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701827f5
编写于
7月 05, 2017
作者:
W
wanghaoshuang
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Add grad test and python wrapper for crop layer
上级
90ed2004
变更
8
隐藏空白更改
内联
并排
Showing
8 changed file
with
147 addition
and
17 deletion
+147
-17
paddle/function/CropOp.cpp
paddle/function/CropOp.cpp
+1
-1
paddle/function/CropOpTest.cpp
paddle/function/CropOpTest.cpp
+1
-1
paddle/gserver/layers/CropLayer.cpp
paddle/gserver/layers/CropLayer.cpp
+10
-13
paddle/gserver/tests/CMakeLists.txt
paddle/gserver/tests/CMakeLists.txt
+1
-1
paddle/gserver/tests/test_LayerGrad.cpp
paddle/gserver/tests/test_LayerGrad.cpp
+28
-0
proto/ModelConfig.proto
proto/ModelConfig.proto
+7
-1
python/paddle/trainer/config_parser.py
python/paddle/trainer/config_parser.py
+45
-0
python/paddle/trainer_config_helpers/layers.py
python/paddle/trainer_config_helpers/layers.py
+54
-0
未找到文件。
paddle/function/CropOp.cpp
浏览文件 @
701827f5
...
...
@@ -148,7 +148,7 @@ public:
void
calc
(
const
BufferArgs
&
inputs
,
const
BufferArgs
&
outputs
)
override
{
CHECK_EQ
(
1UL
,
inputs
.
size
());
CHECK_EQ
(
1UL
,
outputs
.
size
());
CHECK_EQ
(
outputs
[
0
].
getArgType
(),
A
SSIGN
_TO
);
CHECK_EQ
(
outputs
[
0
].
getArgType
(),
A
DD
_TO
);
TensorShape
outShape
=
outputs
[
0
].
shape
();
...
...
paddle/function/CropOpTest.cpp
浏览文件 @
701827f5
...
...
@@ -25,7 +25,7 @@ TEST(Crop, real) {
VLOG
(
3
)
<<
" numSamples="
<<
numSamples
<<
" channels="
<<
channels
<<
" imgSizeH="
<<
imgSizeH
<<
" imgSizeW="
<<
imgSizeW
;
for
(
bool
test_grad
:
{
false
,
true
})
{
Function
Compare
compare
(
CpuGpuFunc
Compare
compare
(
test_grad
?
"CropGrad"
:
"Crop"
,
FuncConfig
()
.
set
<
std
::
vector
<
uint32_t
>>
(
"crop_corner"
,
{
0
,
1
,
1
,
1
})
...
...
paddle/gserver/layers/CropLayer.cpp
浏览文件 @
701827f5
...
...
@@ -14,7 +14,6 @@ limitations under the License. */
#include "CropLayer.h"
#include "paddle/utils/Stat.h"
namespace
paddle
{
REGISTER_LAYER
(
crop
,
CropLayer
);
...
...
@@ -24,10 +23,9 @@ bool CropLayer::init(const LayerMap& layerMap,
/* Initialize the basic parent class */
Layer
::
init
(
layerMap
,
parameterMap
);
auto
&
crop_conf
=
config_
.
inputs
(
0
).
crop_conf
();
crop_axis_
=
crop_conf
.
axis
();
for
(
int
i
=
0
;
i
<
crop_conf
.
offset_size
();
i
++
)
{
crop_offsets_
[
i
]
=
crop_conf
.
offset
(
i
);
crop_axis_
=
config_
.
axis
();
for
(
int
i
=
0
;
i
<
config_
.
offset_size
();
i
++
)
{
crop_offsets_
.
push_back
(
config_
.
offset
(
i
));
}
// 1. get input_0 shape
...
...
@@ -38,7 +36,6 @@ bool CropLayer::init(const LayerMap& layerMap,
?
input0_img_conf
.
img_size_y
()
:
input0_img_conf
.
img_size
(),
input0_img_conf
.
img_size
()});
// 2. get output shape from input_1 or crop shap conf
if
(
config_
.
inputs_size
()
==
2
)
{
auto
&
input1_img_conf
=
config_
.
inputs
(
1
).
image_conf
();
...
...
@@ -49,19 +46,19 @@ bool CropLayer::init(const LayerMap& layerMap,
:
input1_img_conf
.
img_size
(),
input1_img_conf
.
img_size
()});
}
else
{
targetDims_
=
TensorShape
({
c
rop_conf
.
shape
(
0
),
c
rop_conf
.
shape
(
1
),
c
rop_conf
.
shape
(
2
),
c
rop_conf
.
shape
(
3
)});
targetDims_
=
TensorShape
({
c
onfig_
.
shape
(
0
),
c
onfig_
.
shape
(
1
),
c
onfig_
.
shape
(
2
),
c
onfig_
.
shape
(
3
)});
}
// 3. get final crop shape
int
dimSize
=
4
;
for
(
int
i
=
0
;
i
<
dimSize
;
i
++
)
{
if
(
i
>=
crop_axis_
)
{
crop_shape_
[
i
]
=
targetDims_
[
i
]
;
crop_shape_
.
push_back
(
targetDims_
[
i
])
;
}
else
{
crop_shape_
[
i
]
=
inDims_
[
i
]
;
crop_shape_
.
push_back
(
inDims_
[
i
])
;
}
}
...
...
@@ -99,7 +96,7 @@ void CropLayer::setOutDims(const size_t batchSize) {
}
void
CropLayer
::
setTensorDim
(
const
size_t
batchSize
)
{
CHECK_EQ
(
static_cast
<
int
>
(
inputLayers_
.
size
()),
1
);
CHECK_EQ
(
static_cast
<
int
>
(
inputLayers_
.
size
()),
2
);
inDims_
.
setDim
(
0
,
batchSize
);
int
h
=
inputLayers_
[
0
]
->
getOutput
().
getFrameHeight
();
if
(
h
!=
0
)
inDims_
.
setDim
(
2
,
h
);
...
...
paddle/gserver/tests/CMakeLists.txt
浏览文件 @
701827f5
...
...
@@ -56,7 +56,7 @@ add_test(NAME test_DetectionOutput
add_unittest_without_exec
(
test_ConvUnify
test_ConvUnify.cpp
LayerGradUtil.cpp
)
add_test
(
NAME test_ConvUnify
COMMAND test_ConvUnify
)
################# test_BatchNorm #######################
...
...
paddle/gserver/tests/test_LayerGrad.cpp
浏览文件 @
701827f5
...
...
@@ -1792,6 +1792,34 @@ TEST(Layer, RowConvLayer) {
}
}
TEST
(
Layer
,
CropLayer
)
{
TestConfig
config
;
// config input_0
config
.
inputDefs
.
push_back
({
INPUT_DATA
,
"layer_0"
,
1024
,
0
});
LayerInputConfig
*
input
=
config
.
layerConfig
.
add_inputs
();
ImageConfig
*
img
=
input
->
mutable_image_conf
();
img
->
set_channels
(
4
);
img
->
set_img_size
(
16
);
config
.
layerConfig
.
set_axis
(
2
);
config
.
layerConfig
.
add_offset
(
0
);
config
.
layerConfig
.
add_offset
(
0
);
// config input_1
config
.
inputDefs
.
push_back
({
INPUT_DATA
,
"layer_1"
,
128
,
0
});
input
=
config
.
layerConfig
.
add_inputs
();
img
=
input
->
mutable_image_conf
();
img
->
set_channels
(
2
);
img
->
set_img_size
(
8
);
// config crop layer
config
.
layerConfig
.
set_type
(
"crop"
);
config
.
layerConfig
.
set_name
(
"cropLayer"
);
for
(
auto
useGpu
:
{
false
,
true
})
{
testLayerGrad
(
config
,
"crop"
,
100
,
false
,
useGpu
,
false
);
}
}
int
main
(
int
argc
,
char
**
argv
)
{
testing
::
InitGoogleTest
(
&
argc
,
argv
);
initMain
(
argc
,
argv
);
...
...
proto/ModelConfig.proto
浏览文件 @
701827f5
...
...
@@ -472,10 +472,16 @@ message LayerConfig {
// blank label used in ctc loss
optional
uint32
blank
=
52
[
default
=
0
];
// stride parameter for seqlastins layer, AverageLayer, MaxLayer, which
// stride parameter for seqlastins layer, AverageLayer, MaxLayer, which
// controls the scope of pooling operation. can be set > 0.
// leave empty or set to -1 to disable this stride pooling.
optional
int32
seq_pool_stride
=
53
[
default
=
-
1
];
// for crop layer
optional
int32
axis
=
54
[
default
=
2
];
repeated
uint32
offset
=
55
;
repeated
uint32
shape
=
56
;
}
message
EvaluatorConfig
{
...
...
python/paddle/trainer/config_parser.py
浏览文件 @
701827f5
...
...
@@ -1986,6 +1986,51 @@ class PadLayer(LayerBase):
self
.
config
.
size
=
out_ch
*
out_h
*
out_w
@
config_layer
(
'crop'
)
class
CropLayer
(
LayerBase
):
def
__init__
(
self
,
inputs
,
axis
,
offset
,
shape
,
name
,
**
xargs
):
super
(
CropLayer
,
self
).
__init__
(
name
,
'crop'
,
0
,
inputs
=
inputs
,
**
xargs
)
self
.
conf
.
axis
=
axis
self
.
conf
.
axis
=
offset
self
.
conf
.
axis
=
shape
crop
=
self
.
inputs
[
0
].
crop
self
.
config
.
inputs
[
0
].
crop_conf
.
axis
=
crop
.
axis
self
.
config
.
inputs
[
0
].
crop_conf
.
offset
.
extend
(
crop
.
offset
)
self
.
config
.
inputs
[
0
].
crop_conf
.
shape
.
extend
(
crop
.
shape
)
# get channel, width and height from input_0 layer
input_layer
=
self
.
get_input_layer
(
0
)
image_conf
=
self
.
config
.
inputs
[
0
].
image_conf
image_conf
.
img_size
=
input_layer
.
width
image_conf
.
img_size_y
=
input_layer
.
height
image_conf
.
channels
=
input_layer
.
size
/
(
input_layer
.
width
*
input_layer
.
height
)
out_ch
=
image_conf
.
channels
out_h
=
image_conf
.
img_size
out_w
=
image_conf
.
img_size_y
if
len
(
self
.
inputs
)
==
2
:
# get channels, width and height from input_1 layer
input_layer
=
self
.
get_input_layer
(
1
)
image_conf
=
self
.
config
.
inputs
[
1
].
image_conf
image_conf
.
img_size
=
input_layer
.
width
image_conf
.
img_size_y
=
input_layer
.
height
image_conf
.
channels
=
input_layer
.
size
/
(
input_layer
.
width
*
input_layer
.
height
)
out_ch
=
image_conf
.
channels
out_h
=
image_conf
.
img_size_y
out_w
=
image_conf
.
img_size
else
:
# set channels, width and heigth of current layer
if
len
(
shape
)
>
2
:
out_ch
=
shape
[
-
3
]
if
len
(
shape
)
>
1
:
out_h
=
shape
[
-
2
]
if
len
(
shape
)
>
0
:
out_w
=
shape
[
-
1
]
self
.
set_cnn_layer
(
name
,
out_h
,
out_w
,
out_ch
)
@
config_layer
(
'batch_norm'
)
class
BatchNormLayer
(
LayerBase
):
layer_type
=
'batch_norm'
...
...
python/paddle/trainer_config_helpers/layers.py
浏览文件 @
701827f5
...
...
@@ -217,6 +217,7 @@ class LayerType(object):
SMOOTH_L1
=
'smooth_l1'
PRELU
=
'prelu'
CROP_LAYER
=
'crop'
@
staticmethod
def
is_layer_type
(
type_name
):
...
...
@@ -5853,3 +5854,56 @@ def prelu_layer(input,
layer_type
=
LayerType
.
PRELU
,
parents
=
input
,
size
=
l
.
config
.
size
)
@
wrap_name_default
()
@
layer_support
()
def
crop_layer
(
input
,
axis
,
offset
,
shape
=
None
,
name
=
None
,
layer_attr
=
None
):
"""
The crop layer crop images by offset and shape. User can set crop shape by
args 'shape' explicitly or by reference input layer.
The example usage is:
.. code-block:: python
crop = crop_layer(input=[image_input, reference_input], axis=2, offset=[2, 3])
:param input: The input layer.If two inputs were setted,
the second input will be regarded as reference input
:type input: LayerOutput or Sequence
:param axis: start axis to be cropped. To image input layer:
- 0: batch size
- 1: channels
- 2: height
- 3: width
:type partial_sum: int
:param offset: The crop offset
:type offset: Sequence
:param shape: The shape to be cropped. Default is None.
:type shape: Sqquence | None
:param name: Name of this layer.
:type name: basestring
:return: LayerOutput object.
:rtype: LayerOutput
"""
if
isinstance
(
input
,
LayerOutput
):
input
=
[
input
]
elif
isinstance
(
input
,
Projection
):
input
=
[
input
]
else
:
assert
isinstance
(
input
,
collections
.
Sequence
)
l
=
Layer
(
inputs
=
[
x
.
name
for
x
in
input
],
axis
=
axis
,
offset
=
offset
,
shape
=
shape
,
name
=
name
,
type
=
LayerType
.
CROP_LAYER
,
**
ExtraLayerAttribute
.
to_kwargs
(
layer_attr
))
return
LayerOutput
(
name
=
name
,
layer_type
=
LayerType
.
CROP_LAYER
,
parents
=
input
,
size
=
l
.
config
.
size
)
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