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a76b77a5
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a76b77a5
编写于
11月 12, 2021
作者:
W
Wangzheee
提交者:
GitHub
11月 12, 2021
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电子邮件补丁
差异文件
add_fc_convert_layers_name (#37157)
上级
f584d378
变更
1
显示空白变更内容
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并排
Showing
1 changed file
with
23 addition
and
4 deletion
+23
-4
paddle/fluid/inference/tensorrt/convert/fc_op.cc
paddle/fluid/inference/tensorrt/convert/fc_op.cc
+23
-4
未找到文件。
paddle/fluid/inference/tensorrt/convert/fc_op.cc
浏览文件 @
a76b77a5
...
...
@@ -34,8 +34,8 @@ namespace tensorrt {
class
FcOpConverter
:
public
OpConverter
{
public:
nvinfer1
::
ILayer
*
reshape_before_fc
(
nvinfer1
::
ITensor
*
before_fc
,
nvinfer1
::
Dims
x_dim
,
int
x_num_col_dims
)
{
nvinfer1
::
Dims
x_dim
,
int
x_num_col_dims
,
std
::
string
output_name
)
{
// add shuffle before fc
nvinfer1
::
Dims
reshape_before_fc_dim
;
reshape_before_fc_dim
.
nbDims
=
x_num_col_dims
+
3
;
...
...
@@ -57,6 +57,9 @@ class FcOpConverter : public OpConverter {
auto
*
reshape_before_fc_layer
=
TRT_ENGINE_ADD_LAYER
(
engine_
,
Shuffle
,
*
before_fc
);
reshape_before_fc_layer
->
setReshapeDimensions
(
reshape_before_fc_dim
);
reshape_before_fc_layer
->
setName
(
(
"fc_op_reshape_before_fc: Shuffle (Output: "
+
output_name
+
")"
)
.
c_str
());
return
reshape_before_fc_layer
;
}
...
...
@@ -164,17 +167,25 @@ class FcOpConverter : public OpConverter {
auto
*
fc_layer_int8
=
TRT_ENGINE_ADD_LAYER
(
engine_
,
Convolution
,
*
inputs
,
n_output
,
nv_ksize
,
weight
.
get
(),
bias
.
get
());
fc_layer_int8
->
setName
(
(
"fc_op_int8_conv1x1: Convolution (Output: "
+
output_name
+
")"
)
.
c_str
());
engine_
->
SetTensorDynamicRange
(
fc_layer_int8
->
getOutput
(
0
),
out_scale
);
auto
*
fc_after_reshape_int8
=
reshape_after_fc
(
fc_layer_int8
->
getOutput
(
0
),
x_dim
,
x_num_col_dims
);
if
(
activation_type
==
"relu"
)
{
fc_after_reshape_int8
->
setName
(
(
"fc_op_int8_reshape_after_fc: Shuffle (Output: "
+
output_name
+
")"
)
.
c_str
());
nvinfer1
::
IActivationLayer
*
relu_layer_int8
=
TRT_ENGINE_ADD_LAYER
(
engine_
,
Activation
,
*
(
fc_after_reshape_int8
->
getOutput
(
0
)),
nvinfer1
::
ActivationType
::
kRELU
);
RreplenishLayerAndOutput
(
relu_layer_int8
,
"relu_after_fc_shuffle"
,
{
output_name
},
test_mode
);
}
else
{
RreplenishLayerAndOutput
(
fc_after_reshape_int8
,
"shuffle_after_fc"
,
RreplenishLayerAndOutput
(
fc_after_reshape_int8
,
"fc_op_int8_reshape_after_fc: Shuffle"
,
{
output_name
},
test_mode
);
}
}
else
{
...
...
@@ -182,9 +193,16 @@ class FcOpConverter : public OpConverter {
auto
*
fc_layer_float
=
TRT_ENGINE_ADD_LAYER
(
engine_
,
FullyConnected
,
*
inputs
,
n_output
,
weight
.
get
(),
bias
.
get
());
fc_layer_float
->
setName
(
(
"fc_op_float: FullyConnected (Output: "
+
output_name
+
")"
)
.
c_str
());
auto
*
fc_after_reshape_float
=
reshape_after_fc
(
fc_layer_float
->
getOutput
(
0
),
x_dim
,
x_num_col_dims
);
if
(
activation_type
==
"relu"
)
{
fc_after_reshape_float
->
setName
(
(
"fc_op_float_reshape_after_fc: Shuffle (Output: "
+
output_name
+
")"
)
.
c_str
());
nvinfer1
::
IActivationLayer
*
relu_layer_float
=
TRT_ENGINE_ADD_LAYER
(
engine_
,
Activation
,
*
(
fc_after_reshape_float
->
getOutput
(
0
)),
nvinfer1
::
ActivationType
::
kRELU
);
...
...
@@ -234,7 +252,8 @@ class FcOpConverter : public OpConverter {
"converter expects x_dim.nbDims > x_num_col_dims, but "
"x_dim.nbDims : %d, x_num_col_dims : %d."
,
x_dim
.
nbDims
,
x_num_col_dims
));
auto
*
reshape_before_fc_layer
=
reshape_before_fc
(
X
,
x_dim
,
x_num_col_dims
);
auto
*
reshape_before_fc_layer
=
reshape_before_fc
(
X
,
x_dim
,
x_num_col_dims
,
output_name
);
auto
*
reshape_itensor
=
reshape_before_fc_layer
->
getOutput
(
0
);
if
(
enable_int8
)
{
engine_
->
SetTensorDynamicRange
(
reshape_itensor
,
in_scale
);
...
...
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