文件
下载
差异文件
Merge branch 'develop' of github.com:PaddlePaddle/Paddle into sum_op_dim_fix
上级
c24a9263
fd10669e
变更
17
隐藏空白更改
内联
并排
Showing
17 changed file
with
192 addition
and
68 deletion
+192
-68
paddle/fluid/framework/ir/graph_traits.h
paddle/fluid/framework/ir/graph_traits.h
+4
-0
paddle/fluid/inference/analysis/CMakeLists.txt
paddle/fluid/inference/analysis/CMakeLists.txt
+1
-1
paddle/fluid/inference/analysis/node.cc
paddle/fluid/inference/analysis/node.cc
+0
-11
paddle/fluid/inference/analysis/node.h
paddle/fluid/inference/analysis/node.h
+11
-14
paddle/fluid/inference/analysis/node_tester.cc
paddle/fluid/inference/analysis/node_tester.cc
+21
-0
paddle/fluid/operators/recv_op.cc
paddle/fluid/operators/recv_op.cc
+2
-0
paddle/fluid/operators/send_barrier_op.cc
paddle/fluid/operators/send_barrier_op.cc
+5
-9
paddle/fluid/operators/send_op.cc
paddle/fluid/operators/send_op.cc
+2
-0
paddle/fluid/platform/cuda_device_function.h
paddle/fluid/platform/cuda_device_function.h
+11
-4
paddle/fluid/platform/cuda_helper_test.cu
paddle/fluid/platform/cuda_helper_test.cu
+82
-1
paddle/scripts/submit_local.sh.in
paddle/scripts/submit_local.sh.in
+1
-1
python/paddle/dataset/mnist.py
python/paddle/dataset/mnist.py
+0
-1
python/paddle/fluid/layers/io.py
python/paddle/fluid/layers/io.py
+19
-4
python/paddle/fluid/tests/unittests/dist_se_resnext.py
python/paddle/fluid/tests/unittests/dist_se_resnext.py
+0
-1
python/paddle/fluid/transpiler/distribute_transpiler.py
python/paddle/fluid/transpiler/distribute_transpiler.py
+31
-19
tools/manylinux1/Dockerfile.x64
tools/manylinux1/Dockerfile.x64
+1
-1
tools/manylinux1/build_scripts/build.sh
tools/manylinux1/build_scripts/build.sh
+1
-1
未找到文件。
paddle/fluid/framework/ir/graph_traits.h
浏览文件 @
3efac174
...
...
@@ -12,7 +12,11 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#pragma once
#include <stack>
#include <vector>
#include "paddle/fluid/framework/ir/graph.h"
#include "paddle/fluid/framework/ir/node.h"
...
...
paddle/fluid/inference/analysis/CMakeLists.txt
浏览文件 @
3efac174
...
...
@@ -8,7 +8,7 @@ cc_library(analysis SRCS pass_manager.cc dot.cc node.cc data_flow_graph.cc graph
helper.cc
model_store_pass.cc
DEPS framework_proto proto_desc
)
cc_test
(
test_node SRCS node_tester.cc DEPS analysis
)
cc_test
(
test_node SRCS node_tester.cc DEPS analysis
gflags glog gtest
)
cc_test
(
test_dot SRCS dot_tester.cc DEPS analysis
)
cc_binary
(
inference_analyzer SRCS analyzer_main.cc DEPS analysis
)
...
...
paddle/fluid/inference/analysis/node.cc
浏览文件 @
3efac174
...
...
@@ -20,17 +20,6 @@ namespace paddle {
namespace
inference
{
namespace
analysis
{
template
<
>
std
::
string
&
NodeAttr
::
As
<
std
::
string
>
()
{
if
(
data_
.
empty
())
{
type_index_
=
std
::
type_index
(
typeid
(
std
::
string
));
}
PADDLE_ENFORCE_EQ
(
type_index_
,
std
::
type_index
(
typeid
(
std
::
string
)));
return
data_
;
}
std
::
string
&
NodeAttr
::
String
()
{
return
As
<
std
::
string
>
();
}
std
::
vector
<
Dot
::
Attr
>
Value
::
dot_attrs
()
const
{
return
std
::
vector
<
Dot
::
Attr
>
({
Dot
::
Attr
(
"style"
,
"filled,rounded"
),
Dot
::
Attr
(
"shape"
,
"box"
),
...
...
paddle/fluid/inference/analysis/node.h
浏览文件 @
3efac174
...
...
@@ -29,6 +29,7 @@ limitations under the License. */
#include "paddle/fluid/inference/analysis/device.h"
#include "paddle/fluid/inference/analysis/dot.h"
#include "paddle/fluid/inference/analysis/helper.h"
#include "paddle/fluid/platform/variant.h"
namespace
paddle
{
namespace
inference
{
...
...
@@ -38,39 +39,35 @@ class NodeMap;
// A helper class to maintain the status from Pass.
struct
NodeAttr
{
using
any_t
=
boost
::
variant
<
bool
,
float
,
int32_t
,
int64_t
,
void
*
,
std
::
string
>
;
// NOTE T should be a primary type or a struct combined by several primary
// types.
// NOTE the STL containers should not use here.
// Some usages
// Attr attr;
// attr.Bool() = true;
bool
&
Bool
()
{
return
As
<
bool
>
();
}
float
&
Float
()
{
return
As
<
float
>
();
}
int32_t
&
Int32
()
{
return
As
<
int32_t
>
();
}
int64_t
&
Int64
()
{
return
As
<
int64_t
>
();
}
void
*&
Pointer
()
{
return
As
<
void
*>
();
}
std
::
string
&
String
()
;
std
::
string
&
String
()
{
return
As
<
std
::
string
>
();
}
private:
template
<
typename
T
>
T
&
As
()
{
// init storage in the first usage.
if
(
data_
.
empty
())
{
VLOG
(
4
)
<<
"resize data to "
<<
sizeof
(
T
);
type_index_
=
std
::
type_index
(
typeid
(
T
));
data_
.
resize
(
sizeof
(
T
)
);
if
(
type_index_
==
typeid
(
NodeAttr
))
{
type_index_
=
typeid
(
T
);
any_data_
=
T
(
);
}
else
{
PADDLE_ENFORCE
(
type_index_
==
typeid
(
T
),
"fetch error type"
);
}
PADDLE_ENFORCE
(
framework
::
IsType
<
T
>
(
type_index_
),
"type not matched, origin is %s, want %s"
,
DataTypeNamer
::
Global
().
repr
(
type_index_
),
DataTypeNamer
::
Global
().
repr
<
T
>
());
PADDLE_ENFORCE_EQ
(
data_
.
size
(),
sizeof
(
T
),
"Node attr type recast error"
);
return
*
reinterpret_cast
<
T
*>
(
&
data_
[
0
]);
return
boost
::
get
<
T
>
(
any_data_
);
}
private:
std
::
string
data_
;
any_t
any_
data_
;
std
::
type_index
type_index_
{
typeid
(
NodeAttr
)};
};
...
...
paddle/fluid/inference/analysis/node_tester.cc
浏览文件 @
3efac174
...
...
@@ -20,6 +20,24 @@ namespace paddle {
namespace
inference
{
namespace
analysis
{
TEST
(
NodeAttr
,
bool
)
{
NodeAttr
x
;
x
.
Bool
()
=
true
;
ASSERT_EQ
(
x
.
Bool
(),
true
);
}
TEST
(
NodeAttr
,
int32
)
{
NodeAttr
x
;
x
.
Int32
()
=
32
;
ASSERT_EQ
(
x
.
Int32
(),
32
);
}
TEST
(
NodeAttr
,
string
)
{
NodeAttr
x
;
x
.
String
()
=
"Hello"
;
ASSERT_EQ
(
x
.
String
(),
"Hello"
);
}
TEST
(
Node
,
Attr
)
{
// Node is an abstract class, use Value instead for they share the same Attr
// logic.
...
...
@@ -27,6 +45,9 @@ TEST(Node, Attr) {
auto
*
node
=
nodes
.
Create
(
Node
::
Type
::
kValue
);
node
->
attr
(
"v0"
).
Int32
()
=
2008
;
ASSERT_EQ
(
node
->
attr
(
"v0"
).
Int32
(),
2008
);
node
->
attr
(
"str"
).
String
()
=
"hello world"
;
ASSERT_EQ
(
node
->
attr
(
"str"
).
String
(),
"hello world"
);
}
}
// namespace analysis
...
...
paddle/fluid/operators/recv_op.cc
浏览文件 @
3efac174
...
...
@@ -57,6 +57,8 @@ class RecvOp : public framework::OperatorBase {
class
RecvOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
{
AddInput
(
"X"
,
"(Any) Dummy inputs, used for control dependency"
)
.
AsDuplicable
();
AddOutput
(
"Out"
,
"(Tensor) Variables to get from server."
).
AsDuplicable
();
AddComment
(
R"DOC(
Recv operator
...
...
paddle/fluid/operators/send_barrier_op.cc
浏览文件 @
3efac174
...
...
@@ -37,22 +37,19 @@ class SendBarrierOp : public framework::OperatorBase {
void
RunImpl
(
const
framework
::
Scope
&
scope
,
const
platform
::
Place
&
place
)
const
override
{
std
::
vector
<
std
::
string
>
eps
=
Attr
<
std
::
vector
<
std
::
string
>>
(
"endpoints"
);
bool
sync_mode
=
Attr
<
bool
>
(
"sync_mode"
);
distributed
::
RPCClient
*
rpc_client
=
distributed
::
RPCClient
::
GetInstance
<
RPCCLIENT_T
>
();
VLOG
(
3
)
<<
"SendBarrierOp sync
_mode:"
<<
sync_mode
;
VLOG
(
3
)
<<
"SendBarrierOp sync
"
;
// need to wait before sending send_barrier message
PADDLE_ENFORCE
(
rpc_client
->
Wait
(),
"internal error in RPCClient"
);
if
(
sync_mode
)
{
for
(
auto
&
ep
:
eps
)
{
VLOG
(
3
)
<<
"send barrier, ep: "
<<
ep
;
rpc_client
->
AsyncSendBatchBarrier
(
ep
);
}
PADDLE_ENFORCE
(
rpc_client
->
Wait
(),
"internal error in RPCClient"
);
for
(
auto
&
ep
:
eps
)
{
VLOG
(
3
)
<<
"send barrier, ep: "
<<
ep
;
rpc_client
->
AsyncSendBatchBarrier
(
ep
);
}
PADDLE_ENFORCE
(
rpc_client
->
Wait
(),
"internal error in RPCClient"
);
}
};
...
...
@@ -70,7 +67,6 @@ the Parameter Server would knew all variables have been sent.
"(string vector, default 127.0.0.1:6164)"
"Server endpoints to send variables to."
)
.
SetDefault
({
"127.0.0.1:6164"
});
AddAttr
<
bool
>
(
"sync_mode"
,
"work in sync_mode or not"
).
SetDefault
(
true
);
}
};
...
...
paddle/fluid/operators/send_op.cc
浏览文件 @
3efac174
...
...
@@ -66,6 +66,8 @@ class SendOpMaker : public framework::OpProtoAndCheckerMaker {
void
Make
()
{
AddInput
(
"X"
,
"(Tensor, SelectedRows) Input variables to be sent"
)
.
AsDuplicable
();
AddOutput
(
"Out"
,
"(Any) Dummy outputs, used for control dependency"
)
.
AsDuplicable
();
AddComment
(
R"DOC(
Send operator
...
...
paddle/fluid/platform/cuda_device_function.h
浏览文件 @
3efac174
...
...
@@ -36,7 +36,7 @@ __forceinline__ __device__ T CudaShuffleDownSync(unsigned mask, T val,
#if CUDA_VERSION < 9000
return
__shfl_down
(
val
,
delta
,
width
);
#else
return
__shfl_down_sync
(
mask
,
val
,
delta
,
width
);
return
__shfl_down_sync
(
mask
,
val
,
static_cast
<
unsigned
>
(
delta
)
,
width
);
#endif
}
...
...
@@ -46,9 +46,16 @@ template <>
__forceinline__
__device__
float16
CudaShuffleDownSync
(
unsigned
mask
,
float16
val
,
int
delta
,
int
width
)
{
half
tmp
=
static_cast
<
half
>
(
val
);
__shfl_down
(
tmp
,
static_cast
<
unsigned
>
(
delta
),
width
);
return
float16
(
tmp
);
return
float16
(
__shfl_down
(
static_cast
<
half
>
(
val
),
static_cast
<
unsigned
>
(
delta
),
width
));
}
#else
template
<
>
__forceinline__
__device__
float16
CudaShuffleDownSync
(
unsigned
mask
,
float16
val
,
int
delta
,
int
width
)
{
return
float16
(
__shfl_down_sync
(
mask
,
static_cast
<
half
>
(
val
),
static_cast
<
unsigned
>
(
delta
),
width
));
}
#endif
...
...
paddle/fluid/platform/cuda_helper_test.cu
浏览文件 @
3efac174
...
...
@@ -13,6 +13,7 @@
// limitations under the License.
#include <gtest/gtest.h>
#include <algorithm>
#include <iostream>
#include <random>
...
...
@@ -123,7 +124,7 @@ void TestUnalign(size_t num, const int shift_bit) {
cudaMemcpy
(
out
,
d_in2
,
array_size
,
cudaMemcpyDeviceToHost
);
cudaDeviceSynchronize
();
for
(
size_t
i
=
0
;
i
<
num
/
2
;
++
i
)
{
// NOTE(dzhwinter): the float16 add has small
underflow/overflow
// NOTE(dzhwinter): the float16 add has small
truncate error.
// so we use EXPECT_NEAR to check the result.
EXPECT_NEAR
(
static_cast
<
float
>
(
out
[
i
]),
static_cast
<
float
>
(
AddFunctor
<
float16
>
()(
r_in1
[
i
],
r_in2
[
i
])),
...
...
@@ -151,3 +152,83 @@ TEST(CudaAtomic, float16Unalign) {
TestUnalign
(
static_cast
<
size_t
>
(
1024
),
/*shift_bit*/
3
);
TestUnalign
(
static_cast
<
size_t
>
(
1024
*
1024
),
/*shift_bit*/
3
);
}
// https://devblogs.nvidia.com/faster-parallel-reductions-kepler/
template
<
typename
T
>
static
__forceinline__
__device__
T
WarpReduceSum
(
T
val
)
{
unsigned
mask
=
0u
;
CREATE_SHFL_MASK
(
mask
,
true
);
for
(
int
offset
=
warpSize
/
2
;
offset
>
0
;
offset
/=
2
)
{
val
+=
paddle
::
platform
::
CudaShuffleDownSync
(
mask
,
val
,
offset
);
}
return
val
;
}
template
<
typename
T
>
__forceinline__
__device__
T
BlockReduce
(
T
val
)
{
static
__shared__
T
shared
[
32
];
// Shared mem for 32 partial sums
int
lane
=
threadIdx
.
x
%
warpSize
;
int
wid
=
threadIdx
.
x
/
warpSize
;
val
=
WarpReduceSum
(
val
);
// Each warp performs partial reduction
if
(
lane
==
0
)
shared
[
wid
]
=
val
;
// Write reduced value to shared memory
__syncthreads
();
// Wait for all partial reductions
// read from shared memory only if that warp existed
val
=
(
threadIdx
.
x
<
blockDim
.
x
/
warpSize
)
?
shared
[
lane
]
:
static_cast
<
T
>
(
0
);
if
(
wid
==
0
)
val
=
WarpReduceSum
(
val
);
// Final reduce within first warp
return
val
;
}
template
<
typename
T
>
__global__
void
DeviceReduceSum
(
T
*
in
,
T
*
out
,
size_t
N
)
{
T
sum
(
0
);
for
(
int
i
=
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
;
i
<
N
;
i
+=
blockDim
.
x
*
gridDim
.
x
)
{
sum
+=
in
[
i
];
}
sum
=
BlockReduce
<
T
>
(
sum
);
__syncthreads
();
if
(
threadIdx
.
x
==
0
)
out
[
blockIdx
.
x
]
=
sum
;
}
template
<
typename
T
>
void
TestReduce
(
size_t
num
,
float
atol
=
0.01
)
{
T
*
in1
;
T
*
d_in1
,
*
d_in2
;
size_t
size
=
sizeof
(
T
)
*
num
;
cudaMalloc
(
reinterpret_cast
<
void
**>
(
&
d_in1
),
size
);
cudaMalloc
(
reinterpret_cast
<
void
**>
(
&
d_in2
),
sizeof
(
T
));
in1
=
reinterpret_cast
<
T
*>
(
malloc
(
size
));
std
::
minstd_rand
engine
;
std
::
uniform_real_distribution
<
double
>
dist
(
0.0
,
1.0
);
for
(
size_t
i
=
0
;
i
<
num
;
++
i
)
{
in1
[
i
]
=
static_cast
<
T
>
(
dist
(
engine
));
}
auto
out
=
std
::
accumulate
(
in1
,
in1
+
num
,
static_cast
<
T
>
(
0
));
cudaMemcpy
(
d_in1
,
in1
,
size
,
cudaMemcpyHostToDevice
);
cudaDeviceSynchronize
();
DeviceReduceSum
<
T
><<<
1
,
PADDLE_CUDA_NUM_THREADS
>>>
(
d_in1
,
d_in2
,
num
);
cudaMemcpy
(
in1
,
d_in2
,
sizeof
(
T
),
cudaMemcpyDeviceToHost
);
cudaDeviceSynchronize
();
// NOTE(dzhwinter): the float16 add has small underflow/overflow
// so we use EXPECT_NEAR to check the result.
EXPECT_NEAR
(
static_cast
<
float
>
(
in1
[
0
]),
static_cast
<
float
>
(
out
),
atol
);
free
(
in1
);
cudaFree
(
d_in1
);
cudaFree
(
d_in2
);
}
TEST
(
CudaShuffleSync
,
float16
)
{
TestReduce
<
float
>
(
10
);
TestReduce
<
float
>
(
1000
);
// float16 will overflow or accumulate truncate errors in big size.
TestReduce
<
float16
>
(
10
);
TestReduce
<
float16
>
(
100
,
/*atol error*/
1.0
);
}
paddle/scripts/submit_local.sh.in
浏览文件 @
3efac174
...
...
@@ -54,7 +54,7 @@ function cpu_config() {
if
[
$platform
==
"Linux"
]
;
then
ht
=
`
lscpu |grep
"per core"
|awk
-F
':'
'{print $2}'
|xargs
`
elif
[
$platform
==
"Darwin"
]
;
then
if
[
`
sysctl
-n
hw.physicalcpu
`
-eq
`
sysctl
-n
hw.logicalcpu
`
]
;
then
if
[
`
sysctl
-n
hw.physicalcpu
`
-eq
`
sysctl
-n
hw.logicalcpu
`
]
;
then
# HT is OFF
ht
=
1
fi
...
...
python/paddle/dataset/mnist.py
浏览文件 @
3efac174
...
...
@@ -24,7 +24,6 @@ import paddle.dataset.common
import
subprocess
import
numpy
import
platform
import
six
import
tempfile
from
six.moves
import
range
__all__
=
[
'train'
,
'test'
,
'convert'
]
...
...
python/paddle/fluid/layers/io.py
浏览文件 @
3efac174
...
...
@@ -24,7 +24,7 @@ from .layer_function_generator import templatedoc
from
..
import
core
from
..executor
import
global_scope
from
..framework
import
convert_np_dtype_to_dtype_
,
default_main_program
,
\
default_startup_program
,
program_guard
,
Program
default_startup_program
,
program_guard
,
Program
,
Variable
from
..layer_helper
import
LayerHelper
from
..unique_name
import
generate
as
unique_name
...
...
@@ -209,7 +209,7 @@ class ListenAndServ(object):
})
def
Send
(
endpoints
,
send_vars
,
sync
=
True
):
def
Send
(
endpoints
,
send_vars
,
dummy_output
=
None
,
sync
=
True
):
"""
Send variables to the server side, and get vars from server
side when server have finished running server side program.
...
...
@@ -223,6 +223,13 @@ def Send(endpoints, send_vars, sync=True):
"""
assert
(
type
(
send_vars
)
==
list
)
if
dummy_output
is
None
:
dummy_output
=
[]
elif
isinstance
(
dummy_output
,
Variable
):
dummy_output
=
[
dummy_output
]
assert
(
type
(
dummy_output
)
==
list
)
epmap
=
endpoints
.
split
(
","
)
endpoints
=
list
(
set
(
epmap
))
...
...
@@ -232,6 +239,7 @@ def Send(endpoints, send_vars, sync=True):
helper
.
append_op
(
type
=
"send"
,
inputs
=
{
"X"
:
send_vars
},
outputs
=
{
"Out"
:
dummy_output
},
attrs
=
{
"endpoints"
:
endpoints
,
"epmap"
:
epmap
,
...
...
@@ -241,7 +249,7 @@ def Send(endpoints, send_vars, sync=True):
helper
.
append_op
(
type
=
"send_barrier"
,
attrs
=
{
"endpoints"
:
endpoints
})
def
Recv
(
endpoints
,
get_vars
,
sync
=
True
):
def
Recv
(
endpoints
,
get_vars
,
dummy_input
=
None
,
sync
=
True
):
"""
Receive variables from server side
...
...
@@ -256,13 +264,20 @@ def Recv(endpoints, get_vars, sync=True):
"""
assert
(
type
(
get_vars
)
==
list
)
if
dummy_input
is
None
:
dummy_input
=
[]
elif
isinstance
(
dummy_input
,
Variable
):
dummy_input
=
[
dummy_input
]
assert
(
type
(
dummy_input
)
==
list
)
epmap
=
endpoints
.
split
(
","
)
endpoints
=
list
(
set
(
epmap
))
helper
=
LayerHelper
(
"Recv"
,
**
locals
())
helper
.
append_op
(
type
=
"recv"
,
inputs
=
{
"X"
:
get_vars
},
inputs
=
{
"X"
:
dummy_input
},
outputs
=
{
"Out"
:
get_vars
},
attrs
=
{
"endpoints"
:
endpoints
,
"epmap"
:
epmap
})
...
...
python/paddle/fluid/tests/unittests/dist_se_resnext.py
浏览文件 @
3efac174
...
...
@@ -16,7 +16,6 @@ from __future__ import print_function
import
numpy
as
np
import
argparse
import
six
import
time
import
math
...
...
python/paddle/fluid/transpiler/distribute_transpiler.py
浏览文件 @
3efac174
...
...
@@ -34,6 +34,7 @@ import math
import
random
import
numpy
as
np
import
collections
import
six
from
.ps_dispatcher
import
RoundRobin
,
HashName
,
PSDispatcher
from
..
import
core
,
framework
...
...
@@ -210,6 +211,9 @@ class DistributeTranspiler(object):
ps_dispatcher
=
self
.
config
.
split_method
(
self
.
pserver_endpoints
)
self
.
has_distributed_lookup_table
=
self
.
_has_distributed_lookup_table
()
self
.
param_name_to_grad_name
=
dict
()
for
param_var
,
grad_var
in
self
.
params_grads
:
self
.
param_name_to_grad_name
[
param_var
.
name
]
=
grad_var
.
name
# step 1: split and create vars, then put splited vars in dicts for later use.
self
.
_init_splited_vars
()
...
...
@@ -229,34 +233,39 @@ class DistributeTranspiler(object):
random
.
seed
(
self
.
origin_program
.
random_seed
)
random
.
shuffle
(
grad_var_mapping_items
)
for
orig_varname
,
splited_vars
in
grad_var_mapping_items
:
grad_name_to_send_dummy_out
=
dict
()
for
grad_varname
,
splited_vars
in
grad_var_mapping_items
:
eplist
=
ps_dispatcher
.
dispatch
(
splited_vars
)
if
not
self
.
config
.
slice_var_up
:
assert
(
len
(
splited_vars
)
==
1
)
splited_grad_varname
=
grad_varname
if
len
(
splited_vars
)
==
1
:
orig
_varname
=
splited_vars
[
0
].
name
splited_grad
_varname
=
splited_vars
[
0
].
name
index
=
find_op_by_output_arg
(
program
.
global_block
(),
orig
_varname
)
splited_grad
_varname
)
elif
len
(
splited_vars
)
>
1
:
orig_var
=
program
.
global_block
().
vars
[
orig
_varname
]
orig_var
=
program
.
global_block
().
vars
[
splited_grad
_varname
]
index
=
find_op_by_output_arg
(
program
.
global_block
(),
orig
_varname
)
splited_grad
_varname
)
self
.
_insert_split_op
(
program
,
orig_var
,
index
,
splited_vars
)
index
+=
1
else
:
AssertionError
(
"Can not insert the send op by original "
"variable name :"
,
orig
_varname
)
"variable name :"
,
splited_grad
_varname
)
dummy_output
=
program
.
global_block
().
create_var
()
grad_name_to_send_dummy_out
[
grad_varname
]
=
dummy_output
program
.
global_block
().
_insert_op
(
index
=
index
+
1
,
type
=
"send"
,
inputs
=
{
"X"
:
splited_vars
},
outputs
=
{},
outputs
=
{
"Out"
:
dummy_output
},
attrs
=
{
"epmap"
:
eplist
,
RPC_OP_ROLE_ATTR_NAME
:
RPC_OP_ROLE_ATTR_VALUE
RPC_OP_ROLE_ATTR_NAME
:
RPC_OP_ROLE_ATTR_VALUE
,
"sync_mode"
:
not
self
.
sync_mode
,
})
for
_
,
var
in
enumerate
(
splited_vars
):
send_vars
.
append
(
var
)
...
...
@@ -268,7 +277,6 @@ class DistributeTranspiler(object):
outputs
=
{},
attrs
=
{
"endpoints"
:
pserver_endpoints
,
"sync_mode"
:
self
.
sync_mode
,
RPC_OP_ROLE_ATTR_NAME
:
RPC_OP_ROLE_ATTR_VALUE
})
...
...
@@ -284,19 +292,21 @@ class DistributeTranspiler(object):
self
.
param_grad_ep_mapping
[
ep
][
"grads"
].
append
(
send_vars
[
i
])
# step4: Concat the parameters splits together after recv.
for
varname
,
splited_var
in
six
.
iteritems
(
self
.
param_var_mapping
):
for
param_
varname
,
splited_var
in
six
.
iteritems
(
self
.
param_var_mapping
):
eps
=
[]
for
var
in
splited_var
:
index
=
[
v
.
name
for
v
in
recv_vars
].
index
(
var
.
name
)
eps
.
append
(
eplist
[
index
])
grad_send_dummy_out
=
grad_name_to_send_dummy_out
[
self
.
param_name_to_grad_name
[
param_varname
]]
program
.
global_block
().
append_op
(
type
=
"recv"
,
inputs
=
{},
inputs
=
{
"X"
:
[
grad_send_dummy_out
]
},
outputs
=
{
"Out"
:
splited_var
},
attrs
=
{
"epmap"
:
eps
,
RPC_OP_ROLE_ATTR_NAME
:
RPC_OP_ROLE_ATTR_VALUE
RPC_OP_ROLE_ATTR_NAME
:
RPC_OP_ROLE_ATTR_VALUE
,
"sync_mode"
:
not
self
.
sync_mode
})
if
self
.
sync_mode
:
...
...
@@ -309,10 +319,10 @@ class DistributeTranspiler(object):
RPC_OP_ROLE_ATTR_NAME
:
RPC_OP_ROLE_ATTR_VALUE
})
for
varname
,
splited_var
in
six
.
iteritems
(
self
.
param_var_mapping
):
for
param_
varname
,
splited_var
in
six
.
iteritems
(
self
.
param_var_mapping
):
if
len
(
splited_var
)
<=
1
:
continue
orig_param
=
program
.
global_block
().
vars
[
varname
]
orig_param
=
program
.
global_block
().
vars
[
param_
varname
]
program
.
global_block
().
append_op
(
type
=
"concat"
,
inputs
=
{
"X"
:
splited_var
},
...
...
@@ -380,7 +390,7 @@ class DistributeTranspiler(object):
op
=
startup_program
.
global_block
().
append_op
(
type
=
"recv"
,
inputs
=
{},
inputs
=
{
"X"
:
[]
},
outputs
=
{
"Out"
:
splited_var
},
attrs
=
{
"epmap"
:
eps
,
...
...
@@ -786,19 +796,21 @@ class DistributeTranspiler(object):
self
.
config
.
min_block_size
)
assert
(
len
(
grad_blocks
)
==
len
(
param_blocks
))
# origin_
varname -> [splited_var
]
# origin_
param_name -> [splited_param_vars
]
self
.
param_var_mapping
=
self
.
_create_vars_from_blocklist
(
self
.
origin_program
,
param_blocks
)
# origin_grad_name -> [splited_grad_vars]
self
.
grad_var_mapping
=
self
.
_create_vars_from_blocklist
(
self
.
origin_program
,
grad_blocks
,
add_trainer_suffix
=
self
.
trainer_num
>
1
)
# dict(grad_splited_var -> param_splited_var)
self
.
grad_param_mapping
=
collections
.
OrderedDict
()
for
g
,
p
in
zip
(
grad_blocks
,
param_blocks
):
g_name
,
g_bid
,
_
=
g
.
split
(
":"
)
p_name
,
p_bid
,
_
=
p
.
split
(
":"
)
self
.
grad_param_mapping
[
self
.
grad_var_mapping
[
g_name
][
int
(
g_bid
)]]
=
\
self
.
param_var_mapping
[
p_name
][
int
(
p_bid
)]
self
.
param_var_mapping
[
p_name
][
int
(
p_bid
)]
# create mapping of endpoint -> split var to create pserver side program
self
.
param_grad_ep_mapping
=
collections
.
OrderedDict
()
...
...
@@ -919,7 +931,7 @@ class DistributeTranspiler(object):
index
=
op_index
+
2
,
type
=
"send"
,
inputs
=
{
'X'
:
self
.
trainer_side_table_grad_list
},
outputs
=
{},
outputs
=
{
'Out'
:
[]
},
attrs
=
{
"sync_mode"
:
True
,
"epmap"
:
pserver_endpoints
,
...
...
tools/manylinux1/Dockerfile.x64
浏览文件 @
3efac174
...
...
@@ -13,7 +13,7 @@ ENV PATH /opt/rh/devtoolset-2/root/usr/bin:$PATH
ENV LD_LIBRARY_PATH /opt/rh/devtoolset-2/root/usr/lib64:/opt/rh/devtoolset-2/root/usr/lib:/usr/local/lib64:/usr/local/lib:${LD_LIBRARY_PATH}
ENV PKG_CONFIG_PATH=/usr/local/lib/pkgconfig
RUN yum install -y sqlite-devel zlib-devel openssl-devel pcre-devel vim tk-devel tkinter libtool xz
freetype-devel libpng-devel
graphviz
RUN yum install -y sqlite-devel zlib-devel openssl-devel pcre-devel vim tk-devel tkinter libtool xz graphviz
COPY build_scripts /build_scripts
RUN bash build_scripts/build.sh && \
bash build_scripts/install_nccl2.sh && rm -r build_scripts
...
...
tools/manylinux1/build_scripts/build.sh
浏览文件 @
3efac174
...
...
@@ -28,7 +28,7 @@ AUTOCONF_HASH=954bd69b391edc12d6a4a51a2dd1476543da5c6bbf05a95b59dc0dd6fd4c2969
PYTHON_COMPILE_DEPS
=
"zlib-devel bzip2-devel ncurses-devel sqlite-devel readline-devel tk-devel gdbm-devel db4-devel libpcap-devel xz-devel"
# Libraries that are allowed as part of the manylinux1 profile
MANYLINUX1_DEPS
=
"glibc-devel libstdc++-devel glib2-devel libX11-devel libXext-devel libXrender-devel mesa-libGL-devel libICE-devel libSM-devel ncurses-devel"
MANYLINUX1_DEPS
=
"glibc-devel libstdc++-devel glib2-devel libX11-devel libXext-devel libXrender-devel mesa-libGL-devel libICE-devel libSM-devel ncurses-devel
freetype-devel libpng-devel
"
# Get build utilities
MY_DIR
=
$(
dirname
"
${
BASH_SOURCE
[0]
}
"
)
...
...
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