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体验新版 GitCode,发现更多精彩内容 >>
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1800fef1
编写于
8月 14, 2018
作者:
M
minqiyang
浏览文件
操作
浏览文件
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差异文件
Merge branch 'develop' of
https://github.com/PaddlePaddle/Paddle
into port_pybind11
上级
92aa2061
83c85f34
变更
27
隐藏空白更改
内联
并排
Showing
27 changed file
with
309 addition
and
258 deletion
+309
-258
cmake/configure.cmake
cmake/configure.cmake
+8
-0
cmake/external/anakin.cmake
cmake/external/anakin.cmake
+45
-36
cmake/inference_lib.cmake
cmake/inference_lib.cmake
+1
-1
doc/fluid/api/executor.rst
doc/fluid/api/executor.rst
+0
-8
doc/fluid/api/fluid.rst
doc/fluid/api/fluid.rst
+0
-16
paddle/fluid/API.spec
paddle/fluid/API.spec
+0
-18
paddle/fluid/inference/analysis/analyzer.cc
paddle/fluid/inference/analysis/analyzer.cc
+3
-3
paddle/fluid/inference/api/CMakeLists.txt
paddle/fluid/inference/api/CMakeLists.txt
+12
-17
paddle/fluid/inference/api/paddle_inference_api.h
paddle/fluid/inference/api/paddle_inference_api.h
+1
-1
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
+4
-1
paddle/fluid/inference/tensorrt/convert/softmax_op.cc
paddle/fluid/inference/tensorrt/convert/softmax_op.cc
+49
-0
paddle/fluid/inference/tensorrt/convert/test_softmax_op.cc
paddle/fluid/inference/tensorrt/convert/test_softmax_op.cc
+49
-0
paddle/fluid/inference/tensorrt/convert/ut_helper.h
paddle/fluid/inference/tensorrt/convert/ut_helper.h
+17
-7
paddle/fluid/operators/elementwise_add_op.cu
paddle/fluid/operators/elementwise_add_op.cu
+0
-54
paddle/fluid/operators/elementwise_add_op.h
paddle/fluid/operators/elementwise_add_op.h
+8
-33
paddle/fluid/pybind/pybind.cc
paddle/fluid/pybind/pybind.cc
+1
-1
python/paddle/fluid/__init__.py
python/paddle/fluid/__init__.py
+1
-3
python/paddle/fluid/concurrency.py
python/paddle/fluid/concurrency.py
+3
-4
python/paddle/fluid/executor.py
python/paddle/fluid/executor.py
+34
-34
python/paddle/fluid/parallel_executor.py
python/paddle/fluid/parallel_executor.py
+3
-3
python/paddle/fluid/tests/unittests/test_dist_transpiler.py
python/paddle/fluid/tests/unittests/test_dist_transpiler.py
+30
-0
python/paddle/fluid/tests/unittests/test_fetch_var.py
python/paddle/fluid/tests/unittests/test_fetch_var.py
+1
-1
python/paddle/fluid/tests/unittests/test_py_reader_push_pop.py
...n/paddle/fluid/tests/unittests/test_py_reader_push_pop.py
+2
-1
python/paddle/fluid/tests/unittests/transformer_model.py
python/paddle/fluid/tests/unittests/transformer_model.py
+1
-1
python/paddle/fluid/transpiler/distribute_transpiler.py
python/paddle/fluid/transpiler/distribute_transpiler.py
+31
-10
python/paddle/fluid/transpiler/inference_transpiler.py
python/paddle/fluid/transpiler/inference_transpiler.py
+4
-4
python/requirements.txt
python/requirements.txt
+1
-1
未找到文件。
cmake/configure.cmake
浏览文件 @
1800fef1
...
...
@@ -97,6 +97,14 @@ if(WITH_GPU)
endif
()
include_directories
(
${
TENSORRT_INCLUDE_DIR
}
)
endif
()
if
(
WITH_ANAKIN
)
if
(
${
CUDA_VERSION_MAJOR
}
VERSION_LESS 8
)
message
(
FATAL_ERROR
"Anakin needs CUDA >= 8.0 to compile"
)
endif
()
if
(
${
CUDNN_MAJOR_VERSION
}
VERSION_LESS 7
)
message
(
FATAL_ERROR
"Anakin needs CUDNN >= 7.0 to compile"
)
endif
()
endif
()
elseif
(
WITH_AMD_GPU
)
add_definitions
(
-DPADDLE_WITH_HIP
)
set
(
CMAKE_C_FLAGS
"
${
CMAKE_C_FLAGS
}
-D__HIP_PLATFORM_HCC__"
)
...
...
cmake/external/anakin.cmake
浏览文件 @
1800fef1
...
...
@@ -2,10 +2,22 @@ if (NOT WITH_ANAKIN)
return
()
endif
()
set
(
ANAKIN_INSTALL_DIR
"
${
THIRD_PARTY_PATH
}
/install/anakin"
CACHE PATH
"Anakin install path."
FORCE
)
set
(
ANAKIN_INCLUDE
"
${
ANAKIN_INSTALL_DIR
}
"
CACHE STRING
"root of Anakin header files"
)
set
(
ANAKIN_LIBRARY
"
${
ANAKIN_INSTALL_DIR
}
"
CACHE STRING
"path of Anakin library"
)
INCLUDE
(
ExternalProject
)
set
(
ANAKIN_SOURCE_DIR
${
THIRD_PARTY_PATH
}
/anakin
)
# the anakin install dir is only default one now
set
(
ANAKIN_INSTALL_DIR
${
THIRD_PARTY_PATH
}
/anakin/src/extern_anakin/output
)
set
(
ANAKIN_INCLUDE
${
ANAKIN_INSTALL_DIR
}
)
set
(
ANAKIN_LIBRARY
${
ANAKIN_INSTALL_DIR
}
)
set
(
ANAKIN_SHARED_LIB
${
ANAKIN_LIBRARY
}
/libanakin.so
)
set
(
ANAKIN_SABER_LIB
${
ANAKIN_LIBRARY
}
/libanakin_saber_common.so
)
# TODO(luotao): ANAKIN_MODLE_URL will move to demo ci later.
set
(
ANAKIN_MODLE_URL
"http://paddle-inference-dist.bj.bcebos.com/mobilenet_v2.anakin.bin"
)
execute_process
(
COMMAND bash -c
"mkdir -p
${
ANAKIN_SOURCE_DIR
}
"
)
execute_process
(
COMMAND bash -c
"cd
${
ANAKIN_SOURCE_DIR
}
; wget -q --no-check-certificate
${
ANAKIN_MODLE_URL
}
"
)
include_directories
(
${
ANAKIN_INCLUDE
}
)
include_directories
(
${
ANAKIN_INCLUDE
}
/saber/
)
set
(
ANAKIN_COMPILE_EXTRA_FLAGS
-Wno-error=unused-but-set-variable -Wno-unused-but-set-variable
...
...
@@ -20,36 +32,33 @@ set(ANAKIN_COMPILE_EXTRA_FLAGS
-Wno-reorder
-Wno-error=cpp
)
set
(
ANAKIN_LIBRARY_URL
"https://github.com/pangge/Anakin/releases/download/Version0.1.0/anakin.tar.gz"
)
# A helper function used in Anakin, currently, to use it, one need to recursively include
# nearly all the header files.
function
(
fetch_include_recursively root_dir
)
if
(
IS_DIRECTORY
${
root_dir
}
)
include_directories
(
${
root_dir
}
)
endif
()
file
(
GLOB ALL_SUB RELATIVE
${
root_dir
}
${
root_dir
}
/*
)
foreach
(
sub
${
ALL_SUB
}
)
if
(
IS_DIRECTORY
${
root_dir
}
/
${
sub
}
)
fetch_include_recursively
(
${
root_dir
}
/
${
sub
}
)
endif
()
endforeach
()
endfunction
()
if
(
NOT EXISTS
"
${
ANAKIN_INSTALL_DIR
}
"
)
# download library
message
(
STATUS
"Download Anakin library from
${
ANAKIN_LIBRARY_URL
}
"
)
execute_process
(
COMMAND bash -c
"mkdir -p
${
ANAKIN_INSTALL_DIR
}
"
)
execute_process
(
COMMAND bash -c
"rm -rf
${
ANAKIN_INSTALL_DIR
}
/*"
)
execute_process
(
COMMAND bash -c
"cd
${
ANAKIN_INSTALL_DIR
}
; wget --no-check-certificate -q
${
ANAKIN_LIBRARY_URL
}
"
)
execute_process
(
COMMAND bash -c
"mkdir -p
${
ANAKIN_INSTALL_DIR
}
"
)
execute_process
(
COMMAND bash -c
"cd
${
ANAKIN_INSTALL_DIR
}
; tar xzf anakin.tar.gz"
)
endif
()
ExternalProject_Add
(
extern_anakin
${
EXTERNAL_PROJECT_LOG_ARGS
}
# TODO(luotao): use PaddlePaddle/Anakin later
GIT_REPOSITORY
"https://github.com/luotao1/Anakin"
GIT_TAG
"3957ae9263eaa0b1986758dac60a88852afb09be"
PREFIX
${
ANAKIN_SOURCE_DIR
}
UPDATE_COMMAND
""
CMAKE_ARGS -DUSE_GPU_PLACE=YES
-DUSE_X86_PLACE=YES
-DBUILD_WITH_UNIT_TEST=NO
-DPROTOBUF_ROOT=
${
THIRD_PARTY_PATH
}
/install/protobuf
-DMKLML_ROOT=
${
THIRD_PARTY_PATH
}
/install/mklml
-DCUDNN_ROOT=
${
CUDNN_ROOT
}
${
EXTERNAL_OPTIONAL_ARGS
}
CMAKE_CACHE_ARGS -DCMAKE_INSTALL_PREFIX:PATH=
${
ANAKIN_INSTALL_DIR
}
)
if
(
WITH_ANAKIN
)
message
(
STATUS
"Anakin for inference is enabled"
)
message
(
STATUS
"Anakin is set INCLUDE:
${
ANAKIN_INCLUDE
}
LIBRARY:
${
ANAKIN_LIBRARY
}
"
)
fetch_include_recursively
(
${
ANAKIN_INCLUDE
}
)
link_directories
(
${
ANAKIN_LIBRARY
}
)
endif
()
message
(
STATUS
"Anakin for inference is enabled"
)
message
(
STATUS
"Anakin is set INCLUDE:
${
ANAKIN_INCLUDE
}
LIBRARY:
${
ANAKIN_LIBRARY
}
"
)
add_library
(
anakin_shared SHARED IMPORTED GLOBAL
)
set_property
(
TARGET anakin_shared PROPERTY IMPORTED_LOCATION
${
ANAKIN_SHARED_LIB
}
)
add_dependencies
(
anakin_shared extern_anakin protobuf mklml
)
add_library
(
anakin_saber SHARED IMPORTED GLOBAL
)
set_property
(
TARGET anakin_saber PROPERTY IMPORTED_LOCATION
${
ANAKIN_SABER_LIB
}
)
add_dependencies
(
anakin_saber extern_anakin protobuf mklml
)
list
(
APPEND external_project_dependencies anakin_shared anakin_saber
)
cmake/inference_lib.cmake
浏览文件 @
1800fef1
...
...
@@ -143,7 +143,7 @@ if (WITH_ANAKIN AND WITH_GPU)
copy
(
anakin_inference_lib DEPS paddle_inference_api inference_anakin_api
SRCS
${
PADDLE_BINARY_DIR
}
/paddle/fluid/inference/api/libinference_anakin_api*
# compiled anakin api
${
PADDLE_BINARY_DIR
}
/third_party/install/anakin/*.tar.gz
# anakin release
${
ANAKIN_INSTALL_DIR
}
# anakin release
DSTS
${
dst_dir
}
/inference/anakin
${
dst_dir
}
/inference/anakin
)
list
(
APPEND inference_deps anakin_inference_lib
)
endif
()
...
...
doc/fluid/api/executor.rst
浏览文件 @
1800fef1
...
...
@@ -38,11 +38,3 @@ _switch_scope
.. autofunction:: paddle.fluid.executor._switch_scope
:noindex:
.. _api_fluid_executor_fetch_var:
fetch_var
---------
.. autofunction:: paddle.fluid.executor.fetch_var
:noindex:
doc/fluid/api/fluid.rst
浏览文件 @
1800fef1
...
...
@@ -106,22 +106,6 @@ _switch_scope
.. autofunction:: paddle.fluid._switch_scope
:noindex:
.. _api_fluid_fetch_var:
fetch_var
---------
.. autofunction:: paddle.fluid.fetch_var
:noindex:
.. _api_fluid_Go:
Go
--
.. autoclass:: paddle.fluid.Go
:members:
:noindex:
.. _api_fluid_make_channel:
...
...
paddle/fluid/API.spec
浏览文件 @
1800fef1
...
...
@@ -34,21 +34,10 @@ paddle.fluid.default_main_program ArgSpec(args=[], varargs=None, keywords=None,
paddle.fluid.program_guard ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
paddle.fluid.get_var ArgSpec(args=['name', 'program'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.Executor.__init__ ArgSpec(args=['self', 'place'], varargs=None, keywords=None, defaults=None)
paddle.fluid.Executor.as_lodtensor ArgSpec(args=['self', 'data'], varargs=None, keywords=None, defaults=None)
paddle.fluid.Executor.close ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.Executor.run ArgSpec(args=['self', 'program', 'feed', 'fetch_list', 'feed_var_name', 'fetch_var_name', 'scope', 'return_numpy', 'use_program_cache'], varargs=None, keywords=None, defaults=(None, None, None, 'feed', 'fetch', None, True, False))
paddle.fluid.global_scope ArgSpec(args=[], varargs=None, keywords=None, defaults=None)
paddle.fluid.scope_guard ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
paddle.fluid.fetch_var ArgSpec(args=['name', 'scope', 'return_numpy'], varargs=None, keywords=None, defaults=(None, True))
paddle.fluid.Go.__init__ ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.Go.construct_go_op ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.make_channel ArgSpec(args=['dtype', 'capacity'], varargs=None, keywords=None, defaults=(0,))
paddle.fluid.channel_send ArgSpec(args=['channel', 'value', 'is_copy'], varargs=None, keywords=None, defaults=(False,))
paddle.fluid.channel_recv ArgSpec(args=['channel', 'return_value'], varargs=None, keywords=None, defaults=None)
paddle.fluid.channel_close ArgSpec(args=['channel'], varargs=None, keywords=None, defaults=None)
paddle.fluid.Select.__init__ ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.Select.case ArgSpec(args=['self', 'channel_action_fn', 'channel', 'value', 'is_copy'], varargs=None, keywords=None, defaults=(False,))
paddle.fluid.Select.default ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.Trainer.__init__ ArgSpec(args=['self', 'train_func', 'optimizer_func', 'param_path', 'place', 'parallel', 'checkpoint_config'], varargs=None, keywords=None, defaults=(None, None, False, None))
paddle.fluid.Trainer.save_params ArgSpec(args=['self', 'param_path'], varargs=None, keywords=None, defaults=None)
paddle.fluid.Trainer.stop ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
...
...
@@ -62,20 +51,16 @@ paddle.fluid.CheckpointConfig.__init__ ArgSpec(args=['self', 'checkpoint_dir', '
paddle.fluid.Inferencer.__init__ ArgSpec(args=['self', 'infer_func', 'param_path', 'place', 'parallel'], varargs=None, keywords=None, defaults=(None, False))
paddle.fluid.Inferencer.infer ArgSpec(args=['self', 'inputs', 'return_numpy'], varargs=None, keywords=None, defaults=(True,))
paddle.fluid.DistributeTranspiler.__init__ ArgSpec(args=['self', 'config'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.DistributeTranspiler.create_splited_vars ArgSpec(args=['self', 'source_var', 'block', 'tag'], varargs=None, keywords=None, defaults=None)
paddle.fluid.DistributeTranspiler.get_pserver_program ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None)
paddle.fluid.DistributeTranspiler.get_startup_program ArgSpec(args=['self', 'endpoint', 'pserver_program'], varargs=None, keywords=None, defaults=None)
paddle.fluid.DistributeTranspiler.get_trainer_program ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.DistributeTranspiler.transpile ArgSpec(args=['self', 'trainer_id', 'program', 'pservers', 'trainers', 'sync_mode'], varargs=None, keywords=None, defaults=(None, '127.0.0.1:6174', 1, True))
paddle.fluid.InferenceTranspiler.__init__
paddle.fluid.InferenceTranspiler.fuse_batch_norm ArgSpec(args=['self', 'program', 'place', 'scope'], varargs=None, keywords=None, defaults=None)
paddle.fluid.InferenceTranspiler.fuse_relu_mkldnn ArgSpec(args=['self', 'program'], varargs=None, keywords=None, defaults=None)
paddle.fluid.InferenceTranspiler.transpile ArgSpec(args=['self', 'program', 'place', 'scope'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.memory_optimize ArgSpec(args=['input_program', 'skip_opt_set', 'print_log', 'level'], varargs=None, keywords=None, defaults=(None, False, 0))
paddle.fluid.release_memory ArgSpec(args=['input_program', 'skip_opt_set'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.DistributeTranspilerConfig.__init__
paddle.fluid.ParallelExecutor.__init__ ArgSpec(args=['self', 'use_cuda', 'loss_name', 'main_program', 'share_vars_from', 'exec_strategy', 'build_strategy', 'num_trainers', 'trainer_id'], varargs=None, keywords='kwargs', defaults=(None, None, None, None, None, 1, 0))
paddle.fluid.ParallelExecutor.bcast_params ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.ParallelExecutor.run ArgSpec(args=['self', 'fetch_list', 'feed', 'feed_dict', 'return_numpy'], varargs=None, keywords=None, defaults=(None, None, True))
paddle.fluid.ExecutionStrategy.__init__ __init__(self: paddle.fluid.core.ExecutionStrategy) -> None
paddle.fluid.BuildStrategy.GradientScaleStrategy.__init__ __init__(self: paddle.fluid.core.GradientScaleStrategy, arg0: int) -> None
...
...
@@ -338,14 +323,11 @@ paddle.fluid.contrib.BeamSearchDecoder.read_array ArgSpec(args=['self', 'init',
paddle.fluid.contrib.BeamSearchDecoder.update_array ArgSpec(args=['self', 'array', 'value'], varargs=None, keywords=None, defaults=None)
paddle.fluid.contrib.memory_usage ArgSpec(args=['program', 'batch_size'], varargs=None, keywords=None, defaults=None)
paddle.fluid.transpiler.DistributeTranspiler.__init__ ArgSpec(args=['self', 'config'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.transpiler.DistributeTranspiler.create_splited_vars ArgSpec(args=['self', 'source_var', 'block', 'tag'], varargs=None, keywords=None, defaults=None)
paddle.fluid.transpiler.DistributeTranspiler.get_pserver_program ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None)
paddle.fluid.transpiler.DistributeTranspiler.get_startup_program ArgSpec(args=['self', 'endpoint', 'pserver_program'], varargs=None, keywords=None, defaults=None)
paddle.fluid.transpiler.DistributeTranspiler.get_trainer_program ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.transpiler.DistributeTranspiler.transpile ArgSpec(args=['self', 'trainer_id', 'program', 'pservers', 'trainers', 'sync_mode'], varargs=None, keywords=None, defaults=(None, '127.0.0.1:6174', 1, True))
paddle.fluid.transpiler.InferenceTranspiler.__init__
paddle.fluid.transpiler.InferenceTranspiler.fuse_batch_norm ArgSpec(args=['self', 'program', 'place', 'scope'], varargs=None, keywords=None, defaults=None)
paddle.fluid.transpiler.InferenceTranspiler.fuse_relu_mkldnn ArgSpec(args=['self', 'program'], varargs=None, keywords=None, defaults=None)
paddle.fluid.transpiler.InferenceTranspiler.transpile ArgSpec(args=['self', 'program', 'place', 'scope'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.transpiler.memory_optimize ArgSpec(args=['input_program', 'skip_opt_set', 'print_log', 'level'], varargs=None, keywords=None, defaults=(None, False, 0))
paddle.fluid.transpiler.release_memory ArgSpec(args=['input_program', 'skip_opt_set'], varargs=None, keywords=None, defaults=(None,))
...
...
paddle/fluid/inference/analysis/analyzer.cc
浏览文件 @
1800fef1
...
...
@@ -44,13 +44,13 @@ class DfgPassManagerImpl final : public DfgPassManager {
if
(
FLAGS_inference_analysis_enable_tensorrt_subgraph_engine
)
{
auto
trt_teller
=
[
&
](
const
Node
*
node
)
{
std
::
unordered_set
<
std
::
string
>
teller_set
(
{
"elementwise_add"
,
"mul"
,
"conv2d"
,
"pool2d"
,
"relu"
});
{
"elementwise_add"
,
"mul"
,
"conv2d"
,
"pool2d"
,
"relu"
,
"softmax"
});
if
(
!
node
->
IsFunction
())
return
false
;
const
auto
*
func
=
static_cast
<
const
Function
*>
(
node
);
if
(
teller_set
.
count
(
func
->
func_type
()))
if
(
teller_set
.
count
(
func
->
func_type
()))
{
return
true
;
else
{
}
else
{
return
false
;
}
};
...
...
paddle/fluid/inference/api/CMakeLists.txt
浏览文件 @
1800fef1
...
...
@@ -45,7 +45,6 @@ endfunction(inference_api_test)
cc_library
(
paddle_inference_api SRCS api.cc api_impl.cc DEPS lod_tensor
)
cc_test
(
test_paddle_inference_api
SRCS api_tester.cc
DEPS paddle_inference_api
)
...
...
@@ -62,22 +61,18 @@ inference_api_test(test_api_tensorrt_subgraph_engine SRC api_tensorrt_subgraph_e
endif
()
if
(
WITH_ANAKIN
)
# only needed in CI
# Due to Anakin do not have official library releases and the versions of protobuf and cuda do not match Paddle's,
# so anakin library will not be merged to our official inference library. To use anakin prediction API, one need to
# compile the libinference_anakin_api.a and compile with anakin.so.
fetch_include_recursively
(
${
ANAKIN_INCLUDE
}
)
# compile the libinference_anakin_api.a and anakin.so.
nv_library
(
inference_anakin_api SRCS api.cc api_anakin_engine.cc
)
nv_library
(
inference_anakin_api_shared SHARED SRCS api.cc api_anakin_engine.cc
)
target_compile_options
(
inference_anakin_api BEFORE PUBLIC
${
ANAKIN_COMPILE_EXTRA_FLAGS
}
)
target_compile_options
(
inference_anakin_api_shared BEFORE PUBLIC
${
ANAKIN_COMPILE_EXTRA_FLAGS
}
)
target_link_libraries
(
inference_anakin_api anakin anakin_saber_common
)
target_link_libraries
(
inference_anakin_api_shared anakin anakin_saber_common
)
nv_library
(
inference_anakin_api SRCS api.cc api_anakin_engine.cc DEPS anakin_shared anakin_saber
)
#nv_library(inference_anakin_api_shared SHARED SRCS api.cc api_anakin_engine.cc DEPS anakin)
function
(
anakin_target target_name
)
target_compile_options
(
${
target_name
}
BEFORE PUBLIC
${
ANAKIN_COMPILE_EXTRA_FLAGS
}
)
endfunction
()
anakin_target
(
inference_anakin_api
)
#anakin_target(inference_anakin_api_shared)
if
(
WITH_TESTING
)
# this test is unstable, disable it first.
#cc_test(inference_anakin_test SRCS api_anakin_engine_tester.cc
#ARGS --model=${ANAKIN_INSTALL_DIR}/mobilenet_v2.anakin.bin
#DEPS inference_anakin_api_shared)
#target_compile_options(inference_anakin_test BEFORE PUBLIC ${ANAKIN_COMPILE_EXTRA_FLAGS})
endif
(
WITH_TESTING
)
cc_test
(
inference_anakin_test SRCS api_anakin_engine_tester.cc
ARGS --model=
${
ANAKIN_SOURCE_DIR
}
/mobilenet_v2.anakin.bin
DEPS inference_anakin_api dynload_cuda SERIAL
)
target_compile_options
(
inference_anakin_test BEFORE PUBLIC
${
ANAKIN_COMPILE_EXTRA_FLAGS
}
)
endif
(
WITH_TESTING
)
endif
()
paddle/fluid/inference/api/paddle_inference_api.h
浏览文件 @
1800fef1
...
...
@@ -45,7 +45,7 @@ class PaddleBuf {
PaddleBuf
(
void
*
data
,
size_t
length
)
:
data_
(
data
),
length_
(
length
),
memory_owned_
{
false
}
{}
// Own memory.
PaddleBuf
(
size_t
length
)
explicit
PaddleBuf
(
size_t
length
)
:
data_
(
new
char
[
length
]),
length_
(
length
),
memory_owned_
(
true
)
{}
// Resize to `length` bytes.
void
Resize
(
size_t
length
);
...
...
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
浏览文件 @
1800fef1
# Add TRT tests
nv_library
(
tensorrt_converter
SRCS mul_op.cc conv2d_op.cc fc_op.cc pool2d_op.cc elementwise_op.cc
activation_op.cc
activation_op.cc
softmax_op.cc
DEPS tensorrt_engine operator scope framework_proto op_registry
)
nv_test
(
test_op_converter SRCS test_op_converter.cc DEPS
...
...
@@ -21,3 +21,6 @@ nv_test(test_trt_pool2d_op SRCS test_pool2d_op.cc pool2d_op.cc
nv_test
(
test_trt_elementwise_op SRCS test_elementwise_op.cc elementwise_op.cc
DEPS
${
FLUID_CORE_MODULES
}
tensorrt_engine elementwise_add_op SERIAL
)
nv_test
(
test_trt_softmax_op SRCS test_softmax_op.cc softmax_op.cc
DEPS
${
FLUID_CORE_MODULES
}
tensorrt_engine softmax_op SERIAL
)
paddle/fluid/inference/tensorrt/convert/softmax_op.cc
0 → 100644
浏览文件 @
1800fef1
/* 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
{
/*
* SoftMaxOp, ISoftMaxLayer in TRT. This Layer doesn't has weights.
*/
class
SoftMaxOpConverter
:
public
OpConverter
{
public:
void
operator
()(
const
framework
::
proto
::
OpDesc
&
op
,
const
framework
::
Scope
&
scope
,
bool
test_mode
)
override
{
VLOG
(
4
)
<<
"convert a fluid softmax op to tensorrt softmax layer without bias"
;
framework
::
OpDesc
op_desc
(
op
,
nullptr
);
// Declare inputs
auto
*
input1
=
engine_
->
GetITensor
(
op_desc
.
Input
(
"X"
)[
0
]);
auto
*
layer
=
TRT_ENGINE_ADD_LAYER
(
engine_
,
SoftMax
,
*
const_cast
<
nvinfer1
::
ITensor
*>
(
input1
));
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
(
softmax
);
REGISTER_TRT_OP_CONVERTER
(
softmax
,
SoftMaxOpConverter
);
paddle/fluid/inference/tensorrt/convert/test_softmax_op.cc
0 → 100644
浏览文件 @
1800fef1
/* 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 "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/inference/tensorrt/convert/ut_helper.h"
namespace
paddle
{
namespace
inference
{
namespace
tensorrt
{
TEST
(
SoftMaxOpConverter
,
main
)
{
framework
::
Scope
scope
;
std
::
unordered_set
<
std
::
string
>
parameters
;
TRTConvertValidation
validator
(
8
,
parameters
,
scope
,
1000
);
std
::
vector
<
int
>
tensor_shape
{
8
,
10
};
validator
.
DeclInputVar
(
"softmax-X"
,
tensor_shape
,
nvinfer1
::
DimsCHW
(
10
,
1
,
1
));
validator
.
DeclOutputVar
(
"softmax-Out"
,
nvinfer1
::
DimsCHW
(
10
,
1
,
1
));
// Prepare Op description
framework
::
OpDesc
desc
;
desc
.
SetType
(
"softmax"
);
desc
.
SetInput
(
"X"
,
{
"softmax-X"
});
desc
.
SetOutput
(
"Out"
,
{
"softmax-Out"
});
LOG
(
INFO
)
<<
"set OP"
;
validator
.
SetOp
(
*
desc
.
Proto
());
LOG
(
INFO
)
<<
"execute"
;
validator
.
Execute
(
3
);
}
}
// namespace tensorrt
}
// namespace inference
}
// namespace paddle
USE_OP
(
softmax
);
paddle/fluid/inference/tensorrt/convert/ut_helper.h
浏览文件 @
1800fef1
...
...
@@ -79,6 +79,12 @@ class TRTConvertValidation {
}
// Declare a Variable as input with random initialization.
void
DeclInputVar
(
const
std
::
string
&
name
,
const
std
::
vector
<
int
>
tensor_dims
,
const
nvinfer1
::
Dims
&
trt_dims
)
{
DeclVar
(
name
,
tensor_dims
);
engine_
->
DeclareInput
(
name
,
nvinfer1
::
DataType
::
kFLOAT
,
trt_dims
);
}
void
DeclInputVar
(
const
std
::
string
&
name
,
const
nvinfer1
::
Dims
&
dims
)
{
DeclVar
(
name
,
dims
);
// Declare TRT inputs.
...
...
@@ -94,12 +100,18 @@ class TRTConvertValidation {
DeclVar
(
name
,
dims
);
}
// Declare a variable in a fluid Scope.
void
DeclVar
(
const
std
::
string
&
name
,
const
nvinfer1
::
Dims
&
dims
,
bool
is_param
=
false
)
{
void
DeclVar
(
const
std
::
string
&
name
,
const
std
::
vector
<
int
>
dim_vec
)
{
platform
::
CPUPlace
place
;
platform
::
CPUDeviceContext
ctx
(
place
);
auto
*
x
=
scope_
.
Var
(
name
);
auto
*
x_tensor
=
x
->
GetMutable
<
framework
::
LoDTensor
>
();
x_tensor
->
Resize
(
framework
::
make_ddim
(
dim_vec
));
RandomizeTensor
(
x_tensor
,
place
,
ctx
);
}
// Declare a variable in a fluid Scope.
void
DeclVar
(
const
std
::
string
&
name
,
const
nvinfer1
::
Dims
&
dims
,
bool
is_param
=
false
)
{
// 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
...
...
@@ -107,10 +119,8 @@ class TRTConvertValidation {
// 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
));
RandomizeTensor
(
x_tensor
,
place
,
ctx
);
DeclVar
(
name
,
dim_vec
);
}
void
SetOp
(
const
framework
::
proto
::
OpDesc
&
desc
)
{
...
...
paddle/fluid/operators/elementwise_add_op.cu
浏览文件 @
1800fef1
...
...
@@ -16,60 +16,6 @@ limitations under the License. */
#include "paddle/fluid/operators/elementwise_add_op.h"
#include "paddle/fluid/platform/float16.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
T
>
__global__
void
ElementwiseAddCUDAKernel
(
const
T
*
x
,
const
T
*
y
,
T
*
z
,
int
n
,
int
post
,
int
size
)
{
int
idx_x
=
threadIdx
.
x
+
blockIdx
.
x
*
blockDim
.
x
;
if
(
idx_x
<
size
)
{
int
idx_y
=
idx_x
/
post
-
(
idx_x
/
(
n
*
post
))
*
n
;
z
[
idx_x
]
=
x
[
idx_x
]
+
y
[
idx_y
];
}
}
template
<
typename
T
>
class
ElementwiseAddKernel
<
platform
::
CUDADeviceContext
,
T
>
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
using
Tensor
=
framework
::
Tensor
;
const
auto
x
=
ctx
.
Input
<
Tensor
>
(
"X"
);
const
auto
y
=
ctx
.
Input
<
Tensor
>
(
"Y"
);
auto
z
=
ctx
.
Output
<
Tensor
>
(
"Out"
);
auto
*
z_data
=
z
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
auto
&
device
=
*
(
ctx
.
cuda_device_context
().
eigen_device
());
const
framework
::
DDim
&
x_dim
=
x
->
dims
();
framework
::
DDim
y_dim
=
y
->
dims
();
int
size
=
x
->
numel
();
if
(
x_dim
==
y_dim
)
{
auto
dim
=
framework
::
make_ddim
({
size
});
auto
z_eigen
=
framework
::
EigenTensor
<
T
,
1
>::
From
(
*
z
,
dim
);
auto
x_eigen
=
framework
::
EigenTensor
<
T
,
1
>::
From
(
*
x
,
dim
);
auto
y_eigen
=
framework
::
EigenTensor
<
T
,
1
>::
From
(
*
y
,
dim
);
z_eigen
.
device
(
device
)
=
x_eigen
+
y_eigen
;
}
else
{
int
axis
=
ctx
.
Attr
<
int
>
(
"axis"
);
axis
=
(
axis
==
-
1
?
x_dim
.
size
()
-
y_dim
.
size
()
:
axis
);
y_dim
=
trim_trailing_singular_dims
(
y_dim
);
axis
=
(
y_dim
.
size
()
==
0
)
?
x_dim
.
size
()
:
axis
;
int
pre
,
n
,
post
;
get_mid_dims
(
x_dim
,
y_dim
,
axis
,
&
pre
,
&
n
,
&
post
);
int
threads
=
512
;
int
grids
=
(
size
+
threads
-
1
)
/
threads
;
auto
stream
=
ctx
.
cuda_device_context
().
stream
();
ElementwiseAddCUDAKernel
<
T
><<<
grids
,
threads
,
0
,
stream
>>>
(
x
->
data
<
T
>
(),
y
->
data
<
T
>
(),
z_data
,
n
,
post
,
size
);
}
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
namespace
plat
=
paddle
::
platform
;
...
...
paddle/fluid/operators/elementwise_add_op.h
浏览文件 @
1800fef1
...
...
@@ -144,41 +144,16 @@ class ElementwiseAddGradKernel : public framework::OpKernel<T> {
auto
*
dout
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
dx
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
dy
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
// skip out, x, y
auto
*
out
=
dout
;
auto
*
x
=
dout
,
*
y
=
dout
;
if
(
dx
!=
nullptr
)
{
// In fact, we can just share memory, but it may cause a bug of memory
// optimizer
// dx->ShareDataWith(*dout);
framework
::
TensorCopy
(
*
dout
,
ctx
.
GetPlace
(),
ctx
.
template
device_context
<
DeviceContext
>(),
dx
);
}
if
(
dy
==
nullptr
)
return
;
const
framework
::
DDim
&
x_dim
=
dout
->
dims
();
framework
::
DDim
y_dim
=
dy
->
dims
();
if
(
x_dim
==
y_dim
)
{
// dy->ShareDataWith(*dout);
framework
::
TensorCopy
(
*
dout
,
ctx
.
GetPlace
(),
ctx
.
template
device_context
<
DeviceContext
>(),
dy
);
if
(
platform
::
is_cpu_place
(
ctx
.
GetPlace
())
&&
dx
!=
nullptr
&&
dy
!=
nullptr
&&
(
dx
->
dims
()
==
dy
->
dims
()))
{
elementwise_add_grad
<
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
out
,
dout
,
dx
,
dy
);
}
else
{
dy
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
// Perform reduction to dout to calculate dy
int
axis
=
ctx
.
Attr
<
int
>
(
"axis"
);
axis
=
(
axis
==
-
1
?
x_dim
.
size
()
-
y_dim
.
size
()
:
axis
);
y_dim
=
trim_trailing_singular_dims
(
y_dim
);
axis
=
(
y_dim
.
size
()
==
0
)
?
x_dim
.
size
()
:
axis
;
auto
&
device
=
*
(
ctx
.
template
device_context
<
DeviceContext
>().
eigen_device
());
int
pre
,
n
,
post
;
get_mid_dims
(
x_dim
,
y_dim
,
axis
,
&
pre
,
&
n
,
&
post
);
auto
eigen_dout
=
framework
::
EigenTensor
<
T
,
3
>::
From
(
*
dout
,
framework
::
make_ddim
({
pre
,
n
,
post
}));
auto
eigen_dy
=
framework
::
EigenTensor
<
T
,
1
>::
From
(
*
dy
,
framework
::
make_ddim
({
n
}));
eigen_dy
.
device
(
device
)
=
eigen_dout
.
sum
(
framework
::
EigenDim
<
2
>::
From
(
framework
::
make_ddim
({
0
,
2
})));
default_elementwise_add_grad
<
DeviceContext
,
T
>
(
ctx
,
x
,
y
,
out
,
dout
,
dx
,
dy
);
}
}
};
...
...
paddle/fluid/pybind/pybind.cc
浏览文件 @
1800fef1
...
...
@@ -666,7 +666,7 @@ All parameter, weight, gradient are variables in Paddle.
const
std
::
string
&
,
Scope
*
,
std
::
vector
<
Scope
*>
&
,
const
ExecutionStrategy
&
,
const
BuildStrategy
&
,
size_t
,
size_t
>
())
.
def
(
"bcast_params"
,
&
ParallelExecutor
::
BCastParamsToDevices
)
.
def
(
"
_
bcast_params"
,
&
ParallelExecutor
::
BCastParamsToDevices
)
// NOTE: even we return a vec<Scope*>* to Python use reference policy.
// We still cannot get local_scope from this vector, since the element
// of vec<Scope*> will be freed by Python GC. We can only return Scope*
...
...
python/paddle/fluid/__init__.py
浏览文件 @
1800fef1
...
...
@@ -48,8 +48,6 @@ from .data_feeder import DataFeeder
from
.core
import
LoDTensor
,
LoDTensorArray
,
CPUPlace
,
CUDAPlace
,
CUDAPinnedPlace
,
Scope
from
.transpiler
import
DistributeTranspiler
,
InferenceTranspiler
,
\
memory_optimize
,
release_memory
,
DistributeTranspilerConfig
from
.concurrency
import
(
Go
,
make_channel
,
channel_send
,
channel_recv
,
channel_close
,
Select
)
from
.lod_tensor
import
create_lod_tensor
,
create_random_int_lodtensor
from
.
import
clip
from
.
import
profiler
...
...
@@ -61,7 +59,7 @@ from paddle.fluid.layers.math_op_patch import monkey_patch_variable
Tensor
=
LoDTensor
__all__
=
framework
.
__all__
+
executor
.
__all__
+
concurrency
.
__all__
+
\
__all__
=
framework
.
__all__
+
executor
.
__all__
+
\
trainer
.
__all__
+
inferencer
.
__all__
+
transpiler
.
__all__
+
\
parallel_executor
.
__all__
+
lod_tensor
.
__all__
+
[
'io'
,
...
...
python/paddle/fluid/concurrency.py
浏览文件 @
1800fef1
...
...
@@ -19,8 +19,7 @@ from .layers import fill_constant
from
.
import
core
__all__
=
[
'Go'
,
'make_channel'
,
'channel_send'
,
'channel_recv'
,
'channel_close'
,
'Select'
'make_channel'
,
'channel_send'
,
'channel_recv'
,
'channel_close'
,
'Select'
]
...
...
@@ -35,10 +34,10 @@ class Go(BlockGuard):
def
__exit__
(
self
,
exc_type
,
exc_val
,
exc_tb
):
if
exc_type
is
not
None
:
return
False
self
.
construct_go_op
()
self
.
_
construct_go_op
()
return
super
(
Go
,
self
).
__exit__
(
exc_type
,
exc_val
,
exc_tb
)
def
construct_go_op
(
self
):
def
_
construct_go_op
(
self
):
main_program
=
self
.
helper
.
main_program
go_block
=
main_program
.
current_block
()
parent_block
=
main_program
.
block
(
main_program
.
current_block
()
...
...
python/paddle/fluid/executor.py
浏览文件 @
1800fef1
...
...
@@ -18,9 +18,7 @@ import six
from
.framework
import
Program
,
default_main_program
,
Variable
from
.
import
core
__all__
=
[
'Executor'
,
'global_scope'
,
'scope_guard'
,
'_switch_scope'
,
'fetch_var'
]
__all__
=
[
'Executor'
,
'global_scope'
,
'scope_guard'
,
'_switch_scope'
]
g_scope
=
core
.
Scope
()
...
...
@@ -171,7 +169,7 @@ def has_fetch_operators(block, fetch_targets, fetch_holder_name):
return
fetch_count
>
0
def
fetch_var
(
name
,
scope
=
None
,
return_numpy
=
True
):
def
_
fetch_var
(
name
,
scope
=
None
,
return_numpy
=
True
):
"""
Fetch the value of the variable with the given name from the
given scope.
...
...
@@ -222,6 +220,37 @@ def _get_program_cache_key(feed, fetch_list):
return
str
(
feed_var_names
+
fetch_var_names
)
def
_as_lodtensor
(
data
,
place
):
"""
Convert numpy.ndarray to Tensor, its only support Tensor without LoD information.
For higher dimensional sequence data, please use LoDTensor directly.
Examples:
>>> import paddle.fluid as fluid
>>> place = fluid.CPUPlace()
>>> exe = fluid.executor(place)
>>> data = np.array(size=(100, 200, 300))
>>> np_outs = map(lambda x: fluid.executor._as_lodtensor(x, place), data)
>>> ...
Args:
data(numpy.ndarray): a instance of array
Returns:
LoDTensor
"""
if
isinstance
(
data
,
list
):
raise
RuntimeError
(
"Some of your feed data hold LoD information.
\
They can not be completely cast from a list of Python
\
ndarray to LoDTensor. Please convert data to LoDTensor
\
directly before feeding the data.
\
"
)
# single tensor case
tensor
=
core
.
LoDTensor
()
tensor
.
set
(
data
,
place
)
return
tensor
class
Executor
(
object
):
"""
An Executor in Python, only support the single-GPU running. For multi-cards, please refer to
...
...
@@ -250,35 +279,6 @@ class Executor(object):
self
.
program_caches
=
dict
()
self
.
_closed
=
False
def
as_lodtensor
(
self
,
data
):
"""
Convert numpy.ndarray to Tensor, its only support Tensor without LoD information.
For higher dimensional sequence data, please use LoDTensor directly.
Examples:
>>> import paddle.fluid as fluid
>>> exe = fluid.executor(fluid.CPUPlace())
>>> data = np.array(size=(100, 200, 300))
>>> np_outs = map(lambda x: exe.as_lodtensor(x), data)
>>> ...
Args:
data(numpy.ndarray): a instance of array
Returns:
LoDTensor
"""
if
isinstance
(
data
,
list
):
raise
RuntimeError
(
"Some of your feed data hold LoD information.
\
They can not be completely cast from a list of Python
\
ndarray to LoDTensor. Please convert data to LoDTensor
\
directly before feeding the data.
\
"
)
# single tensor case
tensor
=
core
.
LoDTensor
()
tensor
.
set
(
data
,
self
.
place
)
return
tensor
def
_get_program_cache
(
self
,
program_cache_key
):
return
self
.
program_caches
.
get
(
program_cache_key
,
None
)
...
...
@@ -338,7 +338,7 @@ class Executor(object):
feed_target_name
=
op
.
desc
.
output
(
'Out'
)[
0
]
cur_feed
=
feed
[
feed_target_name
]
if
not
isinstance
(
cur_feed
,
core
.
LoDTensor
):
cur_feed
=
self
.
as_lodtensor
(
cur_feed
)
cur_feed
=
_as_lodtensor
(
cur_feed
,
self
.
place
)
idx
=
op
.
desc
.
attr
(
'col'
)
core
.
set_feed_variable
(
scope
,
cur_feed
,
feed_var_name
,
idx
)
else
:
...
...
python/paddle/fluid/parallel_executor.py
浏览文件 @
1800fef1
...
...
@@ -279,19 +279,19 @@ class ParallelExecutor(object):
arr
=
self
.
scope
.
find_var
(
fetch_var_name
).
get_lod_tensor_array
()
if
self
.
is_dist
:
self
.
bcast_params
()
self
.
_
bcast_params
()
if
return_numpy
:
return
executor
.
as_numpy
(
arr
)
return
[
arr
[
i
]
for
i
in
range
(
len
(
arr
))]
def
bcast_params
(
self
):
def
_
bcast_params
(
self
):
"""
Broadcast the parameters to other devices. It is used during
distributed training.
"""
self
.
executor
.
bcast_params
(
set
(
self
.
persistable_vars
))
self
.
executor
.
_
bcast_params
(
set
(
self
.
persistable_vars
))
@
property
def
device_count
(
self
):
...
...
python/paddle/fluid/tests/unittests/test_dist_transpiler.py
浏览文件 @
1800fef1
...
...
@@ -537,5 +537,35 @@ class TestAsyncDistLookupTable(TestDistLookupTableBase):
self
.
assertEqual
([
op
.
type
for
op
in
trainer
.
blocks
[
0
].
ops
],
ops
)
class
TestRMSPropOptimizer
(
TranspilerTest
):
def
net_conf
(
self
):
x
=
fluid
.
layers
.
data
(
name
=
'x'
,
shape
=
[
1000
],
dtype
=
'float32'
)
y_predict
=
fluid
.
layers
.
fc
(
input
=
x
,
size
=
1000
,
act
=
None
,
param_attr
=
fluid
.
ParamAttr
(
name
=
'fc_w'
),
bias_attr
=
fluid
.
ParamAttr
(
name
=
'fc_b'
))
y
=
fluid
.
layers
.
data
(
name
=
'y'
,
shape
=
[
1
],
dtype
=
'float32'
)
cost
=
fluid
.
layers
.
square_error_cost
(
input
=
y_predict
,
label
=
y
)
avg_cost
=
fluid
.
layers
.
mean
(
cost
)
optimizer
=
fluid
.
optimizer
.
RMSProp
(
learning_rate
=
0.1
)
optimizer
.
minimize
(
avg_cost
)
return
def
transpiler_test_impl
(
self
):
pserver
,
startup
=
self
.
get_pserver
(
self
.
pserver1_ep
)
pserver2
,
startup2
=
self
.
get_pserver
(
self
.
pserver2_ep
)
self
.
assertEqual
(
len
(
pserver
.
blocks
),
3
)
# block1~2: optimize pass
self
.
assertEqual
([
op
.
type
for
op
in
pserver
.
blocks
[
1
].
ops
],
[
"sum"
,
"scale"
,
"rmsprop"
])
# the variable #fc_w will be split into two blocks
fc_w_var
=
startup
.
global_block
().
var
(
"fc_w.block1"
)
self
.
assertEqual
(
fc_w_var
.
shape
,
(
500
,
1000
))
moment_var
=
startup
.
global_block
().
var
(
"momentum_1"
)
self
.
assertEqual
(
moment_var
.
shape
,
(
500
,
1000
))
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/test_fetch_var.py
浏览文件 @
1800fef1
...
...
@@ -26,7 +26,7 @@ class TestFetchVar(op_test.OpTest):
layers
.
assign
(
input
=
val
,
output
=
x
)
exe
=
fluid
.
Executor
(
fluid
.
CPUPlace
())
exe
.
run
(
fluid
.
default_main_program
(),
feed
=
{},
fetch_list
=
[])
fetched_x
=
fluid
.
fetch_var
(
"x"
)
fetched_x
=
fluid
.
executor
.
_
fetch_var
(
"x"
)
self
.
assertTrue
(
numpy
.
array_equal
(
fetched_x
,
val
),
"fetch_x=%s val=%s"
%
(
fetched_x
,
val
))
...
...
python/paddle/fluid/tests/unittests/test_py_reader_push_pop.py
浏览文件 @
1800fef1
...
...
@@ -62,7 +62,8 @@ class TestPyReader(unittest.TestCase):
next_data
=
np
.
random
.
uniform
(
low
=
0
,
high
=
1000
,
size
=
(
batch_size
,
)
+
shape
[
1
:]).
astype
(
dtype
)
in_data
.
append
(
executor
.
as_lodtensor
(
next_data
))
in_data
.
append
(
fluid
.
executor
.
_as_lodtensor
(
next_data
,
place
))
self
.
inputs
.
append
(
in_data
)
...
...
python/paddle/fluid/tests/unittests/transformer_model.py
浏览文件 @
1800fef1
...
...
@@ -22,7 +22,7 @@ pos_enc_param_names = (
"src_pos_enc_table"
,
"trg_pos_enc_table"
,
)
batch_size
=
64
batch_size
=
2
def
position_encoding_init
(
n_position
,
d_pos_vec
):
...
...
python/paddle/fluid/transpiler/distribute_transpiler.py
浏览文件 @
1800fef1
...
...
@@ -751,14 +751,14 @@ class DistributeTranspiler(object):
out_name
=
op
.
output
(
"Out"
)
ids_var
=
program
.
global_block
().
vars
[
ids_name
[
0
]]
prefetch_input_vars
=
self
.
create_splited_vars
(
prefetch_input_vars
=
self
.
_
create_splited_vars
(
source_var
=
ids_var
,
block
=
program
.
global_block
(),
tag
=
"_prefetch_in_"
)
self
.
all_prefetch_input_vars
.
append
(
prefetch_input_vars
)
out_var
=
program
.
global_block
().
vars
[
out_name
[
0
]]
prefetch_output_vars
=
self
.
create_splited_vars
(
prefetch_output_vars
=
self
.
_
create_splited_vars
(
source_var
=
out_var
,
block
=
program
.
global_block
(),
tag
=
"_prefetch_out_"
)
...
...
@@ -1040,7 +1040,7 @@ class DistributeTranspiler(object):
program
.
global_block
().
_sync_with_cpp
()
return
var_mapping
def
create_splited_vars
(
self
,
source_var
,
block
,
tag
):
def
_
create_splited_vars
(
self
,
source_var
,
block
,
tag
):
return
[
block
.
create_var
(
name
=
str
(
source_var
.
name
+
tag
+
str
(
index
)),
...
...
@@ -1184,18 +1184,39 @@ class DistributeTranspiler(object):
program
=
optimize_block
.
program
pserver_block
=
program
.
global_block
()
new_inputs
=
collections
.
OrderedDict
()
# update param/grad shape first, then other inputs like
# moment can use the updated shape
def
_get_param_block
(
opt_op
):
# param is already created on global program
param_block
=
None
for
p
in
self
.
param_grad_ep_mapping
[
endpoint
][
"params"
]:
if
same_or_split_var
(
p
.
name
,
opt_op
.
input
(
"Param"
)[
0
]):
param_block
=
p
break
return
param_block
for
key
in
opt_op
.
input_names
:
if
key
==
"Grad"
:
new_inputs
[
key
]
=
merged_var
# For RMSProp optimizer
elif
key
==
"Moment"
or
key
==
"MeanSquare"
:
param_block
=
_get_param_block
(
opt_op
)
if
not
param_block
:
return
moment_var
=
origin_program
.
global_block
().
vars
[
opt_op
.
input
(
key
)[
0
]]
tmpvar
=
pserver_block
.
create_var
(
name
=
moment_var
.
name
,
persistable
=
moment_var
.
persistable
,
dtype
=
moment_var
.
dtype
,
# change to use same shape as param
# TODO(typhoonzero): didn't append .block in the var name,
# may affect checkpoint saving? Need to verify.
shape
=
param_block
.
shape
)
new_inputs
[
key
]
=
tmpvar
elif
key
==
"Param"
:
# param is already created on global program
param_block
=
None
for
p
in
self
.
param_grad_ep_mapping
[
endpoint
][
"params"
]:
if
same_or_split_var
(
p
.
name
,
opt_op
.
input
(
key
)[
0
]):
param_block
=
p
break
param_block
=
_get_param_block
(
opt_op
)
if
not
param_block
:
return
tmpvar
=
pserver_block
.
create_var
(
...
...
@@ -1221,7 +1242,7 @@ class DistributeTranspiler(object):
for
key
in
opt_op
.
input_names
:
new_shape
=
None
if
key
in
[
"Param"
,
"Grad"
,
"LearningRate"
]:
if
key
in
[
"Param"
,
"Grad"
,
"LearningRate"
,
"Moment"
,
"MeanSquare"
]:
continue
var
=
self
.
origin_program
.
global_block
().
vars
[
opt_op
.
input
(
key
)[
0
]]
# update accumulator variable shape
...
...
python/paddle/fluid/transpiler/inference_transpiler.py
浏览文件 @
1800fef1
...
...
@@ -57,10 +57,10 @@ class InferenceTranspiler(object):
scope
=
global_scope
()
if
not
isinstance
(
scope
,
core
.
Scope
):
raise
TypeError
(
"scope should be as Scope type or None"
)
self
.
fuse_batch_norm
(
program
,
place
,
scope
)
self
.
fuse_relu_mkldnn
(
program
)
self
.
_
fuse_batch_norm
(
program
,
place
,
scope
)
self
.
_
fuse_relu_mkldnn
(
program
)
def
fuse_relu_mkldnn
(
self
,
program
):
def
_
fuse_relu_mkldnn
(
self
,
program
):
'''
Transpile the program by fused relu activation for MKLDNN program.
...
...
@@ -104,7 +104,7 @@ class InferenceTranspiler(object):
# And a better solution will be considered later.
program
=
program
.
clone
()
def
fuse_batch_norm
(
self
,
program
,
place
,
scope
):
def
_
fuse_batch_norm
(
self
,
program
,
place
,
scope
):
'''
Transpile the program by fused batch normalization.
...
...
python/requirements.txt
浏览文件 @
1800fef1
requests==2.9.2
numpy>=1.12
numpy>=1.12
,<=1.14 #TODO:change to ">=1.12" when numpy fix bug in 1.15 and higher version
protobuf==3.1
recordio>=0.1.0
matplotlib
...
...
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