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5373fe29
编写于
7月 29, 2018
作者:
T
tensor-tang
浏览文件
操作
浏览文件
下载
差异文件
Merge remote-tracking branch 'ups/develop' into refine/im2col
上级
687a3222
02c31458
变更
49
隐藏空白更改
内联
并排
Showing
49 changed file
with
1313 addition
and
324 deletion
+1313
-324
AUTHORS.md
AUTHORS.md
+1
-0
benchmark/fluid/fluid_benchmark.py
benchmark/fluid/fluid_benchmark.py
+1
-2
cmake/external/grpc.cmake
cmake/external/grpc.cmake
+1
-1
cmake/inference_lib.cmake
cmake/inference_lib.cmake
+2
-9
paddle/fluid/framework/CMakeLists.txt
paddle/fluid/framework/CMakeLists.txt
+3
-3
paddle/fluid/framework/details/multi_devices_graph_builder.cc
...le/fluid/framework/details/multi_devices_graph_builder.cc
+1
-0
paddle/fluid/framework/ir/graph.cc
paddle/fluid/framework/ir/graph.cc
+120
-0
paddle/fluid/inference/CMakeLists.txt
paddle/fluid/inference/CMakeLists.txt
+21
-5
paddle/fluid/inference/api/CMakeLists.txt
paddle/fluid/inference/api/CMakeLists.txt
+1
-28
paddle/fluid/inference/api/api.map
paddle/fluid/inference/api/api.map
+0
-6
paddle/fluid/inference/api/api.sym
paddle/fluid/inference/api/api.sym
+0
-1
paddle/fluid/inference/api/demo_ci/CMakeLists.txt
paddle/fluid/inference/api/demo_ci/CMakeLists.txt
+0
-2
paddle/fluid/inference/check_symbol.sh
paddle/fluid/inference/check_symbol.sh
+2
-2
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
+5
-2
paddle/fluid/inference/tensorrt/convert/mul_op.cc
paddle/fluid/inference/tensorrt/convert/mul_op.cc
+0
-1
paddle/fluid/inference/tensorrt/convert/pool2d_op.cc
paddle/fluid/inference/tensorrt/convert/pool2d_op.cc
+80
-0
paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
...le/fluid/inference/tensorrt/convert/test_activation_op.cc
+1
-1
paddle/fluid/inference/tensorrt/convert/test_fc_op.cc
paddle/fluid/inference/tensorrt/convert/test_fc_op.cc
+2
-3
paddle/fluid/inference/tensorrt/convert/test_mul_op.cc
paddle/fluid/inference/tensorrt/convert/test_mul_op.cc
+2
-2
paddle/fluid/inference/tensorrt/convert/test_pool2d_op.cc
paddle/fluid/inference/tensorrt/convert/test_pool2d_op.cc
+60
-0
paddle/fluid/inference/tensorrt/convert/ut_helper.h
paddle/fluid/inference/tensorrt/convert/ut_helper.h
+29
-7
paddle/fluid/inference/tensorrt/test_engine.cc
paddle/fluid/inference/tensorrt/test_engine.cc
+32
-1
paddle/fluid/inference/tests/book/CMakeLists.txt
paddle/fluid/inference/tests/book/CMakeLists.txt
+2
-2
paddle/fluid/inference/tests/book/test_inference_nlp.cc
paddle/fluid/inference/tests/book/test_inference_nlp.cc
+2
-9
paddle/fluid/operators/.flatten_op.cc.swp
paddle/fluid/operators/.flatten_op.cc.swp
+0
-0
paddle/fluid/operators/CMakeLists.txt
paddle/fluid/operators/CMakeLists.txt
+3
-0
paddle/fluid/operators/distributed/CMakeLists.txt
paddle/fluid/operators/distributed/CMakeLists.txt
+3
-3
paddle/fluid/operators/distributed/grpc_client.cc
paddle/fluid/operators/distributed/grpc_client.cc
+2
-1
paddle/fluid/operators/distributed/grpc_client.h
paddle/fluid/operators/distributed/grpc_client.h
+3
-1
paddle/fluid/operators/distributed/rpc_server_test.cc
paddle/fluid/operators/distributed/rpc_server_test.cc
+12
-13
paddle/fluid/operators/extract_rows_op.cc
paddle/fluid/operators/extract_rows_op.cc
+103
-0
paddle/fluid/operators/flatten_op.cc
paddle/fluid/operators/flatten_op.cc
+169
-0
paddle/fluid/operators/lookup_table_op.cc
paddle/fluid/operators/lookup_table_op.cc
+16
-30
paddle/fluid/operators/lookup_table_op.cu
paddle/fluid/operators/lookup_table_op.cu
+28
-45
paddle/fluid/operators/lookup_table_op.h
paddle/fluid/operators/lookup_table_op.h
+5
-35
paddle/fluid/operators/tensorrt_engine_op.cc
paddle/fluid/operators/tensorrt_engine_op.cc
+0
-3
paddle/fluid/platform/cpu_helper.cc
paddle/fluid/platform/cpu_helper.cc
+2
-0
paddle/fluid/platform/init.cc
paddle/fluid/platform/init.cc
+4
-1
patches/grpc/completion_queue.h
patches/grpc/completion_queue.h
+386
-0
patches/grpc/fix_too_early_destory.patch
patches/grpc/fix_too_early_destory.patch
+0
-47
patches/grpc/grpc_library.h
patches/grpc/grpc_library.h
+64
-0
python/paddle/fluid/__init__.py
python/paddle/fluid/__init__.py
+1
-1
python/paddle/fluid/regularizer.py
python/paddle/fluid/regularizer.py
+14
-2
python/paddle/fluid/tests/unittests/dist_se_resnext.py
python/paddle/fluid/tests/unittests/dist_se_resnext.py
+2
-6
python/paddle/fluid/tests/unittests/test_dist_se_resnext.py
python/paddle/fluid/tests/unittests/test_dist_se_resnext.py
+1
-1
python/paddle/fluid/tests/unittests/test_extract_rows_op.py
python/paddle/fluid/tests/unittests/test_extract_rows_op.py
+58
-0
python/paddle/fluid/tests/unittests/test_flatten_op.py
python/paddle/fluid/tests/unittests/test_flatten_op.py
+68
-0
python/paddle/fluid/tests/unittests/test_lookup_table_op.py
python/paddle/fluid/tests/unittests/test_lookup_table_op.py
+0
-47
tools/codestyle/cpplint_pre_commit.hook
tools/codestyle/cpplint_pre_commit.hook
+1
-1
未找到文件。
AUTHORS.md
浏览文件 @
5373fe29
...
...
@@ -46,6 +46,7 @@
| tianbingsz | Tian-Bing Xu |
| tpatejko | Tomasz Patejko |
| typhoonzero | Yi Wu |
| velconia | Qi-Yang Min |
| wanghaoshuang | Hao-Shuang Wang |
| wangyang59 | Yang Wang |
| wangzhen-nlp | Zhen Wang |
...
...
benchmark/fluid/fluid_benchmark.py
浏览文件 @
5373fe29
...
...
@@ -85,8 +85,7 @@ def dist_transpile(trainer_id, args):
trainer_id
,
pservers
=
pserver_endpoints
,
trainers
=
trainers
,
sync_mode
=
not
args
.
async_mode
,
slice_var_up
=
not
args
.
no_split_var
)
sync_mode
=
not
args
.
async_mode
)
if
training_role
==
"PSERVER"
:
pserver_program
=
t
.
get_pserver_program
(
current_endpoint
)
pserver_startup_program
=
t
.
get_startup_program
(
current_endpoint
,
...
...
cmake/external/grpc.cmake
浏览文件 @
5373fe29
...
...
@@ -50,7 +50,7 @@ ExternalProject_Add(
UPDATE_COMMAND
""
CONFIGURE_COMMAND
""
BUILD_IN_SOURCE 1
PATCH_COMMAND
git apply
${
PADDLE_SOURCE_DIR
}
/patches/grpc/fix_too_early_destory.patc
h
PATCH_COMMAND
cp
${
PADDLE_SOURCE_DIR
}
/patches/grpc/grpc_library.h
${
GRPC_SOURCES_DIR
}
/src/extern_grpc/include/grpcpp/impl/codegen/grpc_library.h && cp
${
PADDLE_SOURCE_DIR
}
/patches/grpc/completion_queue.h
${
GRPC_SOURCES_DIR
}
/src/extern_grpc/include/grpcpp/impl/codegen/completion_queue.
h
# NOTE(yuyang18):
# Disable -Werror, otherwise the compile will fail in MacOS.
# It seems that we cannot configure that by make command.
...
...
cmake/inference_lib.cmake
浏览文件 @
5373fe29
...
...
@@ -148,18 +148,11 @@ if (WITH_ANAKIN AND WITH_GPU)
list
(
APPEND inference_deps anakin_inference_lib
)
endif
()
copy
(
inference_api_lib DEPS paddle_inference_api paddle_inference_api_shared
SRCS
${
src_dir
}
/
${
module
}
/paddle_inference_api.h
${
src_dir
}
/
${
module
}
/demo_ci
${
PADDLE_BINARY_DIR
}
/paddle/fluid/inference/api/libpaddle_inference_api*
DSTS
${
dst_dir
}
/inference
${
dst_dir
}
/inference
${
dst_dir
}
/inference
)
list
(
APPEND inference_deps inference_api_lib
)
set
(
module
"inference"
)
copy
(
inference_lib DEPS
${
inference_deps
}
SRCS
${
src_dir
}
/
${
module
}
/*.h
${
PADDLE_BINARY_DIR
}
/paddle/fluid/inference/libpaddle_fluid.*
DSTS
${
dst_dir
}
/
${
module
}
${
dst_dir
}
/
${
module
}
${
src_dir
}
/
${
module
}
/api/paddle_inference_api.h
${
src_dir
}
/
${
module
}
/api/demo_ci
DSTS
${
dst_dir
}
/
${
module
}
${
dst_dir
}
/
${
module
}
${
dst_dir
}
/
${
module
}
${
dst_dir
}
/
${
module
}
)
set
(
module
"platform"
)
...
...
paddle/fluid/framework/CMakeLists.txt
浏览文件 @
5373fe29
...
...
@@ -8,9 +8,9 @@ cc_test(ddim_test SRCS ddim_test.cc DEPS ddim)
nv_test
(
dim_test SRCS dim_test.cu DEPS ddim
)
cc_library
(
data_type SRCS data_type.cc DEPS framework_proto ddim device_context
)
if
(
WITH_GPU
)
nv_library
(
tensor SRCS tensor.cc tensor_util.cu DEPS place memory data_type
)
nv_library
(
tensor SRCS tensor.cc tensor_util.cu DEPS place memory data_type
device_context
)
else
()
cc_library
(
tensor SRCS tensor.cc tensor_util.cc DEPS place memory data_type
)
cc_library
(
tensor SRCS tensor.cc tensor_util.cc DEPS place memory data_type
device_context
)
endif
()
cc_test
(
tensor_test SRCS tensor_test.cc DEPS tensor
)
...
...
@@ -110,7 +110,7 @@ cc_test(selected_rows_test SRCS selected_rows_test.cc DEPS selected_rows)
cc_test
(
op_kernel_type_test SRCS op_kernel_type_test.cc DEPS place device_context framework_proto
)
cc_test
(
cow_ptr_tests SRCS details/cow_ptr_test.cc
)
# cc_test(channel_test SRCS channel_test.cc)
cc_test
(
tuple_test SRCS tuple_test.cc
)
...
...
paddle/fluid/framework/details/multi_devices_graph_builder.cc
浏览文件 @
5373fe29
...
...
@@ -715,6 +715,7 @@ void MultiDevSSAGraphBuilder::CreateRPCOp(ir::Graph *result,
result
->
CreateOpNode
(
node
->
Op
()),
*
node
->
Op
(),
local_scopes_
[
op_dev_id
],
node
->
Op
()
->
Type
(),
places_
[
op_dev_id
]));
// TODO(panyx0718): This might not be needed anymore.
if
(
node
->
Op
()
->
Type
()
==
"send_barrier"
)
{
ConnectOp
(
result
,
result
->
Get
<
GraphOps
>
(
"ops"
).
back
().
get
(),
"send"
);
}
else
if
(
node
->
Op
()
->
Type
()
==
"recv"
)
{
...
...
paddle/fluid/framework/ir/graph.cc
浏览文件 @
5373fe29
...
...
@@ -24,6 +24,68 @@ namespace paddle {
namespace
framework
{
namespace
ir
{
std
::
vector
<
std
::
string
>
FindDistTrainSendVars
(
const
std
::
vector
<
ir
::
Node
*>
&
nodes
)
{
std
::
vector
<
std
::
string
>
send_vars
;
// since parameters are all in block 0,
// it's enough to only scan send ops in block 0
for
(
auto
&
node
:
nodes
)
{
auto
op_vars
=
node
->
Op
()
->
InputArgumentNames
();
send_vars
.
reserve
(
send_vars
.
size
()
+
std
::
distance
(
op_vars
.
begin
(),
op_vars
.
end
()));
send_vars
.
insert
(
send_vars
.
end
(),
op_vars
.
begin
(),
op_vars
.
end
());
}
return
send_vars
;
}
std
::
vector
<
std
::
string
>
FindDistTrainRecvVars
(
const
std
::
vector
<
ir
::
Node
*>
&
nodes
)
{
std
::
vector
<
std
::
string
>
recv_vars
;
for
(
auto
&
node
:
nodes
)
{
auto
op_vars
=
node
->
Op
()
->
OutputArgumentNames
();
recv_vars
.
reserve
(
recv_vars
.
size
()
+
std
::
distance
(
op_vars
.
begin
(),
op_vars
.
end
()));
recv_vars
.
insert
(
recv_vars
.
end
(),
op_vars
.
begin
(),
op_vars
.
end
());
}
return
recv_vars
;
}
bool
IsDistTrainOp
(
ir
::
Node
*
node
,
const
std
::
vector
<
std
::
string
>
&
send_vars
,
const
std
::
vector
<
std
::
string
>
&
recv_vars
)
{
if
(
send_vars
.
size
()
==
0
||
recv_vars
.
size
()
==
0
)
{
return
false
;
}
/**
* Check any of opvars contains `.block` and in sendvars
*/
auto
checker
=
[](
const
std
::
vector
<
std
::
string
>
&
opvars
,
const
std
::
vector
<
std
::
string
>
&
rpc_vars
)
->
bool
{
for
(
auto
&
var
:
opvars
)
{
// a variable name with the suffix `.block` means it's a splited
// variable by (DistributeTranspiler)
// [python/paddle/fluid/transpiler/distribute_transpiler.py]
if
(
var
.
find
(
".block"
)
!=
std
::
string
::
npos
&&
std
::
find
(
rpc_vars
.
begin
(),
rpc_vars
.
end
(),
var
)
!=
rpc_vars
.
end
())
{
return
true
;
}
}
return
false
;
};
std
::
vector
<
std
::
string
>
input_var_names
;
std
::
vector
<
std
::
string
>
output_var_names
;
for
(
ir
::
Node
*
input
:
node
->
inputs
)
{
input_var_names
.
push_back
(
input
->
Name
());
}
for
(
ir
::
Node
*
output
:
node
->
outputs
)
{
output_var_names
.
push_back
(
output
->
Name
());
}
return
checker
(
output_var_names
,
send_vars
)
||
checker
(
input_var_names
,
recv_vars
);
}
Graph
::
Graph
(
const
ProgramDesc
&
program
)
:
program_
(
program
)
{
VLOG
(
3
)
<<
"block in program:"
<<
program_
.
Size
();
std
::
unordered_map
<
std
::
string
,
VarDesc
*>
all_vars
;
...
...
@@ -61,6 +123,64 @@ Graph::Graph(const ProgramDesc &program) : program_(program) {
var
->
inputs
.
push_back
(
node
);
}
}
std
::
vector
<
ir
::
Node
*>
send_ops
;
ir
::
Node
*
send_bar
=
nullptr
;
std
::
vector
<
ir
::
Node
*>
recv_ops
;
ir
::
Node
*
fetch_bar
=
nullptr
;
for
(
ir
::
Node
*
node
:
Nodes
())
{
if
(
node
->
Name
()
==
"send"
)
{
send_ops
.
push_back
(
node
);
}
else
if
(
node
->
Name
()
==
"send_barrier"
)
{
PADDLE_ENFORCE
(
!
send_bar
,
"only has one send barrier"
);
send_bar
=
node
;
}
else
if
(
node
->
Name
()
==
"recv"
)
{
recv_ops
.
push_back
(
node
);
}
else
if
(
node
->
Name
()
==
"fetch_barrier"
)
{
PADDLE_ENFORCE
(
!
fetch_bar
,
"only has one fetch barrier"
);
fetch_bar
=
node
;
}
}
if
(
send_bar
)
{
for
(
ir
::
Node
*
send
:
send_ops
)
{
ir
::
Node
*
dep_var
=
CreateControlDepVar
();
send
->
outputs
.
push_back
(
dep_var
);
dep_var
->
inputs
.
push_back
(
send
);
send_bar
->
inputs
.
push_back
(
dep_var
);
dep_var
->
outputs
.
push_back
(
send_bar
);
}
for
(
ir
::
Node
*
recv
:
recv_ops
)
{
ir
::
Node
*
dep_var
=
CreateControlDepVar
();
recv
->
inputs
.
push_back
(
dep_var
);
dep_var
->
outputs
.
push_back
(
recv
);
send_bar
->
outputs
.
push_back
(
dep_var
);
dep_var
->
inputs
.
push_back
(
send_bar
);
}
}
if
(
fetch_bar
)
{
for
(
ir
::
Node
*
recv
:
recv_ops
)
{
ir
::
Node
*
dep_var
=
CreateControlDepVar
();
recv
->
outputs
.
push_back
(
dep_var
);
dep_var
->
inputs
.
push_back
(
recv
);
fetch_bar
->
inputs
.
push_back
(
dep_var
);
dep_var
->
outputs
.
push_back
(
fetch_bar
);
}
}
std
::
vector
<
std
::
string
>
send_vars
=
FindDistTrainSendVars
(
send_ops
);
std
::
vector
<
std
::
string
>
recv_vars
=
FindDistTrainRecvVars
(
recv_ops
);
for
(
ir
::
Node
*
node
:
Nodes
())
{
if
(
IsDistTrainOp
(
node
,
send_vars
,
recv_vars
))
{
if
(
fetch_bar
&&
node
->
Name
()
==
"concat"
)
{
ir
::
Node
*
dep_var
=
CreateControlDepVar
();
fetch_bar
->
outputs
.
push_back
(
dep_var
);
dep_var
->
inputs
.
push_back
(
fetch_bar
);
node
->
inputs
.
push_back
(
dep_var
);
dep_var
->
outputs
.
push_back
(
node
);
}
}
}
/**
* We only handle write after read(WAR), since it should not have a write
* after write in program. If there are write after write operators, we need
...
...
paddle/fluid/inference/CMakeLists.txt
浏览文件 @
5373fe29
...
...
@@ -14,8 +14,15 @@ cc_library(paddle_fluid_api
get_property
(
fluid_modules GLOBAL PROPERTY FLUID_MODULES
)
# paddle_fluid_origin exclude inference api interface
cc_library
(
paddle_fluid_origin DEPS
${
fluid_modules
}
paddle_fluid_api
)
if
(
NOT APPLE
)
add_subdirectory
(
api
)
endif
()
# Create static library
cc_library
(
paddle_fluid DEPS
${
fluid_modules
}
paddle_fluid_api
)
cc_library
(
paddle_fluid DEPS
${
fluid_modules
}
paddle_fluid_api
paddle_inference_api
)
if
(
NOT APPLE
)
# TODO(liuyiqu: Temporarily disable the link flag because it is not support on Mac.
set
(
LINK_FLAGS
"-Wl,--retain-symbols-file
${
CMAKE_CURRENT_SOURCE_DIR
}
/paddle_fluid.sym"
)
...
...
@@ -24,7 +31,7 @@ endif()
# Create shared library
cc_library
(
paddle_fluid_shared SHARED
SRCS io.cc
SRCS io.cc
${
CMAKE_CURRENT_SOURCE_DIR
}
/api/api.cc
${
CMAKE_CURRENT_SOURCE_DIR
}
/api/api_impl.cc
DEPS
${
fluid_modules
}
paddle_fluid_api
)
set_target_properties
(
paddle_fluid_shared PROPERTIES OUTPUT_NAME paddle_fluid
)
...
...
@@ -32,12 +39,21 @@ if(NOT APPLE)
# TODO(liuyiqun): Temporarily disable the link flag because it is not support on Mac.
set
(
LINK_FLAGS
"-Wl,--version-script
${
CMAKE_CURRENT_SOURCE_DIR
}
/paddle_fluid.map"
)
set_target_properties
(
paddle_fluid_shared PROPERTIES LINK_FLAGS
"
${
LINK_FLAGS
}
"
)
# check symbol hidden
FILE
(
WRITE
${
CMAKE_CURRENT_BINARY_DIR
}
/check_symbol.cmake
"execute_process(COMMAND bash -c
\"
${
CMAKE_CURRENT_SOURCE_DIR
}
/check_symbol.sh"
"
${
CMAKE_CURRENT_BINARY_DIR
}
/libpaddle_fluid.so
\"
RESULT_VARIABLE symbol_res)
\n
"
"if(NOT
\"\$
{symbol_res}
\"
STREQUAL
\"
0
\"
)
\n
"
" message(FATAL_ERROR
\"
Check symbol failed.
\"
)
\n
"
"endif()
\n
"
)
add_custom_command
(
OUTPUT
"
${
CMAKE_CURRENT_BINARY_DIR
}
/.check_symbol"
COMMAND
${
CMAKE_COMMAND
}
-P
"
${
CMAKE_CURRENT_BINARY_DIR
}
/check_symbol.cmake"
DEPENDS paddle_fluid_shared
)
add_custom_target
(
check_symbol ALL DEPENDS
"
${
CMAKE_CURRENT_BINARY_DIR
}
/.check_symbol"
)
endif
()
if
(
WITH_TESTING
)
# both tests/book and analysis depends the models that generated by python/paddle/fluid/tests/book
add_subdirectory
(
tests/book
)
endif
()
if
(
NOT APPLE
)
add_subdirectory
(
api
)
endif
()
paddle/fluid/inference/api/CMakeLists.txt
浏览文件 @
5373fe29
...
...
@@ -42,35 +42,8 @@ function(inference_api_test TARGET_NAME)
endif
(
WITH_TESTING
)
endfunction
(
inference_api_test
)
cc_library
(
paddle_inference_api
SRCS api.cc api_impl.cc
DEPS
${
FLUID_CORE_MODULES
}
${
GLOB_OP_LIB
}
)
if
(
NOT APPLE
)
set
(
LINK_FLAGS
"-Wl,--retain-symbols-file
${
CMAKE_CURRENT_SOURCE_DIR
}
/api.sym"
)
set_target_properties
(
paddle_inference_api PROPERTIES LINK_FLAGS
"
${
LINK_FLAGS
}
"
)
endif
()
# Here the shared library doesn't depend on other fluid libraries, or double free will occur.
cc_library
(
paddle_inference_api_shared SHARED
SRCS api.cc api_impl.cc
)
add_dependencies
(
paddle_inference_api_shared
${
FLUID_CORE_MODULES
}
${
GLOB_OP_LIB
}
)
set_target_properties
(
paddle_inference_api_shared PROPERTIES OUTPUT_NAME paddle_inference_api
)
cc_library
(
paddle_inference_api SRCS api.cc api_impl.cc DEPS lod_tensor
)
if
(
NOT APPLE
)
set
(
LINK_FLAGS
"-Wl,--version-script
${
CMAKE_CURRENT_SOURCE_DIR
}
/api.map"
)
set_target_properties
(
paddle_inference_api_shared PROPERTIES LINK_FLAGS
"
${
LINK_FLAGS
}
"
)
FILE
(
WRITE
${
CMAKE_CURRENT_BINARY_DIR
}
/check_symbol.cmake
"execute_process(COMMAND bash -c
\"
${
CMAKE_CURRENT_SOURCE_DIR
}
/check_symbol.sh"
"
${
CMAKE_CURRENT_BINARY_DIR
}
/libpaddle_inference_api.so
\"
RESULT_VARIABLE symbol_res)
\n
"
"if(NOT
\"\$
{symbol_res}
\"
STREQUAL
\"
0
\"
)
\n
"
" message(FATAL_ERROR
\"
Check symbol failed.
\"
)
\n
"
"endif()
\n
"
)
add_custom_command
(
OUTPUT
"
${
CMAKE_CURRENT_BINARY_DIR
}
/.check_symbol"
COMMAND
${
CMAKE_COMMAND
}
-P
"
${
CMAKE_CURRENT_BINARY_DIR
}
/check_symbol.cmake"
DEPENDS paddle_inference_api_shared
)
add_custom_target
(
check_symbol ALL DEPENDS
"
${
CMAKE_CURRENT_BINARY_DIR
}
/.check_symbol"
)
endif
()
cc_test
(
test_paddle_inference_api
SRCS api_tester.cc
...
...
paddle/fluid/inference/api/api.map
已删除
100644 → 0
浏览文件 @
687a3222
{
global:
*paddle*;
local:
*;
};
paddle/fluid/inference/api/api.sym
已删除
100644 → 0
浏览文件 @
687a3222
*paddle*
paddle/fluid/inference/api/demo_ci/CMakeLists.txt
浏览文件 @
5373fe29
...
...
@@ -55,11 +55,9 @@ endif()
# Note: libpaddle_inference_api.so/a must put before libpaddle_fluid.so/a
if
(
WITH_STATIC_LIB
)
set
(
DEPS
${
PADDLE_LIB
}
/paddle/fluid/inference/libpaddle_inference_api.a
${
PADDLE_LIB
}
/paddle/fluid/inference/libpaddle_fluid.a
)
else
()
set
(
DEPS
${
PADDLE_LIB
}
/paddle/fluid/inference/libpaddle_inference_api.so
${
PADDLE_LIB
}
/paddle/fluid/inference/libpaddle_fluid.so
)
endif
()
set
(
EXTERNAL_LIB
"-lrt -ldl -lpthread"
)
...
...
paddle/fluid/inference/
api/
check_symbol.sh
→
paddle/fluid/inference/check_symbol.sh
浏览文件 @
5373fe29
...
...
@@ -3,8 +3,8 @@
lib
=
$1
if
[
$#
-ne
1
]
;
then
echo
"No input library"
;
exit
-1
;
fi
num_paddle_syms
=
$(
nm
-D
--defined-only
${
lib
}
|
grep
paddle |
wc
-l
)
num_google_syms
=
$(
nm
-D
--defined-only
${
lib
}
|
grep
google
|
wc
-l
)
num_paddle_syms
=
$(
nm
-D
${
lib
}
|
grep
paddle |
wc
-l
)
num_google_syms
=
$(
nm
-D
${
lib
}
|
grep
google |
grep
-v
paddle |
grep
T
|
wc
-l
)
if
[
$num_paddle_syms
-le
0
]
;
then
echo
"Have no paddle symbols"
;
exit
-1
;
fi
if
[
$num_google_syms
-ge
1
]
;
then
echo
"Have some google symbols"
;
exit
-1
;
fi
...
...
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
浏览文件 @
5373fe29
# Add TRT tests
nv_library
(
tensorrt_converter
SRCS mul_op.cc conv2d_op.cc fc_op.cc
DEPS tensorrt_engine
mul_op
)
SRCS mul_op.cc conv2d_op.cc fc_op.cc
pool2d_op.cc
DEPS tensorrt_engine
operator scope framework_proto op_registry
)
nv_test
(
test_op_converter SRCS test_op_converter.cc DEPS
${
FLUID_CORE_MODULES
}
tensorrt_engine tensorrt_converter
)
...
...
@@ -13,3 +13,6 @@ nv_test(test_trt_fc_op SRCS test_fc_op.cc fc_op.cc
DEPS
${
FLUID_CORE_MODULES
}
tensorrt_engine mul_op SERIAL
)
nv_test
(
test_trt_activation_op SRCS test_activation_op.cc activation_op.cc
DEPS
${
FLUID_CORE_MODULES
}
tensorrt_engine activation_op SERIAL
)
nv_test
(
test_trt_pool2d_op SRCS test_pool2d_op.cc pool2d_op.cc
DEPS
${
FLUID_CORE_MODULES
}
tensorrt_engine pool_op SERIAL
)
paddle/fluid/inference/tensorrt/convert/mul_op.cc
浏览文件 @
5373fe29
...
...
@@ -49,5 +49,4 @@ class MulOpConverter : public OpConverter {
}
// namespace inference
}
// namespace paddle
USE_OP
(
mul
);
REGISTER_TRT_OP_CONVERTER
(
mul
,
MulOpConverter
);
paddle/fluid/inference/tensorrt/convert/pool2d_op.cc
0 → 100644
浏览文件 @
5373fe29
/* 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/inference/tensorrt/convert/op_converter.h"
namespace
paddle
{
namespace
inference
{
namespace
tensorrt
{
/*
* Pool2dOp, IPoolingLayer in TRT. This Layer doesn't has weights.
*/
class
Pool2dOpConverter
:
public
OpConverter
{
public:
void
operator
()(
const
framework
::
proto
::
OpDesc
&
op
,
const
framework
::
Scope
&
scope
,
bool
test_mode
)
override
{
VLOG
(
4
)
<<
"convert a fluid pool2d op to tensorrt pool2d layer without bias"
;
framework
::
OpDesc
op_desc
(
op
,
nullptr
);
// Declare inputs
PADDLE_ENFORCE_EQ
(
op_desc
.
Input
(
"X"
).
size
(),
1
);
PADDLE_ENFORCE_EQ
(
op_desc
.
Output
(
"Out"
).
size
(),
1
);
auto
*
input1
=
engine_
->
GetITensor
(
op_desc
.
Input
(
"X"
)[
0
]);
std
::
string
pool_type
=
boost
::
get
<
std
::
string
>
(
op_desc
.
GetAttr
(
"pooling_type"
));
std
::
vector
<
int
>
ksize
=
boost
::
get
<
std
::
vector
<
int
>>
(
op_desc
.
GetAttr
(
"ksize"
));
std
::
vector
<
int
>
strides
=
boost
::
get
<
std
::
vector
<
int
>>
(
op_desc
.
GetAttr
(
"strides"
));
std
::
vector
<
int
>
paddings
=
boost
::
get
<
std
::
vector
<
int
>>
(
op_desc
.
GetAttr
(
"paddings"
));
const
nvinfer1
::
DimsHW
nv_ksize
(
ksize
[
0
],
ksize
[
1
]);
const
nvinfer1
::
DimsHW
nv_strides
(
strides
[
0
],
strides
[
1
]);
const
nvinfer1
::
DimsHW
nv_paddings
(
paddings
[
0
],
paddings
[
1
]);
PADDLE_ENFORCE_EQ
(
input1
->
getDimensions
().
nbDims
,
3UL
);
nvinfer1
::
PoolingType
nv_pool_type
=
nvinfer1
::
PoolingType
::
kMAX
;
if
(
pool_type
==
"max"
)
{
nv_pool_type
=
nvinfer1
::
PoolingType
::
kMAX
;
}
else
if
(
pool_type
==
"avg"
)
{
nv_pool_type
=
nvinfer1
::
PoolingType
::
kAVERAGE
;
}
else
{
PADDLE_THROW
(
"TensorRT unsupported pooling type!"
);
}
auto
*
layer
=
TRT_ENGINE_ADD_LAYER
(
engine_
,
Pooling
,
*
const_cast
<
nvinfer1
::
ITensor
*>
(
input1
),
nv_pool_type
,
nv_ksize
);
PADDLE_ENFORCE_NOT_NULL
(
layer
,
"pool layer could not be created."
);
layer
->
setStride
(
nv_strides
);
layer
->
setPadding
(
nv_paddings
);
auto
output_name
=
op_desc
.
Output
(
"Out"
)[
0
];
engine_
->
SetITensor
(
output_name
,
layer
->
getOutput
(
0
));
if
(
test_mode
)
{
engine_
->
DeclareOutput
(
output_name
);
}
}
};
}
// namespace tensorrt
}
// namespace inference
}
// namespace paddle
USE_OP
(
pool2d
);
REGISTER_TRT_OP_CONVERTER
(
pool2d
,
Pool2dOpConverter
);
paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
浏览文件 @
5373fe29
...
...
@@ -37,7 +37,7 @@ TEST(ReluOpConverter, main) {
validator
.
SetOp
(
*
desc
.
Proto
());
LOG
(
INFO
)
<<
"execute"
;
validator
.
Execute
(
1
);
validator
.
Execute
(
5
);
}
}
// namespace tensorrt
...
...
paddle/fluid/inference/tensorrt/convert/test_fc_op.cc
浏览文件 @
5373fe29
...
...
@@ -24,9 +24,8 @@ TEST(fc_op, test) {
std
::
unordered_set
<
std
::
string
>
parameters
({
"mul-Y"
});
framework
::
Scope
scope
;
TRTConvertValidation
validator
(
10
,
parameters
,
scope
,
1000
);
validator
.
DeclInputVar
(
"mul-X"
,
nvinfer1
::
Dims
4
(
1
,
10
,
1
,
1
));
validator
.
DeclInputVar
(
"mul-X"
,
nvinfer1
::
Dims
3
(
10
,
1
,
1
));
validator
.
DeclParamVar
(
"mul-Y"
,
nvinfer1
::
Dims2
(
10
,
2
));
// validator.DeclParamVar("mul-Y", nvinfer1::Dims2(8, 2));
validator
.
DeclOutputVar
(
"mul-Out"
,
nvinfer1
::
Dims2
(
1
,
2
));
// Prepare Op description
...
...
@@ -38,7 +37,7 @@ TEST(fc_op, test) {
validator
.
SetOp
(
*
desc
.
Proto
());
validator
.
Execute
(
1
);
validator
.
Execute
(
1
0
);
}
}
// namespace tensorrt
...
...
paddle/fluid/inference/tensorrt/convert/test_mul_op.cc
浏览文件 @
5373fe29
...
...
@@ -23,7 +23,7 @@ namespace tensorrt {
TEST
(
MulOpConverter
,
main
)
{
framework
::
Scope
scope
;
std
::
unordered_set
<
std
::
string
>
parameters
;
TRTConvertValidation
validator
(
10
,
parameters
,
scope
,
1000
);
TRTConvertValidation
validator
(
10
,
parameters
,
scope
,
1000
,
false
);
validator
.
DeclInputVar
(
"mul-X"
,
nvinfer1
::
Dims2
(
10
,
6
));
validator
.
DeclInputVar
(
"mul-Y"
,
nvinfer1
::
Dims2
(
6
,
10
));
validator
.
DeclOutputVar
(
"mul-Out"
,
nvinfer1
::
Dims2
(
10
,
10
));
...
...
@@ -39,7 +39,7 @@ TEST(MulOpConverter, main) {
validator
.
SetOp
(
*
desc
.
Proto
());
LOG
(
INFO
)
<<
"execute"
;
validator
.
Execute
(
1
);
validator
.
Execute
(
2
);
}
}
// namespace tensorrt
...
...
paddle/fluid/inference/tensorrt/convert/test_pool2d_op.cc
0 → 100644
浏览文件 @
5373fe29
/* 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 <gtest/gtest.h>
#include <fstream>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/inference/tensorrt/convert/ut_helper.h"
namespace
paddle
{
namespace
inference
{
namespace
tensorrt
{
TEST
(
Pool2dOpConverter
,
main
)
{
framework
::
Scope
scope
;
std
::
unordered_set
<
std
::
string
>
parameters
;
TRTConvertValidation
validator
(
5
,
parameters
,
scope
,
1
<<
15
);
// The ITensor's Dims should not contain the batch size.
// So, the ITensor's Dims of input and output should be C * H * W.
validator
.
DeclInputVar
(
"pool2d-X"
,
nvinfer1
::
Dims3
(
3
,
4
,
4
));
validator
.
DeclOutputVar
(
"pool2d-Out"
,
nvinfer1
::
Dims3
(
3
,
2
,
2
));
// Prepare Op description
framework
::
OpDesc
desc
;
desc
.
SetType
(
"pool2d"
);
desc
.
SetInput
(
"X"
,
{
"pool2d-X"
});
desc
.
SetOutput
(
"Out"
,
{
"pool2d-Out"
});
std
::
vector
<
int
>
ksize
({
2
,
2
});
std
::
vector
<
int
>
strides
({
2
,
2
});
std
::
vector
<
int
>
paddings
({
0
,
0
});
std
::
string
pooling_t
=
"max"
;
desc
.
SetAttr
(
"pooling_type"
,
pooling_t
);
desc
.
SetAttr
(
"ksize"
,
ksize
);
desc
.
SetAttr
(
"strides"
,
strides
);
desc
.
SetAttr
(
"paddings"
,
paddings
);
LOG
(
INFO
)
<<
"set OP"
;
validator
.
SetOp
(
*
desc
.
Proto
());
LOG
(
INFO
)
<<
"execute"
;
validator
.
Execute
(
3
);
}
}
// namespace tensorrt
}
// namespace inference
}
// namespace paddle
USE_OP
(
pool2d
);
paddle/fluid/inference/tensorrt/convert/ut_helper.h
浏览文件 @
5373fe29
...
...
@@ -63,13 +63,16 @@ class TRTConvertValidation {
public:
TRTConvertValidation
()
=
delete
;
TRTConvertValidation
(
int
batch_size
,
TRTConvertValidation
(
int
max_
batch_size
,
const
std
::
unordered_set
<
std
::
string
>&
parameters
,
framework
::
Scope
&
scope
,
// NOLINT
int
workspace_size
=
1
<<
10
)
:
parameters_
(
parameters
),
scope_
(
scope
)
{
int
workspace_size
=
1
<<
10
,
bool
if_add_batch
=
true
)
:
parameters_
(
parameters
),
scope_
(
scope
),
if_add_batch_
(
if_add_batch
),
max_batch_size_
(
max_batch_size
)
{
// create engine.
engine_
.
reset
(
new
TensorRTEngine
(
batch_size
,
workspace_size
,
&
stream_
));
engine_
.
reset
(
new
TensorRTEngine
(
max_
batch_size
,
workspace_size
,
&
stream_
));
engine_
->
InitNetwork
();
PADDLE_ENFORCE_EQ
(
cudaStreamCreate
(
&
stream_
),
0
);
...
...
@@ -84,7 +87,7 @@ class TRTConvertValidation {
// Declare a parameter varaible in the scope.
void
DeclParamVar
(
const
std
::
string
&
name
,
const
nvinfer1
::
Dims
&
dims
)
{
DeclVar
(
name
,
dims
);
DeclVar
(
name
,
dims
,
true
);
}
void
DeclOutputVar
(
const
std
::
string
&
name
,
const
nvinfer1
::
Dims
&
dims
)
{
...
...
@@ -92,12 +95,18 @@ class TRTConvertValidation {
}
// Declare a variable in a fluid Scope.
void
DeclVar
(
const
std
::
string
&
name
,
const
nvinfer1
::
Dims
&
dims
)
{
void
DeclVar
(
const
std
::
string
&
name
,
const
nvinfer1
::
Dims
&
dims
,
bool
is_param
=
false
)
{
platform
::
CPUPlace
place
;
platform
::
CPUDeviceContext
ctx
(
place
);
// Init Fluid tensor.
std
::
vector
<
int
>
dim_vec
(
dims
.
d
,
dims
.
d
+
dims
.
nbDims
);
// There is no batchsize in ITensor's shape, but We should add it to
// tensor's shape of fluid. If the variable is not parameter and the
// if_add_batch_ flag is true, add the max batchsize to dim_vec.
if
(
is_param
!=
true
&&
if_add_batch_
==
true
)
dim_vec
.
insert
(
dim_vec
.
begin
(),
max_batch_size_
);
auto
*
x
=
scope_
.
Var
(
name
);
auto
*
x_tensor
=
x
->
GetMutable
<
framework
::
LoDTensor
>
();
x_tensor
->
Resize
(
framework
::
make_ddim
(
dim_vec
));
...
...
@@ -131,6 +140,7 @@ class TRTConvertValidation {
void
Execute
(
int
batch_size
)
{
// Execute Fluid Op
PADDLE_ENFORCE_LE
(
batch_size
,
max_batch_size_
);
platform
::
CPUPlace
place
;
platform
::
CPUDeviceContext
ctx
(
place
);
op_
->
Run
(
scope_
,
place
);
...
...
@@ -149,9 +159,15 @@ class TRTConvertValidation {
auto
*
var
=
scope_
.
FindVar
(
output
);
auto
tensor
=
var
->
GetMutable
<
framework
::
LoDTensor
>
();
framework
::
TensorToVector
(
*
tensor
,
ctx
,
&
fluid_out
);
size_t
fluid_out_size
=
fluid_out
.
size
();
if
(
if_add_batch_
==
true
)
{
fluid_out_size
=
batch_size
*
(
framework
::
product
(
tensor
->
dims
())
/
max_batch_size_
);
}
// Compare two output
ASSERT_FALSE
(
fluid_out
.
empty
());
for
(
size_t
i
=
0
;
i
<
fluid_out
.
size
()
;
i
++
)
{
for
(
size_t
i
=
0
;
i
<
fluid_out
_size
;
i
++
)
{
// Loose the threshold for CI in different machine model.
EXPECT_LT
(
std
::
abs
(
fluid_out
[
i
]
-
trt_out
[
i
]),
2e-5
);
}
...
...
@@ -167,6 +183,12 @@ class TRTConvertValidation {
std
::
unique_ptr
<
framework
::
OpDesc
>
op_desc_
;
const
std
::
unordered_set
<
std
::
string
>&
parameters_
;
framework
::
Scope
&
scope_
;
// The ITensor of trt does not cotain the batch size,
// bug, in most cases, we need to set batch size for
// fluid's tensor shape. This variable indicates
// whether to add batch size to tensor shape of fluid.
bool
if_add_batch_
;
int
max_batch_size_
;
};
}
// namespace tensorrt
...
...
paddle/fluid/inference/tensorrt/test_engine.cc
浏览文件 @
5373fe29
...
...
@@ -113,7 +113,7 @@ TEST_F(TensorRTEngineTest, add_layer_multi_dim) {
ASSERT_EQ
(
y_cpu
[
1
],
14.5
);
}
TEST_F
(
TensorRTEngineTest
,
test_conv2d
_temp
)
{
TEST_F
(
TensorRTEngineTest
,
test_conv2d
)
{
// Weight in CPU memory.
float
raw_weight
[
9
]
=
{
1.0
,
1.0
,
1.0
,
1.0
,
1.0
,
1.0
,
1.0
,
1.0
,
1.0
};
float
raw_bias
[
1
]
=
{
0
};
...
...
@@ -146,6 +146,37 @@ TEST_F(TensorRTEngineTest, test_conv2d_temp) {
ASSERT_EQ
(
y_cpu
[
1
],
6.0
);
}
TEST_F
(
TensorRTEngineTest
,
test_pool2d
)
{
// Weight in CPU memory.
auto
*
x
=
engine_
->
DeclareInput
(
"x"
,
nvinfer1
::
DataType
::
kFLOAT
,
nvinfer1
::
Dims3
{
1
,
2
,
2
});
nvinfer1
::
PoolingType
pool_t
=
nvinfer1
::
PoolingType
::
kAVERAGE
;
auto
*
pool_layer
=
TRT_ENGINE_ADD_LAYER
(
engine_
,
Pooling
,
*
const_cast
<
nvinfer1
::
ITensor
*>
(
x
),
pool_t
,
nvinfer1
::
DimsHW
{
2
,
2
});
PADDLE_ENFORCE
(
pool_layer
!=
nullptr
);
pool_layer
->
setStride
(
nvinfer1
::
DimsHW
{
1
,
1
});
pool_layer
->
setPadding
(
nvinfer1
::
DimsHW
{
0
,
0
});
engine_
->
DeclareOutput
(
pool_layer
,
0
,
"y"
);
engine_
->
FreezeNetwork
();
ASSERT_EQ
(
engine_
->
engine
()
->
getNbBindings
(),
2
);
float
x_v
[
8
]
=
{
1.0
,
2.0
,
5.0
,
0.0
,
2.0
,
3.0
,
5.0
,
10.0
};
engine_
->
SetInputFromCPU
(
"x"
,
reinterpret_cast
<
void
*>
(
&
x_v
),
8
*
sizeof
(
float
));
engine_
->
Execute
(
2
);
LOG
(
INFO
)
<<
"to get output"
;
float
*
y_cpu
=
new
float
[
2
];
engine_
->
GetOutputInCPU
(
"y"
,
&
y_cpu
[
0
],
2
*
sizeof
(
float
));
ASSERT_EQ
(
y_cpu
[
0
],
2.0
);
ASSERT_EQ
(
y_cpu
[
1
],
5.0
);
}
}
// namespace tensorrt
}
// namespace inference
}
// namespace paddle
paddle/fluid/inference/tests/book/CMakeLists.txt
浏览文件 @
5373fe29
...
...
@@ -17,7 +17,7 @@ function(inference_test TARGET_NAME)
string
(
REGEX REPLACE
"^_$"
""
arg
"
${
arg
}
"
)
cc_test
(
test_inference_
${
TARGET_NAME
}${
arg
}
SRCS test_inference_
${
TARGET_NAME
}
.cc
DEPS paddle_fluid
DEPS paddle_fluid
_origin
ARGS --dirname=
${
PYTHON_TESTS_DIR
}
/book/
${
TARGET_NAME
}${
arg
}
.inference.model
)
set_tests_properties
(
test_inference_
${
TARGET_NAME
}${
arg
}
PROPERTIES DEPENDS test_
${
TARGET_NAME
}
)
...
...
@@ -43,6 +43,6 @@ inference_test(word2vec)
# TODO(TJ): clean me up
cc_test
(
test_inference_nlp
SRCS test_inference_nlp.cc
DEPS paddle_fluid
DEPS paddle_fluid
_origin
ARGS
--model_path=
${
PADDLE_BINARY_DIR
}
/python/paddle/fluid/tests/book/recognize_digits_mlp.inference.model
)
paddle/fluid/inference/tests/book/test_inference_nlp.cc
浏览文件 @
5373fe29
...
...
@@ -20,9 +20,6 @@ limitations under the License. */
#include "gtest/gtest.h"
#include "paddle/fluid/inference/tests/test_helper.h"
#include "paddle/fluid/platform/cpu_helper.h"
#ifdef PADDLE_WITH_MKLML
#include <omp.h>
#endif
DEFINE_string
(
model_path
,
""
,
"Directory of the inference model."
);
DEFINE_string
(
data_file
,
""
,
"File of input index data."
);
...
...
@@ -30,6 +27,7 @@ DEFINE_int32(repeat, 100, "Running the inference program repeat times");
DEFINE_bool
(
prepare_vars
,
true
,
"Prepare variables before executor"
);
DEFINE_int32
(
num_threads
,
1
,
"Number of threads should be used"
);
DECLARE_bool
(
use_mkldnn
);
DECLARE_int32
(
paddle_num_threads
);
inline
double
GetCurrentMs
()
{
struct
timeval
time
;
...
...
@@ -160,12 +158,7 @@ TEST(inference, nlp) {
std
::
unique_ptr
<
paddle
::
framework
::
Scope
>
scope
(
new
paddle
::
framework
::
Scope
());
#ifdef PADDLE_WITH_MKLML
// only use 1 thread number per std::thread
omp_set_dynamic
(
0
);
omp_set_num_threads
(
1
);
paddle
::
platform
::
SetNumThreads
(
1
);
#endif
paddle
::
platform
::
SetNumThreads
(
FLAGS_paddle_num_threads
);
double
start_ms
=
0
,
stop_ms
=
0
;
if
(
FLAGS_num_threads
>
1
)
{
...
...
paddle/fluid/operators/.flatten_op.cc.swp
0 → 100644
浏览文件 @
5373fe29
文件已添加
paddle/fluid/operators/CMakeLists.txt
浏览文件 @
5373fe29
...
...
@@ -270,6 +270,9 @@ op_library(cos_sim_op DEPS cos_sim_functor)
op_library
(
parallel_do_op DEPS executor
)
op_library
(
unsqueeze_op DEPS reshape_op
)
op_library
(
squeeze_op DEPS reshape_op
)
op_library
(
extract_rows_op DEPS memory
)
op_library
(
flatten_op DEPS reshape_op
)
if
(
WITH_GPU
)
op_library
(
conv_op DEPS vol2col depthwise_conv im2col
)
...
...
paddle/fluid/operators/distributed/CMakeLists.txt
浏览文件 @
5373fe29
...
...
@@ -17,9 +17,9 @@ if(WITH_GRPC)
set
(
DISTRIBUTE_COMPILE_FLAGS
"-Wno-non-virtual-dtor -Wno-error=non-virtual-dtor -Wno-error=delete-non-virtual-dtor"
)
set_source_files_properties
(
grpc_serde_test.cc rpc_server_test.cc PROPERTIES COMPILE_FLAGS
${
DISTRIBUTE_COMPILE_FLAGS
}
)
cc_test
(
grpc_serde_test SRCS grpc_serde_test.cc
DEPS grpc++_unsecure grpc_unsecure gpr cares zlib protobuf sendrecvop_grpc scope profiler math_function SERIAL
)
cc_test
(
rpc_server_test SRCS rpc_server_test.cc
DEPS sendrecvop_grpc grpc++_unsecure grpc_unsecure gpr cares zlib protobuf executor proto_desc lookup_table_op SERIAL
)
DEPS grpc++_unsecure grpc_unsecure gpr cares zlib protobuf sendrecvop_grpc scope profiler math_function SERIAL
)
cc_test
(
rpc_server_test SRCS rpc_server_test.cc
DEPS sendrecvop_grpc grpc++_unsecure grpc_unsecure gpr cares zlib protobuf executor proto_desc lookup_
sparse_
table_op SERIAL
)
return
()
endif
()
...
...
paddle/fluid/operators/distributed/grpc_client.cc
浏览文件 @
5373fe29
...
...
@@ -49,6 +49,7 @@ void GRPCClient::SendComplete() {
}
GRPCClient
::~
GRPCClient
()
{
stopped_
=
true
;
Wait
();
cq_
.
Shutdown
();
{
...
...
@@ -275,7 +276,7 @@ void GRPCClient::Proceed() {
void
*
tag
=
nullptr
;
bool
ok
=
false
;
while
(
cq_
.
Next
(
&
tag
,
&
ok
))
{
while
(
!
stopped_
&&
cq_
.
Next
(
&
tag
,
&
ok
))
{
BaseProcessor
*
c
=
static_cast
<
BaseProcessor
*>
(
tag
);
GPR_ASSERT
(
ok
);
PADDLE_ENFORCE
(
c
);
...
...
paddle/fluid/operators/distributed/grpc_client.h
浏览文件 @
5373fe29
...
...
@@ -174,7 +174,7 @@ class CheckpointNotifyProcessor : public BaseProcessor {
class
GRPCClient
:
public
RPCClient
{
public:
GRPCClient
()
:
ok_
(
true
),
completed_
(
false
)
{}
GRPCClient
()
:
ok_
(
true
),
completed_
(
false
)
,
stopped_
(
false
)
{}
virtual
~
GRPCClient
();
bool
AsyncSendVar
(
const
std
::
string
&
ep
,
const
platform
::
DeviceContext
&
ctx
,
...
...
@@ -237,6 +237,8 @@ class GRPCClient : public RPCClient {
// mutex for sending complete message only once
std
::
mutex
completed_mutex_
;
bool
completed_
;
volatile
bool
stopped_
;
};
}
// namespace distributed
...
...
paddle/fluid/operators/distributed/rpc_server_test.cc
浏览文件 @
5373fe29
...
...
@@ -30,7 +30,7 @@ namespace framework = paddle::framework;
namespace
platform
=
paddle
::
platform
;
namespace
distributed
=
paddle
::
operators
::
distributed
;
USE_
OP
(
lookup
_table
);
USE_
NO_KERNEL_OP
(
lookup_sparse
_table
);
std
::
unique_ptr
<
distributed
::
RPCServer
>
g_rpc_service
;
std
::
unique_ptr
<
distributed
::
RequestHandler
>
g_req_handler
;
...
...
@@ -42,13 +42,13 @@ framework::BlockDesc* AppendPrefetchBlcok(framework::ProgramDesc* program) {
framework
::
VariableNameMap
input
({{
"W"
,
{
"w"
}},
{
"Ids"
,
{
"ids"
}}});
framework
::
VariableNameMap
output
({{
"Output"
,
{
"out"
}}});
auto
op
=
block
->
AppendOp
();
op
->
SetType
(
"lookup_table"
);
op
->
SetType
(
"lookup_
sparse_
table"
);
op
->
SetInput
(
"W"
,
{
"w"
});
op
->
SetInput
(
"Ids"
,
{
"ids"
});
op
->
SetOutput
(
"Out"
,
{
"out"
});
auto
&
out
=
*
root_block
->
Var
(
"out"
);
out
.
SetType
(
framework
::
proto
::
VarType
::
SELECTED_ROWS
);
out
.
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR
);
out
.
SetShape
({
10
,
10
});
return
block
;
...
...
@@ -59,20 +59,19 @@ void CreateVarsOnScope(framework::Scope* scope, platform::CPUPlace* place) {
w_var
->
GetMutable
<
framework
::
SelectedRows
>
();
auto
out_var
=
scope
->
Var
(
"out"
);
out_var
->
GetMutable
<
framework
::
SelectedRows
>
();
out_var
->
GetMutable
<
framework
::
LoDTensor
>
();
auto
ids_var
=
scope
->
Var
(
"ids"
);
ids_var
->
GetMutable
<
framework
::
SelectedRows
>
();
ids_var
->
GetMutable
<
framework
::
LoDTensor
>
();
}
void
InitTensorsOnClient
(
framework
::
Scope
*
scope
,
platform
::
CPUPlace
*
place
,
int64_t
rows_numel
)
{
CreateVarsOnScope
(
scope
,
place
);
auto
ids_var
=
scope
->
Var
(
"ids"
)
->
GetMutable
<
framework
::
SelectedRows
>
();
auto
rows
=
ids_var
->
mutable_rows
();
for
(
int64_t
i
=
0
;
i
<
rows_numel
;
++
i
)
rows
->
push_back
(
i
*
2
);
ids_var
->
mutable_value
()
->
Resize
({
rows_numel
,
1
});
ids_var
->
mutable_value
()
->
mutable_data
<
float
>
(
*
place
);
auto
ids_var
=
scope
->
Var
(
"ids"
)
->
GetMutable
<
framework
::
LoDTensor
>
();
int64_t
*
ids_ptr
=
ids_var
->
mutable_data
<
int64_t
>
(
framework
::
DDim
({
rows_numel
,
1
}),
*
place
);
for
(
int64_t
i
=
0
;
i
<
rows_numel
;
++
i
)
ids_ptr
[
i
]
=
i
*
2
;
}
void
InitTensorsOnServer
(
framework
::
Scope
*
scope
,
platform
::
CPUPlace
*
place
,
...
...
@@ -148,11 +147,11 @@ TEST(PREFETCH, CPU) {
client
->
AsyncPrefetchVar
(
ep
,
ctx
,
scope
,
in_var_name
,
out_var_name
);
client
->
Wait
();
auto
var
=
scope
.
Var
(
out_var_name
);
auto
value
=
var
->
GetMutable
<
framework
::
SelectedRows
>
()
->
value
();
auto
ptr
=
value
.
mutable_data
<
float
>
(
place
);
auto
value
=
var
->
GetMutable
<
framework
::
LoDTensor
>
();
auto
ptr
=
value
->
mutable_data
<
float
>
(
place
);
for
(
int64_t
i
=
0
;
i
<
rows_numel
;
++
i
)
{
EXPECT_EQ
(
ptr
[
0
+
i
*
value
.
dims
()[
1
]],
static_cast
<
float
>
(
i
*
2
));
EXPECT_EQ
(
ptr
[
0
+
i
*
value
->
dims
()[
1
]],
static_cast
<
float
>
(
i
*
2
));
}
}
...
...
paddle/fluid/operators/extract_rows_op.cc
0 → 100644
浏览文件 @
5373fe29
/* 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 <string>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
class
ExtractRowsOpInferShape
:
public
framework
::
InferShapeBase
{
public:
void
operator
()(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of ExtractRowsOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of ExtractRowsOp should not be null."
);
PADDLE_ENFORCE_EQ
(
ctx
->
GetInputsVarType
(
"X"
)[
0
],
framework
::
proto
::
VarType
::
SELECTED_ROWS
,
"The type of input(X) must be SelectedRows."
);
auto
in_dims
=
ctx
->
GetInputDim
(
"X"
);
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
(
std
::
vector
<
int64_t
>
{
in_dims
[
0
],
1
}));
}
};
class
ExtractRowsOp
:
public
framework
::
OperatorBase
{
public:
ExtractRowsOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
const
framework
::
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
)
:
framework
::
OperatorBase
(
type
,
inputs
,
outputs
,
attrs
)
{}
private:
void
RunImpl
(
const
framework
::
Scope
&
scope
,
const
platform
::
Place
&
place
)
const
override
{
auto
&
in
=
scope
.
FindVar
(
Input
(
"X"
))
->
Get
<
framework
::
SelectedRows
>
();
auto
out
=
scope
.
FindVar
(
Output
(
"Out"
))
->
GetMutable
<
framework
::
LoDTensor
>
();
auto
in_rows
=
in
.
rows
();
auto
out_dim
=
framework
::
make_ddim
(
std
::
vector
<
int64_t
>
{
static_cast
<
int64_t
>
(
in_rows
.
size
()),
1
});
auto
dst_ptr
=
out
->
mutable_data
<
int64_t
>
(
out_dim
,
in
.
place
());
if
(
paddle
::
platform
::
is_gpu_place
(
in
.
place
()))
{
#ifdef PADDLE_WITH_CUDA
platform
::
DeviceContextPool
&
pool
=
platform
::
DeviceContextPool
::
Instance
();
auto
*
dev_ctx
=
pool
.
Get
(
in
.
place
());
auto
src_ptr
=
in_rows
.
Data
(
in
.
place
());
auto
stream
=
reinterpret_cast
<
const
platform
::
CUDADeviceContext
&>
(
*
dev_ctx
)
.
stream
();
memory
::
Copy
(
boost
::
get
<
platform
::
CUDAPlace
>
(
out
->
place
()),
dst_ptr
,
boost
::
get
<
platform
::
CUDAPlace
>
(
in
.
place
()),
src_ptr
,
in_rows
.
size
()
*
sizeof
(
int64_t
),
stream
);
#else
PADDLE_THROW
(
"Not compiled with CUDA."
);
#endif
}
else
{
memory
::
Copy
(
platform
::
CPUPlace
(),
dst_ptr
,
platform
::
CPUPlace
(),
in_rows
.
data
(),
in_rows
.
size
()
*
sizeof
(
int64_t
));
}
}
};
class
ExtractRowsOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"X"
,
"(SelectedRows). The input tensor of extract_rows operator,"
" and its type is SelectedRows."
);
AddOutput
(
"Out"
,
"(Tensor). The the rows of input(X)."
);
AddComment
(
R"DOC(
ExtractRows Operator.
The function of extract_rows_op is extracting the rows from the input(X)
whose type is SelectedRows.
)DOC"
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
extract_rows
,
ops
::
ExtractRowsOp
,
ops
::
ExtractRowsOpMaker
,
ops
::
ExtractRowsOpInferShape
);
paddle/fluid/operators/flatten_op.cc
0 → 100644
浏览文件 @
5373fe29
/* 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 <vector>
#include "paddle/fluid/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
using
Tensor
=
framework
::
Tensor
;
class
FlattenOpInferShape
:
public
framework
::
InferShapeBase
{
public:
void
operator
()(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input (X) of Flatten op should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output (Output) of Flatten op should not be null."
);
const
auto
&
axis
=
ctx
->
Attrs
().
Get
<
int
>
(
"axis"
);
const
auto
&
in_dims
=
ctx
->
GetInputDim
(
"X"
);
PADDLE_ENFORCE
(
axis
>=
0
,
"The axis should be greater than or equal to 0."
);
PADDLE_ENFORCE
(
axis
<=
in_dims
.
size
(),
"The axis should be less than or equal to input tensor's rank."
);
const
auto
&
out_dims
=
GetOutputShape
(
axis
,
in_dims
);
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
(
out_dims
));
if
(
in_dims
[
0
]
==
out_dims
[
0
])
{
// Only pass LoD when the first dimension of output and Input(X)
// are the same.
ctx
->
ShareLoD
(
"X"
,
"Out"
);
}
}
static
std
::
vector
<
int32_t
>
GetOutputShape
(
const
int
axis
,
const
framework
::
DDim
&
in_dims
)
{
int64_t
outer
=
1
,
inner
=
1
;
for
(
int
i
=
0
;
i
<
in_dims
.
size
();
++
i
)
{
if
(
i
<
axis
)
{
outer
*=
in_dims
[
i
];
}
else
{
inner
*=
in_dims
[
i
];
}
}
std
::
vector
<
int32_t
>
out_shape
(
2
);
out_shape
[
0
]
=
outer
;
out_shape
[
1
]
=
inner
;
return
out_shape
;
}
};
class
FlattenOp
:
public
framework
::
OperatorBase
{
public:
using
OperatorBase
::
OperatorBase
;
private:
void
RunImpl
(
const
framework
::
Scope
&
scope
,
const
platform
::
Place
&
place
)
const
override
{
auto
&
axis
=
Attr
<
int
>
(
"axis"
);
auto
in_dims
=
scope
.
FindVar
(
Input
(
"X"
))
->
Get
<
framework
::
LoDTensor
>
().
dims
();
const
auto
&
out_dims
=
FlattenOpInferShape
::
GetOutputShape
(
axis
,
in_dims
);
framework
::
AttributeMap
attrs
;
attrs
[
"shape"
]
=
out_dims
;
attrs
[
"inplace"
]
=
false
;
// Invoke Reshape Op
auto
reshape_op
=
framework
::
OpRegistry
::
CreateOp
(
"reshape"
,
{{
"X"
,
{
Input
(
"X"
)}},
{
"Shape"
,
{}}},
{{
"Out"
,
{
Output
(
"Out"
)}}},
attrs
);
reshape_op
->
Run
(
scope
,
place
);
}
};
class
FlattenOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"X"
,
"(Tensor) A tensor of rank >= axis."
);
AddOutput
(
"Out"
,
"A 2D tensor is reshaped input tensor. The input dimensions"
"up to axis are flattened to the outer dimension of the output"
"and the remaining input dimensions are flattened into the inner"
"dimension of the output."
);
AddAttr
<
int
>
(
"axis"
,
"(int)"
"Indicate up to which input dimensions (exclusive) should be"
"flattened to the outer dimension of the output. The value"
"for axis must be in the range [0, R], where R is the rank of"
"the input tensor. When axis = 0, the shape of the output"
"tensor is (1, (d_0 X d_1 ... d_n), where the shape of the"
"input tensor is (d_0, d_1, ... d_n)."
)
.
SetDefault
(
1
);
AddComment
(
R"DOC(
Flatten Operator
Flattens the input tensor into a 2D matrix.
Examples:
Case 1:
Given
X.shape = (3, 100, 100, 4)
and
axis = 2
We get:
Out.shape = (3 * 100, 4 * 100)
Case 2:
Given
X.shape = (3, 100, 100, 4)
and
axis = 0
We get:
Out.shape = (1, 3 * 100 * 100 * 4)
)DOC"
);
}
};
class
FlattenGradInferShape
:
public
framework
::
InferShapeBase
{
public:
void
operator
()(
framework
::
InferShapeContext
*
context
)
const
override
{
context
->
SetOutputDim
(
framework
::
GradVarName
(
"X"
),
context
->
GetInputDim
(
"X"
));
context
->
ShareLoD
(
"X"
,
framework
::
GradVarName
(
"X"
));
}
};
class
FlattenGradOp
:
public
framework
::
OperatorBase
{
public:
using
OperatorBase
::
OperatorBase
;
private:
void
RunImpl
(
const
framework
::
Scope
&
scope
,
const
platform
::
Place
&
place
)
const
override
{
auto
dx_name
=
Output
(
framework
::
GradVarName
(
"X"
));
auto
dout_name
=
Input
(
framework
::
GradVarName
(
"Out"
));
auto
in_dims
=
scope
.
FindVar
(
Input
(
"X"
))
->
Get
<
framework
::
LoDTensor
>
().
dims
();
framework
::
AttributeMap
attrs
;
attrs
[
"shape"
]
=
framework
::
vectorize2int
(
in_dims
);
attrs
[
"inplace"
]
=
false
;
auto
reshape_op
=
framework
::
OpRegistry
::
CreateOp
(
"reshape"
,
{{
"X"
,
{
dout_name
}},
{
"Shape"
,
{}}},
{{
"Out"
,
{
dx_name
}}},
attrs
);
reshape_op
->
Run
(
scope
,
place
);
}
};
}
// namespace operators
}
// namespace paddle
USE_OP
(
reshape
);
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
flatten
,
ops
::
FlattenOp
,
ops
::
FlattenOpMaker
,
ops
::
FlattenOpInferShape
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
REGISTER_OPERATOR
(
flatten_grad
,
ops
::
FlattenGradOp
,
ops
::
FlattenGradInferShape
);
paddle/fluid/operators/lookup_table_op.cc
浏览文件 @
5373fe29
...
...
@@ -33,19 +33,15 @@ class LookupTableOp : public framework::OperatorWithKernel {
auto
table_dims
=
ctx
->
GetInputDim
(
"W"
);
auto
ids_dims
=
ctx
->
GetInputDim
(
"Ids"
);
auto
ids_var_type
=
ctx
->
GetInputsVarType
(
"Ids"
).
front
();
// The type of Ids(Input) is SelectedRows or LoDTensor, when Ids's type
// is LoDTensor, this tensor contains the ids to be looked up in W
// and it must be a column vector with rank = 2 while the 2nd dimension
// size must be 1, when Ids's type is SelectedRows, the rows of Ids
// contains the ids to be looked up in W;
if
(
ids_var_type
==
framework
::
proto
::
VarType
::
LOD_TENSOR
)
{
PADDLE_ENFORCE_EQ
(
ids_dims
.
size
(),
2
);
PADDLE_ENFORCE_EQ
(
ids_dims
[
1
],
1
);
}
PADDLE_ENFORCE_EQ
(
ids_dims
.
size
(),
2
);
PADDLE_ENFORCE_EQ
(
ids_dims
[
1
],
1
);
ctx
->
SetOutputDim
(
"Out"
,
{
ids_dims
[
0
],
table_dims
[
1
]});
ctx
->
ShareLoD
(
"Ids"
,
/*->*/
"Out"
);
if
(
ctx
->
GetOutputsVarType
(
"Out"
)[
0
]
==
framework
::
proto
::
VarType
::
LOD_TENSOR
)
{
ctx
->
ShareLoD
(
"Ids"
,
/*->*/
"Out"
);
}
}
protected:
...
...
@@ -62,17 +58,12 @@ class LookupTableOpMaker : public framework::OpProtoAndCheckerMaker {
AddInput
(
"W"
,
"(Tensor) The input represents embedding tensors, "
"which is a learnable parameter."
);
AddInput
(
"Ids"
,
"(Tensor or SelectedRows) Ids's type can be Tensor or "
"SelectedRows, when Ids's type is Tensor, this tensor contains "
"the ids to be looked up in W and it must be a column vector with "
"rank = 2 while the 2nd dimension size must be 1; when Ids's type is "
"SelectedRows, the rows of Ids contains the ids to be looked up "
"in W."
);
AddOutput
(
"Out"
,
"(Tensor or SelectedRows) The lookup results, which have the "
"same type as W."
);
AddInput
(
"Ids"
,
"An input with type int32 or int64 "
"contains the ids to be looked up in W. "
"Ids must be a column vector with rank = 2. "
"The 2nd dimension size must be 1."
);
AddOutput
(
"Out"
,
"The lookup results, which have the same type as W."
);
AddAttr
<
bool
>
(
"is_sparse"
,
"(boolean, default false) "
"Sparse update."
)
...
...
@@ -90,15 +81,10 @@ class LookupTableOpMaker : public framework::OpProtoAndCheckerMaker {
Lookup Table Operator.
This operator is used to perform lookups on the parameter W,
then concatenated into a dense or sparse tensor.
The type of Ids(Input) is SelectedRows, Tensor or LoDTensor, when Ids's
type is SelectedRows, the rows of Ids contains the ids to be looked up in W;
when Ids's type is Tensor, this tensor contains the ids to be looked up in W
and it must be a column vector with rank = 2 while the 2nd dimension size must be 1,
at this time, Ids can carry the LoD (Level of Details) information, or not, and
the output only shares the LoD information with input Ids.
then concatenated into a dense tensor.
The input Ids can carry the LoD (Level of Details) information,
or not. And the output only shares the LoD information with input Ids.
)DOC"
);
}
...
...
paddle/fluid/operators/lookup_table_op.cu
浏览文件 @
5373fe29
...
...
@@ -23,7 +23,7 @@ namespace operators {
template
<
typename
T
,
int
BlockDimX
,
int
BlockDimY
,
int
GridDimX
,
bool
PaddingFlag
>
__global__
void
LookupTable
(
T
*
output
,
const
T
*
table
,
const
int64_t
*
ids
,
__global__
void
LookupTable
(
T
*
output
,
const
T
*
table
,
const
int64_t
*
ids
,
const
int64_t
N
,
const
int64_t
K
,
const
int64_t
D
,
const
int64_t
padding_idx
)
{
int
idx
=
threadIdx
.
x
;
...
...
@@ -33,8 +33,8 @@ __global__ void LookupTable(T* output, const T* table, const int64_t* ids,
int64_t
id
=
ids
[
idy
];
PADDLE_ASSERT
(
id
>=
0
);
PADDLE_ASSERT
(
id
<
N
);
T
*
out
=
output
+
idy
*
D
;
const
T
*
tab
=
table
+
id
*
D
;
T
*
out
=
output
+
idy
*
D
;
const
T
*
tab
=
table
+
id
*
D
;
for
(
int
i
=
idx
;
i
<
D
;
i
+=
BlockDimX
)
{
if
(
PaddingFlag
)
{
if
(
id
==
padding_idx
)
...
...
@@ -50,7 +50,7 @@ __global__ void LookupTable(T* output, const T* table, const int64_t* ids,
}
template
<
typename
T
,
int
BlockDimX
,
int
BlockDimY
,
int
GridDimX
>
__global__
void
LookupTableGrad
(
T
*
table
,
const
T
*
output
,
const
int64_t
*
ids
,
__global__
void
LookupTableGrad
(
T
*
table
,
const
T
*
output
,
const
int64_t
*
ids
,
const
int64_t
N
,
const
int64_t
K
,
const
int64_t
D
)
{
int
idx
=
threadIdx
.
x
;
...
...
@@ -60,8 +60,8 @@ __global__ void LookupTableGrad(T* table, const T* output, const int64_t* ids,
int
id
=
ids
[
idy
];
PADDLE_ASSERT
(
id
>=
0
);
PADDLE_ASSERT
(
id
<
N
);
const
T
*
out
=
output
+
idy
*
D
;
T
*
tab
=
table
+
id
*
D
;
const
T
*
out
=
output
+
idy
*
D
;
T
*
tab
=
table
+
id
*
D
;
for
(
int
i
=
idx
;
i
<
D
;
i
+=
BlockDimX
)
{
paddle
::
platform
::
CudaAtomicAdd
(
&
tab
[
i
],
out
[
i
]);
}
...
...
@@ -72,36 +72,19 @@ __global__ void LookupTableGrad(T* table, const T* output, const int64_t* ids,
template
<
typename
T
>
class
LookupTableCUDAKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
*
table_t
=
context
.
Input
<
LoDTensor
>
(
"W"
);
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
*
table_t
=
context
.
Input
<
LoDTensor
>
(
"W"
);
auto
*
ids_t
=
context
.
Input
<
LoDTensor
>
(
"Ids"
);
auto
*
output_t
=
context
.
Output
<
LoDTensor
>
(
"Out"
);
int64_t
padding_idx
=
context
.
Attr
<
int64_t
>
(
"padding_idx"
);
auto
*
ids_var
=
context
.
InputVar
(
"Ids"
);
Tensor
*
output_t
=
context
.
Output
<
Tensor
>
(
"Out"
);
int64_t
*
ids
;
int64_t
K
;
// The type of Ids(Input) is SelectedRows or LoDTensor, when Ids's type
// is LoDTensor, this tensor contains the ids to be looked up in W;
// when Ids's type is SelectedRows, the rows of Ids contains the
// ids to be looked up in W.
if
(
ids_var
->
IsType
<
framework
::
LoDTensor
>
())
{
auto
*
ids_t
=
context
.
Input
<
LoDTensor
>
(
"Ids"
);
ids
=
const_cast
<
int64_t
*>
(
ids_t
->
data
<
int64_t
>
());
K
=
ids_t
->
numel
();
}
else
if
(
ids_var
->
IsType
<
framework
::
SelectedRows
>
())
{
auto
*
ids_t
=
context
.
Input
<
framework
::
SelectedRows
>
(
"Ids"
);
ids
=
const_cast
<
int64_t
*>
(
ids_t
->
rows
().
CUDAData
(
context
.
GetPlace
()));
K
=
ids_t
->
rows
().
size
();
output_t
->
Resize
({
K
,
table_t
->
dims
()[
1
]});
}
else
{
PADDLE_THROW
(
"Unsupported Variable Type of Ids"
);
}
size_t
N
=
table_t
->
dims
()[
0
];
size_t
D
=
table_t
->
dims
()[
1
];
auto
*
table
=
table_t
->
data
<
T
>
();
auto
*
output
=
output_t
->
mutable_data
<
T
>
(
context
.
GetPlace
());
size_t
K
=
ids_t
->
numel
();
auto
*
ids
=
ids_t
->
data
<
int64_t
>
();
auto
*
table
=
table_t
->
data
<
T
>
();
auto
*
output
=
output_t
->
mutable_data
<
T
>
(
context
.
GetPlace
());
dim3
threads
(
128
,
8
);
dim3
grids
(
8
,
1
);
...
...
@@ -122,19 +105,19 @@ class LookupTableCUDAKernel : public framework::OpKernel<T> {
template
<
typename
T
>
class
LookupTableGradCUDAKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
&
dev_ctx
=
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
&
dev_ctx
=
context
.
template
device_context
<
platform
::
CUDADeviceContext
>();
bool
is_sparse
=
context
.
Attr
<
bool
>
(
"is_sparse"
);
// Since paddings are not trainable and fixed in forward, the gradient of
// paddings makes no sense and we don't deal with it in backward.
if
(
is_sparse
)
{
auto
*
ids
=
context
.
Input
<
LoDTensor
>
(
"Ids"
);
auto
*
table
=
context
.
Input
<
LoDTensor
>
(
"W"
);
auto
*
d_output
=
context
.
Input
<
LoDTensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
d_table
=
context
.
Output
<
SelectedRows
>
(
framework
::
GradVarName
(
"W"
));
auto
*
ids
=
context
.
Input
<
LoDTensor
>
(
"Ids"
);
auto
*
table
=
context
.
Input
<
LoDTensor
>
(
"W"
);
auto
*
d_output
=
context
.
Input
<
LoDTensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
d_table
=
context
.
Output
<
SelectedRows
>
(
framework
::
GradVarName
(
"W"
));
auto
*
ids_data
=
ids
->
data
<
int64_t
>
();
auto
*
ids_data
=
ids
->
data
<
int64_t
>
();
auto
ids_dim
=
ids
->
dims
();
auto
stream
=
dev_ctx
.
stream
();
...
...
@@ -150,12 +133,12 @@ class LookupTableGradCUDAKernel : public framework::OpKernel<T> {
d_table
->
set_rows
(
new_rows
);
auto
*
d_table_value
=
d_table
->
mutable_value
();
auto
*
d_table_value
=
d_table
->
mutable_value
();
d_table_value
->
Resize
({
ids_dim
[
0
],
table
->
dims
()[
1
]});
d_table_value
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
*
d_table_data
=
d_table_value
->
data
<
T
>
();
auto
*
d_output_data
=
d_output
->
data
<
T
>
();
auto
*
d_table_data
=
d_table_value
->
data
<
T
>
();
auto
*
d_output_data
=
d_output
->
data
<
T
>
();
PADDLE_ENFORCE_EQ
(
d_table_value
->
dims
(),
d_output
->
dims
());
memory
::
Copy
(
gpu_place
,
d_table_data
,
gpu_place
,
d_output_data
,
d_output
->
numel
()
*
sizeof
(
T
),
stream
);
...
...
@@ -168,9 +151,9 @@ class LookupTableGradCUDAKernel : public framework::OpKernel<T> {
int
N
=
d_table_t
->
dims
()[
0
];
int
D
=
d_table_t
->
dims
()[
1
];
int
K
=
ids_t
->
numel
();
const
int64_t
*
ids
=
ids_t
->
data
<
int64_t
>
();
const
T
*
d_output
=
d_output_t
->
data
<
T
>
();
T
*
d_table
=
d_table_t
->
mutable_data
<
T
>
(
context
.
GetPlace
());
const
int64_t
*
ids
=
ids_t
->
data
<
int64_t
>
();
const
T
*
d_output
=
d_output_t
->
data
<
T
>
();
T
*
d_table
=
d_table_t
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
t
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
d_table_t
);
t
.
device
(
*
dev_ctx
.
eigen_device
())
=
t
.
constant
(
static_cast
<
T
>
(
0
));
...
...
paddle/fluid/operators/lookup_table_op.h
浏览文件 @
5373fe29
...
...
@@ -36,43 +36,13 @@ template <typename T>
class
LookupTableKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
*
ids_t
=
context
.
Input
<
LoDTensor
>
(
"Ids"
);
// int tensor
auto
*
output_t
=
context
.
Output
<
LoDTensor
>
(
"Out"
);
// float tensor
auto
*
table_var
=
context
.
InputVar
(
"W"
);
auto
*
ids_var
=
context
.
InputVar
(
"Ids"
);
Tensor
*
output_t
=
context
.
Output
<
Tensor
>
(
"Out"
);
int64_t
padding_idx
=
context
.
Attr
<
int64_t
>
(
"padding_idx"
);
DDim
table_dim
;
if
(
table_var
->
IsType
<
LoDTensor
>
())
{
table_dim
=
context
.
Input
<
LoDTensor
>
(
"W"
)
->
dims
();
}
else
if
(
table_var
->
IsType
<
SelectedRows
>
())
{
auto
*
table_t
=
context
.
Input
<
SelectedRows
>
(
"W"
);
table_dim
=
table_t
->
value
().
dims
();
}
else
{
PADDLE_THROW
(
"The parameter W of a LookupTable "
"must be either LoDTensor or SelectedRows"
);
}
int64_t
*
ids
;
int64_t
ids_numel
;
// The type of Ids(Input) is SelectedRows or LoDTensor, when Ids's type
// is LoDTensor, this tensor contains the ids to be looked up in W;
// when Ids's type is SelectedRows, the rows of Ids contains the
// ids to be looked up in W.
if
(
ids_var
->
IsType
<
LoDTensor
>
())
{
auto
*
ids_t
=
context
.
Input
<
LoDTensor
>
(
"Ids"
);
ids
=
const_cast
<
int64_t
*>
(
ids_t
->
data
<
int64_t
>
());
ids_numel
=
ids_t
->
numel
();
}
else
if
(
ids_var
->
IsType
<
SelectedRows
>
())
{
auto
*
ids_t
=
context
.
Input
<
SelectedRows
>
(
"Ids"
);
ids
=
const_cast
<
int64_t
*>
(
ids_t
->
rows
().
data
());
ids_numel
=
ids_t
->
rows
().
size
();
output_t
->
Resize
({
ids_numel
,
table_dim
[
1
]});
}
else
{
PADDLE_THROW
(
"Unsupported Variable Type of Ids"
);
}
int64_t
padding_idx
=
context
.
Attr
<
int64_t
>
(
"padding_idx"
);
int64_t
*
ids
=
const_cast
<
int64_t
*>
(
ids_t
->
data
<
int64_t
>
());
int64_t
ids_numel
=
ids_t
->
numel
();
if
(
table_var
->
IsType
<
LoDTensor
>
())
{
auto
*
table_t
=
context
.
Input
<
LoDTensor
>
(
"W"
);
...
...
paddle/fluid/operators/tensorrt_engine_op.cc
浏览文件 @
5373fe29
...
...
@@ -163,7 +163,4 @@ REGISTER_OP_CPU_KERNEL(
ops
::
TensorRTEngineKernel
<
paddle
::
platform
::
CPUDeviceContext
,
int
>
,
ops
::
TensorRTEngineKernel
<
paddle
::
platform
::
CPUDeviceContext
,
int64_t
>
);
// A trick to compile with the needed TensorRT op converter.
USE_TRT_CONVERTER
(
mul
)
#endif // PADDLE_WITH_CUDA
paddle/fluid/platform/cpu_helper.cc
浏览文件 @
5373fe29
...
...
@@ -16,6 +16,7 @@ limitations under the License. */
#include "paddle/fluid/platform/enforce.h"
#ifdef PADDLE_WITH_MKLML
#include <omp.h>
#include "paddle/fluid/platform/dynload/mklml.h"
#endif
...
...
@@ -33,6 +34,7 @@ void SetNumThreads(int num_threads) {
#elif defined(PADDLE_WITH_MKLML)
int
real_num_threads
=
num_threads
>
1
?
num_threads
:
1
;
platform
::
dynload
::
MKL_Set_Num_Threads
(
real_num_threads
);
omp_set_num_threads
(
num_threads
);
#else
PADDLE_ENFORCE
(
false
,
"To be implemented."
);
#endif
...
...
paddle/fluid/platform/init.cc
浏览文件 @
5373fe29
...
...
@@ -23,6 +23,9 @@ limitations under the License. */
#include "paddle/fluid/platform/place.h"
#include "paddle/fluid/string/piece.h"
DEFINE_int32
(
paddle_num_threads
,
1
,
"Number of threads for each paddle instance."
);
namespace
paddle
{
namespace
framework
{
...
...
@@ -115,7 +118,7 @@ void InitDevices(bool init_p2p, const std::vector<int> devices) {
places
.
emplace_back
(
platform
::
CPUPlace
());
platform
::
DeviceContextPool
::
Init
(
places
);
#ifndef PADDLE_WITH_MKLDNN
platform
::
SetNumThreads
(
1
);
platform
::
SetNumThreads
(
FLAGS_paddle_num_threads
);
#endif
}
...
...
patches/grpc/completion_queue.h
0 → 100644
浏览文件 @
5373fe29
// 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.
/// A completion queue implements a concurrent producer-consumer queue, with
/// two main API-exposed methods: \a Next and \a AsyncNext. These
/// methods are the essential component of the gRPC C++ asynchronous API.
/// There is also a \a Shutdown method to indicate that a given completion queue
/// will no longer have regular events. This must be called before the
/// completion queue is destroyed.
/// All completion queue APIs are thread-safe and may be used concurrently with
/// any other completion queue API invocation; it is acceptable to have
/// multiple threads calling \a Next or \a AsyncNext on the same or different
/// completion queues, or to call these methods concurrently with a \a Shutdown
/// elsewhere.
/// \remark{All other API calls on completion queue should be completed before
/// a completion queue destructor is called.}
#ifndef GRPCPP_IMPL_CODEGEN_COMPLETION_QUEUE_H
#define GRPCPP_IMPL_CODEGEN_COMPLETION_QUEUE_H
#include <typeinfo>
#include <grpc/impl/codegen/atm.h>
#include <grpcpp/impl/codegen/completion_queue_tag.h>
#include <grpcpp/impl/codegen/core_codegen_interface.h>
#include <grpcpp/impl/codegen/grpc_library.h>
#include <grpcpp/impl/codegen/status.h>
#include <grpcpp/impl/codegen/time.h>
struct
grpc_completion_queue
;
namespace
grpc
{
template
<
class
R
>
class
ClientReader
;
template
<
class
W
>
class
ClientWriter
;
template
<
class
W
,
class
R
>
class
ClientReaderWriter
;
template
<
class
R
>
class
ServerReader
;
template
<
class
W
>
class
ServerWriter
;
namespace
internal
{
template
<
class
W
,
class
R
>
class
ServerReaderWriterBody
;
}
// namespace internal
class
Channel
;
class
ChannelInterface
;
class
ClientContext
;
class
CompletionQueue
;
class
Server
;
class
ServerBuilder
;
class
ServerContext
;
class
ServerInterface
;
namespace
internal
{
class
CompletionQueueTag
;
class
RpcMethod
;
template
<
class
ServiceType
,
class
RequestType
,
class
ResponseType
>
class
RpcMethodHandler
;
template
<
class
ServiceType
,
class
RequestType
,
class
ResponseType
>
class
ClientStreamingHandler
;
template
<
class
ServiceType
,
class
RequestType
,
class
ResponseType
>
class
ServerStreamingHandler
;
template
<
class
ServiceType
,
class
RequestType
,
class
ResponseType
>
class
BidiStreamingHandler
;
class
UnknownMethodHandler
;
template
<
class
Streamer
,
bool
WriteNeeded
>
class
TemplatedBidiStreamingHandler
;
template
<
class
InputMessage
,
class
OutputMessage
>
class
BlockingUnaryCallImpl
;
}
// namespace internal
extern
CoreCodegenInterface
*
g_core_codegen_interface
;
/// A thin wrapper around \ref grpc_completion_queue (see \ref
/// src/core/lib/surface/completion_queue.h).
/// See \ref doc/cpp/perf_notes.md for notes on best practices for high
/// performance servers.
class
CompletionQueue
:
private
GrpcLibraryCodegen
{
public:
/// Default constructor. Implicitly creates a \a grpc_completion_queue
/// instance.
CompletionQueue
()
:
CompletionQueue
(
grpc_completion_queue_attributes
{
GRPC_CQ_CURRENT_VERSION
,
GRPC_CQ_NEXT
,
GRPC_CQ_DEFAULT_POLLING
})
{}
/// Wrap \a take, taking ownership of the instance.
///
/// \param take The completion queue instance to wrap. Ownership is taken.
explicit
CompletionQueue
(
grpc_completion_queue
*
take
);
/// Destructor. Destroys the owned wrapped completion queue / instance.
~
CompletionQueue
()
{
if
(
typeid
(
*
g_core_codegen_interface
).
hash_code
()
!=
typeid
(
CoreCodegenInterface
).
hash_code
())
{
g_core_codegen_interface
->
grpc_completion_queue_destroy
(
cq_
);
}
}
/// Tri-state return for AsyncNext: SHUTDOWN, GOT_EVENT, TIMEOUT.
enum
NextStatus
{
SHUTDOWN
,
///< The completion queue has been shutdown and fully-drained
GOT_EVENT
,
///< Got a new event; \a tag will be filled in with its
///< associated value; \a ok indicating its success.
TIMEOUT
///< deadline was reached.
};
/// Read from the queue, blocking until an event is available or the queue is
/// shutting down.
///
/// \param tag[out] Updated to point to the read event's tag.
/// \param ok[out] true if read a successful event, false otherwise.
///
/// Note that each tag sent to the completion queue (through RPC operations
/// or alarms) will be delivered out of the completion queue by a call to
/// Next (or a related method), regardless of whether the operation succeeded
/// or not. Success here means that this operation completed in the normal
/// valid manner.
///
/// Server-side RPC request: \a ok indicates that the RPC has indeed
/// been started. If it is false, the server has been Shutdown
/// before this particular call got matched to an incoming RPC.
///
/// Client-side StartCall/RPC invocation: \a ok indicates that the RPC is
/// going to go to the wire. If it is false, it not going to the wire. This
/// would happen if the channel is either permanently broken or
/// transiently broken but with the fail-fast option. (Note that async unary
/// RPCs don't post a CQ tag at this point, nor do client-streaming
/// or bidi-streaming RPCs that have the initial metadata corked option set.)
///
/// Client-side Write, Client-side WritesDone, Server-side Write,
/// Server-side Finish, Server-side SendInitialMetadata (which is
/// typically included in Write or Finish when not done explicitly):
/// \a ok means that the data/metadata/status/etc is going to go to the
/// wire. If it is false, it not going to the wire because the call
/// is already dead (i.e., canceled, deadline expired, other side
/// dropped the channel, etc).
///
/// Client-side Read, Server-side Read, Client-side
/// RecvInitialMetadata (which is typically included in Read if not
/// done explicitly): \a ok indicates whether there is a valid message
/// that got read. If not, you know that there are certainly no more
/// messages that can ever be read from this stream. For the client-side
/// operations, this only happens because the call is dead. For the
/// server-sider operation, though, this could happen because the client
/// has done a WritesDone already.
///
/// Client-side Finish: \a ok should always be true
///
/// Server-side AsyncNotifyWhenDone: \a ok should always be true
///
/// Alarm: \a ok is true if it expired, false if it was canceled
///
/// \return true if got an event, false if the queue is fully drained and
/// shut down.
bool
Next
(
void
**
tag
,
bool
*
ok
)
{
return
(
AsyncNextInternal
(
tag
,
ok
,
g_core_codegen_interface
->
gpr_inf_future
(
GPR_CLOCK_REALTIME
))
!=
SHUTDOWN
);
}
/// Read from the queue, blocking up to \a deadline (or the queue's shutdown).
/// Both \a tag and \a ok are updated upon success (if an event is available
/// within the \a deadline). A \a tag points to an arbitrary location usually
/// employed to uniquely identify an event.
///
/// \param tag[out] Upon sucess, updated to point to the event's tag.
/// \param ok[out] Upon sucess, true if a successful event, false otherwise
/// See documentation for CompletionQueue::Next for explanation of ok
/// \param deadline[in] How long to block in wait for an event.
///
/// \return The type of event read.
template
<
typename
T
>
NextStatus
AsyncNext
(
void
**
tag
,
bool
*
ok
,
const
T
&
deadline
)
{
TimePoint
<
T
>
deadline_tp
(
deadline
);
return
AsyncNextInternal
(
tag
,
ok
,
deadline_tp
.
raw_time
());
}
/// EXPERIMENTAL
/// First executes \a F, then reads from the queue, blocking up to
/// \a deadline (or the queue's shutdown).
/// Both \a tag and \a ok are updated upon success (if an event is available
/// within the \a deadline). A \a tag points to an arbitrary location usually
/// employed to uniquely identify an event.
///
/// \param F[in] Function to execute before calling AsyncNext on this queue.
/// \param tag[out] Upon sucess, updated to point to the event's tag.
/// \param ok[out] Upon sucess, true if read a regular event, false otherwise.
/// \param deadline[in] How long to block in wait for an event.
///
/// \return The type of event read.
template
<
typename
T
,
typename
F
>
NextStatus
DoThenAsyncNext
(
F
&&
f
,
void
**
tag
,
bool
*
ok
,
const
T
&
deadline
)
{
CompletionQueueTLSCache
cache
=
CompletionQueueTLSCache
(
this
);
f
();
if
(
cache
.
Flush
(
tag
,
ok
))
{
return
GOT_EVENT
;
}
else
{
return
AsyncNext
(
tag
,
ok
,
deadline
);
}
}
/// Request the shutdown of the queue.
///
/// \warning This method must be called at some point if this completion queue
/// is accessed with Next or AsyncNext. \a Next will not return false
/// until this method has been called and all pending tags have been drained.
/// (Likewise for \a AsyncNext returning \a NextStatus::SHUTDOWN .)
/// Only once either one of these methods does that (that is, once the queue
/// has been \em drained) can an instance of this class be destroyed.
/// Also note that applications must ensure that no work is enqueued on this
/// completion queue after this method is called.
void
Shutdown
();
/// Returns a \em raw pointer to the underlying \a grpc_completion_queue
/// instance.
///
/// \warning Remember that the returned instance is owned. No transfer of
/// owership is performed.
grpc_completion_queue
*
cq
()
{
return
cq_
;
}
protected:
/// Private constructor of CompletionQueue only visible to friend classes
CompletionQueue
(
const
grpc_completion_queue_attributes
&
attributes
)
{
cq_
=
g_core_codegen_interface
->
grpc_completion_queue_create
(
g_core_codegen_interface
->
grpc_completion_queue_factory_lookup
(
&
attributes
),
&
attributes
,
NULL
);
InitialAvalanching
();
// reserve this for the future shutdown
}
private:
// Friend synchronous wrappers so that they can access Pluck(), which is
// a semi-private API geared towards the synchronous implementation.
template
<
class
R
>
friend
class
::
grpc
::
ClientReader
;
template
<
class
W
>
friend
class
::
grpc
::
ClientWriter
;
template
<
class
W
,
class
R
>
friend
class
::
grpc
::
ClientReaderWriter
;
template
<
class
R
>
friend
class
::
grpc
::
ServerReader
;
template
<
class
W
>
friend
class
::
grpc
::
ServerWriter
;
template
<
class
W
,
class
R
>
friend
class
::
grpc
::
internal
::
ServerReaderWriterBody
;
template
<
class
ServiceType
,
class
RequestType
,
class
ResponseType
>
friend
class
::
grpc
::
internal
::
RpcMethodHandler
;
template
<
class
ServiceType
,
class
RequestType
,
class
ResponseType
>
friend
class
::
grpc
::
internal
::
ClientStreamingHandler
;
template
<
class
ServiceType
,
class
RequestType
,
class
ResponseType
>
friend
class
::
grpc
::
internal
::
ServerStreamingHandler
;
template
<
class
Streamer
,
bool
WriteNeeded
>
friend
class
::
grpc
::
internal
::
TemplatedBidiStreamingHandler
;
friend
class
::
grpc
::
internal
::
UnknownMethodHandler
;
friend
class
::
grpc
::
Server
;
friend
class
::
grpc
::
ServerContext
;
friend
class
::
grpc
::
ServerInterface
;
template
<
class
InputMessage
,
class
OutputMessage
>
friend
class
::
grpc
::
internal
::
BlockingUnaryCallImpl
;
/// EXPERIMENTAL
/// Creates a Thread Local cache to store the first event
/// On this completion queue queued from this thread. Once
/// initialized, it must be flushed on the same thread.
class
CompletionQueueTLSCache
{
public:
CompletionQueueTLSCache
(
CompletionQueue
*
cq
);
~
CompletionQueueTLSCache
();
bool
Flush
(
void
**
tag
,
bool
*
ok
);
private:
CompletionQueue
*
cq_
;
bool
flushed_
;
};
NextStatus
AsyncNextInternal
(
void
**
tag
,
bool
*
ok
,
gpr_timespec
deadline
);
/// Wraps \a grpc_completion_queue_pluck.
/// \warning Must not be mixed with calls to \a Next.
bool
Pluck
(
internal
::
CompletionQueueTag
*
tag
)
{
auto
deadline
=
g_core_codegen_interface
->
gpr_inf_future
(
GPR_CLOCK_REALTIME
);
auto
ev
=
g_core_codegen_interface
->
grpc_completion_queue_pluck
(
cq_
,
tag
,
deadline
,
nullptr
);
bool
ok
=
ev
.
success
!=
0
;
void
*
ignored
=
tag
;
GPR_CODEGEN_ASSERT
(
tag
->
FinalizeResult
(
&
ignored
,
&
ok
));
GPR_CODEGEN_ASSERT
(
ignored
==
tag
);
// Ignore mutations by FinalizeResult: Pluck returns the C API status
return
ev
.
success
!=
0
;
}
/// Performs a single polling pluck on \a tag.
/// \warning Must not be mixed with calls to \a Next.
///
/// TODO: sreek - This calls tag->FinalizeResult() even if the cq_ is already
/// shutdown. This is most likely a bug and if it is a bug, then change this
/// implementation to simple call the other TryPluck function with a zero
/// timeout. i.e:
/// TryPluck(tag, gpr_time_0(GPR_CLOCK_REALTIME))
void
TryPluck
(
internal
::
CompletionQueueTag
*
tag
)
{
auto
deadline
=
g_core_codegen_interface
->
gpr_time_0
(
GPR_CLOCK_REALTIME
);
auto
ev
=
g_core_codegen_interface
->
grpc_completion_queue_pluck
(
cq_
,
tag
,
deadline
,
nullptr
);
if
(
ev
.
type
==
GRPC_QUEUE_TIMEOUT
)
return
;
bool
ok
=
ev
.
success
!=
0
;
void
*
ignored
=
tag
;
// the tag must be swallowed if using TryPluck
GPR_CODEGEN_ASSERT
(
!
tag
->
FinalizeResult
(
&
ignored
,
&
ok
));
}
/// Performs a single polling pluck on \a tag. Calls tag->FinalizeResult if
/// the pluck() was successful and returned the tag.
///
/// This exects tag->FinalizeResult (if called) to return 'false' i.e expects
/// that the tag is internal not something that is returned to the user.
void
TryPluck
(
internal
::
CompletionQueueTag
*
tag
,
gpr_timespec
deadline
)
{
auto
ev
=
g_core_codegen_interface
->
grpc_completion_queue_pluck
(
cq_
,
tag
,
deadline
,
nullptr
);
if
(
ev
.
type
==
GRPC_QUEUE_TIMEOUT
||
ev
.
type
==
GRPC_QUEUE_SHUTDOWN
)
{
return
;
}
bool
ok
=
ev
.
success
!=
0
;
void
*
ignored
=
tag
;
GPR_CODEGEN_ASSERT
(
!
tag
->
FinalizeResult
(
&
ignored
,
&
ok
));
}
/// Manage state of avalanching operations : completion queue tags that
/// trigger other completion queue operations. The underlying core completion
/// queue should not really shutdown until all avalanching operations have
/// been finalized. Note that we maintain the requirement that an avalanche
/// registration must take place before CQ shutdown (which must be maintained
/// elsehwere)
void
InitialAvalanching
()
{
gpr_atm_rel_store
(
&
avalanches_in_flight_
,
static_cast
<
gpr_atm
>
(
1
));
}
void
RegisterAvalanching
()
{
gpr_atm_no_barrier_fetch_add
(
&
avalanches_in_flight_
,
static_cast
<
gpr_atm
>
(
1
));
}
void
CompleteAvalanching
();
grpc_completion_queue
*
cq_
;
// owned
gpr_atm
avalanches_in_flight_
;
};
/// A specific type of completion queue used by the processing of notifications
/// by servers. Instantiated by \a ServerBuilder.
class
ServerCompletionQueue
:
public
CompletionQueue
{
public:
bool
IsFrequentlyPolled
()
{
return
polling_type_
!=
GRPC_CQ_NON_LISTENING
;
}
private:
grpc_cq_polling_type
polling_type_
;
friend
class
ServerBuilder
;
/// \param is_frequently_polled Informs the GRPC library about whether the
/// server completion queue would be actively polled (by calling Next() or
/// AsyncNext()). By default all server completion queues are assumed to be
/// frequently polled.
ServerCompletionQueue
(
grpc_cq_polling_type
polling_type
)
:
CompletionQueue
(
grpc_completion_queue_attributes
{
GRPC_CQ_CURRENT_VERSION
,
GRPC_CQ_NEXT
,
polling_type
}),
polling_type_
(
polling_type
)
{}
};
}
// namespace grpc
#endif // GRPCPP_IMPL_CODEGEN_COMPLETION_QUEUE_H
patches/grpc/fix_too_early_destory.patch
已删除
100644 → 0
浏览文件 @
687a3222
diff --git a/include/grpcpp/impl/codegen/completion_queue.h b/include/grpcpp/impl/codegen/completion_queue.h
index 80c7c41982..3f7d8a7714 100644
--- a/include/grpcpp/impl/codegen/completion_queue.h
+++ b/include/grpcpp/impl/codegen/completion_queue.h
@@ -32,6 +32,8 @@
#ifndef GRPCPP_IMPL_CODEGEN_COMPLETION_QUEUE_H
#define GRPCPP_IMPL_CODEGEN_COMPLETION_QUEUE_H
+#include <typeinfo>
+
#include <grpc/impl/codegen/atm.h>
#include <grpcpp/impl/codegen/completion_queue_tag.h>
#include <grpcpp/impl/codegen/core_codegen_interface.h>
@@ -106,7 +108,9 @@
class CompletionQueue : private GrpcLibraryCodegen {
/// Destructor. Destroys the owned wrapped completion queue / instance.
~CompletionQueue() {
- g_core_codegen_interface->grpc_completion_queue_destroy(cq_);
+ if (typeid(*g_core_codegen_interface).hash_code() != typeid(CoreCodegenInterface).hash_code()) {
+ g_core_codegen_interface->grpc_completion_queue_destroy(cq_);
+ }
}
/// Tri-state return for AsyncNext: SHUTDOWN, GOT_EVENT, TIMEOUT.
diff --git a/include/grpcpp/impl/codegen/grpc_library.h b/include/grpcpp/impl/codegen/grpc_library.h
index 17c904d71a..a092b2204d 100644
--- a/include/grpcpp/impl/codegen/grpc_library.h
+++ b/include/grpcpp/impl/codegen/grpc_library.h
@@ -19,6 +19,8 @@
#ifndef GRPCPP_IMPL_CODEGEN_GRPC_LIBRARY_H
#define GRPCPP_IMPL_CODEGEN_GRPC_LIBRARY_H
+#include <typeinfo>
+
#include <grpcpp/impl/codegen/core_codegen_interface.h>
namespace grpc {
@@ -47,7 +49,8 @@
class GrpcLibraryCodegen {
}
}
virtual ~GrpcLibraryCodegen() {
- if (grpc_init_called_) {
+ if (grpc_init_called_ &&
+ typeid(*g_glip).hash_code() != typeid(GrpcLibraryInterface).hash_code()) {
GPR_CODEGEN_ASSERT(g_glip &&
"gRPC library not initialized. See "
"grpc::internal::GrpcLibraryInitializer.");
patches/grpc/grpc_library.h
0 → 100644
浏览文件 @
5373fe29
// 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.
#ifndef GRPCPP_IMPL_CODEGEN_GRPC_LIBRARY_H
#define GRPCPP_IMPL_CODEGEN_GRPC_LIBRARY_H
#include <typeinfo>
#include <grpcpp/impl/codegen/core_codegen_interface.h>
namespace
grpc
{
class
GrpcLibraryInterface
{
public:
virtual
~
GrpcLibraryInterface
()
=
default
;
virtual
void
init
()
=
0
;
virtual
void
shutdown
()
=
0
;
};
/// Initialized by \a grpc::GrpcLibraryInitializer from
/// <grpcpp/impl/grpc_library.h>
extern
GrpcLibraryInterface
*
g_glip
;
/// Classes that require gRPC to be initialized should inherit from this class.
class
GrpcLibraryCodegen
{
public:
GrpcLibraryCodegen
(
bool
call_grpc_init
=
true
)
:
grpc_init_called_
(
false
)
{
if
(
call_grpc_init
)
{
GPR_CODEGEN_ASSERT
(
g_glip
&&
"gRPC library not initialized. See "
"grpc::internal::GrpcLibraryInitializer."
);
g_glip
->
init
();
grpc_init_called_
=
true
;
}
}
virtual
~
GrpcLibraryCodegen
()
{
if
(
grpc_init_called_
&&
typeid
(
*
g_glip
).
hash_code
()
!=
typeid
(
GrpcLibraryInterface
).
hash_code
())
{
GPR_CODEGEN_ASSERT
(
g_glip
&&
"gRPC library not initialized. See "
"grpc::internal::GrpcLibraryInitializer."
);
g_glip
->
shutdown
();
}
}
private:
bool
grpc_init_called_
;
};
}
// namespace grpc
#endif // GRPCPP_IMPL_CODEGEN_GRPC_LIBRARY_H
python/paddle/fluid/__init__.py
浏览文件 @
5373fe29
...
...
@@ -123,7 +123,7 @@ def __bootstrap__():
read_env_flags
=
[
'use_pinned_memory'
,
'check_nan_inf'
,
'benchmark'
,
'warpctc_dir'
,
'eager_delete_scope'
,
'use_mkldnn'
,
'initial_cpu_memory_in_mb'
,
'init_allocated_mem'
,
'free_idle_memory'
'init_allocated_mem'
,
'free_idle_memory'
,
'paddle_num_threads'
]
if
core
.
is_compiled_with_dist
():
read_env_flags
.
append
(
'rpc_deadline'
)
...
...
python/paddle/fluid/regularizer.py
浏览文件 @
5373fe29
...
...
@@ -142,14 +142,20 @@ class L2DecayRegularizer(WeightDecayRegularizer):
dtype
=
"float32"
,
shape
=
param
.
shape
,
lod_level
=
param
.
lod_level
)
if
grad
.
type
==
core
.
VarDesc
.
VarType
.
SELECTED_ROWS
:
idx
=
block
.
create_var
(
dtype
=
"int64"
,
shape
=
param
.
shape
,
type
=
core
.
VarDesc
.
VarType
.
LOD_TENSOR
)
decay
=
block
.
create_var
(
dtype
=
"float32"
,
shape
=
param
.
shape
,
type
=
core
.
VarDesc
.
VarType
.
SELECTED_ROWS
)
block
.
append_op
(
type
=
'extract_rows'
,
inputs
=
{
'X'
:
grad
},
outputs
=
{
'Out'
:
idx
})
block
.
append_op
(
type
=
'lookup_table'
,
inputs
=
{
'W'
:
param
,
'Ids'
:
grad
},
'Ids'
:
idx
},
outputs
=
{
'Out'
:
decay
},
attrs
=
{
'is_sparse'
:
True
})
param
=
decay
...
...
@@ -216,14 +222,20 @@ class L1DecayRegularizer(WeightDecayRegularizer):
dtype
=
"float32"
,
shape
=
param
.
shape
,
lod_level
=
param
.
lod_level
)
if
grad
.
type
==
core
.
VarDesc
.
VarType
.
SELECTED_ROWS
:
idx
=
block
.
create_var
(
dtype
=
"int64"
,
shape
=
param
.
shape
,
type
=
core
.
VarDesc
.
VarType
.
LOD_TENSOR
)
decay
=
block
.
create_var
(
dtype
=
"float32"
,
shape
=
param
.
shape
,
type
=
core
.
VarDesc
.
VarType
.
SELECTED_ROWS
)
block
.
append_op
(
type
=
'extract_rows'
,
inputs
=
{
'X'
:
grad
},
outputs
=
{
'Out'
:
idx
})
block
.
append_op
(
type
=
'lookup_table'
,
inputs
=
{
'W'
:
param
,
'Ids'
:
grad
},
'Ids'
:
idx
},
outputs
=
{
'Out'
:
decay
},
attrs
=
{
'is_sparse'
:
True
})
...
...
python/paddle/fluid/tests/unittests/dist_se_resnext.py
浏览文件 @
5373fe29
...
...
@@ -278,7 +278,7 @@ class DistSeResneXt2x2:
def
run_trainer
(
self
,
place
,
endpoints
,
trainer_id
,
trainers
,
is_dist
=
True
):
test_program
,
avg_cost
,
train_reader
,
test_reader
,
batch_acc
,
predict
=
get_model
(
batch_size
=
2
0
)
batch_size
=
2
)
if
is_dist
:
t
=
get_transpiler
(
trainer_id
,
fluid
.
default_main_program
(),
endpoints
,
...
...
@@ -294,11 +294,7 @@ class DistSeResneXt2x2:
strategy
.
num_threads
=
1
strategy
.
allow_op_delay
=
False
exe
=
fluid
.
ParallelExecutor
(
True
,
loss_name
=
avg_cost
.
name
,
exec_strategy
=
strategy
,
num_trainers
=
trainers
,
trainer_id
=
trainer_id
)
True
,
loss_name
=
avg_cost
.
name
,
exec_strategy
=
strategy
)
feed_var_list
=
[
var
for
var
in
trainer_prog
.
global_block
().
vars
.
itervalues
()
...
...
python/paddle/fluid/tests/unittests/test_dist_se_resnext.py
浏览文件 @
5373fe29
...
...
@@ -56,7 +56,7 @@ class TestDistSeResneXt2x2(unittest.TestCase):
except
os
.
error
:
retry_times
-=
1
def
no
n
_test_with_place
(
self
):
def
no_test_with_place
(
self
):
# *ATTENTION* THIS TEST NEEDS AT LEAST 2GPUS TO RUN
required_envs
=
{
"PATH"
:
os
.
getenv
(
"PATH"
),
...
...
python/paddle/fluid/tests/unittests/test_extract_rows_op.py
0 → 100644
浏览文件 @
5373fe29
# 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.
import
unittest
import
numpy
as
np
import
paddle.fluid.core
as
core
from
paddle.fluid.op
import
Operator
from
op_test
import
OpTest
class
TestExtractRows
(
OpTest
):
def
check_with_place
(
self
,
place
):
scope
=
core
.
Scope
()
# create and initialize Variable
feature_len
=
12
rows
=
[
0
,
4
,
4
,
7
]
np_array
=
np
.
ones
((
len
(
rows
),
feature_len
)).
astype
(
"float32"
)
in_x
=
scope
.
var
(
'X'
).
get_selected_rows
()
in_x
.
set_height
(
len
(
rows
))
in_x
.
set_rows
(
rows
)
in_x_tensor
=
in_x
.
get_tensor
()
in_x_tensor
.
set
(
np_array
,
place
)
# create Out Variable
out_tensor
=
scope
.
var
(
'Out'
).
get_tensor
()
# create and run lookup_table operator
extract_rows_op
=
Operator
(
"extract_rows"
,
X
=
'X'
,
Out
=
'Out'
)
extract_rows_op
.
run
(
scope
,
place
)
# get result from Out
result_array
=
np
.
array
(
out_tensor
)
result_array
=
[
ele
[
0
]
for
ele
in
result_array
]
assert
result_array
==
rows
def
test_concat_rows
(
self
):
places
=
[
core
.
CPUPlace
()]
if
core
.
is_compiled_with_cuda
():
places
.
append
(
core
.
CUDAPlace
(
0
))
for
place
in
places
:
self
.
check_with_place
(
place
)
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/test_flatten_op.py
0 → 100644
浏览文件 @
5373fe29
# 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.
import
unittest
import
numpy
as
np
from
op_test
import
OpTest
class
TestFlattenOp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"flatten"
self
.
init_test_case
()
self
.
inputs
=
{
"X"
:
np
.
random
.
random
(
self
.
in_shape
).
astype
(
"float32"
)}
self
.
init_attrs
()
self
.
outputs
=
{
"Out"
:
self
.
inputs
[
"X"
].
reshape
(
self
.
new_shape
)}
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
self
.
check_grad
([
"X"
],
"Out"
)
def
init_test_case
(
self
):
self
.
in_shape
=
(
3
,
2
,
2
,
5
)
self
.
axis
=
1
self
.
new_shape
=
(
3
,
20
)
def
init_attrs
(
self
):
self
.
attrs
=
{
"axis"
:
self
.
axis
}
class
TestFlattenOp
(
TestFlattenOp
):
def
init_test_case
(
self
):
self
.
in_shape
=
(
3
,
2
,
2
,
3
)
self
.
axis
=
0
self
.
new_shape
=
(
1
,
36
)
class
TestFlattenOpWithDefaultAxis
(
TestFlattenOp
):
def
init_test_case
(
self
):
self
.
in_shape
=
(
3
,
2
,
2
,
3
)
self
.
new_shape
=
(
3
,
12
)
def
init_attrs
(
self
):
self
.
attrs
=
{}
class
TestFlattenOpSixDims
(
TestFlattenOp
):
def
init_test_case
(
self
):
self
.
in_shape
=
(
3
,
2
,
3
,
2
,
4
,
4
)
self
.
axis
=
4
self
.
new_shape
=
(
36
,
16
)
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/test_lookup_table_op.py
浏览文件 @
5373fe29
...
...
@@ -49,53 +49,6 @@ class TestLookupTableOpWithPadding(TestLookupTableOp):
pass
class
TestLookupTableIdsIsSelectedRows
(
OpTest
):
def
check_with_place
(
self
,
place
):
scope
=
core
.
Scope
()
# create and initialize Variable
height
=
10
rows
=
[
0
,
4
,
4
,
7
]
row_numel
=
12
# create and initialize W Variable
W
=
scope
.
var
(
'W'
).
get_tensor
()
W_array
=
np
.
full
((
height
,
row_numel
),
1.0
).
astype
(
"float32"
)
for
i
in
range
(
height
):
W_array
[
i
]
*=
i
W
.
set
(
W_array
,
place
)
# create and initialize Ids Variable
ids_selected_rows
=
scope
.
var
(
'Ids'
).
get_selected_rows
()
ids_selected_rows
.
set_height
(
len
(
rows
))
ids_selected_rows
.
set_rows
(
rows
)
np_array
=
np
.
ones
((
len
(
rows
),
row_numel
)).
astype
(
"float32"
)
ids_tensor
=
ids_selected_rows
.
get_tensor
()
ids_tensor
.
set
(
np_array
,
place
)
# create Out Variable
Out
=
scope
.
var
(
'Out'
).
get_selected_rows
()
# create and run lookup_table operator
concat_rows_op
=
Operator
(
"lookup_table"
,
W
=
'W'
,
Ids
=
'Ids'
,
Out
=
'Out'
)
concat_rows_op
.
run
(
scope
,
place
)
# get result from Out
Out_tensor
=
Out
.
get_tensor
()
result_array
=
np
.
array
(
Out_tensor
)
# all(): return True if all elements of the iterable are true (or if the iterable is empty)
for
idx
,
row
in
enumerate
(
rows
):
assert
(
row
==
result_array
[
idx
]).
all
()
def
test_concat_rows
(
self
):
places
=
[
core
.
CPUPlace
()]
if
core
.
is_compiled_with_cuda
():
places
.
append
(
core
.
CUDAPlace
(
0
))
for
place
in
places
:
self
.
check_with_place
(
place
)
class
TestLookupTableWIsSelectedRows
(
OpTest
):
def
check_with_place
(
self
,
place
):
scope
=
core
.
Scope
()
...
...
tools/codestyle/cpplint_pre_commit.hook
浏览文件 @
5373fe29
...
...
@@ -4,7 +4,7 @@ TOTAL_ERRORS=0
# The trick to remove deleted files: https://stackoverflow.com/a/2413151
for
file
in
$(
git diff
--cached
--name-status
|
awk
'$1 != "D" {print $2}'
)
;
do
if
[[
$file
=
~ ^
(
paddle/legacy/api/.
*
|paddle/legacy/capi/.
*
|paddle/contrib/.
*
|paddle/legacy/cuda/.
*
|paddle/legacy/function/.
*
|paddle/legacy/gserver/.
*
|paddle/legacy/math/.
*
|paddle/legacy/optimizer/.
*
|paddle/legacy/parameter/.
*
|paddle/legacy/pserver/.
*
|paddle/legacy/trainer/.
*
|paddle/legacy/utils/.
*
|paddle/testing/TestUtil.
*
)
]]
;
then
if
[[
$file
=
~ ^
(
paddle/legacy/api/.
*
|paddle/legacy/capi/.
*
|paddle/contrib/.
*
|paddle/legacy/cuda/.
*
|paddle/legacy/function/.
*
|paddle/legacy/gserver/.
*
|paddle/legacy/math/.
*
|paddle/legacy/optimizer/.
*
|paddle/legacy/parameter/.
*
|paddle/legacy/pserver/.
*
|paddle/legacy/trainer/.
*
|paddle/legacy/utils/.
*
|paddle/testing/TestUtil.
*
|patches/grpc/.
*
)
]]
;
then
continue
;
else
cpplint
--filter
=
-readability
/fn_size
$file
;
...
...
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