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b8051e79
编写于
12月 21, 2018
作者:
S
sneaxiy
浏览文件
操作
浏览文件
下载
差异文件
merge develop
test=develop
上级
df1e4e2f
95cbe07c
变更
21
隐藏空白更改
内联
并排
Showing
21 changed file
with
884 addition
and
4 deletion
+884
-4
paddle/fluid/API.spec
paddle/fluid/API.spec
+1
-0
paddle/fluid/framework/op_desc.h
paddle/fluid/framework/op_desc.h
+2
-0
paddle/fluid/framework/shape_inference.h
paddle/fluid/framework/shape_inference.h
+2
-0
paddle/fluid/inference/tests/api/analyzer_dam_tester.cc
paddle/fluid/inference/tests/api/analyzer_dam_tester.cc
+11
-0
paddle/fluid/inference/tests/api/analyzer_lac_tester.cc
paddle/fluid/inference/tests/api/analyzer_lac_tester.cc
+11
-0
paddle/fluid/inference/tests/api/analyzer_ner_tester.cc
paddle/fluid/inference/tests/api/analyzer_ner_tester.cc
+11
-0
paddle/fluid/inference/tests/api/analyzer_resnet50_tester.cc
paddle/fluid/inference/tests/api/analyzer_resnet50_tester.cc
+11
-0
paddle/fluid/inference/tests/api/analyzer_rnn1_tester.cc
paddle/fluid/inference/tests/api/analyzer_rnn1_tester.cc
+11
-0
paddle/fluid/inference/tests/api/analyzer_rnn2_tester.cc
paddle/fluid/inference/tests/api/analyzer_rnn2_tester.cc
+11
-0
paddle/fluid/inference/tests/api/analyzer_seq_conv1_tester.cc
...le/fluid/inference/tests/api/analyzer_seq_conv1_tester.cc
+11
-0
paddle/fluid/inference/tests/api/analyzer_text_classification_tester.cc
...nference/tests/api/analyzer_text_classification_tester.cc
+11
-0
paddle/fluid/inference/tests/api/analyzer_vis_tester.cc
paddle/fluid/inference/tests/api/analyzer_vis_tester.cc
+11
-0
paddle/fluid/inference/tests/api/tester_helper.h
paddle/fluid/inference/tests/api/tester_helper.h
+22
-1
paddle/fluid/operators/CMakeLists.txt
paddle/fluid/operators/CMakeLists.txt
+5
-2
paddle/fluid/operators/py_func_op.cc
paddle/fluid/operators/py_func_op.cc
+313
-0
paddle/fluid/operators/py_func_op.h
paddle/fluid/operators/py_func_op.h
+25
-0
paddle/fluid/pybind/CMakeLists.txt
paddle/fluid/pybind/CMakeLists.txt
+3
-0
paddle/fluid/pybind/protobuf.cc
paddle/fluid/pybind/protobuf.cc
+1
-1
paddle/fluid/pybind/pybind.cc
paddle/fluid/pybind/pybind.cc
+7
-0
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+221
-0
python/paddle/fluid/tests/unittests/test_py_func_op.py
python/paddle/fluid/tests/unittests/test_py_func_op.py
+183
-0
未找到文件。
paddle/fluid/API.spec
浏览文件 @
b8051e79
...
...
@@ -208,6 +208,7 @@ paddle.fluid.layers.bilinear_tensor_product ArgSpec(args=['x', 'y', 'size', 'act
paddle.fluid.layers.merge_selected_rows ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.get_tensor_from_selected_rows ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.lstm ArgSpec(args=['input', 'init_h', 'init_c', 'max_len', 'hidden_size', 'num_layers', 'dropout_prob', 'is_bidirec', 'is_test', 'name', 'default_initializer', 'seed'], varargs=None, keywords=None, defaults=(0.0, False, False, None, None, -1))
paddle.fluid.layers.py_func ArgSpec(args=['func', 'x', 'out', 'backward_func', 'skip_vars_in_backward_input'], varargs=None, keywords=None, defaults=(None, None))
paddle.fluid.layers.psroi_pool ArgSpec(args=['input', 'rois', 'output_channels', 'spatial_scale', 'pooled_height', 'pooled_width', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.huber_loss ArgSpec(args=['input', 'label', 'delta'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.data ArgSpec(args=['name', 'shape', 'append_batch_size', 'dtype', 'lod_level', 'type', 'stop_gradient'], varargs=None, keywords=None, defaults=(True, 'float32', 0, VarType.LOD_TENSOR, True))
...
...
paddle/fluid/framework/op_desc.h
浏览文件 @
b8051e79
...
...
@@ -123,6 +123,8 @@ class OpDesc {
BlockDesc
*
Block
()
{
return
this
->
block_
;
}
const
BlockDesc
*
Block
()
const
{
return
this
->
block_
;
}
private:
template
<
typename
MapType
>
static
std
::
vector
<
typename
MapType
::
key_type
>
MapKeys
(
const
MapType
&
map
)
{
...
...
paddle/fluid/framework/shape_inference.h
浏览文件 @
b8051e79
...
...
@@ -25,6 +25,8 @@ limitations under the License. */
namespace
paddle
{
namespace
framework
{
class
OperatorBase
;
using
InferShapeVarPtr
=
boost
::
variant
<
VarDesc
*
,
Variable
*>
;
class
InferShapeContext
{
...
...
paddle/fluid/inference/tests/api/analyzer_dam_tester.cc
浏览文件 @
b8051e79
...
...
@@ -254,5 +254,16 @@ TEST(Analyzer_dam, compare) { compare(); }
TEST
(
Analyzer_dam
,
compare_mkldnn
)
{
compare
(
true
/* use_mkldnn */
);
}
#endif
// Compare Deterministic result
TEST
(
Analyzer_dam
,
compare_determine
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
CompareDeterministic
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
}
// namespace inference
}
// namespace paddle
paddle/fluid/inference/tests/api/analyzer_lac_tester.cc
浏览文件 @
b8051e79
...
...
@@ -180,6 +180,17 @@ TEST(Analyzer_LAC, compare) {
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
// Compare Deterministic result
TEST
(
Analyzer_LAC
,
compare_determine
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
CompareDeterministic
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
}
// namespace analysis
}
// namespace inference
}
// namespace paddle
paddle/fluid/inference/tests/api/analyzer_ner_tester.cc
浏览文件 @
b8051e79
...
...
@@ -179,5 +179,16 @@ TEST(Analyzer_Chinese_ner, compare) {
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
// Compare Deterministic result
TEST
(
Analyzer_Chinese_ner
,
compare_determine
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
CompareDeterministic
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
}
// namespace inference
}
// namespace paddle
paddle/fluid/inference/tests/api/analyzer_resnet50_tester.cc
浏览文件 @
b8051e79
...
...
@@ -85,6 +85,17 @@ TEST(Analyzer_resnet50, compare) { compare(); }
TEST
(
Analyzer_resnet50
,
compare_mkldnn
)
{
compare
(
true
/* use_mkldnn */
);
}
#endif
// Compare Deterministic result
TEST
(
Analyzer_resnet50
,
compare_determine
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
CompareDeterministic
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
}
// namespace analysis
}
// namespace inference
}
// namespace paddle
paddle/fluid/inference/tests/api/analyzer_rnn1_tester.cc
浏览文件 @
b8051e79
...
...
@@ -265,6 +265,17 @@ TEST(Analyzer_rnn1, compare) {
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
// Compare Deterministic result
TEST
(
Analyzer_rnn1
,
compare_determine
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
CompareDeterministic
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
// Test Multi-Thread.
TEST
(
Analyzer_rnn1
,
multi_thread
)
{
contrib
::
AnalysisConfig
cfg
;
...
...
paddle/fluid/inference/tests/api/analyzer_rnn2_tester.cc
浏览文件 @
b8051e79
...
...
@@ -158,5 +158,16 @@ TEST(Analyzer_rnn2, compare) {
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
// Compare Deterministic result
TEST
(
Analyzer_rnn2
,
compare_determine
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
CompareDeterministic
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
}
// namespace inference
}
// namespace paddle
paddle/fluid/inference/tests/api/analyzer_seq_conv1_tester.cc
浏览文件 @
b8051e79
...
...
@@ -204,5 +204,16 @@ TEST(Analyzer_seq_conv1, compare) {
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
// Compare Deterministic result
TEST
(
Analyzer_seq_conv1
,
compare_determine
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
CompareDeterministic
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
}
// namespace inference
}
// namespace paddle
paddle/fluid/inference/tests/api/analyzer_text_classification_tester.cc
浏览文件 @
b8051e79
...
...
@@ -106,6 +106,17 @@ TEST(Analyzer_Text_Classification, compare) {
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
// Compare Deterministic result
TEST
(
Analyzer_Text_Classification
,
compare_determine
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
CompareDeterministic
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
TEST
(
Analyzer_Text_Classification
,
compare_against_embedding_fc_lstm_fused
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
...
...
paddle/fluid/inference/tests/api/analyzer_vis_tester.cc
浏览文件 @
b8051e79
...
...
@@ -145,6 +145,17 @@ TEST(Analyzer_vis, compare) { compare(); }
TEST
(
Analyzer_vis
,
compare_mkldnn
)
{
compare
(
true
/* use_mkldnn */
);
}
#endif
// Compare Deterministic result
TEST
(
Analyzer_vis
,
compare_determine
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
CompareDeterministic
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
}
// namespace analysis
}
// namespace inference
}
// namespace paddle
paddle/fluid/inference/tests/api/tester_helper.h
浏览文件 @
b8051e79
...
...
@@ -45,6 +45,7 @@ DEFINE_bool(use_analysis, true,
"Running the inference program in analysis mode."
);
DEFINE_bool
(
record_benchmark
,
false
,
"Record benchmark after profiling the model"
);
DEFINE_double
(
accuracy
,
1e-3
,
"Result Accuracy."
);
DECLARE_bool
(
profile
);
DECLARE_int32
(
paddle_num_threads
);
...
...
@@ -85,7 +86,7 @@ void CompareResult(const std::vector<PaddleTensor> &outputs,
float
*
pdata
=
static_cast
<
float
*>
(
out
.
data
.
data
());
float
*
pdata_ref
=
static_cast
<
float
*>
(
ref_out
.
data
.
data
());
for
(
size_t
j
=
0
;
j
<
size
;
++
j
)
{
EXPECT_NEAR
(
pdata_ref
[
j
],
pdata
[
j
],
1e-3
);
EXPECT_NEAR
(
pdata_ref
[
j
],
pdata
[
j
],
FLAGS_accuracy
);
}
break
;
}
...
...
@@ -283,6 +284,26 @@ void TestPrediction(const PaddlePredictor::Config *config,
}
}
void
CompareDeterministic
(
const
PaddlePredictor
::
Config
*
config
,
const
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
&
inputs
)
{
int
batch_size
=
FLAGS_batch_size
;
int
num_times
=
FLAGS_repeat
;
auto
predictor
=
CreateTestPredictor
(
config
,
FLAGS_use_analysis
);
// warmup run
std
::
vector
<
PaddleTensor
>
warmup_outputs
,
outputs
;
predictor
->
Run
(
inputs
[
0
],
&
warmup_outputs
,
batch_size
);
// run num_times to Compare Deterministic Result.
for
(
int
i
=
0
;
i
<
num_times
;
i
++
)
{
for
(
size_t
j
=
0
;
j
<
inputs
.
size
();
j
++
)
{
predictor
->
Run
(
inputs
[
j
],
&
outputs
,
batch_size
);
CompareResult
(
outputs
,
warmup_outputs
);
}
}
}
void
CompareNativeAndAnalysis
(
const
PaddlePredictor
::
Config
*
config
,
const
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
&
inputs
)
{
...
...
paddle/fluid/operators/CMakeLists.txt
浏览文件 @
b8051e79
...
...
@@ -42,8 +42,7 @@ if (WITH_DISTRIBUTE)
SET
(
OP_PREFETCH_DEPS
${
OP_PREFETCH_DEPS
}
parameter_prefetch
)
endif
()
register_operators
(
EXCLUDES warpctc_op conv_fusion_op DEPS
${
OP_HEADER_DEPS
}
${
OP_PREFETCH_DEPS
}
)
register_operators
(
EXCLUDES py_func_op warpctc_op conv_fusion_op DEPS
${
OP_HEADER_DEPS
}
${
OP_PREFETCH_DEPS
}
)
# warpctc_op needs cudnn 7 above
if
(
WITH_GPU AND NOT WIN32
)
...
...
@@ -92,4 +91,8 @@ cc_test(save_load_op_test SRCS save_load_op_test.cc DEPS save_op load_op)
cc_test
(
save_load_combine_op_test SRCS save_load_combine_op_test.cc DEPS save_combine_op load_combine_op
)
nv_test
(
dropout_op_test SRCS dropout_op_test.cc DEPS dropout_op tensor
)
if
(
WITH_PYTHON
)
cc_library
(
py_func_op SRCS py_func_op.cc DEPS op_registry python pybind
)
endif
()
set
(
GLOB_OP_LIB
${
OP_LIBRARY
}
CACHE INTERNAL
"Global OP library"
)
paddle/fluid/operators/py_func_op.cc
0 → 100644
浏览文件 @
b8051e79
// 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/operators/py_func_op.h"
#include <set>
#include <string>
#include <vector>
#include "Python.h"
#include "paddle/fluid/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
namespace
py
=
::
pybind11
;
static
std
::
vector
<
py
::
object
>
g_py_callables
;
const
char
kForwardPythonCallableId
[]
=
"forward_callable_id"
;
const
char
kBackwardPythonCallableId
[]
=
"backward_callable_id"
;
const
char
kPyFuncBackwardSkipVars
[]
=
"backward_skip_vars"
;
size_t
AppendPythonCallableObjectAndReturnId
(
const
py
::
object
&
py_obj
)
{
g_py_callables
.
emplace_back
(
py_obj
);
return
g_py_callables
.
size
()
-
1
;
}
// Return py::object* instead of py::object
// Returning py::object would cause reference count increasing
// but without GIL, reference count in Python may not be safe
static
py
::
object
*
GetPythonCallableObject
(
size_t
i
)
{
PADDLE_ENFORCE_LT
(
i
,
g_py_callables
.
size
(),
"Invalid python callable id"
);
return
&
g_py_callables
[
i
];
}
static
std
::
string
PythonFuncDebugString
(
const
py
::
object
&
py_callable
)
{
py
::
gil_scoped_acquire
guard
;
std
::
string
wrapper_func_str
=
py
::
str
(
py_callable
);
auto
inner_func
=
py_callable
.
attr
(
"_func"
);
std
::
string
inner_func_str
=
py
::
str
(
inner_func
);
return
inner_func_str
+
" wrapped by "
+
wrapper_func_str
;
}
static
void
CallPythonFunc
(
py
::
object
*
callable
,
const
std
::
vector
<
framework
::
LoDTensor
>
&
ins
,
std
::
vector
<
framework
::
LoDTensor
*>
*
outs
)
{
py
::
gil_scoped_acquire
guard
;
py
::
tuple
in_args
(
ins
.
size
());
for
(
size_t
i
=
0
;
i
<
ins
.
size
();
++
i
)
{
in_args
[
i
]
=
ins
[
i
].
IsInitialized
()
?
py
::
cast
(
ins
[
i
])
:
py
::
cast
(
nullptr
);
}
auto
ret
=
(
*
callable
)(
*
in_args
);
auto
ret_tuple
=
py
::
cast
<
py
::
tuple
>
(
ret
);
size_t
ret_num
=
py
::
len
(
ret_tuple
);
size_t
out_num
=
outs
->
size
();
if
(
UNLIKELY
(
ret_num
!=
out_num
))
{
// Python function has no return values or returns None
// In this case, ret_num = 1 && ret[0] == None && out_num should be 0
// Otherwise, ret_num must be equal to out_num
PADDLE_ENFORCE
(
ret_num
==
1
&&
out_num
==
0
&&
py
::
cast
<
framework
::
LoDTensor
*>
(
ret_tuple
[
0
])
==
nullptr
,
"Output number not match. Expected %d, actual %d"
,
out_num
,
ret_num
);
}
for
(
size_t
i
=
0
;
i
<
out_num
;
++
i
)
{
auto
*
out
=
(
*
outs
)[
i
];
if
(
out
==
nullptr
)
{
continue
;
}
try
{
auto
*
py_out_tensor
=
py
::
cast
<
framework
::
LoDTensor
*>
(
ret_tuple
[
i
]);
PADDLE_ENFORCE_NOT_NULL
(
py_out_tensor
,
"Output tensor %d should not be nullptr"
,
i
);
out
->
set_lod
(
py_out_tensor
->
lod
());
out
->
ShareDataWith
(
*
py_out_tensor
);
}
catch
(
py
::
cast_error
&
)
{
PADDLE_THROW
(
"The %d-th output must be LoDTensor"
,
i
);
}
}
}
class
PyFuncOpVarTypInference
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op
,
framework
::
BlockDesc
*
block
)
const
override
{
auto
&
outs
=
op
.
Outputs
();
bool
has_out
=
(
outs
.
count
(
"Out"
)
>
0
&&
!
outs
.
at
(
"Out"
).
empty
());
auto
&
ins
=
op
.
Inputs
();
bool
has_in
=
(
ins
.
count
(
"X"
)
>
0
&&
!
ins
.
at
(
"X"
).
empty
());
/**
* X or Out can be empty, so that py_func can be more flexible
* to support Python functions with no input or no output
*/
PADDLE_ENFORCE
(
has_in
||
has_out
,
"Input(X) or Output(Out) must exist"
);
PADDLE_ENFORCE_GE
(
boost
::
get
<
int
>
(
op
.
GetAttr
(
kForwardPythonCallableId
)),
0
,
"Function id cannot be less than 0"
);
if
(
!
has_out
)
return
;
/**
* Traverse all outputs, check if name of any output ends with @GRAD.
* If found, set its shape, dtype, lod_level, type to be the same as
* the corresponding forward variable
*/
const
std
::
string
kGradVarSuffix
=
framework
::
kGradVarSuffix
;
auto
&
out_var_names
=
outs
.
at
(
"Out"
);
for
(
auto
&
out_var_name
:
out_var_names
)
{
if
(
out_var_name
==
framework
::
kEmptyVarName
||
out_var_name
.
size
()
<
kGradVarSuffix
.
size
())
{
continue
;
}
size_t
len
=
out_var_name
.
size
()
-
kGradVarSuffix
.
size
();
if
(
out_var_name
.
substr
(
len
)
==
kGradVarSuffix
)
{
auto
fwd_var_name
=
out_var_name
.
substr
(
0
,
len
);
auto
*
out_var_desc
=
block
->
FindVarRecursive
(
out_var_name
);
auto
*
fwd_var_desc
=
block
->
FindVarRecursive
(
fwd_var_name
);
PADDLE_ENFORCE_NOT_NULL
(
out_var_desc
,
"Backward variable %s not found"
,
out_var_name
);
PADDLE_ENFORCE_NOT_NULL
(
fwd_var_desc
,
"Forward variable %s not found"
,
fwd_var_name
);
VLOG
(
10
)
<<
"Infer var_desc of Output("
<<
out_var_name
<<
") as Input("
<<
fwd_var_name
<<
")"
;
out_var_desc
->
SetShape
(
fwd_var_desc
->
GetShape
());
out_var_desc
->
SetDataType
(
fwd_var_desc
->
GetDataType
());
out_var_desc
->
SetLoDLevel
(
fwd_var_desc
->
GetLoDLevel
());
out_var_desc
->
SetType
(
fwd_var_desc
->
GetType
());
}
}
}
};
class
PyFuncOpShapeInference
:
public
framework
::
InferShapeBase
{
public:
void
operator
()(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
!
ctx
->
IsRuntime
(),
"Infer shape cannot be called in runtime."
);
}
};
class
PyFuncOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"X"
,
"Inputs of py_func op."
).
AsDuplicable
();
AddOutput
(
"Out"
,
"Outputs of py_func op"
).
AsDuplicable
();
AddAttr
<
int
>
(
kForwardPythonCallableId
,
"Index of registered forward Python function."
)
.
SetDefault
(
0
);
AddAttr
<
int
>
(
kBackwardPythonCallableId
,
"Index of registered backward Python function."
)
.
SetDefault
(
-
1
);
AddAttr
<
std
::
vector
<
std
::
string
>>
(
kPyFuncBackwardSkipVars
,
"Unused forward in/out in backward op"
)
.
SetDefault
(
std
::
vector
<
std
::
string
>
());
AddComment
(
R"DOC("PyFunc Op")DOC"
);
}
};
/**
* There are several benefits when backward op of py_func op is
* still py_func op.
*
* - Less codes are needed, since codes of backward is almost
* the same as forward.
*
* - To support high order derivative, so that py_func is
* infinite-order differentiable
*/
class
PyFuncOpGradDescMaker
:
public
framework
::
GradOpDescMakerBase
{
private:
static
std
::
string
DebugString
(
const
std
::
vector
<
std
::
string
>
&
strs
)
{
if
(
strs
.
empty
())
return
""
;
std
::
string
ret
=
strs
[
0
];
for
(
size_t
i
=
1
;
i
<
strs
.
size
();
++
i
)
{
ret
+=
" "
;
ret
+=
strs
[
i
];
}
return
ret
;
}
public:
using
framework
::
GradOpDescMakerBase
::
GradOpDescMakerBase
;
std
::
vector
<
std
::
unique_ptr
<
framework
::
OpDesc
>>
operator
()()
const
override
{
auto
&
fwd_attrs
=
Attrs
();
// no backward op when backward_id is less than 0
if
(
boost
::
get
<
int
>
(
fwd_attrs
.
at
(
kBackwardPythonCallableId
))
<
0
)
{
return
{};
}
std
::
unique_ptr
<
framework
::
OpDesc
>
grad_op
(
new
framework
::
OpDesc
());
grad_op
->
SetType
(
"py_func"
);
framework
::
AttributeMap
bwd_attrs
;
bwd_attrs
[
kForwardPythonCallableId
]
=
fwd_attrs
.
at
(
kBackwardPythonCallableId
);
bwd_attrs
[
kBackwardPythonCallableId
]
=
-
1
;
grad_op
->
SetAttrMap
(
bwd_attrs
);
// All forward inputs
auto
fwd_ins
=
Input
(
"X"
);
// All forward outputs
auto
fwd_outs
=
Output
(
"Out"
);
// For memory reused, some inputs/output in forward part may be not needed
// in backward part. Skipping these vars helps to save memory
auto
&
backward_skip_var_list
=
boost
::
get
<
std
::
vector
<
std
::
string
>>
(
fwd_attrs
.
at
(
kPyFuncBackwardSkipVars
));
std
::
unordered_set
<
std
::
string
>
backward_skip_var_set
(
backward_skip_var_list
.
begin
(),
backward_skip_var_list
.
end
());
std
::
vector
<
std
::
string
>
bwd_ins
;
bwd_ins
.
reserve
(
fwd_ins
.
size
()
+
fwd_outs
.
size
());
for
(
auto
&
fwd_in
:
fwd_ins
)
{
if
(
backward_skip_var_set
.
count
(
fwd_in
)
==
0
)
{
bwd_ins
.
emplace_back
(
fwd_in
);
}
}
for
(
auto
&
fwd_out
:
fwd_outs
)
{
if
(
backward_skip_var_set
.
count
(
fwd_out
)
==
0
)
{
bwd_ins
.
emplace_back
(
fwd_out
);
}
}
// Backward OG cannot be skipped
// But in Python side, if OG is kEmptyVarName, input tensor would be None
auto
fwd_out_grads
=
OutputGrad
(
"Out"
);
bwd_ins
.
reserve
(
bwd_ins
.
size
()
+
fwd_out_grads
.
size
());
bwd_ins
.
insert
(
bwd_ins
.
end
(),
fwd_out_grads
.
begin
(),
fwd_out_grads
.
end
());
// Backward IG cannot be skipped
// But in Python side, if IG is not needed, users can just return None
auto
bwd_outs
=
InputGrad
(
"X"
,
false
);
VLOG
(
10
)
<<
"PyFunc Grad Input: "
<<
DebugString
(
bwd_ins
);
VLOG
(
10
)
<<
"PyFunc Grad Output: "
<<
DebugString
(
bwd_outs
);
grad_op
->
SetInput
(
"X"
,
bwd_ins
);
grad_op
->
SetOutput
(
"Out"
,
bwd_outs
);
std
::
vector
<
std
::
unique_ptr
<
framework
::
OpDesc
>>
ret
(
1
);
ret
[
0
]
=
std
::
move
(
grad_op
);
return
ret
;
}
};
class
PyFuncOp
:
public
framework
::
OperatorBase
{
public:
using
framework
::
OperatorBase
::
OperatorBase
;
protected:
void
RunImpl
(
const
framework
::
Scope
&
scope
,
const
platform
::
Place
&
place
)
const
override
{
auto
&
in_arg_names
=
Inputs
(
"X"
);
auto
&
out_arg_names
=
Outputs
(
"Out"
);
std
::
vector
<
framework
::
LoDTensor
>
inputs
(
in_arg_names
.
size
());
for
(
size_t
i
=
0
;
i
<
in_arg_names
.
size
();
++
i
)
{
auto
in_var
=
scope
.
FindVar
(
in_arg_names
[
i
]);
// When py_func op is called in backward, in_var may be null
if
(
in_var
==
nullptr
)
{
continue
;
}
auto
&
in_tensor
=
in_var
->
Get
<
framework
::
LoDTensor
>
();
if
(
!
in_tensor
.
IsInitialized
())
{
continue
;
}
if
(
platform
::
is_gpu_place
(
in_tensor
.
place
()))
{
framework
::
TensorCopySync
(
in_tensor
,
platform
::
CPUPlace
(),
&
inputs
[
i
]);
}
else
{
inputs
[
i
].
ShareDataWith
(
in_tensor
);
}
inputs
[
i
].
set_lod
(
in_tensor
.
lod
());
}
std
::
vector
<
framework
::
LoDTensor
*>
outputs
(
out_arg_names
.
size
());
for
(
size_t
i
=
0
;
i
<
out_arg_names
.
size
();
++
i
)
{
auto
*
out_var
=
scope
.
FindVar
(
out_arg_names
[
i
]);
outputs
[
i
]
=
out_var
?
out_var
->
GetMutable
<
framework
::
LoDTensor
>
()
:
nullptr
;
}
auto
callable_id
=
static_cast
<
size_t
>
(
Attr
<
int
>
(
kForwardPythonCallableId
));
auto
*
py_callable
=
GetPythonCallableObject
(
callable_id
);
VLOG
(
10
)
<<
"Call Python function with id "
<<
callable_id
<<
": "
<<
PythonFuncDebugString
(
*
py_callable
);
CallPythonFunc
(
py_callable
,
inputs
,
&
outputs
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
py_func
,
ops
::
PyFuncOp
,
ops
::
PyFuncOpMaker
,
ops
::
PyFuncOpVarTypInference
,
ops
::
PyFuncOpShapeInference
,
ops
::
PyFuncOpGradDescMaker
);
paddle/fluid/operators/py_func_op.h
0 → 100644
浏览文件 @
b8051e79
// 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.
#pragma once
#include "pybind11/pybind11.h"
namespace
paddle
{
namespace
operators
{
size_t
AppendPythonCallableObjectAndReturnId
(
const
::
pybind11
::
object
&
py_obj
);
}
// namespace operators
}
// namespace paddle
paddle/fluid/pybind/CMakeLists.txt
浏览文件 @
b8051e79
set
(
PYBIND_DEPS pybind python proto_desc memory executor async_executor prune feed_fetch_method pass_builder parallel_executor profiler layer
)
if
(
WITH_PYTHON
)
list
(
APPEND PYBIND_DEPS py_func_op
)
endif
()
set
(
PYBIND_SRCS pybind.cc exception.cc protobuf.cc const_value.cc recordio.cc async_executor_py.cc imperative.cc
)
if
(
WITH_PYTHON
)
...
...
paddle/fluid/pybind/protobuf.cc
浏览文件 @
b8051e79
...
...
@@ -328,7 +328,7 @@ void BindOpDesc(pybind11::module *m) {
.
def
(
"infer_var_type"
,
&
pd
::
OpDesc
::
InferVarType
)
.
def
(
"set_is_target"
,
&
pd
::
OpDesc
::
SetIsTarget
)
.
def
(
"serialize_to_string"
,
SerializeMessage
<
pd
::
OpDesc
>
)
.
def
(
"block"
,
&
pd
::
OpDesc
::
Block
,
.
def
(
"block"
,
[](
pd
::
OpDesc
&
self
)
{
return
self
.
Block
();
}
,
pybind11
::
return_value_policy
::
reference
);
}
...
...
paddle/fluid/pybind/pybind.cc
浏览文件 @
b8051e79
...
...
@@ -37,6 +37,7 @@ limitations under the License. */
#include "paddle/fluid/imperative/layer.h"
#include "paddle/fluid/memory/allocation/allocator_strategy.h"
#include "paddle/fluid/operators/activation_op.h"
#include "paddle/fluid/operators/py_func_op.h"
#include "paddle/fluid/operators/reader/lod_tensor_blocking_queue.h"
#include "paddle/fluid/platform/cpu_info.h"
#include "paddle/fluid/platform/enforce.h"
...
...
@@ -110,6 +111,12 @@ PYBIND11_MODULE(core, m) {
BindException
(
&
m
);
m
.
def
(
"_append_python_callable_object_and_return_id"
,
[](
py
::
object
py_obj
)
->
size_t
{
return
paddle
::
operators
::
AppendPythonCallableObjectAndReturnId
(
py_obj
);
});
py
::
class_
<
imperative
::
VarBase
,
PyVarBase
>
(
m
,
"VarBase"
,
R"DOC()DOC"
)
.
def
(
py
::
init
<>
())
.
def
(
"_run_backward"
,
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
b8051e79
...
...
@@ -18,7 +18,9 @@ All layers just related to the neural network.
from
__future__
import
print_function
import
numpy
as
np
import
six
import
os
import
inspect
from
..layer_helper
import
LayerHelper
from
..initializer
import
Normal
,
Constant
from
..framework
import
Variable
,
OpProtoHolder
...
...
@@ -176,6 +178,7 @@ __all__ = [
'merge_selected_rows'
,
'get_tensor_from_selected_rows'
,
'lstm'
,
'py_func'
,
'psroi_pool'
,
'huber_loss'
,
]
...
...
@@ -9327,6 +9330,224 @@ def get_tensor_from_selected_rows(x, name=None):
return
out
class
PyFuncRegistry
(
object
):
_register_funcs
=
[]
def
__init__
(
self
,
func
):
if
func
is
None
or
not
callable
(
func
):
raise
TypeError
(
'func must be a Python function'
)
self
.
_func
=
func
# find named args using reflection
args
=
inspect
.
getargspec
(
self
.
_func
)
if
len
(
args
[
0
])
==
0
and
args
[
1
]
is
None
and
args
[
2
]
is
None
:
# Function with no inputs
self
.
_named_args
=
None
else
:
self
.
_named_args
=
args
[
0
]
self
.
_id
=
core
.
_append_python_callable_object_and_return_id
(
self
)
'''
Why record self here?
1. For debug usage. Users can call
:code:`py_func.registered_func(idx)` method
to find the registered function corresponding
to :code:`idx`.
2. For increasing reference count of self.
It seems that to release Python object
whose reference count is 1 would cause
segmentation fault error in C++ side.
May be lack of Python GC in C++ side?
'''
PyFuncRegistry
.
_register_funcs
.
append
(
self
)
@
classmethod
def
registered_func
(
cls
,
idx
):
return
cls
.
_register_funcs
[
idx
].
_func
@
classmethod
def
registered_func_num
(
cls
):
return
len
(
cls
.
_register_funcs
)
@
property
def
id
(
self
):
return
self
.
_id
def
__call__
(
self
,
*
args
):
if
self
.
_named_args
is
None
:
func_ret
=
self
.
_func
()
else
:
kwargs
=
dict
()
idx
=
0
for
arg
in
self
.
_named_args
:
kwargs
[
arg
]
=
args
[
idx
]
idx
+=
1
func_ret
=
self
.
_func
(
*
args
[
idx
:],
**
kwargs
)
if
not
isinstance
(
func_ret
,
(
list
,
tuple
)):
func_ret
=
(
func_ret
,
)
ret
=
[]
for
each_ret
in
func_ret
:
if
each_ret
is
None
or
isinstance
(
each_ret
,
core
.
LoDTensor
):
ret
.
append
(
each_ret
)
continue
if
not
isinstance
(
each_ret
,
np
.
ndarray
):
each_ret
=
np
.
array
(
each_ret
)
tensor
=
core
.
LoDTensor
()
tensor
.
set
(
each_ret
,
core
.
CPUPlace
())
ret
.
append
(
tensor
)
return
tuple
(
ret
)
@
templatedoc
()
def
py_func
(
func
,
x
,
out
,
backward_func
=
None
,
skip_vars_in_backward_input
=
None
):
"""
PyFunc Operator.
User can use :code:`py_func` to register operators in Python side.
The inputs of :code:`func` is :code:`LoDTensor` and outputs can be
numpy array or :code:`LoDTensor`. Paddle would call the registered
:code:`func` in forward part, and call :code:`backward_func` in
backward part (if :code:`backward_func` is not None).
User should set the right data type and shape of :code:`out` before
calling this function. However, data types and shapes of gradients of
:code:`out` and :code:`x` would be inferred automatically.
Input orders of :code:`backward_func` would be: forward inputs
:code:`x`, forward outputs :code:`out` and backward input gradients of
:code:`out`. If some variables of :code:`out` have no gradient, the input
tensor would be None in Python side. If some variables of :code:`in` have
no gradient, users should return None.
This function can also be used to debug the running network. User can
add a :code:`py_func` operator without output, and print input
:code:`x` inside :code:`func`.
Args:
func (callable): forward Python function.
x (Variable|list(Variable)|tuple(Variable)): inputs of :code:`func`.
out (Variable|list(Variable)|tuple(Variable)): outputs of :code:`func`.
Paddle cannot infer shapes and data types of :code:`out`. Users
should create :code:`out` beforehand.
backward_func (callable|None): backward Python function.
None means no backward. Default None.
skip_vars_in_backward_input (Variable|list(Variable)|tuple(Variable)):
Variables that are not needed in :code:`backward_func` inputs.
These variables must be any of :code:`x` and :code:`out`.
If set, these vars would not be inputs of :code:`backward_func`,
Only useful when :code:`backward_func` is not None. Default None.
Returns:
out (Variable|list(Variable)|tuple(Variable)): input :code:`out`
Examples:
>>> import paddle.fluid as fluid
>>> import six
>>>
>>> def create_tmp_var(name, dtype, shape):
>>> return fluid.default_main_program().current_block().create_var(
>>> name=name, dtype=dtype, shape=shape)
>>>
>>> # tanh activation has been provided by Paddle C++ op
>>> # Here, we only use tanh to be an example to show the usage
>>> # of py_func
>>> def tanh(x):
>>> return np.tanh(x)
>>>
>>> # forward input x is skipped
>>> def tanh_grad(y, dy):
>>> return np.array(dy) * (1 - np.square(np.array(y)))
>>>
>>> def debug_func(x):
>>> print(x)
>>>
>>> def simple_net(img, label):
>>> hidden = img
>>> for idx in six.moves.range(4):
>>> hidden = fluid.layers.fc(hidden, size=200)
>>> new_hidden = create_tmp_var(name='hidden_{}'.format(idx),
>>> dtype=hidden.dtype, shape=hidden.shape)
>>>
>>> # user-defined layers with forward and backward
>>> hidden = fluid.layers.py_func(func=tanh, x=hidden,
>>> out=new_hidden, backward_func=tanh_grad,
>>> skip_vars_in_backward_input=hidden)
>>>
>>> # user-defined debug layers to print variables
>>> fluid.layers.py_func(func=debug_func, x=hidden, out=None)
>>>
>>> prediction = fluid.layers.fc(hidden, size=10, act='softmax')
>>> loss = fluid.layers.cross_entropy(input=prediction, label=label)
>>> return fluid.layers.mean(loss)
"""
helper
=
LayerHelper
(
'py_func'
,
**
locals
())
if
x
is
None
:
x
=
[]
elif
isinstance
(
x
,
Variable
):
x
=
[
x
]
elif
not
isinstance
(
x
,
(
list
,
tuple
)):
raise
TypeError
(
'Input must be Variable/list(Variable)/tuple(Variable)'
)
if
out
is
None
:
out_list
=
[]
elif
isinstance
(
out
,
Variable
):
out_list
=
[
out
]
elif
isinstance
(
out
,
(
list
,
tuple
)):
out_list
=
out
else
:
raise
TypeError
(
'Output must be Variable/list(Variable)/tuple(Variable)'
)
fwd_func_id
=
PyFuncRegistry
(
func
).
id
bwd_func_id
=
PyFuncRegistry
(
backward_func
).
id
if
backward_func
is
not
None
else
-
1
for
each_out
in
out_list
:
if
len
(
each_out
.
shape
)
==
0
:
raise
ValueError
(
'Output shapes of py_func op should be provided by users manually'
)
backward_skip_vars
=
set
()
if
backward_func
is
not
None
and
skip_vars_in_backward_input
is
not
None
:
if
isinstance
(
skip_vars_in_backward_input
,
Variable
):
skip_vars_in_backward_input
=
[
skip_vars_in_backward_input
]
fwd_in_out
=
[
v
.
name
for
v
in
x
]
fwd_in_out
.
extend
([
v
.
name
for
v
in
out_list
])
fwd_in_out
=
set
(
fwd_in_out
)
backward_skip_vars
=
set
()
for
v
in
skip_vars_in_backward_input
:
if
not
v
.
name
in
fwd_in_out
:
raise
ValueError
(
'Variable {} is not found in forward inputs and outputs'
.
format
(
v
.
name
))
backward_skip_vars
.
add
(
v
.
name
)
helper
.
append_op
(
type
=
'py_func'
,
inputs
=
{
'X'
:
x
},
outputs
=
{
'Out'
:
out_list
},
attrs
=
{
'forward_callable_id'
:
fwd_func_id
,
'backward_callable_id'
:
bwd_func_id
,
'backward_skip_vars'
:
list
(
backward_skip_vars
)
})
return
out
# For debug usage
py_func
.
registered_func
=
PyFuncRegistry
.
registered_func
py_func
.
registered_func_num
=
PyFuncRegistry
.
registered_func_num
@
templatedoc
()
def
psroi_pool
(
input
,
rois
,
...
...
python/paddle/fluid/tests/unittests/test_py_func_op.py
0 → 100644
浏览文件 @
b8051e79
# 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
os
import
paddle.fluid
as
fluid
import
paddle
import
unittest
import
six
import
numpy
as
np
dev_cnt
=
2
if
fluid
.
core
.
is_compiled_with_cuda
():
dev_cnt
=
fluid
.
core
.
get_cuda_device_count
()
os
.
environ
[
'CPU_NUM'
]
=
str
(
dev_cnt
)
def
dummy_func_with_no_input
():
return
float
(
1.0
)
def
dummy_func_with_no_output
(
x
):
pass
def
tanh
(
x
):
return
np
.
tanh
(
x
)
def
tanh_grad
(
y
,
dy
):
return
np
.
array
(
dy
)
*
(
1
-
np
.
square
(
np
.
array
(
y
)))
def
cross_entropy
(
logits
,
labels
):
logits
=
np
.
array
(
logits
)
labels
=
np
.
array
(
labels
)
M
=
logits
.
shape
[
0
]
N
=
logits
.
shape
[
1
]
ret
=
np
.
ndarray
([
M
,
1
]).
astype
(
logits
.
dtype
)
for
idx
in
six
.
moves
.
range
(
M
):
ret
[
idx
][
0
]
=
-
np
.
log
(
logits
[
idx
][
labels
[
idx
][
0
]])
return
ret
def
cross_entropy_grad
(
logits
,
labels
,
bwd_dout
):
logits
=
np
.
array
(
logits
)
labels
=
np
.
array
(
labels
)
bwd_dout
=
np
.
array
(
bwd_dout
)
M
=
logits
.
shape
[
0
]
N
=
logits
.
shape
[
1
]
dlogits
=
np
.
zeros
([
M
,
N
]).
astype
(
logits
.
dtype
)
for
idx
in
six
.
moves
.
range
(
M
):
dlogits
[
idx
][
labels
[
idx
][
0
]]
=
-
bwd_dout
[
idx
]
/
logits
[
idx
][
labels
[
idx
][
0
]]
return
dlogits
,
None
def
simple_fc_net
(
img
,
label
,
use_py_func_op
):
hidden
=
img
for
idx
in
range
(
4
):
hidden
=
fluid
.
layers
.
fc
(
hidden
,
size
=
200
,
bias_attr
=
fluid
.
ParamAttr
(
initializer
=
fluid
.
initializer
.
Constant
(
value
=
1.0
)))
if
not
use_py_func_op
:
hidden
=
fluid
.
layers
.
tanh
(
hidden
)
else
:
new_hidden
=
fluid
.
default_main_program
().
current_block
(
).
create_var
(
name
=
'hidden_{}'
.
format
(
idx
),
dtype
=
'float32'
,
shape
=
hidden
.
shape
)
hidden
=
fluid
.
layers
.
py_func
(
func
=
tanh
,
x
=
hidden
,
out
=
new_hidden
,
backward_func
=
tanh_grad
,
skip_vars_in_backward_input
=
hidden
)
prediction
=
fluid
.
layers
.
fc
(
hidden
,
size
=
10
,
act
=
'softmax'
)
if
not
use_py_func_op
:
loss
=
fluid
.
layers
.
cross_entropy
(
input
=
prediction
,
label
=
label
)
else
:
loss
=
fluid
.
default_main_program
().
current_block
().
create_var
(
name
=
'loss'
,
dtype
=
'float32'
,
shape
=
[
-
1
,
1
])
loss
=
fluid
.
layers
.
py_func
(
func
=
cross_entropy
,
x
=
[
prediction
,
label
],
out
=
loss
,
backward_func
=
cross_entropy_grad
,
skip_vars_in_backward_input
=
loss
)
dummy_var
=
fluid
.
default_main_program
().
current_block
().
create_var
(
name
=
'test_tmp_var'
,
dtype
=
'float32'
,
shape
=
[
1
])
fluid
.
layers
.
py_func
(
func
=
dummy_func_with_no_input
,
x
=
None
,
out
=
dummy_var
)
fluid
.
layers
.
py_func
(
func
=
dummy_func_with_no_output
,
x
=
loss
,
out
=
None
)
loss
=
fluid
.
layers
.
mean
(
loss
)
return
loss
def
reader
():
for
_
in
six
.
moves
.
range
(
dev_cnt
*
100
):
yield
np
.
random
.
random
([
784
]),
np
.
random
.
random_integers
(
size
=
[
1
],
low
=
0
,
high
=
9
)
def
test_main
(
use_cuda
,
use_py_func_op
,
use_parallel_executor
):
if
use_cuda
and
not
fluid
.
core
.
is_compiled_with_cuda
():
return
None
with
fluid
.
program_guard
(
fluid
.
Program
(),
fluid
.
Program
()):
with
fluid
.
scope_guard
(
fluid
.
core
.
Scope
()):
fluid
.
default_main_program
().
random_seed
=
1
fluid
.
default_startup_program
().
random_seed
=
1
np
.
random
.
seed
(
1
)
img
=
fluid
.
layers
.
data
(
name
=
'image'
,
shape
=
[
784
],
dtype
=
'float32'
)
label
=
fluid
.
layers
.
data
(
name
=
'label'
,
shape
=
[
1
],
dtype
=
'int64'
)
loss
=
simple_fc_net
(
img
,
label
,
use_py_func_op
)
optimizer
=
fluid
.
optimizer
.
SGD
(
learning_rate
=
1e-3
)
optimizer
.
minimize
(
loss
)
place
=
fluid
.
CUDAPlace
(
0
)
if
use_cuda
else
fluid
.
CPUPlace
()
feeder
=
fluid
.
DataFeeder
(
feed_list
=
[
img
,
label
],
place
=
place
)
r
=
paddle
.
batch
(
reader
,
batch_size
=
10
)
exe
=
fluid
.
Executor
(
place
)
exe
.
run
(
fluid
.
default_startup_program
())
if
use_parallel_executor
:
exe
=
fluid
.
ParallelExecutor
(
use_cuda
=
use_cuda
,
loss_name
=
loss
.
name
)
fetch_list
=
[
loss
.
name
]
else
:
fetch_list
=
[
loss
]
ret
=
[]
for
epoch_id
in
six
.
moves
.
range
(
2
):
for
d
in
r
():
L
,
=
exe
.
run
(
feed
=
feeder
.
feed
(
d
),
fetch_list
=
fetch_list
)
ret
.
append
(
L
)
return
np
.
array
(
ret
)
class
TestPyFuncOpUseExecutor
(
unittest
.
TestCase
):
def
setUp
(
self
):
self
.
use_parallel_executor
=
False
def
test_loss_diff
(
self
):
losses
=
[]
for
use_cuda
in
[
True
,
False
]:
for
use_py_func_op
in
[
True
,
False
]:
L
=
test_main
(
use_cuda
,
use_py_func_op
,
self
.
use_parallel_executor
)
if
L
is
not
None
:
losses
.
append
(
L
)
for
idx
in
six
.
moves
.
range
(
len
(
losses
)
-
1
):
max_diff
=
np
.
max
(
np
.
abs
(
losses
[
idx
]
-
losses
[
0
]))
self
.
assertAlmostEqual
(
max_diff
,
0
,
delta
=
1e-3
)
class
TestPyFuncOpUseParallelExecutor
(
unittest
.
TestCase
):
def
setUp
(
self
):
self
.
use_parallel_executor
=
True
if
__name__
==
'__main__'
:
unittest
.
main
()
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