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体验新版 GitCode,发现更多精彩内容 >>
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7b67f398
编写于
10月 19, 2021
作者:
W
wangxinxin08
提交者:
GitHub
10月 19, 2021
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差异文件
add nearest_interp_v2 trt plugin (#34126)
* add nearest_interp_v2 trt plugin
上级
8cc8e411
变更
9
隐藏空白更改
内联
并排
Showing
9 changed file
with
450 addition
and
38 deletion
+450
-38
paddle/fluid/inference/api/analysis_predictor.cc
paddle/fluid/inference/api/analysis_predictor.cc
+1
-0
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
+1
-0
paddle/fluid/inference/tensorrt/convert/nearest_interp_v2_op.cc
.../fluid/inference/tensorrt/convert/nearest_interp_v2_op.cc
+108
-0
paddle/fluid/inference/tensorrt/convert/test_nearest_interp_v2_op.cc
...d/inference/tensorrt/convert/test_nearest_interp_v2_op.cc
+54
-0
paddle/fluid/inference/tensorrt/op_teller.cc
paddle/fluid/inference/tensorrt/op_teller.cc
+29
-1
paddle/fluid/inference/tests/infer_ut/test_det_mv3_db.cc
paddle/fluid/inference/tests/infer_ut/test_det_mv3_db.cc
+4
-37
python/paddle/fluid/tests/unittests/ir/inference/CMakeLists.txt
.../paddle/fluid/tests/unittests/ir/inference/CMakeLists.txt
+1
-0
python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_nearest_interp_v2.py
...ttests/ir/inference/test_trt_convert_nearest_interp_v2.py
+101
-0
python/paddle/fluid/tests/unittests/ir/inference/test_trt_nearest_interp_v2_op.py
...s/unittests/ir/inference/test_trt_nearest_interp_v2_op.py
+151
-0
未找到文件。
paddle/fluid/inference/api/analysis_predictor.cc
浏览文件 @
7b67f398
...
@@ -1403,6 +1403,7 @@ USE_TRT_CONVERTER(roi_align);
...
@@ -1403,6 +1403,7 @@ USE_TRT_CONVERTER(roi_align);
USE_TRT_CONVERTER
(
affine_channel
);
USE_TRT_CONVERTER
(
affine_channel
);
USE_TRT_CONVERTER
(
multiclass_nms
);
USE_TRT_CONVERTER
(
multiclass_nms
);
USE_TRT_CONVERTER
(
nearest_interp
);
USE_TRT_CONVERTER
(
nearest_interp
);
USE_TRT_CONVERTER
(
nearest_interp_v2
);
USE_TRT_CONVERTER
(
reshape
);
USE_TRT_CONVERTER
(
reshape
);
USE_TRT_CONVERTER
(
reduce_sum
);
USE_TRT_CONVERTER
(
reduce_sum
);
USE_TRT_CONVERTER
(
gather_nd
);
USE_TRT_CONVERTER
(
gather_nd
);
...
...
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
浏览文件 @
7b67f398
...
@@ -18,6 +18,7 @@ nv_library(tensorrt_converter
...
@@ -18,6 +18,7 @@ nv_library(tensorrt_converter
tile_op.cc
tile_op.cc
conv3d_op.cc
conv3d_op.cc
mish_op.cc
mish_op.cc
nearest_interp_v2_op.cc
DEPS tensorrt_engine tensorrt_plugin operator scope framework_proto op_registry
)
DEPS tensorrt_engine tensorrt_plugin operator scope framework_proto op_registry
)
nv_test
(
test_op_converter SRCS test_op_converter.cc DEPS
nv_test
(
test_op_converter SRCS test_op_converter.cc DEPS
...
...
paddle/fluid/inference/tensorrt/convert/nearest_interp_v2_op.cc
0 → 100644
浏览文件 @
7b67f398
/* Copyright (c) 2021 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. */
#include "paddle/fluid/framework/data_layout.h"
#include "paddle/fluid/inference/tensorrt/convert/op_converter.h"
namespace
paddle
{
namespace
framework
{
class
Scope
;
namespace
proto
{
class
OpDesc
;
}
// namespace proto
}
// namespace framework
}
// namespace paddle
namespace
paddle
{
namespace
inference
{
namespace
tensorrt
{
class
NearestInterpolateV2OpConverter
:
public
OpConverter
{
public:
void
operator
()(
const
framework
::
proto
::
OpDesc
&
op
,
const
framework
::
Scope
&
scope
,
bool
test_mode
)
override
{
VLOG
(
3
)
<<
"convert a fluid nearest_interp_v2 op"
;
framework
::
OpDesc
op_desc
(
op
,
nullptr
);
std
::
string
input_name
=
op_desc
.
Input
(
"X"
).
front
();
std
::
string
output_name
=
op_desc
.
Output
(
"Out"
).
front
();
auto
input
=
engine_
->
GetITensor
(
input_name
);
auto
data_layout
=
framework
::
StringToDataLayout
(
BOOST_GET_CONST
(
std
::
string
,
op_desc
.
GetAttr
(
"data_layout"
)));
auto
interp_method
=
BOOST_GET_CONST
(
std
::
string
,
op_desc
.
GetAttr
(
"interp_method"
));
bool
align_corners
=
BOOST_GET_CONST
(
bool
,
op_desc
.
GetAttr
(
"align_corners"
));
auto
input_names
=
op_desc
.
Input
(
"X"
);
auto
scale
=
BOOST_GET_CONST
(
std
::
vector
<
float
>
,
op_desc
.
GetAttr
(
"scale"
));
auto
out_h
=
BOOST_GET_CONST
(
int
,
op_desc
.
GetAttr
(
"out_h"
));
auto
out_w
=
BOOST_GET_CONST
(
int
,
op_desc
.
GetAttr
(
"out_w"
));
auto
layer
=
TRT_ENGINE_ADD_LAYER
(
engine_
,
Resize
,
*
input
);
layer
->
setAlignCorners
(
align_corners
);
auto
in_dim
=
input
->
getDimensions
();
float
scale_h
=
1.
f
;
float
scale_w
=
1.
f
;
std
::
vector
<
float
>
scales
;
if
(
out_h
>
0
&&
out_w
>
0
)
{
// axis are different in static/dynamic mode
bool
with_dynamic
=
engine_
->
with_dynamic_shape
();
int
h_axis
=
(
data_layout
==
framework
::
DataLayout
::
kNCHW
)
+
with_dynamic
;
int
w_axis
=
(
data_layout
==
framework
::
DataLayout
::
kNCHW
)
+
1
+
with_dynamic
;
scale_h
=
static_cast
<
float
>
(
out_h
)
/
static_cast
<
float
>
(
in_dim
.
d
[
h_axis
]);
scale_w
=
static_cast
<
float
>
(
out_w
)
/
static_cast
<
float
>
(
in_dim
.
d
[
w_axis
]);
}
else
{
scale_h
=
scale
[
0
];
scale_w
=
scale
[
1
];
}
if
(
engine_
->
with_dynamic_shape
())
{
scales
.
push_back
(
1.
f
);
}
if
(
data_layout
==
framework
::
DataLayout
::
kNCHW
)
{
scales
.
push_back
(
1.
f
);
scales
.
push_back
(
scale_h
);
scales
.
push_back
(
scale_w
);
}
else
if
(
data_layout
==
framework
::
DataLayout
::
kNHWC
)
{
// NHWC
scales
.
push_back
(
scale_h
);
scales
.
push_back
(
scale_w
);
scales
.
push_back
(
1.
f
);
}
else
{
PADDLE_THROW
(
platform
::
errors
::
InvalidArgument
(
"Data layout must be NCHW or NHWC."
));
}
layer
->
setScales
(
scales
.
data
(),
scales
.
size
());
RreplenishLayerAndOutput
(
layer
,
"nearest_interp_v2"
,
{
output_name
},
test_mode
);
}
};
}
// namespace tensorrt
}
// namespace inference
}
// namespace paddle
REGISTER_TRT_OP_CONVERTER
(
nearest_interp_v2
,
NearestInterpolateV2OpConverter
);
paddle/fluid/inference/tensorrt/convert/test_nearest_interp_v2_op.cc
0 → 100644
浏览文件 @
7b67f398
/* Copyright (c) 2021 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. */
#include <gtest/gtest.h>
#include "paddle/fluid/inference/tensorrt/convert/op_converter.h"
#include "paddle/fluid/inference/tensorrt/convert/ut_helper.h"
namespace
paddle
{
namespace
inference
{
namespace
tensorrt
{
TEST
(
nearest_interp_v2_op
,
test_swish
)
{
std
::
unordered_set
<
std
::
string
>
parameters
;
framework
::
Scope
scope
;
TRTConvertValidation
validator
(
10
,
parameters
,
scope
,
1000
);
validator
.
DeclInputVar
(
"interp-X"
,
nvinfer1
::
Dims3
(
3
,
32
,
32
));
validator
.
DeclOutputVar
(
"interp-Out"
,
nvinfer1
::
Dims3
(
3
,
64
,
64
));
// Prepare Op description
framework
::
OpDesc
desc
;
desc
.
SetType
(
"nearest_interp_v2"
);
desc
.
SetInput
(
"X"
,
{
"interp-X"
});
desc
.
SetOutput
(
"Out"
,
{
"interp-Out"
});
std
::
vector
<
float
>
scale
({
2.
f
,
2.
f
});
desc
.
SetAttr
(
"data_layout"
,
"NCHW"
);
desc
.
SetAttr
(
"interp_method"
,
"nearest"
);
desc
.
SetAttr
(
"align_corners"
,
false
);
desc
.
SetAttr
(
"scale"
,
scale
);
desc
.
SetAttr
(
"out_h"
,
0
);
desc
.
SetAttr
(
"out_w"
,
0
);
validator
.
SetOp
(
*
desc
.
Proto
());
validator
.
Execute
(
1
);
}
}
// namespace tensorrt
}
// namespace inference
}
// namespace paddle
USE_OP
(
nearest_interp_v2
);
paddle/fluid/inference/tensorrt/op_teller.cc
浏览文件 @
7b67f398
...
@@ -141,7 +141,8 @@ struct SimpleOpTypeSetTeller : public Teller {
...
@@ -141,7 +141,8 @@ struct SimpleOpTypeSetTeller : public Teller {
"reduce_mean"
,
"reduce_mean"
,
"conv3d"
,
"conv3d"
,
"conv3d_transpose"
,
"conv3d_transpose"
,
"mish"
};
"mish"
,
"nearest_interp_v2"
};
};
};
bool
OpTeller
::
Tell
(
const
framework
::
ir
::
Node
*
node
,
bool
use_no_calib_int8
,
bool
OpTeller
::
Tell
(
const
framework
::
ir
::
Node
*
node
,
bool
use_no_calib_int8
,
...
@@ -599,6 +600,33 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
...
@@ -599,6 +600,33 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
}
}
}
}
if
(
op_type
==
"nearest_interp_v2"
)
{
std
::
vector
<
std
::
string
>
attrs
{
"data_layout"
,
"interp_method"
,
"align_corners"
,
"scale"
,
"out_h"
,
"out_w"
};
for
(
auto
const
attr
:
attrs
)
{
if
(
!
desc
.
HasAttr
(
attr
))
return
false
;
}
auto
data_layout
=
framework
::
StringToDataLayout
(
BOOST_GET_CONST
(
std
::
string
,
desc
.
GetAttr
(
"data_layout"
)));
if
(
data_layout
!=
framework
::
DataLayout
::
kNCHW
&&
data_layout
!=
framework
::
DataLayout
::
kNHWC
)
return
false
;
auto
interp_method
=
BOOST_GET_CONST
(
std
::
string
,
desc
.
GetAttr
(
"interp_method"
));
if
(
interp_method
!=
"nearest"
)
return
false
;
auto
scale
=
BOOST_GET_CONST
(
std
::
vector
<
float
>
,
desc
.
GetAttr
(
"scale"
));
auto
out_h
=
BOOST_GET_CONST
(
int
,
desc
.
GetAttr
(
"out_h"
));
auto
out_w
=
BOOST_GET_CONST
(
int
,
desc
.
GetAttr
(
"out_w"
));
if
(
!
(
out_h
>
0
&&
out_w
>
0
))
{
if
(
scale
[
0
]
<=
0.
f
||
scale
[
1
]
<=
0.
f
)
{
VLOG
(
3
)
<<
"scale factor must be greater than 0 if out_h or out_w is "
"not set."
;
return
false
;
}
}
}
if
(
op_type
==
"roi_align"
)
{
if
(
op_type
==
"roi_align"
)
{
if
(
!
with_dynamic_shape
)
return
false
;
if
(
!
with_dynamic_shape
)
return
false
;
...
...
paddle/fluid/inference/tests/infer_ut/test_det_mv3_db.cc
浏览文件 @
7b67f398
...
@@ -35,44 +35,11 @@ paddle::test::Record PrepareInput(int batch_size, int image_shape = 640) {
...
@@ -35,44 +35,11 @@ paddle::test::Record PrepareInput(int batch_size, int image_shape = 640) {
void
PrepareDynamicShape
(
paddle_infer
::
Config
*
config
,
int
max_batch_size
=
4
)
{
void
PrepareDynamicShape
(
paddle_infer
::
Config
*
config
,
int
max_batch_size
=
4
)
{
// set dynamic shape range
// set dynamic shape range
std
::
map
<
std
::
string
,
std
::
vector
<
int
>>
min_input_shape
=
{
std
::
map
<
std
::
string
,
std
::
vector
<
int
>>
min_input_shape
=
{
{
"x"
,
{
1
,
3
,
50
,
50
}},
{
"x"
,
{
1
,
3
,
50
,
50
}}};
{
"conv2d_92.tmp_0"
,
{
1
,
120
,
20
,
20
}},
{
"conv2d_91.tmp_0"
,
{
1
,
24
,
10
,
10
}},
{
"conv2d_59.tmp_0"
,
{
1
,
96
,
20
,
20
}},
{
"nearest_interp_v2_1.tmp_0"
,
{
1
,
256
,
10
,
10
}},
{
"nearest_interp_v2_2.tmp_0"
,
{
1
,
256
,
20
,
20
}},
{
"conv2d_124.tmp_0"
,
{
1
,
256
,
20
,
20
}},
{
"nearest_interp_v2_3.tmp_0"
,
{
1
,
64
,
20
,
20
}},
{
"nearest_interp_v2_4.tmp_0"
,
{
1
,
64
,
20
,
20
}},
{
"nearest_interp_v2_5.tmp_0"
,
{
1
,
64
,
20
,
20
}},
{
"elementwise_add_7"
,
{
1
,
56
,
2
,
2
}},
{
"nearest_interp_v2_0.tmp_0"
,
{
1
,
256
,
2
,
2
}}};
std
::
map
<
std
::
string
,
std
::
vector
<
int
>>
max_input_shape
=
{
std
::
map
<
std
::
string
,
std
::
vector
<
int
>>
max_input_shape
=
{
{
"x"
,
{
max_batch_size
,
3
,
2000
,
2000
}},
{
"x"
,
{
max_batch_size
,
3
,
1600
,
1600
}}};
{
"conv2d_92.tmp_0"
,
{
max_batch_size
,
120
,
400
,
400
}},
{
"conv2d_91.tmp_0"
,
{
max_batch_size
,
24
,
200
,
200
}},
{
"conv2d_59.tmp_0"
,
{
max_batch_size
,
96
,
400
,
400
}},
{
"nearest_interp_v2_1.tmp_0"
,
{
max_batch_size
,
256
,
200
,
200
}},
{
"nearest_interp_v2_2.tmp_0"
,
{
max_batch_size
,
256
,
400
,
400
}},
{
"conv2d_124.tmp_0"
,
{
max_batch_size
,
256
,
400
,
400
}},
{
"nearest_interp_v2_3.tmp_0"
,
{
max_batch_size
,
64
,
400
,
400
}},
{
"nearest_interp_v2_4.tmp_0"
,
{
max_batch_size
,
64
,
400
,
400
}},
{
"nearest_interp_v2_5.tmp_0"
,
{
max_batch_size
,
64
,
400
,
400
}},
{
"elementwise_add_7"
,
{
max_batch_size
,
56
,
400
,
400
}},
{
"nearest_interp_v2_0.tmp_0"
,
{
max_batch_size
,
256
,
400
,
400
}}};
std
::
map
<
std
::
string
,
std
::
vector
<
int
>>
opt_input_shape
=
{
std
::
map
<
std
::
string
,
std
::
vector
<
int
>>
opt_input_shape
=
{
{
"x"
,
{
1
,
3
,
640
,
640
}},
{
"x"
,
{
1
,
3
,
640
,
640
}}};
{
"conv2d_92.tmp_0"
,
{
1
,
120
,
160
,
160
}},
{
"conv2d_91.tmp_0"
,
{
1
,
24
,
80
,
80
}},
{
"conv2d_59.tmp_0"
,
{
1
,
96
,
160
,
160
}},
{
"nearest_interp_v2_1.tmp_0"
,
{
1
,
256
,
80
,
80
}},
{
"nearest_interp_v2_2.tmp_0"
,
{
1
,
256
,
160
,
160
}},
{
"conv2d_124.tmp_0"
,
{
1
,
256
,
160
,
160
}},
{
"nearest_interp_v2_3.tmp_0"
,
{
1
,
64
,
160
,
160
}},
{
"nearest_interp_v2_4.tmp_0"
,
{
1
,
64
,
160
,
160
}},
{
"nearest_interp_v2_5.tmp_0"
,
{
1
,
64
,
160
,
160
}},
{
"elementwise_add_7"
,
{
1
,
56
,
40
,
40
}},
{
"nearest_interp_v2_0.tmp_0"
,
{
1
,
256
,
40
,
40
}}};
config
->
SetTRTDynamicShapeInfo
(
min_input_shape
,
max_input_shape
,
config
->
SetTRTDynamicShapeInfo
(
min_input_shape
,
max_input_shape
,
opt_input_shape
);
opt_input_shape
);
}
}
...
@@ -123,7 +90,7 @@ TEST(tensorrt_tester_det_mv3_db, multi_thread2_trt_fp32_dynamic_shape_bz2) {
...
@@ -123,7 +90,7 @@ TEST(tensorrt_tester_det_mv3_db, multi_thread2_trt_fp32_dynamic_shape_bz2) {
FLAGS_modeldir
+
"/inference.pdiparams"
);
FLAGS_modeldir
+
"/inference.pdiparams"
);
config
.
EnableUseGpu
(
100
,
0
);
config
.
EnableUseGpu
(
100
,
0
);
config
.
EnableTensorRtEngine
(
config
.
EnableTensorRtEngine
(
1
<<
20
,
2
,
3
,
paddle_infer
::
PrecisionType
::
kFloat32
,
tru
e
,
false
);
1
<<
20
,
2
,
3
,
paddle_infer
::
PrecisionType
::
kFloat32
,
fals
e
,
false
);
PrepareDynamicShape
(
&
config
,
4
);
PrepareDynamicShape
(
&
config
,
4
);
// get groudtruth by disbale ir
// get groudtruth by disbale ir
paddle_infer
::
services
::
PredictorPool
pred_pool_no_ir
(
config_no_ir
,
1
);
paddle_infer
::
services
::
PredictorPool
pred_pool_no_ir
(
config_no_ir
,
1
);
...
...
python/paddle/fluid/tests/unittests/ir/inference/CMakeLists.txt
浏览文件 @
7b67f398
...
@@ -68,4 +68,5 @@ set_tests_properties(test_trt_conv_quant_dequant_pass PROPERTIES TIMEOUT 100)
...
@@ -68,4 +68,5 @@ set_tests_properties(test_trt_conv_quant_dequant_pass PROPERTIES TIMEOUT 100)
set_tests_properties
(
test_trt_matmul_quant_dequant PROPERTIES TIMEOUT 100
)
set_tests_properties
(
test_trt_matmul_quant_dequant PROPERTIES TIMEOUT 100
)
set_tests_properties
(
test_trt_conv3d_op PROPERTIES TIMEOUT 60
)
set_tests_properties
(
test_trt_conv3d_op PROPERTIES TIMEOUT 60
)
set_tests_properties
(
test_trt_conv3d_transpose_op PROPERTIES TIMEOUT 60
)
set_tests_properties
(
test_trt_conv3d_transpose_op PROPERTIES TIMEOUT 60
)
set_tests_properties
(
test_trt_nearest_interp_v2_op PROPERTIES TIMEOUT 30
)
endif
()
endif
()
python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_nearest_interp_v2.py
0 → 100644
浏览文件 @
7b67f398
# Copyright (c) 2021 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.
from
trt_layer_auto_scan_test
import
TrtLayerAutoScanTest
,
SkipReasons
from
program_config
import
TensorConfig
,
ProgramConfig
import
numpy
as
np
import
paddle.inference
as
paddle_infer
from
functools
import
partial
from
typing
import
Optional
,
List
,
Callable
,
Dict
,
Any
,
Set
class
TrtConvertNearestInterpV2Test
(
TrtLayerAutoScanTest
):
def
is_program_valid
(
self
,
program_config
:
ProgramConfig
)
->
bool
:
return
True
def
sample_program_configs
(
self
):
def
generate_input
():
return
np
.
ones
([
1
,
3
,
32
,
32
]).
astype
(
np
.
float32
)
ops_config
=
[{
"op_type"
:
"nearest_interp_v2"
,
"op_inputs"
:
{
"X"
:
[
"input_data"
]
},
"op_outputs"
:
{
"Out"
:
[
"interp_output_data"
]
},
"op_attrs"
:
{
"data_layout"
:
"NCHW"
,
"interp_method"
:
"nearest"
,
"align_corners"
:
False
,
"scale"
:
[
2.
,
2.
],
"out_h"
:
0
,
"out_w"
:
0
}
}]
ops
=
self
.
generate_op_config
(
ops_config
)
program_config
=
ProgramConfig
(
ops
=
ops
,
weights
=
{},
inputs
=
{
"input_data"
:
TensorConfig
(
data_gen
=
generate_input
)},
outputs
=
[
"interp_output_data"
])
yield
program_config
def
sample_predictor_configs
(
self
,
program_config
)
->
(
paddle_infer
.
Config
,
List
[
int
],
float
):
def
generate_dynamic_shape
(
attrs
):
self
.
dynamic_shape
.
min_input_shape
=
{
"input_data"
:
[
1
,
3
,
32
,
32
]}
self
.
dynamic_shape
.
max_input_shape
=
{
"input_data"
:
[
4
,
3
,
64
,
64
]}
self
.
dynamic_shape
.
opt_input_shape
=
{
"input_data"
:
[
1
,
3
,
64
,
64
]}
def
clear_dynamic_shape
():
self
.
dynamic_shape
.
min_input_shape
=
{}
self
.
dynamic_shape
.
max_input_shape
=
{}
self
.
dynamic_shape
.
opt_input_shape
=
{}
def
generate_trt_nodes_num
(
attrs
,
dynamic_shape
):
return
1
,
2
attrs
=
[
program_config
.
ops
[
i
].
attrs
for
i
in
range
(
len
(
program_config
.
ops
))
]
# for static_shape
clear_dynamic_shape
()
self
.
trt_param
.
precision
=
paddle_infer
.
PrecisionType
.
Float32
yield
self
.
create_inference_config
(),
generate_trt_nodes_num
(
attrs
,
False
),
1e-5
self
.
trt_param
.
precision
=
paddle_infer
.
PrecisionType
.
Half
yield
self
.
create_inference_config
(),
generate_trt_nodes_num
(
attrs
,
False
),
1e-2
# for dynamic_shape
generate_dynamic_shape
(
attrs
)
self
.
trt_param
.
precision
=
paddle_infer
.
PrecisionType
.
Float32
yield
self
.
create_inference_config
(),
generate_trt_nodes_num
(
attrs
,
True
),
1e-5
self
.
trt_param
.
precision
=
paddle_infer
.
PrecisionType
.
Half
yield
self
.
create_inference_config
(),
generate_trt_nodes_num
(
attrs
,
True
),
1e-2
def
test
(
self
):
self
.
run_test
()
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/ir/inference/test_trt_nearest_interp_v2_op.py
0 → 100644
浏览文件 @
7b67f398
# Copyright (c) 2021 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.
from
__future__
import
print_function
import
unittest
import
numpy
as
np
from
inference_pass_test
import
InferencePassTest
import
paddle.fluid.core
as
core
from
paddle
import
fluid
import
paddle.nn.functional
as
F
from
paddle.fluid.core
import
PassVersionChecker
from
paddle.fluid.core
import
AnalysisConfig
class
TRTNearestInterpTest
(
InferencePassTest
):
def
setUp
(
self
):
self
.
set_params
()
with
fluid
.
program_guard
(
self
.
main_program
,
self
.
startup_program
):
if
self
.
data_layout
==
'NCHW'
:
shape
=
[
-
1
,
self
.
channels
,
self
.
origin_shape
[
0
],
self
.
origin_shape
[
1
]
]
else
:
shape
=
[
-
1
,
self
.
origin_shape
[
0
],
self
.
origin_shape
[
1
],
self
.
channels
]
data
=
fluid
.
data
(
name
=
'data'
,
shape
=
shape
,
dtype
=
'float32'
)
resize_out
=
self
.
append_nearest_interp
(
data
)
out
=
fluid
.
layers
.
batch_norm
(
resize_out
,
is_test
=
True
)
if
self
.
data_layout
==
'NCHW'
:
shape
=
[
self
.
bs
,
self
.
channels
,
self
.
origin_shape
[
0
],
self
.
origin_shape
[
1
]
]
else
:
shape
=
[
self
.
bs
,
self
.
origin_shape
[
0
],
self
.
origin_shape
[
1
],
self
.
channels
]
self
.
feeds
=
{
'data'
:
np
.
random
.
random
(
shape
).
astype
(
'float32'
),
}
self
.
enable_trt
=
True
self
.
trt_parameters
=
TRTNearestInterpTest
.
TensorRTParam
(
1
<<
30
,
self
.
bs
,
1
,
AnalysisConfig
.
Precision
.
Float32
,
False
,
False
)
self
.
fetch_list
=
[
out
]
def
set_params
(
self
):
self
.
bs
=
4
self
.
scale
=
-
1
self
.
channels
=
3
self
.
origin_shape
=
(
32
,
32
)
# HW
self
.
resize_shape
=
(
64
,
64
)
# HW
self
.
align_corners
=
False
self
.
data_layout
=
'NCHW'
def
append_nearest_interp
(
self
,
data
):
if
self
.
scale
>
0.
:
return
F
.
interpolate
(
data
,
scale_factor
=
self
.
scale
,
align_corners
=
self
.
align_corners
,
mode
=
'nearest'
,
data_format
=
self
.
data_layout
)
return
F
.
interpolate
(
data
,
size
=
self
.
resize_shape
,
align_corners
=
self
.
align_corners
,
mode
=
'nearest'
,
data_format
=
self
.
data_layout
)
def
test_check_output
(
self
):
if
core
.
is_compiled_with_cuda
():
use_gpu
=
True
self
.
check_output_with_option
(
use_gpu
,
flatten
=
True
)
self
.
assertTrue
(
PassVersionChecker
.
IsCompatible
(
'tensorrt_subgraph_pass'
))
class
TRTNearestInterpTest1
(
TRTNearestInterpTest
):
def
set_params
(
self
):
self
.
bs
=
4
self
.
scale
=
2.
self
.
channels
=
3
self
.
origin_shape
=
(
32
,
32
)
# HW
self
.
resize_shape
=
(
64
,
64
)
# HW
self
.
align_corners
=
False
self
.
data_layout
=
'NCHW'
class
TRTNearestInterpTest2
(
TRTNearestInterpTest
):
def
set_params
(
self
):
self
.
bs
=
4
self
.
scale
=
-
1
self
.
channels
=
3
self
.
origin_shape
=
(
32
,
32
)
# HW
self
.
resize_shape
=
(
47
,
48
)
# HW
self
.
align_corners
=
False
self
.
data_layout
=
'NCHW'
class
TRTNearestInterpTest3
(
TRTNearestInterpTest
):
def
set_params
(
self
):
self
.
bs
=
4
self
.
scale
=
-
1
self
.
channels
=
3
self
.
origin_shape
=
(
32
,
32
)
# HW
self
.
resize_shape
=
(
64
,
64
)
# HW
self
.
align_corners
=
False
self
.
data_layout
=
'NHWC'
class
TRTNearestInterpTest4
(
TRTNearestInterpTest
):
def
set_params
(
self
):
self
.
bs
=
4
self
.
scale
=
2.
self
.
channels
=
3
self
.
origin_shape
=
(
32
,
32
)
# HW
self
.
resize_shape
=
(
64
,
64
)
# HW
self
.
align_corners
=
False
self
.
data_layout
=
'NHWC'
class
TRTNearestInterpTest5
(
TRTNearestInterpTest
):
def
set_params
(
self
):
self
.
bs
=
4
self
.
scale
=
-
1
self
.
channels
=
3
self
.
origin_shape
=
(
32
,
32
)
# HW
self
.
resize_shape
=
(
47
,
48
)
# HW
self
.
align_corners
=
False
self
.
data_layout
=
'NHWC'
if
__name__
==
"__main__"
:
unittest
.
main
()
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