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体验新版 GitCode,发现更多精彩内容 >>
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ab57d389
编写于
7月 15, 2019
作者:
G
guru4elephant
提交者:
GitHub
7月 15, 2019
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差异文件
make auc op compatible with 1 dim (#18551)
* make auc op compatible with 1 dim
上级
b71b4543
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
71 addition
and
3 deletion
+71
-3
paddle/fluid/operators/metrics/auc_op.cc
paddle/fluid/operators/metrics/auc_op.cc
+3
-2
paddle/fluid/operators/metrics/auc_op.h
paddle/fluid/operators/metrics/auc_op.h
+4
-1
python/paddle/fluid/tests/unittests/test_auc_single_pred_op.py
...n/paddle/fluid/tests/unittests/test_auc_single_pred_op.py
+64
-0
未找到文件。
paddle/fluid/operators/metrics/auc_op.cc
浏览文件 @
ab57d389
...
@@ -28,8 +28,9 @@ class AucOp : public framework::OperatorWithKernel {
...
@@ -28,8 +28,9 @@ class AucOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Label"
),
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Label"
),
"Input of Label should not be null."
);
"Input of Label should not be null."
);
auto
predict_width
=
ctx
->
GetInputDim
(
"Predict"
)[
1
];
auto
predict_width
=
ctx
->
GetInputDim
(
"Predict"
)[
1
];
PADDLE_INFERSHAPE_ENFORCE_EQ
(
ctx
,
predict_width
,
2
,
PADDLE_INFERSHAPE_ENFORCE_LE
(
ctx
,
predict_width
,
2
,
"Only support binary classification"
);
"Only support binary classification,"
"prediction dims[1] should be 1 or 2"
);
auto
predict_height
=
ctx
->
GetInputDim
(
"Predict"
)[
0
];
auto
predict_height
=
ctx
->
GetInputDim
(
"Predict"
)[
0
];
auto
label_height
=
ctx
->
GetInputDim
(
"Label"
)[
0
];
auto
label_height
=
ctx
->
GetInputDim
(
"Label"
)[
0
];
...
...
paddle/fluid/operators/metrics/auc_op.h
浏览文件 @
ab57d389
...
@@ -75,7 +75,10 @@ class AucKernel : public framework::OpKernel<T> {
...
@@ -75,7 +75,10 @@ class AucKernel : public framework::OpKernel<T> {
const
auto
*
label_data
=
label
->
data
<
int64_t
>
();
const
auto
*
label_data
=
label
->
data
<
int64_t
>
();
for
(
size_t
i
=
0
;
i
<
batch_size
;
i
++
)
{
for
(
size_t
i
=
0
;
i
<
batch_size
;
i
++
)
{
auto
predict_data
=
inference_data
[
i
*
inference_width
+
1
];
// if predict_data[i] has dim of 2, then predict_data[i][1] is pos prob
// if predict_data[i] has dim of 1, then predict_data[i][0] is pos prob
auto
predict_data
=
inference_data
[
i
*
inference_width
+
(
inference_width
-
1
)];
PADDLE_ENFORCE_LE
(
predict_data
,
1
,
PADDLE_ENFORCE_LE
(
predict_data
,
1
,
"The predict data must less or equal 1."
);
"The predict data must less or equal 1."
);
PADDLE_ENFORCE_GE
(
predict_data
,
0
,
PADDLE_ENFORCE_GE
(
predict_data
,
0
,
...
...
python/paddle/fluid/tests/unittests/test_auc_single_pred_op.py
0 → 100644
浏览文件 @
ab57d389
# Copyright (c) 2018 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
op_test
import
OpTest
from
paddle.fluid
import
metrics
class
TestAucSinglePredOp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"auc"
pred
=
np
.
random
.
random
((
128
,
2
)).
astype
(
"float32"
)
pred0
=
pred
[:,
0
].
reshape
(
128
,
1
)
labels
=
np
.
random
.
randint
(
0
,
2
,
(
128
,
1
)).
astype
(
"int64"
)
num_thresholds
=
200
stat_pos
=
np
.
zeros
((
num_thresholds
+
1
,
)).
astype
(
"int64"
)
stat_neg
=
np
.
zeros
((
num_thresholds
+
1
,
)).
astype
(
"int64"
)
self
.
inputs
=
{
'Predict'
:
pred0
,
'Label'
:
labels
,
"StatPos"
:
stat_pos
,
"StatNeg"
:
stat_neg
}
self
.
attrs
=
{
'curve'
:
'ROC'
,
'num_thresholds'
:
num_thresholds
,
"slide_steps"
:
1
}
python_auc
=
metrics
.
Auc
(
name
=
"auc"
,
curve
=
'ROC'
,
num_thresholds
=
num_thresholds
)
for
i
in
range
(
128
):
pred
[
i
][
1
]
=
pred
[
i
][
0
]
python_auc
.
update
(
pred
,
labels
)
self
.
outputs
=
{
'AUC'
:
np
.
array
(
python_auc
.
eval
()),
'StatPosOut'
:
np
.
array
(
python_auc
.
_stat_pos
),
'StatNegOut'
:
np
.
array
(
python_auc
.
_stat_neg
)
}
def
test_check_output
(
self
):
self
.
check_output
()
if
__name__
==
"__main__"
:
unittest
.
main
()
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