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0be34949
编写于
9月 09, 2017
作者:
C
chengduo
提交者:
GitHub
9月 09, 2017
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差异文件
Merge pull request #3594 from chengduoZH/Adapting_to_the_BatchNorm_structure_to_support_3D_data
Adapting to the BatchNorm structure to support 3D data
上级
2fefaa1c
5500153a
变更
15
隐藏空白更改
内联
并排
Showing
15 changed file
with
354 addition
and
16 deletion
+354
-16
paddle/gserver/layers/BatchNormBaseLayer.cpp
paddle/gserver/layers/BatchNormBaseLayer.cpp
+5
-1
paddle/gserver/layers/BatchNormBaseLayer.h
paddle/gserver/layers/BatchNormBaseLayer.h
+1
-0
paddle/gserver/layers/CudnnBatchNormLayer.cpp
paddle/gserver/layers/CudnnBatchNormLayer.cpp
+2
-2
paddle/gserver/tests/test_LayerGrad.cpp
paddle/gserver/tests/test_LayerGrad.cpp
+49
-0
proto/ModelConfig.proto
proto/ModelConfig.proto
+1
-0
python/paddle/trainer/config_parser.py
python/paddle/trainer/config_parser.py
+78
-11
python/paddle/trainer_config_helpers/layers.py
python/paddle/trainer_config_helpers/layers.py
+7
-1
python/paddle/trainer_config_helpers/tests/configs/file_list.sh
.../paddle/trainer_config_helpers/tests/configs/file_list.sh
+1
-1
python/paddle/trainer_config_helpers/tests/configs/protostr/img_layers.protostr
...config_helpers/tests/configs/protostr/img_layers.protostr
+1
-0
python/paddle/trainer_config_helpers/tests/configs/protostr/img_trans_layers.protostr
..._helpers/tests/configs/protostr/img_trans_layers.protostr
+1
-0
python/paddle/trainer_config_helpers/tests/configs/protostr/test_BatchNorm3D.protostr
..._helpers/tests/configs/protostr/test_BatchNorm3D.protostr
+92
-0
python/paddle/trainer_config_helpers/tests/configs/protostr/test_bi_grumemory.protostr
...helpers/tests/configs/protostr/test_bi_grumemory.protostr
+3
-0
python/paddle/trainer_config_helpers/tests/configs/protostr/test_recursive_topology.protostr
...s/tests/configs/protostr/test_recursive_topology.protostr
+96
-0
python/paddle/trainer_config_helpers/tests/configs/protostr/util_layers.protostr
...onfig_helpers/tests/configs/protostr/util_layers.protostr
+6
-0
python/paddle/trainer_config_helpers/tests/configs/test_BatchNorm3D.py
.../trainer_config_helpers/tests/configs/test_BatchNorm3D.py
+11
-0
未找到文件。
paddle/gserver/layers/BatchNormBaseLayer.cpp
浏览文件 @
0be34949
...
...
@@ -62,14 +62,18 @@ void BatchNormBaseLayer::calFeatureMapSize() {
const
ImageConfig
&
conf
=
config_
.
inputs
(
0
).
image_conf
();
imageH_
=
inputLayers_
[
0
]
->
getOutput
().
getFrameHeight
();
imageW_
=
inputLayers_
[
0
]
->
getOutput
().
getFrameWidth
();
imageD_
=
inputLayers_
[
0
]
->
getOutput
().
getFrameDepth
();
if
(
0
==
imageD_
)
imageD_
=
conf
.
img_size_z
();
if
(
imageH_
==
0
&&
imageW_
==
0
)
{
imageH_
=
conf
.
has_img_size_y
()
?
conf
.
img_size_y
()
:
conf
.
img_size
();
imageW_
=
conf
.
img_size
();
}
else
{
getOutput
().
setFrameHeight
(
imageH_
);
getOutput
().
setFrameWidth
(
imageW_
);
getOutput
().
setFrameDepth
(
imageD_
);
}
imgPixels_
=
imageH_
*
imageW_
;
imgPixels_
=
imageH_
*
imageW_
*
imageD_
;
}
}
// namespace paddle
paddle/gserver/layers/BatchNormBaseLayer.h
浏览文件 @
0be34949
...
...
@@ -80,6 +80,7 @@ protected:
/// Height or width of input image feature.
/// Both of them are 1 if the input is fully-connected layer.
int
imageD_
;
int
imageH_
;
int
imageW_
;
/// Height * Width.
...
...
paddle/gserver/layers/CudnnBatchNormLayer.cpp
浏览文件 @
0be34949
...
...
@@ -37,7 +37,7 @@ bool CudnnBatchNormLayer::init(const LayerMap& layerMap,
}
void
CudnnBatchNormLayer
::
reshape
(
int
batchSize
)
{
hl_tensor_reshape
(
ioDesc_
,
batchSize
,
channels_
,
imageH_
,
imageW_
);
hl_tensor_reshape
(
ioDesc_
,
batchSize
,
channels_
,
imageH_
*
imageD_
,
imageW_
);
}
void
CudnnBatchNormLayer
::
forward
(
PassType
passType
)
{
...
...
@@ -104,7 +104,7 @@ void CudnnBatchNormLayer::forward(PassType passType) {
EPS
,
batchSize
,
channels_
,
imageH_
,
imageH_
*
imageD_
,
imageW_
);
}
}
...
...
paddle/gserver/tests/test_LayerGrad.cpp
浏览文件 @
0be34949
...
...
@@ -1703,6 +1703,55 @@ TEST(Layer, BatchNormalizationLayer) {
#endif
}
void
testBatchNorm3DLayer
(
const
string
&
type
,
bool
trans
,
bool
useGpu
)
{
TestConfig
config
;
const
int
CHANNELS
=
10
;
const
int
IMG_SIZE
=
16
;
const
int
IMG_SIZE_Y
=
8
;
const
int
IMG_SIZE_Z
=
8
;
size_t
size
=
CHANNELS
*
IMG_SIZE
*
IMG_SIZE_Y
*
IMG_SIZE_Z
;
config
.
layerConfig
.
set_type
(
type
);
config
.
layerConfig
.
set_size
(
size
);
config
.
layerConfig
.
set_active_type
(
"sigmoid"
);
config
.
biasSize
=
CHANNELS
;
config
.
inputDefs
.
push_back
({
INPUT_DATA
,
"layer_0"
,
/* dim= */
size
,
/* paraSize= */
CHANNELS
});
config
.
inputDefs
.
push_back
({
INPUT_DATA
,
"layer_1_running_mean"
,
1
,
CHANNELS
});
config
.
inputDefs
.
back
().
isStatic
=
true
;
config
.
inputDefs
.
push_back
({
INPUT_DATA
,
"layer_2_running_var"
,
1
,
CHANNELS
});
config
.
inputDefs
.
back
().
isStatic
=
true
;
LayerInputConfig
*
input
=
config
.
layerConfig
.
add_inputs
();
config
.
layerConfig
.
add_inputs
();
config
.
layerConfig
.
add_inputs
();
ImageConfig
*
img_conf
=
input
->
mutable_image_conf
();
img_conf
->
set_channels
(
CHANNELS
);
img_conf
->
set_img_size
(
IMG_SIZE
);
img_conf
->
set_img_size_y
(
IMG_SIZE_Y
);
img_conf
->
set_img_size_z
(
IMG_SIZE_Z
);
testLayerGrad
(
config
,
"batch_norm"
,
64
,
/* trans= */
trans
,
useGpu
,
/* useWeight */
true
);
}
TEST
(
Layer
,
testBatchNorm3DLayer
)
{
testBatchNorm3DLayer
(
"batch_norm"
,
false
,
false
);
#ifndef PADDLE_ONLY_CPU
testBatchNorm3DLayer
(
"batch_norm"
,
false
,
true
);
if
(
hl_get_cudnn_lib_version
()
>=
int
(
4000
))
{
testBatchNorm3DLayer
(
"cudnn_batch_norm"
,
false
,
true
);
}
#endif
}
void
testConvOperator
(
bool
isDeconv
)
{
TestConfig
config
;
const
int
NUM_FILTERS
=
16
;
...
...
proto/ModelConfig.proto
浏览文件 @
0be34949
...
...
@@ -520,6 +520,7 @@ message LayerConfig {
// for HuberRegressionLoss
optional
double
delta
=
57
[
default
=
1.0
];
// for 3D data
optional
uint64
depth
=
58
[
default
=
1
];
// for switch order layer
...
...
python/paddle/trainer/config_parser.py
浏览文件 @
0be34949
...
...
@@ -1332,6 +1332,12 @@ def parse_image(image, input_layer_name, image_conf):
get_img_size
(
input_layer_name
,
image_conf
.
channels
)
def
parse_image3d
(
image
,
input_layer_name
,
image_conf
):
image_conf
.
channels
=
image
.
channels
image_conf
.
img_size
,
image_conf
.
img_size_y
,
image_conf
.
img_size_z
=
\
get_img3d_size
(
input_layer_name
,
image_conf
.
channels
)
def
parse_norm
(
norm
,
input_layer_name
,
norm_conf
):
norm_conf
.
norm_type
=
norm
.
norm_type
config_assert
(
...
...
@@ -2365,6 +2371,7 @@ class BatchNormLayer(LayerBase):
name
,
inputs
,
bias
=
True
,
img3D
=
False
,
use_global_stats
=
True
,
moving_average_fraction
=
0.9
,
batch_norm_type
=
None
,
...
...
@@ -2410,15 +2417,33 @@ class BatchNormLayer(LayerBase):
input_layer
=
self
.
get_input_layer
(
0
)
image_conf
=
self
.
config
.
inputs
[
0
].
image_conf
parse_image
(
self
.
inputs
[
0
].
image
,
input_layer
.
name
,
image_conf
)
# Only pass the width and height of input to batch_norm layer
# when either of it is non-zero.
if
input_layer
.
width
!=
0
or
input_layer
.
height
!=
0
:
self
.
set_cnn_layer
(
name
,
image_conf
.
img_size_y
,
image_conf
.
img_size
,
image_conf
.
channels
,
False
)
if
img3D
:
parse_image3d
(
self
.
inputs
[
0
].
image
,
input_layer
.
name
,
image_conf
)
# Only pass the width and height of input to batch_norm layer
# when either of it is non-zero.
if
input_layer
.
width
!=
0
or
input_layer
.
height
!=
0
:
self
.
set_cnn_layer
(
input_layer_name
=
name
,
depth
=
image_conf
.
img_size_z
,
height
=
image_conf
.
img_size_y
,
width
=
image_conf
.
img_size
,
channels
=
image_conf
.
channels
,
is_print
=
True
)
else
:
self
.
set_layer_size
(
input_layer
.
size
)
else
:
self
.
set_layer_size
(
input_layer
.
size
)
parse_image
(
self
.
inputs
[
0
].
image
,
input_layer
.
name
,
image_conf
)
# Only pass the width and height of input to batch_norm layer
# when either of it is non-zero.
if
input_layer
.
width
!=
0
or
input_layer
.
height
!=
0
:
self
.
set_cnn_layer
(
input_layer_name
=
name
,
height
=
image_conf
.
img_size_y
,
width
=
image_conf
.
img_size
,
channels
=
image_conf
.
channels
,
is_print
=
True
)
else
:
self
.
set_layer_size
(
input_layer
.
size
)
psize
=
self
.
calc_parameter_size
(
image_conf
)
dims
=
[
1
,
psize
]
...
...
@@ -2433,6 +2458,28 @@ class BatchNormLayer(LayerBase):
self
.
create_bias_parameter
(
bias
,
psize
)
def
set_cnn_layer
(
self
,
input_layer_name
,
depth
=
None
,
height
=
None
,
width
=
None
,
channels
=
None
,
is_print
=
True
):
depthIsNone
=
False
if
depth
is
None
:
depth
=
1
depthIsNone
=
True
size
=
depth
*
height
*
width
*
channels
self
.
set_layer_size
(
size
)
self
.
set_layer_height_width
(
height
,
width
)
self
.
set_layer_depth
(
depth
)
if
is_print
and
depthIsNone
:
print
(
"output for %s: c = %d, h = %d, w = %d, size = %d"
%
(
input_layer_name
,
channels
,
height
,
width
,
size
))
elif
is_print
:
print
(
"output for %s: c = %d, d = %d, h = %d, w = %d, size = %d"
%
(
input_layer_name
,
channels
,
depth
,
height
,
width
,
size
))
def
calc_parameter_size
(
self
,
image_conf
):
return
image_conf
.
channels
...
...
@@ -2694,9 +2741,20 @@ class AddToLayer(LayerBase):
super
(
AddToLayer
,
self
).
__init__
(
name
,
'addto'
,
0
,
inputs
=
inputs
,
**
xargs
)
config_assert
(
len
(
inputs
)
>
0
,
'inputs cannot be empty for AddToLayer'
)
for
input_index
in
xrange
(
len
(
self
.
inputs
)):
input_layer
=
self
.
get_input_layer
(
input_index
)
self
.
set_layer_size
(
input_layer
.
size
)
if
len
(
self
.
inputs
)
>
1
:
for
input_index
in
xrange
(
len
(
self
.
inputs
)):
assert
self
.
get_input_layer
(
0
).
height
==
self
.
get_input_layer
(
input_index
).
height
assert
self
.
get_input_layer
(
0
).
width
==
self
.
get_input_layer
(
input_index
).
width
assert
self
.
get_input_layer
(
0
).
depth
==
self
.
get_input_layer
(
input_index
).
depth
self
.
set_layer_size
(
self
.
get_input_layer
(
0
).
size
)
self
.
set_layer_height_width
(
self
.
get_input_layer
(
0
).
height
,
\
self
.
get_input_layer
(
0
).
width
)
self
.
set_layer_depth
(
self
.
get_input_layer
(
0
).
depth
)
self
.
create_bias_parameter
(
bias
,
self
.
config
.
size
)
...
...
@@ -3376,11 +3434,20 @@ class ConcatenateLayer(LayerBase):
name
,
'concat'
,
0
,
inputs
=
inputs
,
**
xargs
)
size
=
0
for
input_index
in
xrange
(
len
(
self
.
inputs
)):
assert
self
.
get_input_layer
(
0
).
height
==
self
.
get_input_layer
(
input_index
).
height
assert
self
.
get_input_layer
(
0
).
width
==
self
.
get_input_layer
(
input_index
).
width
assert
self
.
get_input_layer
(
0
).
depth
==
self
.
get_input_layer
(
input_index
).
depth
input_layer
=
self
.
get_input_layer
(
input_index
)
input
=
self
.
inputs
[
input_index
]
if
self
.
config
.
size
==
0
:
size
+=
input_layer
.
size
self
.
set_layer_height_width
(
self
.
get_input_layer
(
0
).
height
,
\
self
.
get_input_layer
(
0
).
width
)
self
.
set_layer_depth
(
self
.
get_input_layer
(
0
).
depth
)
self
.
set_layer_size
(
size
)
...
...
python/paddle/trainer_config_helpers/layers.py
浏览文件 @
0be34949
...
...
@@ -354,6 +354,10 @@ class LayerOutput(object):
def
height
(
self
):
return
cp
.
g_layer_map
[
self
.
full_name
].
height
@
property
def
depth
(
self
):
return
cp
.
g_layer_map
[
self
.
full_name
].
depth
def
set_input
(
self
,
input
):
"""
Set the input for a memory layer. Can only be used for memory layer
...
...
@@ -943,7 +947,7 @@ def data_layer(name, size, depth=None, height=None, width=None,
if
height
is
not
None
and
width
is
not
None
:
num_filters
=
size
/
(
width
*
height
*
depth
)
assert
num_filters
*
width
*
height
*
depth
==
size
,
\
"size=%s width=%s height=%s depth=%s"
%
(
size
,
width
,
height
,
depth
)
"size=%s width=%s height=%s depth=%s"
%
(
size
,
width
,
height
,
depth
)
return
LayerOutput
(
name
,
LayerType
.
DATA
,
size
=
size
,
num_filters
=
num_filters
)
...
...
@@ -2953,6 +2957,7 @@ def img_cmrnorm_layer(input,
def
batch_norm_layer
(
input
,
act
=
None
,
name
=
None
,
img3D
=
False
,
num_channels
=
None
,
bias_attr
=
None
,
param_attr
=
None
,
...
...
@@ -3042,6 +3047,7 @@ def batch_norm_layer(input,
(
batch_norm_type
==
"cudnn_batch_norm"
)
l
=
Layer
(
name
=
name
,
img3D
=
img3D
,
inputs
=
Input
(
input
.
name
,
image
=
Image
(
channels
=
num_channels
),
**
param_attr
.
attr
),
active_type
=
act
.
name
,
...
...
python/paddle/trainer_config_helpers/tests/configs/file_list.sh
浏览文件 @
0be34949
...
...
@@ -10,6 +10,6 @@ test_prelu_layer test_row_conv test_detection_output_layer test_multibox_loss_la
test_recursive_topology test_gated_unit_layer test_clip_layer test_row_l2_norm_layer
test_kmax_seq_socre_layer test_sub_nested_seq_select_layer test_scale_shift_layer
test_seq_slice_layer test_cross_entropy_over_beam test_pooling3D_layer
test_conv3d_layer test_deconv3d_layer
)
test_conv3d_layer test_deconv3d_layer
test_BatchNorm3D
)
export
whole_configs
=(
test_split_datasource
)
python/paddle/trainer_config_helpers/tests/configs/protostr/img_layers.protostr
浏览文件 @
0be34949
...
...
@@ -62,6 +62,7 @@ layers {
moving_average_fraction: 0.9
height: 227
width: 227
depth: 1
}
layers {
name: "__crmnorm_0__"
...
...
python/paddle/trainer_config_helpers/tests/configs/protostr/img_trans_layers.protostr
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0be34949
...
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@@ -62,6 +62,7 @@ layers {
moving_average_fraction: 0.9
height: 256
width: 256
depth: 1
}
layers {
name: "__crmnorm_0__"
...
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python/paddle/trainer_config_helpers/tests/configs/protostr/test_BatchNorm3D.protostr
0 → 100644
浏览文件 @
0be34949
type: "nn"
layers {
name: "data3D"
type: "data"
size: 360
active_type: ""
height: 6
width: 20
depth: 3
}
layers {
name: "__batch_norm_0__"
type: "batch_norm"
size: 360
active_type: "relu"
inputs {
input_layer_name: "data3D"
input_parameter_name: "___batch_norm_0__.w0"
image_conf {
channels: 1
img_size: 20
img_size_y: 6
img_size_z: 3
}
}
inputs {
input_layer_name: "data3D"
input_parameter_name: "___batch_norm_0__.w1"
}
inputs {
input_layer_name: "data3D"
input_parameter_name: "___batch_norm_0__.w2"
}
bias_parameter_name: "___batch_norm_0__.wbias"
moving_average_fraction: 0.9
height: 6
width: 20
depth: 3
}
parameters {
name: "___batch_norm_0__.w0"
size: 1
initial_mean: 1.0
initial_std: 0.0
initial_strategy: 0
initial_smart: false
}
parameters {
name: "___batch_norm_0__.w1"
size: 1
initial_mean: 0.0
initial_std: 0.0
dims: 1
dims: 1
initial_strategy: 0
initial_smart: false
is_static: true
is_shared: true
}
parameters {
name: "___batch_norm_0__.w2"
size: 1
initial_mean: 0.0
initial_std: 0.0
dims: 1
dims: 1
initial_strategy: 0
initial_smart: false
is_static: true
is_shared: true
}
parameters {
name: "___batch_norm_0__.wbias"
size: 1
initial_mean: 0.0
initial_std: 0.0
dims: 1
dims: 1
initial_strategy: 0
initial_smart: false
}
input_layer_names: "data3D"
output_layer_names: "__batch_norm_0__"
sub_models {
name: "root"
layer_names: "data3D"
layer_names: "__batch_norm_0__"
input_layer_names: "data3D"
output_layer_names: "__batch_norm_0__"
is_recurrent_layer_group: false
}
python/paddle/trainer_config_helpers/tests/configs/protostr/test_bi_grumemory.protostr
浏览文件 @
0be34949
...
...
@@ -74,6 +74,9 @@ layers {
inputs {
input_layer_name: "__bidirectional_gru_0___bw"
}
height: 0
width: 0
depth: 1
}
parameters {
name: "___bidirectional_gru_0___fw_transform.w0"
...
...
python/paddle/trainer_config_helpers/tests/configs/protostr/test_recursive_topology.protostr
浏览文件 @
0be34949
...
...
@@ -16,6 +16,9 @@ layers {
inputs {
input_layer_name: "data"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_1__"
...
...
@@ -28,6 +31,9 @@ layers {
inputs {
input_layer_name: "__addto_0__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_2__"
...
...
@@ -40,6 +46,9 @@ layers {
inputs {
input_layer_name: "__addto_1__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_3__"
...
...
@@ -52,6 +61,9 @@ layers {
inputs {
input_layer_name: "__addto_2__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_4__"
...
...
@@ -64,6 +76,9 @@ layers {
inputs {
input_layer_name: "__addto_3__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_5__"
...
...
@@ -76,6 +91,9 @@ layers {
inputs {
input_layer_name: "__addto_4__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_6__"
...
...
@@ -88,6 +106,9 @@ layers {
inputs {
input_layer_name: "__addto_5__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_7__"
...
...
@@ -100,6 +121,9 @@ layers {
inputs {
input_layer_name: "__addto_6__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_8__"
...
...
@@ -112,6 +136,9 @@ layers {
inputs {
input_layer_name: "__addto_7__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_9__"
...
...
@@ -124,6 +151,9 @@ layers {
inputs {
input_layer_name: "__addto_8__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_10__"
...
...
@@ -136,6 +166,9 @@ layers {
inputs {
input_layer_name: "__addto_9__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_11__"
...
...
@@ -148,6 +181,9 @@ layers {
inputs {
input_layer_name: "__addto_10__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_12__"
...
...
@@ -160,6 +196,9 @@ layers {
inputs {
input_layer_name: "__addto_11__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_13__"
...
...
@@ -172,6 +211,9 @@ layers {
inputs {
input_layer_name: "__addto_12__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_14__"
...
...
@@ -184,6 +226,9 @@ layers {
inputs {
input_layer_name: "__addto_13__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_15__"
...
...
@@ -196,6 +241,9 @@ layers {
inputs {
input_layer_name: "__addto_14__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_16__"
...
...
@@ -208,6 +256,9 @@ layers {
inputs {
input_layer_name: "__addto_15__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_17__"
...
...
@@ -220,6 +271,9 @@ layers {
inputs {
input_layer_name: "__addto_16__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_18__"
...
...
@@ -232,6 +286,9 @@ layers {
inputs {
input_layer_name: "__addto_17__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_19__"
...
...
@@ -244,6 +301,9 @@ layers {
inputs {
input_layer_name: "__addto_18__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_20__"
...
...
@@ -256,6 +316,9 @@ layers {
inputs {
input_layer_name: "__addto_19__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_21__"
...
...
@@ -268,6 +331,9 @@ layers {
inputs {
input_layer_name: "__addto_20__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_22__"
...
...
@@ -280,6 +346,9 @@ layers {
inputs {
input_layer_name: "__addto_21__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_23__"
...
...
@@ -292,6 +361,9 @@ layers {
inputs {
input_layer_name: "__addto_22__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_24__"
...
...
@@ -304,6 +376,9 @@ layers {
inputs {
input_layer_name: "__addto_23__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_25__"
...
...
@@ -316,6 +391,9 @@ layers {
inputs {
input_layer_name: "__addto_24__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_26__"
...
...
@@ -328,6 +406,9 @@ layers {
inputs {
input_layer_name: "__addto_25__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_27__"
...
...
@@ -340,6 +421,9 @@ layers {
inputs {
input_layer_name: "__addto_26__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_28__"
...
...
@@ -352,6 +436,9 @@ layers {
inputs {
input_layer_name: "__addto_27__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_29__"
...
...
@@ -364,6 +451,9 @@ layers {
inputs {
input_layer_name: "__addto_28__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_30__"
...
...
@@ -376,6 +466,9 @@ layers {
inputs {
input_layer_name: "__addto_29__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__addto_31__"
...
...
@@ -388,6 +481,9 @@ layers {
inputs {
input_layer_name: "__addto_30__"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__fc_layer_0__"
...
...
python/paddle/trainer_config_helpers/tests/configs/protostr/util_layers.protostr
浏览文件 @
0be34949
...
...
@@ -22,6 +22,9 @@ layers {
inputs {
input_layer_name: "b"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__concat_0__"
...
...
@@ -34,6 +37,9 @@ layers {
inputs {
input_layer_name: "b"
}
height: 0
width: 0
depth: 1
}
layers {
name: "__concat_1__"
...
...
python/paddle/trainer_config_helpers/tests/configs/test_BatchNorm3D.py
0 → 100644
浏览文件 @
0be34949
from
paddle.trainer_config_helpers
import
*
settings
(
batch_size
=
1000
,
learning_rate
=
1e-4
)
#data = data_layer(name='data', size=180, width=30, height=6)
#batchNorm = batch_norm_layer(data, num_channels=1)
#outputs(batchNorm)
data3D
=
data_layer
(
name
=
'data3D'
,
size
=
120
*
3
,
width
=
20
,
height
=
6
,
depth
=
3
)
batchNorm3D
=
batch_norm_layer
(
data3D
,
num_channels
=
1
,
img3D
=
True
)
outputs
(
batchNorm3D
)
编辑
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