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体验新版 GitCode,发现更多精彩内容 >>
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eebd7868
编写于
9月 22, 2017
作者:
李
李寅
浏览文件
操作
浏览文件
下载
差异文件
Merge branch 'master' into 'master'
Refactor conv related op See merge request !55
上级
f16cf77e
736ceb5f
变更
19
隐藏空白更改
内联
并排
Showing
19 changed file
with
83 addition
and
110 deletion
+83
-110
mace/core/logging.h
mace/core/logging.h
+11
-1
mace/core/net.cc
mace/core/net.cc
+2
-0
mace/core/tensor.h
mace/core/tensor.h
+1
-1
mace/core/workspace.cc
mace/core/workspace.cc
+4
-0
mace/kernels/conv_2d.h
mace/kernels/conv_2d.h
+2
-14
mace/kernels/depthwise_conv2d.h
mace/kernels/depthwise_conv2d.h
+3
-14
mace/kernels/global_avg_pooling.h
mace/kernels/global_avg_pooling.h
+1
-4
mace/kernels/pooling.h
mace/kernels/pooling.h
+1
-3
mace/ops/conv_2d.cc
mace/ops/conv_2d.cc
+2
-2
mace/ops/conv_2d.h
mace/ops/conv_2d.h
+10
-7
mace/ops/conv_2d_benchmark.cc
mace/ops/conv_2d_benchmark.cc
+1
-1
mace/ops/conv_2d_test.cc
mace/ops/conv_2d_test.cc
+5
-5
mace/ops/conv_pool_2d_base.h
mace/ops/conv_pool_2d_base.h
+1
-42
mace/ops/depthwise_conv2d.h
mace/ops/depthwise_conv2d.h
+11
-5
mace/ops/depthwise_conv2d_test.cc
mace/ops/depthwise_conv2d_test.cc
+3
-3
mace/ops/depthwise_conv_2d_benchmark.cc
mace/ops/depthwise_conv_2d_benchmark.cc
+1
-1
mace/ops/pooling.h
mace/ops/pooling.h
+1
-0
mace/python/tools/tf_converter.py
mace/python/tools/tf_converter.py
+1
-0
mace/python/tools/tf_converter_lib.py
mace/python/tools/tf_converter_lib.py
+22
-7
未找到文件。
mace/core/logging.h
浏览文件 @
eebd7868
...
...
@@ -8,6 +8,7 @@
#include <limits>
#include <sstream>
#include <string>
#include <vector>
#undef ERROR
...
...
@@ -41,7 +42,16 @@ template <typename... Args>
string
MakeString
(
const
Args
&
...
args
)
{
std
::
stringstream
ss
;
MakeStringInternal
(
ss
,
args
...);
return
string
(
ss
.
str
());
return
ss
.
str
();
}
template
<
typename
T
>
string
MakeString
(
const
std
::
vector
<
T
>
&
args
)
{
std
::
stringstream
ss
;
for
(
const
T
&
arg
:
args
)
{
ss
<<
arg
<<
", "
;
}
return
ss
.
str
();
}
// Specializations for already-a-string types.
...
...
mace/core/net.cc
浏览文件 @
eebd7868
...
...
@@ -35,6 +35,8 @@ bool SimpleNet::Run() {
LOG
(
ERROR
)
<<
"Operator failed: "
<<
ProtoDebugString
(
op
->
debug_def
());
return
false
;
}
VLOG
(
1
)
<<
"Op "
<<
op
->
debug_def
().
name
()
<<
" has shape: "
<<
internal
::
MakeString
(
op
->
Output
(
0
)
->
shape
());
}
return
true
;
}
...
...
mace/core/tensor.h
浏览文件 @
eebd7868
...
...
@@ -137,7 +137,7 @@ class Tensor {
alloc_
->
CopyBytes
(
raw_mutable_data
(),
src
,
size
);
}
inline
void
DebugPrint
()
{
inline
void
DebugPrint
()
const
{
std
::
stringstream
os
;
for
(
int
i
:
shape_
)
{
os
<<
i
<<
", "
;
...
...
mace/core/workspace.cc
浏览文件 @
eebd7868
...
...
@@ -53,6 +53,10 @@ Tensor* Workspace::GetTensor(const string& name) {
void
Workspace
::
LoadModelTensor
(
const
NetDef
&
net_def
,
DeviceType
type
)
{
Serializer
serializer
;
for
(
auto
&
tensor_proto
:
net_def
.
tensors
())
{
VLOG
(
1
)
<<
"Load tensor: "
<<
tensor_proto
.
name
()
<<
" has shape: "
<<
internal
::
MakeString
(
vector
<
index_t
>
(
tensor_proto
.
dims
().
begin
(),
tensor_proto
.
dims
().
end
()));
tensor_map_
[
tensor_proto
.
name
()]
=
serializer
.
Deserialize
(
tensor_proto
,
type
);
}
...
...
mace/kernels/conv_2d.h
浏览文件 @
eebd7868
...
...
@@ -12,19 +12,8 @@ namespace mace {
namespace
kernels
{
template
<
DeviceType
D
,
typename
T
>
class
Conv2dFunctor
{
public:
Conv2dFunctor
(
const
index_t
*
input_shape
,
const
index_t
*
filter_shape
,
const
int
*
strides
,
const
Padding
padding
,
const
int
*
dilations
)
:
strides_
(
strides
),
paddings_
(
2
,
0
),
dilations_
(
dilations
)
{
CalPaddingSize
(
input_shape
,
filter_shape
,
dilations_
,
strides_
,
padding
,
paddings_
.
data
());
}
struct
Conv2dFunctor
{
Conv2dFunctor
()
{}
Conv2dFunctor
(
const
int
*
strides
,
const
std
::
vector
<
int
>
&
paddings
,
const
int
*
dilations
)
:
...
...
@@ -112,7 +101,6 @@ class Conv2dFunctor {
}
}
private:
const
int
*
strides_
;
// [stride_h, stride_w]
std
::
vector
<
int
>
paddings_
;
// [padding_h, padding_w]
const
int
*
dilations_
;
// [dilation_h, dilation_w]
...
...
mace/kernels/depthwise_conv2d.h
浏览文件 @
eebd7868
...
...
@@ -13,18 +13,8 @@ namespace mace {
namespace
kernels
{
template
<
DeviceType
D
,
typename
T
>
class
DepthwiseConv2dFunctor
{
public:
DepthwiseConv2dFunctor
(
const
index_t
*
input_shape
,
const
index_t
*
filter_shape
,
const
int
*
strides
,
const
Padding
padding
,
const
int
*
dilations
)
:
strides_
(
strides
),
paddings_
(
2
,
0
),
dilations_
(
dilations
)
{
CalPaddingSize
(
input_shape
,
filter_shape
,
dilations_
,
strides_
,
padding
,
paddings_
.
data
());
}
struct
DepthwiseConv2dFunctor
{
DepthwiseConv2dFunctor
()
{}
DepthwiseConv2dFunctor
(
const
int
*
strides
,
const
std
::
vector
<
int
>
&
paddings
,
const
int
*
dilations
)
:
...
...
@@ -39,7 +29,6 @@ class DepthwiseConv2dFunctor {
const
T
*
bias
,
// c_out
T
*
output
,
// NCHW
const
index_t
*
output_shape
)
{
MACE_CHECK_NOTNULL
(
output
);
index_t
batch
=
output_shape
[
0
];
...
...
@@ -111,7 +100,7 @@ class DepthwiseConv2dFunctor {
}
}
}
private:
const
int
*
strides_
;
// [stride_h, stride_w]
std
::
vector
<
int
>
paddings_
;
// [padding_h, padding_w]
const
int
*
dilations_
;
// [dilation_h, dilation_w]
...
...
mace/kernels/global_avg_pooling.h
浏览文件 @
eebd7868
...
...
@@ -11,10 +11,7 @@ namespace mace {
namespace
kernels
{
template
<
DeviceType
D
,
typename
T
>
class
GlobalAvgPoolingFunctor
{
public:
GlobalAvgPoolingFunctor
()
{}
struct
GlobalAvgPoolingFunctor
{
void
operator
()(
const
T
*
input
,
const
index_t
*
input_shape
,
T
*
output
)
{
index_t
batch
=
input_shape
[
0
];
index_t
channels
=
input_shape
[
1
];
...
...
mace/kernels/pooling.h
浏览文件 @
eebd7868
...
...
@@ -18,8 +18,7 @@ enum PoolingType {
namespace
kernels
{
template
<
DeviceType
D
,
typename
T
>
class
PoolingFunctor
{
public:
struct
PoolingFunctor
{
PoolingFunctor
(
const
PoolingType
pooling_type
,
const
int
*
kernels
,
const
int
*
strides
,
...
...
@@ -114,7 +113,6 @@ class PoolingFunctor {
}
}
private:
const
PoolingType
pooling_type_
;
const
int
*
kernels_
;
const
int
*
strides_
;
...
...
mace/ops/conv_2d.cc
浏览文件 @
eebd7868
...
...
@@ -6,10 +6,10 @@
namespace
mace
{
REGISTER_CPU_OPERATOR
(
Conv2
d
,
Conv2dOp
<
DeviceType
::
CPU
,
float
>
);
REGISTER_CPU_OPERATOR
(
Conv2
D
,
Conv2dOp
<
DeviceType
::
CPU
,
float
>
);
#if __ARM_NEON
REGISTER_NEON_OPERATOR
(
Conv2
d
,
Conv2dOp
<
DeviceType
::
NEON
,
float
>
);
REGISTER_NEON_OPERATOR
(
Conv2
D
,
Conv2dOp
<
DeviceType
::
NEON
,
float
>
);
#endif // __ARM_NEON
}
// namespace mace
mace/ops/conv_2d.h
浏览文件 @
eebd7868
...
...
@@ -17,12 +17,10 @@ template<DeviceType D, typename T>
class
Conv2dOp
:
public
ConvPool2dOpBase
<
D
,
T
>
{
public:
Conv2dOp
(
const
OperatorDef
&
op_def
,
Workspace
*
ws
)
:
ConvPool2dOpBase
<
D
,
T
>
(
op_def
,
ws
),
functor_
(
this
->
Input
(
INPUT
)
->
shape
().
data
(),
this
->
Input
(
FILTER
)
->
shape
().
data
(),
this
->
strides_
.
data
(),
this
->
padding_
,
this
->
dilations_
.
data
())
{}
:
ConvPool2dOpBase
<
D
,
T
>
(
op_def
,
ws
)
{
functor_
.
strides_
=
this
->
strides_
.
data
();
functor_
.
dilations_
=
this
->
dilations_
.
data
();
}
bool
Run
()
override
{
const
Tensor
*
input
=
this
->
Input
(
INPUT
);
...
...
@@ -37,8 +35,13 @@ class Conv2dOp : public ConvPool2dOpBase<D, T> {
std
::
vector
<
index_t
>
output_shape
(
4
);
std
::
vector
<
int
>
paddings
(
2
);
this
->
CalOutputSize
(
input
->
shape
().
data
(),
filter
->
shape
().
data
(),
output_shape
.
data
());
kernels
::
CalcPaddingAndOutputSize
(
input
->
shape
().
data
(),
filter
->
shape
().
data
(),
this
->
dilations_
.
data
(),
this
->
strides_
.
data
(),
this
->
padding_
,
output_shape
.
data
(),
paddings
.
data
());
output
->
Resize
(
output_shape
);
functor_
.
paddings_
=
paddings
;
functor_
(
input
->
data
<
T
>
(),
input
->
shape
().
data
(),
filter
->
data
<
T
>
(),
filter
->
shape
().
data
(),
bias_data
,
output
->
mutable_data
<
T
>
(),
...
...
mace/ops/conv_2d_benchmark.cc
浏览文件 @
eebd7868
...
...
@@ -25,7 +25,7 @@ static void Conv2d(int iters,
mace
::
testing
::
StopTiming
();
OpsTestNet
net
;
OpDefBuilder
(
"Conv2
d
"
,
"Conv2dTest"
)
OpDefBuilder
(
"Conv2
D
"
,
"Conv2dTest"
)
.
Input
(
"Input"
)
.
Input
(
"Filter"
)
.
Input
(
"Bias"
)
...
...
mace/ops/conv_2d_test.cc
浏览文件 @
eebd7868
...
...
@@ -13,7 +13,7 @@ class Conv2dOpTest : public OpsTestBase {};
TEST_F
(
Conv2dOpTest
,
Simple_VALID
)
{
// Construct graph
auto
&
net
=
test_net
();
OpDefBuilder
(
"Conv2
d
"
,
"Conv2dTest"
)
OpDefBuilder
(
"Conv2
D
"
,
"Conv2dTest"
)
.
Input
(
"Input"
)
.
Input
(
"Filter"
)
.
Input
(
"Bias"
)
...
...
@@ -47,7 +47,7 @@ TEST_F(Conv2dOpTest, Simple_VALID) {
TEST_F
(
Conv2dOpTest
,
Simple_SAME
)
{
// Construct graph
auto
&
net
=
test_net
();
OpDefBuilder
(
"Conv2
d
"
,
"Conv2dTest"
)
OpDefBuilder
(
"Conv2
D
"
,
"Conv2dTest"
)
.
Input
(
"Input"
)
.
Input
(
"Filter"
)
.
Input
(
"Bias"
)
...
...
@@ -83,7 +83,7 @@ TEST_F(Conv2dOpTest, Simple_SAME) {
TEST_F
(
Conv2dOpTest
,
Combined
)
{
// Construct graph
auto
&
net
=
test_net
();
OpDefBuilder
(
"Conv2
d"
,
"Conv2d
Test"
)
OpDefBuilder
(
"Conv2
D"
,
"Conv2D
Test"
)
.
Input
(
"Input"
)
.
Input
(
"Filter"
)
.
Input
(
"Bias"
)
...
...
@@ -121,7 +121,7 @@ TEST_F(Conv2dOpTest, Combined) {
TEST_F
(
Conv2dOpTest
,
Conv1x1
)
{
// Construct graph
auto
&
net
=
test_net
();
OpDefBuilder
(
"Conv2
d"
,
"Conv2d
Test"
)
OpDefBuilder
(
"Conv2
D"
,
"Conv2D
Test"
)
.
Input
(
"Input"
)
.
Input
(
"Filter"
)
.
Input
(
"Bias"
)
...
...
@@ -179,7 +179,7 @@ TEST_F(Conv2dOpTest, ConvNxNS12) {
index_t
output_channels
=
1
+
rand
()
%
10
;
// Construct graph
auto
&
net
=
test_net
();
OpDefBuilder
(
"Conv2
d
"
,
"Conv2dTest"
)
OpDefBuilder
(
"Conv2
D
"
,
"Conv2dTest"
)
.
Input
(
"Input"
)
.
Input
(
"Filter"
)
.
Input
(
"Bias"
)
...
...
mace/ops/conv_pool_2d_base.h
浏览文件 @
eebd7868
...
...
@@ -19,48 +19,7 @@ class ConvPool2dOpBase : public Operator<D, T> {
padding_
(
static_cast
<
Padding
>
(
OperatorBase
::
GetSingleArgument
<
int
>
(
"padding"
,
static_cast
<
int
>
(
SAME
)))),
dilations_
(
OperatorBase
::
GetRepeatedArgument
<
int
>
(
"dilations"
,
{
1
,
1
}))
{}
void
CalOutputSize
(
const
index_t
*
input_shape
,
// NCHW
const
index_t
*
filter_shape
,
// OIHW
index_t
*
output_shape
)
{
MACE_CHECK
(
dilations_
[
0
]
>
0
&&
dilations_
[
1
]
>
0
,
"Invalid dilations, must >= 1"
);
MACE_CHECK
((
dilations_
[
0
]
==
1
||
strides_
[
0
]
==
1
)
&&
(
dilations_
[
1
]
==
1
||
strides_
[
1
]
==
1
),
"If dilations > 1, strides should be 1"
);
MACE_CHECK_NOTNULL
(
output_shape
);
/*
* Convlution/pooling arithmetic:
* o = (i + 2 * p - k - (k - 1) * (d - 1)) / s + 1
* For details, see https://arxiv.org/pdf/1603.07285.pdf or
* http://deeplearning.net/software/theano/tutorial/conv_arithmetic.html
*/
index_t
output_height
=
0
,
output_width
=
0
;
switch
(
padding_
)
{
case
VALID
:
output_height
=
(
input_shape
[
2
]
-
(
filter_shape
[
2
]
-
1
)
*
dilations_
[
0
]
-
1
)
/
strides_
[
0
]
+
1
;
output_width
=
(
input_shape
[
3
]
-
(
filter_shape
[
3
]
-
1
)
*
dilations_
[
1
]
-
1
)
/
strides_
[
1
]
+
1
;
break
;
case
SAME
:
output_height
=
(
input_shape
[
2
]
-
1
)
/
strides_
[
0
]
+
1
;
output_width
=
(
input_shape
[
3
]
-
1
)
/
strides_
[
1
]
+
1
;
break
;
case
FULL
:
output_height
=
(
input_shape
[
2
]
+
(
filter_shape
[
2
]
-
1
)
*
dilations_
[
0
]
-
1
)
/
strides_
[
0
]
+
1
;
output_width
=
(
input_shape
[
3
]
+
(
filter_shape
[
3
]
-
1
)
*
dilations_
[
1
]
-
1
)
/
strides_
[
1
]
+
1
;
break
;
default:
MACE_CHECK
(
false
,
"Unsupported padding type: "
,
padding_
);
}
output_shape
[
0
]
=
input_shape
[
0
];
output_shape
[
1
]
=
filter_shape
[
0
];
output_shape
[
2
]
=
output_height
;
output_shape
[
3
]
=
output_width
;
}
protected:
std
::
vector
<
int
>
strides_
;
Padding
padding_
;
...
...
mace/ops/depthwise_conv2d.h
浏览文件 @
eebd7868
...
...
@@ -18,10 +18,10 @@ template<DeviceType D, typename T>
class
DepthwiseConv2dOp
:
public
ConvPool2dOpBase
<
D
,
T
>
{
public:
DepthwiseConv2dOp
(
const
OperatorDef
&
op_def
,
Workspace
*
ws
)
:
ConvPool2dOpBase
<
D
,
T
>
(
op_def
,
ws
)
,
functor_
(
this
->
Input
(
INPUT
)
->
shape
().
data
(),
this
->
Input
(
FILTER
)
->
shape
().
data
(),
this
->
strides_
.
data
(),
this
->
padding_
,
this
->
dilations_
.
data
())
{};
:
ConvPool2dOpBase
<
D
,
T
>
(
op_def
,
ws
)
{
functor_
.
strides_
=
this
->
strides_
.
data
();
functor_
.
dilations_
=
this
->
dilations_
.
data
();
}
bool
Run
()
override
{
const
Tensor
*
input
=
this
->
Input
(
INPUT
);
...
...
@@ -38,8 +38,14 @@ class DepthwiseConv2dOp : public ConvPool2dOpBase<D, T> {
filter_shape
[
0
]
*=
filter_shape
[
1
];
filter_shape
[
1
]
=
1
;
std
::
vector
<
index_t
>
output_shape
(
4
);
this
->
CalOutputSize
(
input
->
shape
().
data
(),
filter_shape
.
data
(),
output_shape
.
data
());
std
::
vector
<
int
>
paddings
(
2
);
kernels
::
CalcPaddingAndOutputSize
(
input
->
shape
().
data
(),
filter_shape
.
data
(),
this
->
dilations_
.
data
(),
this
->
strides_
.
data
(),
this
->
padding_
,
output_shape
.
data
(),
paddings
.
data
());
output
->
Resize
(
output_shape
);
functor_
.
paddings_
=
paddings
;
functor_
(
input
->
data
<
T
>
(),
input
->
shape
().
data
(),
filter
->
data
<
T
>
(),
filter_shape
.
data
(),
bias_data
,
output
->
mutable_data
<
T
>
(),
...
...
mace/ops/depthwise_conv2d_test.cc
浏览文件 @
eebd7868
...
...
@@ -10,9 +10,10 @@ using namespace mace;
class
DepthwiseConv2dOpTest
:
public
OpsTestBase
{};
TEST_F
(
DepthwiseConv2dOpTest
,
Simple_VALID
)
{
testing
::
internal
::
LogToStderr
();
// Construct graph
auto
&
net
=
test_net
();
OpDefBuilder
(
"DepthwiseConv2d"
,
"DepthwiseConv2
d
Test"
)
OpDefBuilder
(
"DepthwiseConv2d"
,
"DepthwiseConv2
D
Test"
)
.
Input
(
"Input"
)
.
Input
(
"Filter"
)
.
Input
(
"Bias"
)
...
...
@@ -35,7 +36,6 @@ TEST_F(DepthwiseConv2dOpTest, Simple_VALID) {
3.0
f
,
7.0
f
,
11.0
f
,
15.0
f
,
4.0
f
,
8.0
f
,
12.0
f
,
16.0
f
});
net
.
AddInputFromArray
<
float
>
(
"Bias"
,
{
4
},
{
.1
f
,
.2
f
,
.3
f
,
.4
f
});
// Run
net
.
RunOp
();
...
...
@@ -61,7 +61,7 @@ TEST_F(DepthwiseConv2dOpTest, ConvNxNS12) {
index_t
multiplier
=
3
+
rand
()
%
10
;
// Construct graph
auto
&
net
=
test_net
();
OpDefBuilder
(
"DepthwiseConv2d"
,
"DepthwiseConv2
d
Test"
)
OpDefBuilder
(
"DepthwiseConv2d"
,
"DepthwiseConv2
D
Test"
)
.
Input
(
"Input"
)
.
Input
(
"Filter"
)
.
Input
(
"Bias"
)
...
...
mace/ops/depthwise_conv_2d_benchmark.cc
浏览文件 @
eebd7868
...
...
@@ -25,7 +25,7 @@ static void DepthwiseConv2d(int iters,
mace
::
testing
::
StopTiming
();
OpsTestNet
net
;
OpDefBuilder
(
"DepthwiseConv2
d"
,
"DepthwiseConv2d
Test"
)
OpDefBuilder
(
"DepthwiseConv2
D"
,
"DepthwiseConv2D
Test"
)
.
Input
(
"Input"
)
.
Input
(
"Filter"
)
.
Input
(
"Bias"
)
...
...
mace/ops/pooling.h
浏览文件 @
eebd7868
...
...
@@ -28,6 +28,7 @@ class PoolingOp : public ConvPool2dOpBase<D, T> {
std
::
vector
<
index_t
>
output_shape
(
4
);
std
::
vector
<
int
>
paddings
(
2
);
std
::
vector
<
index_t
>
filter_shape
(
4
);
// TODO(chenghui): is it kind of a hack?
filter_shape
[
0
]
=
input
->
shape
()[
1
];
filter_shape
[
1
]
=
input
->
shape
()[
0
];
filter_shape
[
2
]
=
kernels_
[
0
];
...
...
mace/python/tools/tf_converter.py
浏览文件 @
eebd7868
...
...
@@ -23,6 +23,7 @@ def main(unused_args):
with
gfile
.
GFile
(
FLAGS
.
output
,
"wb"
)
as
f
:
f
.
write
(
output_graph_def
.
SerializeToString
())
with
gfile
.
GFile
(
FLAGS
.
output
+
'_txt'
,
"wb"
)
as
f
:
output_graph_def
.
ClearField
(
'tensors'
)
f
.
write
(
str
(
output_graph_def
))
...
...
mace/python/tools/tf_converter_lib.py
浏览文件 @
eebd7868
from
mace.proto
import
mace_pb2
import
tensorflow
as
tf
import
numpy
as
np
padding_mode
=
{
'VALID'
:
0
,
...
...
@@ -24,11 +25,20 @@ def convert_ops(unresolved_ops, net_def):
tf_tensor
=
first_op
.
outputs
[
0
].
eval
()
tensor
=
net_def
.
tensors
.
add
()
tensor
.
name
=
first_op
.
outputs
[
0
].
name
tensor
.
dims
.
extend
(
tf_tensor
.
shape
)
# TODO: support other type than float
tensor
.
data_type
=
mace_pb2
.
DT_FLOAT
shape
=
list
(
tf_tensor
.
shape
)
if
(
first_op
.
name
.
find
(
'pointwise_kernel'
)
!=
-
1
or
first_op
.
name
.
find
(
'depthwise_kernel'
)
!=
-
1
or
first_op
.
name
.
endswith
(
'weights'
)
or
first_op
.
name
.
endswith
(
'kernel'
))
\
and
first_op
.
outputs
[
0
].
consumers
()[
0
].
type
.
find
(
'Conv'
)
!=
-
1
:
tf_tensor
=
np
.
transpose
(
tf_tensor
,
axes
=
(
3
,
2
,
0
,
1
))
shape
=
[
shape
[
3
],
shape
[
2
],
shape
[
0
],
shape
[
1
]]
# print (tensor.name, shape)
tensor
.
dims
.
extend
(
shape
)
tensor
.
float_data
.
extend
(
tf_tensor
.
astype
(
float
).
flat
)
# net_def.tensors.extend([tensor])
elif
first_op
.
type
==
'Conv2D'
or
first_op
.
type
==
'DepthwiseConv2dNative'
:
op_def
=
net_def
.
op
.
add
()
op_def
.
name
=
first_op
.
name
...
...
@@ -43,10 +53,12 @@ def convert_ops(unresolved_ops, net_def):
padding_arg
.
i
=
padding_mode
[
first_op
.
get_attr
(
'padding'
)]
strides_arg
=
op_def
.
arg
.
add
()
strides_arg
.
name
=
'strides'
strides_arg
.
ints
.
extend
(
first_op
.
get_attr
(
'strides'
))
strides_arg
.
ints
.
extend
(
first_op
.
get_attr
(
'strides'
)
[
2
:]
)
data_format_arg
=
op_def
.
arg
.
add
()
data_format_arg
.
name
=
'data_format'
data_format_arg
.
s
=
first_op
.
get_attr
(
'data_format'
)
if
first_op
.
get_attr
(
'data_format'
)
!=
'NCHW'
:
raise
Exception
(
'only support NCHW now'
)
if
ops_count
>=
2
and
unresolved_ops
[
1
].
type
==
'BiasAdd'
:
bias_add_op
=
unresolved_ops
[
1
]
...
...
@@ -93,7 +105,7 @@ def convert_ops(unresolved_ops, net_def):
op_def
.
type
=
first_op
.
type
op_def
.
input
.
extend
([
input
.
name
for
input
in
first_op
.
inputs
])
op_def
.
output
.
extend
([
output
.
name
for
output
in
first_op
.
outputs
])
elif
first_op
.
type
==
'AvgPool'
:
elif
first_op
.
type
==
'AvgPool'
or
first_op
.
type
==
'MaxPool'
:
op_def
=
net_def
.
op
.
add
()
op_def
.
name
=
first_op
.
name
op_def
.
type
=
'Pooling'
...
...
@@ -107,12 +119,15 @@ def convert_ops(unresolved_ops, net_def):
padding_arg
.
i
=
padding_mode
[
first_op
.
get_attr
(
'padding'
)]
strides_arg
=
op_def
.
arg
.
add
()
strides_arg
.
name
=
'strides'
strides_arg
.
ints
.
extend
(
first_op
.
get_attr
(
'strides'
)[
1
:
-
1
])
strides_arg
.
name
=
'kernels'
strides_arg
.
ints
.
extend
(
first_op
.
get_attr
(
'ksize'
)[
1
:
-
1
])
strides_arg
.
ints
.
extend
(
first_op
.
get_attr
(
'strides'
)[
2
:])
kernels_arg
=
op_def
.
arg
.
add
()
kernels_arg
.
name
=
'kernels'
kernels_arg
.
ints
.
extend
(
first_op
.
get_attr
(
'ksize'
)[
2
:])
data_format_arg
=
op_def
.
arg
.
add
()
data_format_arg
.
name
=
'data_format'
data_format_arg
.
s
=
first_op
.
get_attr
(
'data_format'
)
if
first_op
.
get_attr
(
'data_format'
)
!=
'NCHW'
:
raise
Exception
(
'only support NCHW now'
)
else
:
raise
Exception
(
'Unknown Op: '
+
first_op
.
name
)
pass
...
...
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