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体验新版 GitCode,发现更多精彩内容 >>
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1dbbe20e
编写于
6月 29, 2022
作者:
C
ccrrong
提交者:
GitHub
6月 29, 2022
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电子邮件补丁
差异文件
add equal trt converter (#43461)
* add comparisons trt converter
上级
6132476d
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
283 addition
and
0 deletion
+283
-0
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/equal_op.cc
paddle/fluid/inference/tensorrt/convert/equal_op.cc
+94
-0
paddle/fluid/inference/tensorrt/op_teller.cc
paddle/fluid/inference/tensorrt/op_teller.cc
+21
-0
python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_equal.py
...id/tests/unittests/ir/inference/test_trt_convert_equal.py
+166
-0
未找到文件。
paddle/fluid/inference/api/analysis_predictor.cc
浏览文件 @
1dbbe20e
...
...
@@ -2078,6 +2078,7 @@ USE_TRT_CONVERTER(transformer_input_convert)
USE_TRT_CONVERTER
(
cast
)
USE_TRT_CONVERTER
(
recover_padding
)
USE_TRT_CONVERTER
(
remove_padding
)
USE_TRT_CONVERTER
(
equal
);
USE_TRT_CONVERTER
(
top_k
)
USE_TRT_CONVERTER
(
top_k_v2
)
USE_TRT_CONVERTER
(
squeeze2
)
...
...
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
浏览文件 @
1dbbe20e
...
...
@@ -62,6 +62,7 @@ list(
transformer_input_convert_op.cc
cast_op.cc
remove_padding_op.cc
equal_op.cc
recover_padding_op.cc
preln_residual_bias.cc
c_allreduce_op.cc
...
...
paddle/fluid/inference/tensorrt/convert/equal_op.cc
0 → 100644
浏览文件 @
1dbbe20e
/* Copyright (c) 2022 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/inference/tensorrt/convert/op_converter.h"
#include "paddle/fluid/inference/tensorrt/plugin/elementwise_op_plugin.h"
namespace
paddle
{
namespace
framework
{
class
Scope
;
namespace
proto
{
class
OpDesc
;
}
// namespace proto
}
// namespace framework
}
// namespace paddle
namespace
paddle
{
namespace
inference
{
namespace
tensorrt
{
class
EqualOpConverter
:
public
OpConverter
{
public:
EqualOpConverter
()
{}
void
operator
()(
const
framework
::
proto
::
OpDesc
&
op
,
const
framework
::
Scope
&
scope
,
bool
test_mode
)
override
{
#if IS_TRT_VERSION_GE(8000)
framework
::
OpDesc
op_desc
(
op
,
nullptr
);
nvinfer1
::
ILayer
*
layer
=
nullptr
;
auto
*
X
=
engine_
->
GetITensor
(
op_desc
.
Input
(
"X"
).
front
());
auto
*
Y
=
engine_
->
GetITensor
(
op_desc
.
Input
(
"Y"
).
front
());
nvinfer1
::
Dims
dims_x
=
X
->
getDimensions
();
nvinfer1
::
Dims
dims_y
=
Y
->
getDimensions
();
int
axis
=
BOOST_GET_CONST
(
int
,
op_desc
.
GetAttr
(
"axis"
));
if
(
axis
<
0
)
{
axis
=
std
::
abs
(
dims_x
.
nbDims
-
dims_y
.
nbDims
);
}
auto
output_name
=
op_desc
.
Output
(
"Out"
)[
0
];
nvinfer1
::
IShuffleLayer
*
expand_layer
=
nullptr
;
if
(
dims_x
.
nbDims
>
dims_y
.
nbDims
)
{
nvinfer1
::
Dims
expand_shape
;
expand_shape
.
nbDims
=
dims_x
.
nbDims
;
for
(
int
i
=
0
;
i
<
expand_shape
.
nbDims
;
i
++
)
{
expand_shape
.
d
[
i
]
=
1
;
}
for
(
int
i
=
0
;
i
<
dims_y
.
nbDims
;
i
++
)
{
expand_shape
.
d
[
i
+
axis
]
=
dims_y
.
d
[
i
];
}
expand_layer
=
TRT_ENGINE_ADD_LAYER
(
engine_
,
Shuffle
,
*
Y
);
expand_layer
->
setReshapeDimensions
(
expand_shape
);
Y
=
expand_layer
->
getOutput
(
0
);
}
else
if
(
dims_x
.
nbDims
<
dims_y
.
nbDims
)
{
nvinfer1
::
Dims
expand_shape
;
expand_shape
.
nbDims
=
dims_y
.
nbDims
;
for
(
int
i
=
0
;
i
<
expand_shape
.
nbDims
;
i
++
)
{
expand_shape
.
d
[
i
]
=
1
;
}
for
(
int
i
=
0
;
i
<
dims_x
.
nbDims
;
i
++
)
{
expand_shape
.
d
[
i
+
axis
]
=
dims_x
.
d
[
i
];
}
expand_layer
=
TRT_ENGINE_ADD_LAYER
(
engine_
,
Shuffle
,
*
X
);
expand_layer
->
setReshapeDimensions
(
expand_shape
);
X
=
expand_layer
->
getOutput
(
0
);
}
layer
=
TRT_ENGINE_ADD_LAYER
(
engine_
,
ElementWise
,
*
X
,
*
Y
,
nvinfer1
::
ElementWiseOperation
::
kEQUAL
);
RreplenishLayerAndOutput
(
layer
,
"equal"
,
{
output_name
},
test_mode
);
#else
PADDLE_THROW
(
platform
::
errors
::
Fatal
(
"ElementWise Equal Operation is only supported "
"on TRT 8 or higher version."
));
#endif
}
};
}
// namespace tensorrt
}
// namespace inference
}
// namespace paddle
REGISTER_TRT_OP_CONVERTER
(
equal
,
EqualOpConverter
);
paddle/fluid/inference/tensorrt/op_teller.cc
浏览文件 @
1dbbe20e
...
...
@@ -110,6 +110,7 @@ struct SimpleOpTypeSetTeller : public Teller {
"elementwise_mul"
,
"elementwise_div"
,
"elementwise_pow"
,
"equal"
,
"dropout"
,
"prelu"
,
"conv2d_transpose"
,
...
...
@@ -213,6 +214,7 @@ struct SimpleOpTypeSetTeller : public Teller {
"elementwise_mul"
,
"elementwise_div"
,
"elementwise_pow"
,
"equal"
,
"dropout"
,
"prelu"
,
"conv2d_transpose"
,
...
...
@@ -2049,6 +2051,25 @@ bool OpTeller::Tell(const framework::ir::Node* node,
}
#endif
if
(
op_type
==
"equal"
)
{
#if !IS_TRT_VERSION_GE(8000)
VLOG
(
3
)
<<
"compare is not supported when TensorRT < 8.0"
;
return
false
;
#else
int
axis
=
BOOST_GET_CONST
(
int
,
desc
.
GetAttr
(
"axis"
));
if
(
axis
==
0
)
{
return
false
;
}
auto
*
block
=
desc
.
Block
();
if
(
block
==
nullptr
)
{
VLOG
(
3
)
<<
"The block desc is nullptr, we can't continue to analyze. "
"Developers need to check whether block_desc is passed in "
"the pass."
;
return
false
;
}
#endif
}
if
((
*
teller
)(
op_type
,
desc
,
use_no_calib_int8
))
return
true
;
}
...
...
python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_equal.py
0 → 100644
浏览文件 @
1dbbe20e
# Copyright (c) 2022 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
unittest
import
numpy
as
np
import
paddle.inference
as
paddle_infer
from
functools
import
partial
from
typing
import
Optional
,
List
,
Callable
,
Dict
,
Any
,
Set
class
TrtConvertElementwiseTest_one_input_corner_case
(
TrtLayerAutoScanTest
):
def
is_program_valid
(
self
,
program_config
:
ProgramConfig
)
->
bool
:
attrs
=
[
program_config
.
ops
[
i
].
attrs
for
i
in
range
(
len
(
program_config
.
ops
))
]
if
attrs
[
0
][
'axis'
]
==
0
:
return
false
ver
=
paddle_infer
.
get_trt_compile_version
()
if
ver
[
0
]
*
1000
+
ver
[
1
]
*
100
+
ver
[
2
]
*
10
<
8415
:
return
False
return
True
def
sample_program_configs
(
self
):
def
generate_input
(
shape
):
return
np
.
random
.
random
(
shape
).
astype
(
np
.
float32
)
for
batch
in
[
1
,
2
,
4
]:
for
shape
in
[[
batch
,
1
],
[
batch
,
1
,
32
],
[
batch
,
1
,
16
,
32
]]:
for
axis
in
[
-
1
if
len
(
shape
)
==
1
else
1
]:
self
.
dims
=
len
(
shape
)
dics
=
[{
"axis"
:
axis
},
{
"in_dtype"
:
0
,
"out_dtype"
:
5
}]
ops_config
=
[{
"op_type"
:
"equal"
,
"op_inputs"
:
{
"X"
:
[
"input_data1"
],
"Y"
:
[
"input_data2"
]
},
"op_outputs"
:
{
"Out"
:
[
"compare_output_data"
]
},
"op_attrs"
:
dics
[
0
]
},
{
"op_type"
:
"cast"
,
"op_inputs"
:
{
"X"
:
[
"compare_output_data"
]
},
"op_outputs"
:
{
"Out"
:
[
"output_data"
]
},
"op_attrs"
:
dics
[
1
]
}]
ops
=
self
.
generate_op_config
(
ops_config
)
program_config
=
ProgramConfig
(
ops
=
ops
,
weights
=
{},
inputs
=
{
"input_data1"
:
TensorConfig
(
data_gen
=
partial
(
generate_input
,
shape
)),
"input_data2"
:
TensorConfig
(
data_gen
=
partial
(
generate_input
,
shape
))
},
outputs
=
[
"output_data"
])
yield
program_config
def
sample_predictor_configs
(
self
,
program_config
)
->
(
paddle_infer
.
Config
,
List
[
int
],
float
):
def
generate_dynamic_shape
(
attrs
):
# The input.dims[1] must be equal to the weight's length.
if
self
.
dims
==
2
:
self
.
dynamic_shape
.
min_input_shape
=
{
"input_data1"
:
[
1
,
1
],
"input_data2"
:
[
1
,
1
]
}
self
.
dynamic_shape
.
max_input_shape
=
{
"input_data1"
:
[
4
,
1
],
"input_data2"
:
[
4
,
1
]
}
self
.
dynamic_shape
.
opt_input_shape
=
{
"input_data1"
:
[
2
,
1
],
"input_data2"
:
[
2
,
1
]
}
elif
self
.
dims
==
3
:
self
.
dynamic_shape
.
min_input_shape
=
{
"input_data1"
:
[
1
,
1
,
4
],
"input_data2"
:
[
1
,
1
,
4
]
}
self
.
dynamic_shape
.
max_input_shape
=
{
"input_data1"
:
[
4
,
1
,
256
],
"input_data2"
:
[
1
,
1
,
256
]
}
self
.
dynamic_shape
.
opt_input_shape
=
{
"input_data1"
:
[
2
,
1
,
16
],
"input_data2"
:
[
2
,
1
,
16
]
}
elif
self
.
dims
==
4
:
self
.
dynamic_shape
.
min_input_shape
=
{
"input_data1"
:
[
1
,
1
,
4
,
4
],
"input_data2"
:
[
1
,
1
,
4
,
4
]
}
self
.
dynamic_shape
.
max_input_shape
=
{
"input_data1"
:
[
4
,
1
,
128
,
256
],
"input_data2"
:
[
4
,
1
,
128
,
256
]
}
self
.
dynamic_shape
.
opt_input_shape
=
{
"input_data1"
:
[
2
,
1
,
32
,
16
],
"input_data2"
:
[
2
,
1
,
32
,
16
]
}
def
clear_dynamic_shape
():
self
.
dynamic_shape
.
max_input_shape
=
{}
self
.
dynamic_shape
.
min_input_shape
=
{}
self
.
dynamic_shape
.
opt_input_shape
=
{}
def
generate_trt_nodes_num
(
attrs
,
dynamic_shape
):
if
self
.
dims
==
1
:
return
0
,
3
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-5
# 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-5
def
test
(
self
):
self
.
run_test
()
if
__name__
==
"__main__"
:
unittest
.
main
()
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