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f0475488
编写于
5月 17, 2018
作者:
Y
yuyang18
浏览文件
操作
浏览文件
下载
差异文件
Merge branch 'develop' of
https://github.com/PaddlePaddle/Paddle
into feature/trainer_by_pe
上级
791af3a0
63012df4
变更
30
隐藏空白更改
内联
并排
Showing
30 changed file
with
288 addition
and
111 deletion
+288
-111
benchmark/fluid/mnist.py
benchmark/fluid/mnist.py
+10
-6
benchmark/fluid/resnet.py
benchmark/fluid/resnet.py
+8
-4
benchmark/fluid/vgg.py
benchmark/fluid/vgg.py
+8
-4
cmake/external/snappy.cmake
cmake/external/snappy.cmake
+0
-2
cmake/external/snappystream.cmake
cmake/external/snappystream.cmake
+0
-2
cmake/inference_lib.cmake
cmake/inference_lib.cmake
+6
-0
doc/fluid/design/concepts/functions_operators_layers.md
doc/fluid/design/concepts/functions_operators_layers.md
+1
-1
paddle/CMakeLists.txt
paddle/CMakeLists.txt
+1
-1
paddle/fluid/framework/data_type.cc
paddle/fluid/framework/data_type.cc
+1
-0
paddle/fluid/framework/data_type.h
paddle/fluid/framework/data_type.h
+7
-1
paddle/fluid/framework/details/fetch_op_handle.cc
paddle/fluid/framework/details/fetch_op_handle.cc
+8
-7
paddle/fluid/framework/details/op_handle_base.h
paddle/fluid/framework/details/op_handle_base.h
+8
-0
paddle/fluid/framework/details/threaded_ssa_graph_executor.cc
...le/fluid/framework/details/threaded_ssa_graph_executor.cc
+1
-1
paddle/fluid/framework/framework.proto
paddle/fluid/framework/framework.proto
+1
-0
paddle/fluid/framework/lod_tensor_test.cc
paddle/fluid/framework/lod_tensor_test.cc
+13
-4
paddle/fluid/framework/operator.h
paddle/fluid/framework/operator.h
+0
-1
paddle/fluid/inference/tensorrt/convert/op_converter.h
paddle/fluid/inference/tensorrt/convert/op_converter.h
+1
-1
paddle/fluid/operators/math/math_function.cc
paddle/fluid/operators/math/math_function.cc
+3
-1
paddle/fluid/operators/smooth_l1_loss_op.cc
paddle/fluid/operators/smooth_l1_loss_op.cc
+23
-2
paddle/fluid/platform/CMakeLists.txt
paddle/fluid/platform/CMakeLists.txt
+1
-1
paddle/scripts/paddle_build.sh
paddle/scripts/paddle_build.sh
+2
-0
python/paddle/fluid/data_feeder.py
python/paddle/fluid/data_feeder.py
+2
-2
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+21
-17
python/paddle/fluid/tests/book/test_label_semantic_roles.py
python/paddle/fluid/tests/book/test_label_semantic_roles.py
+6
-21
python/paddle/fluid/tests/test_data_feeder.py
python/paddle/fluid/tests/test_data_feeder.py
+54
-7
python/paddle/fluid/tests/unittests/CMakeLists.txt
python/paddle/fluid/tests/unittests/CMakeLists.txt
+4
-2
python/paddle/fluid/tests/unittests/test_network_with_dtype.py
...n/paddle/fluid/tests/unittests/test_network_with_dtype.py
+15
-20
python/paddle/fluid/tests/unittests/test_parallel_executor.py
...on/paddle/fluid/tests/unittests/test_parallel_executor.py
+2
-3
python/paddle/fluid/trainer.py
python/paddle/fluid/trainer.py
+33
-0
tools/test_runner.py
tools/test_runner.py
+48
-0
未找到文件。
benchmark/fluid/mnist.py
浏览文件 @
f0475488
...
...
@@ -159,6 +159,7 @@ def run_benchmark(model, args):
paddle
.
dataset
.
mnist
.
train
(),
batch_size
=
args
.
batch_size
)
accuracy
=
fluid
.
metrics
.
Accuracy
()
train_exe
=
fluid
.
ParallelExecutor
(
use_cuda
=
True
,
loss_name
=
avg_cost
.
name
)
iters
,
num_samples
,
start_time
=
0
,
0
,
time
.
time
()
for
pass_id
in
range
(
args
.
pass_num
):
accuracy
.
reset
()
...
...
@@ -175,17 +176,20 @@ def run_benchmark(model, args):
y_data
=
np
.
array
(
map
(
lambda
x
:
x
[
1
],
data
)).
astype
(
"int64"
)
y_data
=
y_data
.
reshape
([
len
(
y_data
),
1
])
outs
=
exe
.
run
(
fluid
.
default_main_program
(),
outs
=
train_exe
.
run
(
feed
=
{
"pixel"
:
img_data
,
"label"
:
y_data
},
fetch_list
=
[
avg_cost
,
batch_acc
,
batch_size_tensor
]
fetch_list
=
[
avg_cost
.
name
,
batch_acc
.
name
,
batch_size_tensor
.
name
]
)
# The accuracy is the accumulation of batches, but not the current batch.
accuracy
.
update
(
value
=
outs
[
1
],
weight
=
outs
[
2
])
accuracy
.
update
(
value
=
np
.
array
(
np
.
mean
(
outs
[
1
])),
weight
=
np
.
mean
(
np
.
array
(
outs
[
2
])))
iters
+=
1
num_samples
+=
len
(
y_data
)
loss
=
np
.
array
(
outs
[
0
]
)
acc
=
np
.
array
(
outs
[
1
]
)
loss
=
np
.
mean
(
np
.
array
(
outs
[
0
])
)
acc
=
np
.
mean
(
np
.
array
(
outs
[
1
])
)
train_losses
.
append
(
loss
)
train_accs
.
append
(
acc
)
print
(
"Pass: %d, Iter: %d, Loss: %f, Accuracy: %f"
%
...
...
benchmark/fluid/resnet.py
浏览文件 @
f0475488
...
...
@@ -241,6 +241,7 @@ def run_benchmark(model, args):
exe
=
fluid
.
Executor
(
place
)
exe
.
run
(
fluid
.
default_startup_program
())
accuracy
=
fluid
.
average
.
WeightedAverage
()
train_exe
=
fluid
.
ParallelExecutor
(
use_cuda
=
True
,
loss_name
=
avg_cost
.
name
)
if
args
.
use_fake_data
:
data
=
train_reader
().
next
()
image
=
np
.
array
(
map
(
lambda
x
:
x
[
0
].
reshape
(
dshape
),
data
)).
astype
(
...
...
@@ -264,14 +265,17 @@ def run_benchmark(model, args):
data
)).
astype
(
'float32'
)
label
=
np
.
array
(
map
(
lambda
x
:
x
[
1
],
data
)).
astype
(
'int64'
)
label
=
label
.
reshape
([
-
1
,
1
])
loss
,
acc
,
weight
=
exe
.
run
(
fluid
.
default_main_program
(),
loss
,
acc
,
weight
=
train_exe
.
run
(
feed
=
{
'data'
:
image
,
'label'
:
label
},
fetch_list
=
[
avg_cost
,
batch_acc
,
batch_size_tensor
])
fetch_list
=
[
avg_cost
.
name
,
batch_acc
.
name
,
batch_size_tensor
.
name
])
iters
+=
1
num_samples
+=
len
(
label
)
accuracy
.
add
(
value
=
acc
,
weight
=
weight
)
accuracy
.
add
(
value
=
np
.
array
(
np
.
mean
(
acc
)),
weight
=
np
.
mean
(
weight
))
loss
=
np
.
mean
(
np
.
array
(
loss
))
acc
=
np
.
mean
(
np
.
array
(
acc
))
train_losses
.
append
(
loss
)
train_accs
.
append
(
acc
)
print
(
"Pass: %d, Iter: %d, Loss: %f, Accuracy: %f"
%
...
...
benchmark/fluid/vgg.py
浏览文件 @
f0475488
...
...
@@ -169,6 +169,7 @@ def main():
iters
,
num_samples
,
start_time
=
0
,
0
,
time
.
time
()
accuracy
=
fluid
.
average
.
WeightedAverage
()
train_exe
=
fluid
.
ParallelExecutor
(
use_cuda
=
True
,
loss_name
=
avg_cost
.
name
)
for
pass_id
in
range
(
args
.
pass_num
):
accuracy
.
reset
()
train_accs
=
[]
...
...
@@ -184,14 +185,17 @@ def main():
y_data
=
np
.
array
(
map
(
lambda
x
:
x
[
1
],
data
)).
astype
(
"int64"
)
y_data
=
y_data
.
reshape
([
-
1
,
1
])
loss
,
acc
,
weight
=
exe
.
run
(
fluid
.
default_main_program
(),
loss
,
acc
,
weight
=
train_exe
.
run
(
feed
=
{
"pixel"
:
img_data
,
"label"
:
y_data
},
fetch_list
=
[
avg_cost
,
batch_acc
,
batch_size_tensor
])
accuracy
.
add
(
value
=
acc
,
weight
=
weight
)
fetch_list
=
[
avg_cost
.
name
,
batch_acc
.
name
,
batch_size_tensor
.
name
])
accuracy
.
add
(
value
=
np
.
array
(
np
.
mean
(
acc
)),
weight
=
np
.
mean
(
weight
))
iters
+=
1
num_samples
+=
len
(
y_data
)
loss
=
np
.
mean
(
np
.
array
(
loss
))
acc
=
np
.
mean
(
np
.
array
(
acc
))
print
(
"Pass = %d, Iter = %d, Loss = %f, Accuracy = %f"
%
(
pass_id
,
iters
,
loss
,
acc
)
...
...
cmake/external/snappy.cmake
浏览文件 @
f0475488
...
...
@@ -47,8 +47,6 @@ ExternalProject_Add(
-DCMAKE_INSTALL_LIBDIR:PATH=
${
SNAPPY_INSTALL_DIR
}
/lib
-DCMAKE_POSITION_INDEPENDENT_CODE:BOOL=ON
-DCMAKE_BUILD_TYPE:STRING=
${
THIRD_PARTY_BUILD_TYPE
}
BUILD_COMMAND make -j8
INSTALL_COMMAND make install
)
add_library
(
snappy STATIC IMPORTED GLOBAL
)
...
...
cmake/external/snappystream.cmake
浏览文件 @
f0475488
...
...
@@ -46,8 +46,6 @@ ExternalProject_Add(
-DCMAKE_INSTALL_PREFIX:PATH=
${
SNAPPYSTREAM_INSTALL_DIR
}
-DCMAKE_INSTALL_LIBDIR:PATH=
${
SNAPPYSTREAM_INSTALL_DIR
}
/lib
-DCMAKE_BUILD_TYPE:STRING=
${
THIRD_PARTY_BUILD_TYPE
}
BUILD_COMMAND make -j8
INSTALL_COMMAND make install
DEPENDS snappy
)
...
...
cmake/inference_lib.cmake
浏览文件 @
f0475488
...
...
@@ -148,4 +148,10 @@ copy(string_lib
DSTS
${
dst_dir
}
/
${
module
}
${
dst_dir
}
/
${
module
}
/tinyformat
)
set
(
module
"pybind"
)
copy
(
pybind_lib
SRCS
${
CMAKE_CURRENT_BINARY_DIR
}
/paddle/fluid/
${
module
}
/pybind.h
DSTS
${
dst_dir
}
/
${
module
}
)
add_custom_target
(
inference_lib_dist DEPENDS
${
inference_lib_dist_dep
}
)
doc/fluid/design/concepts/functions_operators_layers.md
浏览文件 @
f0475488
...
...
@@ -40,7 +40,7 @@ template <typename T>
class
FCOp
:
public
OperatorBase
{
public:
void
Run
(...)
{
add
(
mul
(
Input
<
T
>
(
"X"
),
Input
<
T
>
(
"W"
)),
Input
<
T
>
(
"b"
);
add
(
mul
(
Input
<
T
>
(
"X"
),
Input
<
T
>
(
"W"
)),
Input
<
T
>
(
"b"
)
)
;
}
};
REGISTER_OP
(
FCOp
,
"fc"
);
...
...
paddle/CMakeLists.txt
浏览文件 @
f0475488
...
...
@@ -24,6 +24,6 @@ if(NOT WITH_FLUID_ONLY)
endif
()
add_subdirectory
(
testing
)
if
(
NOT MOBILE_INFERENCE AND NOT RPI
)
if
(
NOT MOBILE_INFERENCE AND NOT RPI
AND NOT WITH_C_API
)
add_subdirectory
(
fluid
)
endif
()
paddle/fluid/framework/data_type.cc
浏览文件 @
f0475488
...
...
@@ -58,6 +58,7 @@ static DataTypeMap* InitDataTypeMap() {
RegType
(
bool
,
proto
::
VarType
::
BOOL
);
RegType
(
size_t
,
proto
::
VarType
::
SIZE_T
);
RegType
(
int16_t
,
proto
::
VarType
::
INT16
);
RegType
(
uint8_t
,
proto
::
VarType
::
UINT8
);
#undef RegType
return
retv
;
...
...
paddle/fluid/framework/data_type.h
浏览文件 @
f0475488
...
...
@@ -47,8 +47,14 @@ inline void VisitDataType(proto::VarType::Type type, Visitor visitor) {
case
proto
::
VarType
::
BOOL
:
visitor
.
template
operator
()
<
bool
>();
break
;
case
proto
::
VarType
::
UINT8
:
visitor
.
template
operator
()
<
uint8_t
>();
break
;
case
proto
::
VarType
::
INT16
:
visitor
.
template
operator
()
<
int16_t
>();
break
;
default:
PADDLE_THROW
(
"Not supported
"
);
PADDLE_THROW
(
"Not supported
%d"
,
type
);
}
}
...
...
paddle/fluid/framework/details/fetch_op_handle.cc
浏览文件 @
f0475488
...
...
@@ -48,17 +48,18 @@ void FetchOpHandle::RunImpl() {
WaitInputVarGenerated
(
platform
::
CPUPlace
());
tensors_
.
resize
(
inputs_
.
size
());
auto
*
var_handle
=
static_cast
<
VarHandle
*>
(
inputs_
[
0
]);
auto
&
var_name
=
var_handle
->
name_
;
platform
::
CPUPlace
cpu
;
auto
&
scopes
=
*
local_scopes_
;
for
(
size_t
i
=
0
;
i
<
scopes
.
size
();
++
i
)
{
auto
&
scope
=
scopes
[
i
];
auto
*
var
=
scope
->
FindVar
(
kLocalExecScopeName
)
->
Get
<
Scope
*>
()
->
FindVar
(
var_name
);
for
(
size_t
i
=
0
;
i
<
inputs_
.
size
();
++
i
)
{
auto
*
var_handle
=
static_cast
<
VarHandle
*>
(
inputs_
[
i
]);
auto
&
scope
=
scopes
.
at
(
var_handle
->
scope_idx_
);
auto
*
var
=
scope
->
FindVar
(
kLocalExecScopeName
)
->
Get
<
Scope
*>
()
->
FindVar
(
var_handle
->
name_
);
PADDLE_ENFORCE_NOT_NULL
(
var
,
"Cannot find variable %s in execution scope"
,
var_name
);
var_handle
->
name_
);
auto
&
t
=
var
->
Get
<
framework
::
LoDTensor
>
();
if
(
platform
::
is_gpu_place
(
t
.
place
()))
{
#ifdef PADDLE_WITH_CUDA
...
...
paddle/fluid/framework/details/op_handle_base.h
浏览文件 @
f0475488
...
...
@@ -70,6 +70,14 @@ class OpHandleBase {
const
std
::
vector
<
VarHandleBase
*>
&
Inputs
()
const
{
return
inputs_
;
}
size_t
NoDupInputSize
()
const
{
std
::
unordered_set
<
VarHandleBase
*>
res
;
for
(
auto
*
var
:
inputs_
)
{
res
.
emplace
(
var
);
}
return
res
.
size
();
}
const
std
::
vector
<
VarHandleBase
*>
&
Outputs
()
const
{
return
outputs_
;
}
protected:
...
...
paddle/fluid/framework/details/threaded_ssa_graph_executor.cc
浏览文件 @
f0475488
...
...
@@ -174,7 +174,7 @@ void ThreadedSSAGraphExecutor::InsertFetchOps(
void
ThreadedSSAGraphExecutor
::
InsertPendingOp
(
std
::
unordered_map
<
OpHandleBase
*
,
size_t
>
*
pending_ops
,
OpHandleBase
*
op_instance
)
const
{
pending_ops
->
insert
({
op_instance
,
op_instance
->
Inputs
().
s
ize
()});
pending_ops
->
insert
({
op_instance
,
op_instance
->
NoDupInputS
ize
()});
}
void
ThreadedSSAGraphExecutor
::
InsertPendingVar
(
...
...
paddle/fluid/framework/framework.proto
浏览文件 @
f0475488
...
...
@@ -103,6 +103,7 @@ message VarType {
FP64
=
6
;
// Tensor<size_t> is used in C++.
SIZE_T
=
19
;
UINT8
=
20
;
// Other types that may need additional descriptions
LOD_TENSOR
=
7
;
...
...
paddle/fluid/framework/lod_tensor_test.cc
浏览文件 @
f0475488
...
...
@@ -228,11 +228,12 @@ TEST(LoD, CheckAbsLoD) {
ASSERT_FALSE
(
CheckAbsLoD
(
abs_lod0
));
}
TEST
(
LoDTensor
,
RecordIO
)
{
template
<
typename
T
>
static
void
TestRecordIO
()
{
LoDTensor
tensor
;
int
*
tmp
=
tensor
.
mutable_data
<
int
>
(
make_ddim
({
4
,
5
}),
platform
::
CPUPlace
());
T
*
tmp
=
tensor
.
mutable_data
<
T
>
(
make_ddim
({
4
,
5
}),
platform
::
CPUPlace
());
for
(
int
i
=
0
;
i
<
20
;
++
i
)
{
tmp
[
i
]
=
i
;
tmp
[
i
]
=
static_cast
<
T
>
(
i
)
;
}
std
::
stringstream
*
stream
=
new
std
::
stringstream
();
...
...
@@ -247,7 +248,7 @@ TEST(LoDTensor, RecordIO) {
auto
assert_tensor_ok
=
[](
const
LoDTensor
&
tensor
)
{
for
(
int
i
=
0
;
i
<
20
;
++
i
)
{
ASSERT_EQ
(
tensor
.
data
<
int
>
()[
i
],
i
);
ASSERT_EQ
(
tensor
.
data
<
T
>
()[
i
],
static_cast
<
T
>
(
i
)
);
}
};
...
...
@@ -265,5 +266,13 @@ TEST(LoDTensor, RecordIO) {
}
}
TEST
(
LoDTensor
,
RecordIO
)
{
TestRecordIO
<
int
>
();
TestRecordIO
<
int16_t
>
();
TestRecordIO
<
uint8_t
>
();
TestRecordIO
<
float
>
();
TestRecordIO
<
double
>
();
}
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/operator.h
浏览文件 @
f0475488
...
...
@@ -33,7 +33,6 @@ limitations under the License. */
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/variant.h"
#include "paddle/utils/Error.h"
namespace
paddle
{
namespace
framework
{
...
...
paddle/fluid/inference/tensorrt/convert/op_converter.h
浏览文件 @
f0475488
...
...
@@ -49,7 +49,7 @@ class OpConverter {
// convert fluid block to tensorrt network
void
ConvertBlock
(
const
framework
::
proto
::
BlockDesc
&
block
,
TensorRTEngine
*
engine
)
{
for
(
size_
t
i
=
0
;
i
<
block
.
ops_size
();
i
++
)
{
for
(
in
t
i
=
0
;
i
<
block
.
ops_size
();
i
++
)
{
const
auto
&
op
=
block
.
ops
(
i
);
OpConverter
::
Run
(
op
,
engine
);
}
...
...
paddle/fluid/operators/math/math_function.cc
浏览文件 @
f0475488
...
...
@@ -38,7 +38,9 @@ template struct SetConstant<platform::CPUDeviceContext, bool>;
template struct Transpose<platform::CPUDeviceContext, double, RANK>; \
template struct Transpose<platform::CPUDeviceContext, int, RANK>; \
template struct Transpose<platform::CPUDeviceContext, int64_t, RANK>; \
template struct Transpose<platform::CPUDeviceContext, bool, RANK>;
template struct Transpose<platform::CPUDeviceContext, bool, RANK>; \
template struct Transpose<platform::CPUDeviceContext, int16_t, RANK>; \
template struct Transpose<platform::CPUDeviceContext, uint8_t, RANK>;
DEFINE_CPU_TRANS
(
1
);
DEFINE_CPU_TRANS
(
2
);
...
...
paddle/fluid/operators/smooth_l1_loss_op.cc
浏览文件 @
f0475488
...
...
@@ -105,7 +105,7 @@ class SmoothL1LossGradOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
auto
in_dims
=
ctx
->
GetInputDim
(
"
X
"
);
auto
in_dims
=
ctx
->
GetInputDim
(
"
Diff
"
);
auto
out_dims
=
ctx
->
GetInputDim
(
framework
::
GradVarName
(
"Out"
));
PADDLE_ENFORCE_GE
(
out_dims
.
size
(),
2
,
...
...
@@ -127,12 +127,33 @@ class SmoothL1LossGradOp : public framework::OperatorWithKernel {
}
};
class
SmoothL1LossGradMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
auto
*
op
=
new
framework
::
OpDesc
();
op
->
SetType
(
"smooth_l1_loss_grad"
);
op
->
SetInput
(
"InsideWeight"
,
Input
(
"InsideWeight"
));
op
->
SetInput
(
"OutsideWeight"
,
Input
(
"OutsideWeight"
));
op
->
SetInput
(
"Diff"
,
Output
(
"Diff"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
op
->
SetAttrMap
(
Attrs
());
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"Y"
),
InputGrad
(
"Y"
));
return
std
::
unique_ptr
<
framework
::
OpDesc
>
(
op
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
smooth_l1_loss
,
ops
::
SmoothL1LossOp
,
ops
::
SmoothL1LossOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
ops
::
SmoothL1LossGradMaker
);
REGISTER_OPERATOR
(
smooth_l1_loss_grad
,
ops
::
SmoothL1LossGradOp
);
REGISTER_OP_CPU_KERNEL
(
smooth_l1_loss
,
...
...
paddle/fluid/platform/CMakeLists.txt
浏览文件 @
f0475488
proto_library
(
profiler_proto SRCS profiler.proto
)
proto_library
(
profiler_proto SRCS profiler.proto
DEPS framework_proto
)
py_proto_compile
(
profiler_py_proto SRCS profiler.proto
)
add_custom_target
(
profiler_py_proto_init ALL COMMAND
${
CMAKE_COMMAND
}
-E touch __init__.py
)
...
...
paddle/scripts/paddle_build.sh
浏览文件 @
f0475488
...
...
@@ -480,6 +480,7 @@ function main() {
build
)
cmake_gen
${
PYTHON_ABI
:-
""
}
build
gen_dockerfile
;;
build_android
)
build_android
...
...
@@ -504,6 +505,7 @@ function main() {
;;
capi
)
cmake_gen
${
PYTHON_ABI
:-
""
}
build
gen_capi_package
;;
fluid_inference_lib
)
...
...
python/paddle/fluid/data_feeder.py
浏览文件 @
f0475488
...
...
@@ -54,9 +54,9 @@ class DataToLoDTensorConverter(object):
self
.
data
.
append
(
data
)
else
:
cur_lod_len
=
len
(
data
)
lod
[
-
1
].
append
(
lod
[
-
1
][
-
1
]
+
cur_lod_len
)
lod
[
0
].
append
(
lod
[
0
][
-
1
]
+
cur_lod_len
)
for
each_data
in
data
:
self
.
_feed_impl_
(
each_data
,
lod
[
:
-
1
],
lod_level
-
1
)
self
.
_feed_impl_
(
each_data
,
lod
[
1
:
],
lod_level
-
1
)
def
done
(
self
):
arr
=
numpy
.
array
(
self
.
data
,
dtype
=
self
.
dtype
).
reshape
(
self
.
shape
)
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
f0475488
...
...
@@ -1329,6 +1329,8 @@ def sequence_pool(input, pool_type):
sqrt : out.data = [2.82, 6.93, 4.24], where 2.82=(1+3)/sqrt(2),
6.93=(2+4+6)/sqrt(3), 4.24=(5+1)/sqrt(2)
max : out.data = [3, 6, 5], where 3=max(1,3), 6=max(2,4,6), 5=max(5,1)
last : out.data = [3, 6, 1], where 3=last(1,3), 6=last(2,4,6), 1=last(5,1)
first : out.data = [1, 2, 5], where 1=first(1,3), 2=first(2,4,6), 5=first(5,1)
Args:
input(variable): The input variable which is a LoDTensor.
...
...
@@ -1348,6 +1350,8 @@ def sequence_pool(input, pool_type):
sum_x = fluid.layers.sequence_pool(input=x, pool_type='sum')
sqrt_x = fluid.layers.sequence_pool(input=x, pool_type='sqrt')
max_x = fluid.layers.sequence_pool(input=x, pool_type='max')
last_x = fluid.layers.sequence_pool(input=x, pool_type='last')
first_x = fluid.layers.sequence_pool(input=x, pool_type='first')
"""
helper
=
LayerHelper
(
'sequence_pool'
,
**
locals
())
dtype
=
helper
.
input_dtype
()
...
...
@@ -3263,35 +3267,35 @@ def smooth_l1(x, y, inside_weight=None, outside_weight=None, sigma=None):
"""
**Smooth L1 Loss Operator. **
This operator computes the smooth
l
1 loss for X and Y.
This operator computes the smooth
L
1 loss for X and Y.
The operator takes the first dimension of X and Y as batch size.
For each instance, it computes the smooth
l
1 loss element by element first
For each instance, it computes the smooth
L
1 loss element by element first
and then sums all the losses. So the shape of Out is [batch_size, 1].
Args:
x (Variable): A tensor with rank at least 2. The input value of smooth
l
1 loss op with shape [batch_size, dim1, ..., dimN].
L
1 loss op with shape [batch_size, dim1, ..., dimN].
y (Variable): A tensor with rank at least 2. The target value of smooth
l
1 loss op with same shape as x.
L
1 loss op with same shape as x.
inside_weight (Variable|None): A tensor with rank at least 2. This
input is optional and should have same shape with x. If provided,
the result of (x - y) will be multiplied by this tensor element by
element.
outside_weight (Variable|None): A tensor with rank at least 2. This
input is optional and should have same shape with x. If provided,
the out smooth
l
1 loss will be multiplied by this tensor element
the out smooth
L
1 loss will be multiplied by this tensor element
by element.
sigma (float|None): Hyper parameter of smooth
l
1 loss op. A float scalar
sigma (float|None): Hyper parameter of smooth
L
1 loss op. A float scalar
with default value 1.0.
Returns:
Variable: A tensor with rank be 2. The output smooth
l
1 loss with
Variable: A tensor with rank be 2. The output smooth
L
1 loss with
shape [batch_size, 1].
Examples:
.. code-block:: python
data = fluid.layers.data(name='data', shape=[128], dtype='float32')
label = fluid.layers.data(name='label', shape=[100], dtype='
int64
')
label = fluid.layers.data(name='label', shape=[100], dtype='
float32
')
fc = fluid.layers.fc(input=data, size=100)
out = fluid.layers.smooth_l1(x=fc, y=label)
"""
...
...
@@ -3769,13 +3773,13 @@ def label_smooth(label,
def
roi_pool
(
input
,
rois
,
pooled_height
=
1
,
pooled_width
=
1
,
spatial_scale
=
1.0
):
"""
Region of interest pooling (also known as RoI pooling) is to perform
Region of interest pooling (also known as RoI pooling) is to perform
is to perform max pooling on inputs of nonuniform sizes to obtain
fixed-size feature maps (e.g. 7*7).
The operator has three steps:
1. Dividing each region proposal into equal-sized sections with
the pooled_width and pooled_height
2. Finding the largest value in each section
The operator has three steps:
1. Dividing each region proposal into equal-sized sections with
the pooled_width and pooled_height
2. Finding the largest value in each section
3. Copying these max values to the output buffer
Args:
...
...
@@ -3783,8 +3787,8 @@ def roi_pool(input, rois, pooled_height=1, pooled_width=1, spatial_scale=1.0):
rois (Variable): ROIs (Regions of Interest) to pool over. It should
be a 2-D one level LoTensor of shape [num_rois, 4].
The layout is [x1, y1, x2, y2], where (x1, y1)
is the top left coordinates, and (x2, y2) is the
bottom right coordinates. The num_rois is the
is the top left coordinates, and (x2, y2) is the
bottom right coordinates. The num_rois is the
total number of ROIs in this batch data.
pooled_height (integer): The pooled output height. Default: 1
pooled_width (integer): The pooled output width. Default: 1
...
...
@@ -3793,11 +3797,11 @@ def roi_pool(input, rois, pooled_height=1, pooled_width=1, spatial_scale=1.0):
to the scale used when pooling. Default: 1.0
Returns:
pool_out (Variable): The output is a 4-D tensor of the shape
pool_out (Variable): The output is a 4-D tensor of the shape
(num_rois, channels, pooled_h, pooled_w).
Examples:
pool_out = fluid.layers.roi_pool(input=x, rois=rois, 7, 7, 1.0)
pool_out = fluid.layers.roi_pool(input=x, rois=rois, 7, 7, 1.0)
"""
helper
=
LayerHelper
(
'roi_pool'
,
**
locals
())
dtype
=
helper
.
input_dtype
()
...
...
python/paddle/fluid/tests/book/test_label_semantic_roles.py
浏览文件 @
f0475488
...
...
@@ -182,12 +182,6 @@ def train(use_cuda, save_dirname=None, is_local=True):
crf_decode
=
fluid
.
layers
.
crf_decoding
(
input
=
feature_out
,
param_attr
=
fluid
.
ParamAttr
(
name
=
'crfw'
))
chunk_evaluator
=
fluid
.
evaluator
.
ChunkEvaluator
(
input
=
crf_decode
,
label
=
target
,
chunk_scheme
=
"IOB"
,
num_chunk_types
=
int
(
math
.
ceil
((
label_dict_len
-
1
)
/
2.0
)))
train_data
=
paddle
.
batch
(
paddle
.
reader
.
shuffle
(
paddle
.
dataset
.
conll05
.
test
(),
buf_size
=
8192
),
...
...
@@ -203,7 +197,6 @@ def train(use_cuda, save_dirname=None, is_local=True):
def
train_loop
(
main_program
):
exe
.
run
(
fluid
.
default_startup_program
())
embedding_param
=
fluid
.
global_scope
().
find_var
(
embedding_name
).
get_tensor
()
embedding_param
.
set
(
...
...
@@ -213,27 +206,19 @@ def train(use_cuda, save_dirname=None, is_local=True):
start_time
=
time
.
time
()
batch_id
=
0
for
pass_id
in
xrange
(
PASS_NUM
):
chunk_evaluator
.
reset
(
exe
)
for
data
in
train_data
():
cost
,
precision
,
recall
,
f1_score
=
exe
.
run
(
main_program
,
feed
=
feeder
.
feed
(
data
),
fetch_list
=
[
avg_cost
]
+
chunk_evaluator
.
metrics
)
pass_precision
,
pass_recall
,
pass_f1_score
=
chunk_evaluator
.
eval
(
exe
)
cost
=
exe
.
run
(
main_program
,
feed
=
feeder
.
feed
(
data
),
fetch_list
=
[
avg_cost
])
cost
=
cost
[
0
]
if
batch_id
%
10
==
0
:
print
(
"avg_cost:"
+
str
(
cost
)
+
" precision:"
+
str
(
precision
)
+
" recall:"
+
str
(
recall
)
+
" f1_score:"
+
str
(
f1_score
)
+
" pass_precision:"
+
str
(
pass_precision
)
+
" pass_recall:"
+
str
(
pass_recall
)
+
" pass_f1_score:"
+
str
(
pass_f1_score
))
print
(
"avg_cost:"
+
str
(
cost
))
if
batch_id
!=
0
:
print
(
"second per batch: "
+
str
((
time
.
time
(
)
-
start_time
)
/
batch_id
))
# Set the threshold low to speed up the CI test
if
float
(
pass_precision
)
>
0.01
:
if
float
(
cost
)
<
60.0
:
if
save_dirname
is
not
None
:
# TODO(liuyiqun): Change the target to crf_decode
fluid
.
io
.
save_inference_model
(
save_dirname
,
[
...
...
python/paddle/fluid/tests/test_data_feeder.py
浏览文件 @
f0475488
...
...
@@ -13,15 +13,62 @@
# limitations under the License.
import
paddle.fluid
as
fluid
import
unittest
def
test_converter
():
img
=
fluid
.
layers
.
data
(
name
=
'image'
,
shape
=
[
1
,
28
,
28
])
label
=
fluid
.
layers
.
data
(
name
=
'label'
,
shape
=
[
1
],
dtype
=
'int64'
)
feeder
=
fluid
.
DataFeeder
([
img
,
label
],
fluid
.
CPUPlace
())
result
=
feeder
.
feed
([[[
0
]
*
784
,
[
9
]],
[[
1
]
*
784
,
[
1
]]])
print
(
result
)
class
TestDataFeeder
(
unittest
.
TestCase
):
def
test_lod_level_0_converter
(
self
):
img
=
fluid
.
layers
.
data
(
name
=
'image'
,
shape
=
[
1
,
28
,
28
])
label
=
fluid
.
layers
.
data
(
name
=
'label'
,
shape
=
[
1
],
dtype
=
'int64'
)
feeder
=
fluid
.
DataFeeder
([
img
,
label
],
fluid
.
CPUPlace
())
result
=
feeder
.
feed
([([
0
]
*
784
,
[
9
]),
([
1
]
*
784
,
[
1
])])
print
(
result
)
self
.
assertEqual
(
result
[
'image'
].
shape
(),
[
2
,
1
,
28
,
28
])
self
.
assertEqual
(
result
[
'label'
].
shape
(),
[
2
,
1
])
self
.
assertEqual
(
result
[
'image'
].
lod
(),
[])
self
.
assertEqual
(
result
[
'label'
].
lod
(),
[])
def
test_lod_level_1_converter
(
self
):
# lod_level = 1
# each sentence has a different number of words
sentences
=
fluid
.
layers
.
data
(
name
=
'sentences'
,
shape
=
[
1
],
dtype
=
'int64'
,
lod_level
=
1
)
label
=
fluid
.
layers
.
data
(
name
=
'label'
,
shape
=
[
1
],
dtype
=
'int64'
)
feeder
=
fluid
.
DataFeeder
([
sentences
,
label
],
fluid
.
CPUPlace
())
# lod = [[0, 3, 5, 9]]
# data = [[1, 2, 3], [4, 5], [6, 7, 8, 9]]
# label = [1] * len(data)
result
=
feeder
.
feed
(
[([
1
,
2
,
3
],
[
1
]),
([
4
,
5
],
[
1
]),
([
6
,
7
,
8
,
9
],
[
1
])])
print
(
result
)
self
.
assertEqual
(
result
[
'sentences'
].
shape
(),
[
9
,
1
])
self
.
assertEqual
(
result
[
'label'
].
shape
(),
[
3
,
1
])
self
.
assertEqual
(
result
[
'sentences'
].
lod
(),
[[
0
,
3
,
5
,
9
]])
self
.
assertEqual
(
result
[
'label'
].
lod
(),
[])
def
test_lod_level_2_converter
(
self
):
# lod_level = 2
# paragraphs -> sentences -> words
paragraphs
=
fluid
.
layers
.
data
(
name
=
'paragraphs'
,
shape
=
[
1
],
dtype
=
'int64'
,
lod_level
=
2
)
label
=
fluid
.
layers
.
data
(
name
=
'label'
,
shape
=
[
1
],
dtype
=
'int64'
)
feeder
=
fluid
.
DataFeeder
([
paragraphs
,
label
],
fluid
.
CPUPlace
())
# lod = [[0, 2, 3], [0, 3, 5, 9]]
# data = [[[1, 2, 3], [4, 5]], [[6, 7, 8, 9]]]
# label = [1] * len(data)
result
=
feeder
.
feed
(
[([[
1
,
2
,
3
],
[
4
,
5
]],
[
1
]),
([[
6
,
7
,
8
,
9
]],
[
1
])])
print
(
result
)
self
.
assertEqual
(
result
[
'paragraphs'
].
shape
(),
[
9
,
1
])
self
.
assertEqual
(
result
[
'label'
].
shape
(),
[
2
,
1
])
self
.
assertEqual
(
result
[
'paragraphs'
].
lod
(),
[[
0
,
2
,
3
],
[
0
,
3
,
5
,
9
]])
self
.
assertEqual
(
result
[
'label'
].
lod
(),
[])
if
__name__
==
'__main__'
:
test_converter
()
unittest
.
main
()
python/paddle/fluid/tests/unittests/CMakeLists.txt
浏览文件 @
f0475488
...
...
@@ -28,11 +28,11 @@ function(py_test_modules TARGET_NAME)
if
(
WITH_TESTING
)
set
(
options
""
)
set
(
oneValueArgs
""
)
set
(
multiValueArgs MODULES DEPS
ARGS
ENVS
)
set
(
multiValueArgs MODULES DEPS ENVS
)
cmake_parse_arguments
(
py_test_modules
"
${
options
}
"
"
${
oneValueArgs
}
"
"
${
multiValueArgs
}
"
${
ARGN
}
)
add_test
(
NAME
${
TARGET_NAME
}
COMMAND env PYTHONPATH=
${
PADDLE_BINARY_DIR
}
/python
${
py_test_modules_ENVS
}
${
PYTHON_EXECUTABLE
}
-u -m unittest --verbose
${
py_test_modules_MODULES
}
${
py_test_modules_ARG
S
}
${
PYTHON_EXECUTABLE
}
${
PADDLE_SOURCE_DIR
}
/tools/test_runner.py
${
py_test_modules_MODULE
S
}
WORKING_DIRECTORY
${
CMAKE_CURRENT_BINARY_DIR
}
)
endif
()
endfunction
()
...
...
@@ -66,6 +66,7 @@ list(REMOVE_ITEM TEST_OPS test_fetch_var)
list
(
REMOVE_ITEM TEST_OPS test_parallel_op
)
list
(
REMOVE_ITEM TEST_OPS test_dynrnn_static_input
)
list
(
REMOVE_ITEM TEST_OPS test_dist_train
)
list
(
REMOVE_ITEM TEST_OPS test_network_with_dtype
)
# tests that can be bundled together in one python process for speed.
if
(
WITH_FAST_BUNDLE_TEST
)
...
...
@@ -83,6 +84,7 @@ py_test_modules(test_parallel_executor MODULES test_parallel_executor)
py_test_modules
(
test_warpctc_op MODULES test_warpctc_op ENVS FLAGS_warpctc_dir=
${
WARPCTC_LIB_DIR
}
)
py_test_modules
(
test_train_dyn_rnn MODULES test_dyn_rnn
)
py_test_modules
(
test_mul_op MODULES test_mul_op
)
py_test_modules
(
test_network_with_dtype MODULES test_network_with_dtype
)
# tests that need to be run in separate process.
py_test_modules
(
test_multihead_attention MODULES test_multihead_attention
)
...
...
python/paddle/fluid/tests/unittests/test_network_with_dtype.py
浏览文件 @
f0475488
...
...
@@ -24,33 +24,30 @@ BATCH_SIZE = 20
class
TestNetWithDtype
(
unittest
.
TestCase
):
def
set
_network
(
self
):
def
set
Up
(
self
):
self
.
dtype
=
"float64"
self
.
init_dtype
()
main
=
fluid
.
Program
()
with
fluid
.
program_guard
(
main
):
self
.
x
=
fluid
.
layers
.
data
(
name
=
'x'
,
shape
=
[
13
],
dtype
=
self
.
dtype
)
self
.
y
=
fluid
.
layers
.
data
(
name
=
'y'
,
shape
=
[
1
],
dtype
=
self
.
dtype
)
y_predict
=
fluid
.
layers
.
fc
(
input
=
self
.
x
,
size
=
1
,
act
=
None
)
cost
=
fluid
.
layers
.
square_error_cost
(
input
=
y_predict
,
label
=
self
.
y
)
def
run_net_on_place
(
self
,
place
):
main
=
fluid
.
Program
()
startup
=
fluid
.
Program
()
with
fluid
.
program_guard
(
main
,
startup
):
x
=
fluid
.
layers
.
data
(
name
=
'x'
,
shape
=
[
13
],
dtype
=
self
.
dtype
)
y
=
fluid
.
layers
.
data
(
name
=
'y'
,
shape
=
[
1
],
dtype
=
self
.
dtype
)
y_predict
=
fluid
.
layers
.
fc
(
input
=
x
,
size
=
1
,
act
=
None
)
cost
=
fluid
.
layers
.
square_error_cost
(
input
=
y_predict
,
label
=
y
)
avg_cost
=
fluid
.
layers
.
mean
(
cost
)
self
.
program
=
main
self
.
fetch_list
=
[
avg_cost
]
sgd_optimizer
=
fluid
.
optimizer
.
SGD
(
learning_rate
=
0.001
)
sgd_optimizer
.
minimize
(
avg_cost
)
sgd_optimizer
=
fluid
.
optimizer
.
SGD
(
learning_rate
=
0.001
)
sgd_optimizer
.
minimize
(
avg_cost
)
def
run_net_on_place
(
self
,
place
):
fetch_list
=
[
avg_cost
]
train_reader
=
paddle
.
batch
(
paddle
.
dataset
.
uci_housing
.
train
(),
batch_size
=
BATCH_SIZE
)
feeder
=
fluid
.
DataFeeder
(
place
=
place
,
feed_list
=
[
self
.
x
,
self
.
y
])
feeder
=
fluid
.
DataFeeder
(
place
=
place
,
feed_list
=
[
x
,
y
])
exe
=
fluid
.
Executor
(
place
)
exe
.
run
(
fluid
.
default_startup_program
()
)
exe
.
run
(
startup
)
for
data
in
train_reader
():
exe
.
run
(
self
.
program
,
feed
=
feeder
.
feed
(
data
),
fetch_list
=
self
.
fetch_list
)
exe
.
run
(
main
,
feed
=
feeder
.
feed
(
data
),
fetch_list
=
fetch_list
)
# the main program is runable, the datatype is fully supported
break
...
...
@@ -58,14 +55,12 @@ class TestNetWithDtype(unittest.TestCase):
pass
def
test_cpu
(
self
):
self
.
set_network
()
place
=
fluid
.
CPUPlace
()
self
.
run_net_on_place
(
place
)
def
test_gpu
(
self
):
if
not
core
.
is_compiled_with_cuda
():
return
self
.
set_network
()
place
=
fluid
.
CUDAPlace
(
0
)
self
.
run_net_on_place
(
place
)
...
...
python/paddle/fluid/tests/unittests/test_parallel_executor.py
浏览文件 @
f0475488
...
...
@@ -775,7 +775,7 @@ class TestCRFModel(unittest.TestCase):
build_strategy
=
fluid
.
BuildStrategy
()
build_strategy
.
reduce_strategy
=
fluid
.
BuildStrategy
.
ReduceStrategy
.
Reduce
self
.
check_network_convergence
(
is_sparse
=
Fals
e
,
build_strategy
=
build_strategy
)
is_sparse
=
Tru
e
,
build_strategy
=
build_strategy
)
def
test_update_dense_parameter_reduce
(
self
):
build_strategy
=
fluid
.
BuildStrategy
()
...
...
@@ -849,8 +849,7 @@ class TestFetchOp(unittest.TestCase):
assert
not
math
.
isnan
(
np
.
sum
(
ret
[
i
]))
and
\
not
math
.
isinf
(
np
.
sum
(
ret
[
i
]))
@
unittest
.
skip
(
"this test is buggy"
)
def
test_feed
(
self
):
def
test_fetch_op
(
self
):
tst_reader
=
paddle
.
batch
(
flowers
.
test
(
use_xmap
=
False
),
batch_size
=
16
)
tst_reader_iter
=
tst_reader
()
...
...
python/paddle/fluid/trainer.py
浏览文件 @
f0475488
...
...
@@ -139,7 +139,40 @@ class Trainer(object):
# load params from param_path into scope
io
.
load_persistables
(
exe
,
dirname
=
param_path
)
def
_transpile_nccl2_dist
(
self
):
# PADDLE_TRAINER_IPS
if
"PADDLE_TRAINER_IPS"
not
in
os
.
environ
:
self
.
nccl_id_var
=
None
else
:
self
.
trainer_id
=
int
(
os
.
getenv
(
"PADDLE_TRAINER_ID"
))
port
=
os
.
getenv
(
"PADDLE_PSERVER_PORT"
)
worker_ips
=
os
.
getenv
(
"PADDLE_TRAINER_IPS"
)
worker_endpoints
=
[]
for
ip
in
worker_ips
.
split
(
","
):
worker_endpoints
.
append
(
':'
.
join
([
ip
,
port
]))
self
.
num_trainers
=
len
(
worker_endpoints
)
current_endpoint
=
os
.
getenv
(
"POD_IP"
)
+
":"
+
port
worker_endpoints
.
remove
(
current_endpoint
)
# TODO(wuyi): use self.nccl_id_var, self.num_trainers and self.trainer_id
# in ParallelExecutor to start
# distributed training using NCCL2
self
.
nccl_id_var
=
self
.
startup_program
.
global_block
().
create_var
(
name
=
"NCCLID"
,
persistable
=
True
,
type
=
core
.
VarDesc
.
VarType
.
RAW
)
self
.
startup_program
.
global_block
().
append_op
(
type
=
"gen_nccl_id"
,
inputs
=
{},
outputs
=
{
"NCCLID"
:
self
.
nccl_id_var
},
attrs
=
{
"endpoint"
:
current_endpoint
,
"endpoint_list"
:
worker_endpoints
,
"trainer_id"
:
self
.
trainer_id
})
def
_dist_transpile_if_necessary
(
self
,
optimize_ops
,
params_grads
):
self
.
_transpile_nccl2_dist
()
if
self
.
nccl_id_var
!=
None
:
return
if
"PADDLE_TRAINING_ROLE"
not
in
os
.
environ
:
return
...
...
tools/test_runner.py
0 → 100644
浏览文件 @
f0475488
# 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
os
import
sys
import
paddle.fluid
as
fluid
import
importlib
import
cStringIO
def
main
():
sys
.
path
.
append
(
os
.
getcwd
())
some_test_failed
=
False
for
module_name
in
sys
.
argv
[
1
:]:
buffer
=
cStringIO
.
StringIO
()
main
=
fluid
.
Program
()
startup
=
fluid
.
Program
()
scope
=
fluid
.
core
.
Scope
()
with
fluid
.
program_guard
(
main
,
startup
):
with
fluid
.
scope_guard
(
scope
):
with
fluid
.
unique_name
.
guard
():
test_loader
=
unittest
.
TestLoader
()
module
=
importlib
.
import_module
(
module_name
)
tests
=
test_loader
.
loadTestsFromModule
(
module
)
res
=
unittest
.
TextTestRunner
(
stream
=
buffer
).
run
(
tests
)
if
not
res
.
wasSuccessful
():
some_test_failed
=
True
print
>>
sys
.
stderr
,
module_name
,
'failed
\n
'
,
buffer
.
getvalue
(
)
if
some_test_failed
:
exit
(
1
)
if
__name__
==
'__main__'
:
main
()
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