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05275010
编写于
9月 17, 2021
作者:
津
津
提交者:
GitHub
9月 17, 2021
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差异文件
[inference]add reduce converter test (#35145)
* add test * add test * add test
上级
867f4fa0
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
320 addition
and
0 deletion
+320
-0
paddle/fluid/inference/tensorrt/op_teller.cc
paddle/fluid/inference/tensorrt/op_teller.cc
+10
-0
python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_reduce_mean.py
...ts/unittests/ir/inference/test_trt_convert_reduce_mean.py
+155
-0
python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_reduce_sum.py
...sts/unittests/ir/inference/test_trt_convert_reduce_sum.py
+155
-0
未找到文件。
paddle/fluid/inference/tensorrt/op_teller.cc
浏览文件 @
05275010
...
@@ -1079,6 +1079,16 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
...
@@ -1079,6 +1079,16 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
for
(
auto
x
:
dim
)
{
for
(
auto
x
:
dim
)
{
if
(
!
x
)
return
false
;
if
(
!
x
)
return
false
;
}
}
}
else
{
if
(
BOOST_GET_CONST
(
bool
,
desc
.
GetAttr
(
"reduce_all"
))
&&
!
BOOST_GET_CONST
(
bool
,
desc
.
GetAttr
(
"keep_dim"
)))
return
false
;
}
if
(
desc
.
HasAttr
(
"reduce_all"
))
{
int
out_dtype
=
BOOST_GET_CONST
(
int32_t
,
desc
.
GetAttr
(
"out_dtype"
));
if
(
out_dtype
!=
-
1
)
{
return
false
;
}
}
}
}
}
#if IS_TRT_VERSION_GE(7000)
#if IS_TRT_VERSION_GE(7000)
...
...
python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_reduce_mean.py
0 → 100644
浏览文件 @
05275010
# 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
import
unittest
class
TrtConvertReduceMeanTest
(
TrtLayerAutoScanTest
):
def
is_program_valid
(
self
,
program_config
:
ProgramConfig
)
->
bool
:
inputs
=
program_config
.
inputs
attrs
=
[
program_config
.
ops
[
i
].
attrs
for
i
in
range
(
len
(
program_config
.
ops
))
]
## dim should be in (-rank, rank), and not NONE
rank
=
len
(
inputs
[
'input_data'
].
shape
)
for
x
in
attrs
[
0
][
"dim"
]:
if
x
>=
rank
or
x
<=
-
rank
:
return
False
if
len
(
attrs
[
0
][
"dim"
])
==
0
:
return
False
## skip not use
if
attrs
[
0
][
"out_dtype"
]
!=
-
1
:
return
False
return
True
def
sample_program_configs
(
self
):
def
generate_input1
(
attrs
:
List
[
Dict
[
str
,
Any
]]):
return
np
.
random
.
random
([
1
,
3
,
64
,
64
]).
astype
(
np
.
float32
)
for
keep_dim
in
[
False
,
True
]:
for
dim
in
[[],
[
1
],
[
0
],
[
0
,
1
],
[
1
,
2
,
3
],
[
-
2
,
0
,
3
],
[
-
3
],
[
-
4
,
1
],
[
3
,
4
,
5
]]:
for
reduce_all
in
[
False
,
True
]:
for
out_dtype
in
[
-
1
,
0
,
1
]:
dics
=
[{
"keep_dim"
:
keep_dim
,
"dim"
:
dim
,
"reduce_all"
:
reduce_all
,
"out_dtype"
:
out_dtype
},
{}]
ops_config
=
[{
"op_type"
:
"reduce_mean"
,
"op_inputs"
:
{
"X"
:
[
"input_data"
]
},
"op_outputs"
:
{
"Out"
:
[
"reduce_output_data"
]
},
"op_attrs"
:
dics
[
0
]
}]
ops
=
self
.
generate_op_config
(
ops_config
)
program_config
=
ProgramConfig
(
ops
=
ops
,
weights
=
{},
inputs
=
{
"input_data"
:
TensorConfig
(
data_gen
=
partial
(
generate_input1
,
dics
))
},
outputs
=
[
"reduce_output_data"
])
if
not
self
.
is_program_valid
(
program_config
):
continue
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
):
if
dynamic_shape
:
if
(
not
attrs
[
0
][
'keep_dim'
])
and
attrs
[
0
][
'reduce_all'
]:
return
0
,
3
else
:
return
1
,
2
else
:
if
0
in
attrs
[
0
][
'dim'
]
or
attrs
[
0
][
'reduce_all'
]:
return
0
,
3
else
:
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
,
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
,
1e-5
)
pass
def
add_skip_trt_case
(
self
):
def
teller1
(
program_config
,
predictor_config
):
if
program_config
.
ops
[
0
].
attrs
[
'out_dtype'
]
!=
-
1
:
return
True
return
False
self
.
add_skip_case
(
teller1
,
SkipReasons
.
TRT_NOT_IMPLEMENTED
,
"NOT Implemented: we will add out_dtype not equal to -1 in the future"
)
pass
def
test
(
self
):
self
.
add_skip_trt_case
()
self
.
run_test
()
if
__name__
==
"__main__"
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_reduce_sum.py
0 → 100644
浏览文件 @
05275010
# 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
import
unittest
class
TrtConvertReduceSumTest
(
TrtLayerAutoScanTest
):
def
is_program_valid
(
self
,
program_config
:
ProgramConfig
)
->
bool
:
inputs
=
program_config
.
inputs
attrs
=
[
program_config
.
ops
[
i
].
attrs
for
i
in
range
(
len
(
program_config
.
ops
))
]
## dim should be in (-rank, rank), and not NONE
rank
=
len
(
inputs
[
'input_data'
].
shape
)
for
x
in
attrs
[
0
][
"dim"
]:
if
x
>=
rank
or
x
<=
-
rank
:
return
False
if
len
(
attrs
[
0
][
"dim"
])
==
0
:
return
False
## skip not use
if
attrs
[
0
][
"out_dtype"
]
!=
-
1
:
return
False
return
True
def
sample_program_configs
(
self
):
def
generate_input1
(
attrs
:
List
[
Dict
[
str
,
Any
]]):
return
np
.
random
.
random
([
1
,
3
,
64
,
64
]).
astype
(
np
.
float32
)
for
keep_dim
in
[
False
,
True
]:
for
dim
in
[[],
[
1
],
[
0
],
[
0
,
1
],
[
1
,
2
,
3
],
[
-
2
,
0
,
3
],
[
-
3
],
[
-
4
,
1
],
[
3
,
4
,
5
]]:
for
reduce_all
in
[
False
,
True
]:
for
out_dtype
in
[
-
1
,
0
,
1
]:
dics
=
[{
"keep_dim"
:
keep_dim
,
"dim"
:
dim
,
"reduce_all"
:
reduce_all
,
"out_dtype"
:
out_dtype
},
{}]
ops_config
=
[{
"op_type"
:
"reduce_sum"
,
"op_inputs"
:
{
"X"
:
[
"input_data"
]
},
"op_outputs"
:
{
"Out"
:
[
"reduce_output_data"
]
},
"op_attrs"
:
dics
[
0
]
}]
ops
=
self
.
generate_op_config
(
ops_config
)
program_config
=
ProgramConfig
(
ops
=
ops
,
weights
=
{},
inputs
=
{
"input_data"
:
TensorConfig
(
data_gen
=
partial
(
generate_input1
,
dics
))
},
outputs
=
[
"reduce_output_data"
])
if
not
self
.
is_program_valid
(
program_config
):
continue
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
):
if
dynamic_shape
:
if
(
not
attrs
[
0
][
'keep_dim'
])
and
attrs
[
0
][
'reduce_all'
]:
return
0
,
3
else
:
return
1
,
2
else
:
if
0
in
attrs
[
0
][
'dim'
]
or
attrs
[
0
][
'reduce_all'
]:
return
0
,
3
else
:
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
,
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
,
1e-5
)
pass
def
add_skip_trt_case
(
self
):
def
teller1
(
program_config
,
predictor_config
):
if
program_config
.
ops
[
0
].
attrs
[
'out_dtype'
]
!=
-
1
:
return
True
return
False
self
.
add_skip_case
(
teller1
,
SkipReasons
.
TRT_NOT_IMPLEMENTED
,
"NOT Implemented: we will add out_dtype not equal to -1 in the future"
)
pass
def
test
(
self
):
self
.
add_skip_trt_case
()
self
.
run_test
()
if
__name__
==
"__main__"
:
unittest
.
main
()
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