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体验新版 GitCode,发现更多精彩内容 >>
未验证
提交
baf60e3a
编写于
4月 17, 2019
作者:
H
Hongyu Liu
提交者:
GitHub
4月 17, 2019
浏览文件
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差异文件
Merge pull request #16907 from xuezhong/fix_infershape_bug2
fix infershape bug
上级
40be9590
9c6ee7cf
变更
7
隐藏空白更改
内联
并排
Showing
7 changed file
with
144 addition
and
46 deletion
+144
-46
paddle/fluid/operators/linear_chain_crf_op.cc
paddle/fluid/operators/linear_chain_crf_op.cc
+31
-16
paddle/fluid/operators/metrics/accuracy_op.cc
paddle/fluid/operators/metrics/accuracy_op.cc
+5
-4
paddle/fluid/operators/metrics/auc_op.cc
paddle/fluid/operators/metrics/auc_op.cc
+4
-3
paddle/fluid/operators/sample_logits_op.cc
paddle/fluid/operators/sample_logits_op.cc
+4
-2
paddle/fluid/operators/smooth_l1_loss_op.cc
paddle/fluid/operators/smooth_l1_loss_op.cc
+33
-8
paddle/fluid/operators/squared_l2_distance_op.cc
paddle/fluid/operators/squared_l2_distance_op.cc
+26
-13
paddle/fluid/platform/enforce.h
paddle/fluid/platform/enforce.h
+41
-0
未找到文件。
paddle/fluid/operators/linear_chain_crf_op.cc
浏览文件 @
baf60e3a
...
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/linear_chain_crf_op.h"
#include <memory>
namespace
paddle
{
...
...
@@ -152,12 +153,19 @@ class LinearChainCRFOp : public framework::OperatorWithKernel {
auto
transition_dims
=
ctx
->
GetInputDim
(
"Transition"
);
PADDLE_ENFORCE_EQ
(
transition_dims
.
size
(),
2
,
"The Input(Transition) should be a 2-D tensor."
);
PADDLE_ENFORCE_EQ
(
transition_dims
[
0
]
-
2
,
transition_dims
[
1
],
"An invalid dimension for the Input(Transition), which should "
"be a 2-D tensor with shape [(D + 2) x D]."
);
PADDLE_ENFORCE_EQ
(
emission_dims
[
1
],
transition_dims
[
1
],
bool
check
=
true
;
if
((
!
ctx
->
IsRuntime
())
&&
(
transition_dims
[
0
]
<=
0
||
transition_dims
[
1
]
<=
0
))
{
check
=
false
;
}
if
(
check
)
{
PADDLE_ENFORCE_EQ
(
transition_dims
[
0
]
-
2
,
transition_dims
[
1
],
"An invalid dimension for the Input(Transition), which should "
"be a 2-D tensor with shape [(D + 2) x D]."
);
}
PADDLE_INFERSHAPE_ENFORCE_EQ
(
ctx
,
emission_dims
[
1
],
transition_dims
[
1
],
"The 2nd dimension of the Input(Emission) and the Input(Transition) "
"should be equal to the tag number."
);
...
...
@@ -165,8 +173,8 @@ class LinearChainCRFOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE
(
label_dims
.
size
()
==
2UL
&&
label_dims
[
1
]
==
1UL
,
"The Input(Label) should be a 2-D tensor with the 2nd "
"dimensions fixed to 1."
);
PADDLE_ENFORCE_EQ
(
emission_dims
[
0
],
label_dims
[
0
],
PADDLE_
INFERSHAPE_
ENFORCE_EQ
(
ctx
,
emission_dims
[
0
],
label_dims
[
0
],
"The height of Input(Emission) and the height of Input(Label) "
"should be the same."
);
...
...
@@ -211,12 +219,19 @@ class LinearChainCRFGradOp : public framework::OperatorWithKernel {
auto
transition_exps_dims
=
ctx
->
GetInputDim
(
"TransitionExps"
);
PADDLE_ENFORCE_EQ
(
transition_exps_dims
.
size
(),
2
,
"The Input(TransitionExps) should be a 2-D tensor."
);
PADDLE_ENFORCE_EQ
(
transition_exps_dims
[
0
]
-
2
,
transition_exps_dims
[
1
],
"An invalid dimension for the Input(TransitionExps), which should "
"be a 2-D tensor with shape [(D + 2) x D]."
);
PADDLE_ENFORCE_EQ
(
emission_exps_dims
[
1
],
transition_exps_dims
[
1
],
bool
check
=
true
;
if
((
!
ctx
->
IsRuntime
())
&&
(
transition_exps_dims
[
0
]
<=
0
||
transition_exps_dims
[
1
]
<=
0
))
{
check
=
false
;
}
if
(
check
)
{
PADDLE_ENFORCE_EQ
(
transition_exps_dims
[
0
]
-
2
,
transition_exps_dims
[
1
],
"An invalid dimension for the Input(TransitionExps), which should "
"be a 2-D tensor with shape [(D + 2) x D]."
);
}
PADDLE_INFERSHAPE_ENFORCE_EQ
(
ctx
,
emission_exps_dims
[
1
],
transition_exps_dims
[
1
],
"The 2nd dimension of the Input(EmissionExps) and the "
"Input(TransitionExps) should be equal to the tag number."
);
...
...
@@ -224,8 +239,8 @@ class LinearChainCRFGradOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE
(
label_dims
.
size
()
==
2UL
&&
label_dims
[
1
]
==
1UL
,
"The Input(Label) should be a 2-D tensor with the 2nd "
"dimensions fixed to 1."
);
PADDLE_ENFORCE_EQ
(
emission_exps_dims
[
0
],
label_dims
[
0
],
PADDLE_
INFERSHAPE_
ENFORCE_EQ
(
ctx
,
emission_exps_dims
[
0
],
label_dims
[
0
],
"The height of Input(EmissionExps) and the height of Input(Label) "
"should be the same."
);
...
...
paddle/fluid/operators/metrics/accuracy_op.cc
浏览文件 @
baf60e3a
...
...
@@ -41,10 +41,11 @@ class AccuracyOp : public framework::OperatorWithKernel {
// it's the output of topk.
PADDLE_ENFORCE_EQ
(
label_dim
.
size
(),
2
,
"label's rank must be 2."
);
PADDLE_ENFORCE_EQ
(
label_dim
[
1
],
1
,
"label's second dimension must be 1"
);
PADDLE_ENFORCE_EQ
(
inference_dim
[
0
],
label_dim
[
0
],
"the inference tensor's num_rows must be"
" the same as label."
);
PADDLE_INFERSHAPE_ENFORCE_EQ
(
ctx
,
label_dim
[
1
],
1
,
"label's second dimension must be 1"
);
PADDLE_INFERSHAPE_ENFORCE_EQ
(
ctx
,
inference_dim
[
0
],
label_dim
[
0
],
"the inference tensor's num_rows must be"
" the same as label."
);
ctx
->
SetOutputDim
(
"Accuracy"
,
{
1
});
ctx
->
SetOutputDim
(
"Correct"
,
{
1
});
...
...
paddle/fluid/operators/metrics/auc_op.cc
浏览文件 @
baf60e3a
...
...
@@ -28,12 +28,13 @@ class AucOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Label"
),
"Input of Label should not be null."
);
auto
predict_width
=
ctx
->
GetInputDim
(
"Predict"
)[
1
];
PADDLE_ENFORCE_EQ
(
predict_width
,
2
,
"Only support binary classification"
);
PADDLE_INFERSHAPE_ENFORCE_EQ
(
ctx
,
predict_width
,
2
,
"Only support binary classification"
);
auto
predict_height
=
ctx
->
GetInputDim
(
"Predict"
)[
0
];
auto
label_height
=
ctx
->
GetInputDim
(
"Label"
)[
0
];
PADDLE_
ENFORCE_EQ
(
predict_height
,
label_height
,
"Out and Label should have same height."
);
PADDLE_
INFERSHAPE_ENFORCE_EQ
(
ctx
,
predict_height
,
label_height
,
"Out and Label should have same height."
);
int
num_pred_buckets
=
ctx
->
Attrs
().
Get
<
int
>
(
"num_thresholds"
)
+
1
;
int
slide_steps
=
ctx
->
Attrs
().
Get
<
int
>
(
"slide_steps"
);
...
...
paddle/fluid/operators/sample_logits_op.cc
浏览文件 @
baf60e3a
...
...
@@ -11,7 +11,6 @@ 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/operators/sample_logits_op.h"
#include <memory>
#include "paddle/fluid/operators/math/sample_prob.h"
...
...
@@ -141,7 +140,10 @@ class SampleLogitsOp : public framework::OperatorWithKernel {
"The labels should be a 2-D tensor."
);
const
int
num_samples
=
ctx
->
Attrs
().
Get
<
int
>
(
"num_samples"
);
const
int
num_sampled_classes
=
labels_dims
[
1
]
+
num_samples
;
int
num_sampled_classes
=
labels_dims
[
1
]
+
num_samples
;
if
((
!
ctx
->
IsRuntime
())
&&
labels_dims
[
1
]
<=
0
)
{
num_sampled_classes
=
-
1
;
}
ctx
->
SetOutputDim
(
"Samples"
,
{
logits_dims
[
0
],
num_sampled_classes
});
ctx
->
SetOutputDim
(
"Probabilities"
,
{
logits_dims
[
0
],
num_sampled_classes
});
ctx
->
SetOutputDim
(
"SampledLogits"
,
{
logits_dims
[
0
],
num_sampled_classes
});
...
...
paddle/fluid/operators/smooth_l1_loss_op.cc
浏览文件 @
baf60e3a
...
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/smooth_l1_loss_op.h"
#include <memory>
namespace
paddle
{
namespace
operators
{
...
...
@@ -27,15 +28,39 @@ class SmoothL1LossOp : public framework::OperatorWithKernel {
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
auto
y_dims
=
ctx
->
GetInputDim
(
"Y"
);
PADDLE_ENFORCE_EQ
(
x_dims
,
y_dims
);
bool
check
=
true
;
if
((
!
ctx
->
IsRuntime
())
&&
(
framework
::
product
(
x_dims
)
<=
0
||
framework
::
product
(
y_dims
)
<=
0
))
{
check
=
false
;
}
if
(
check
)
{
PADDLE_ENFORCE_EQ
(
x_dims
,
y_dims
);
}
PADDLE_ENFORCE_GE
(
x_dims
.
size
(),
2
,
"The tensor rank of Input(X) should not be less than 2."
);
if
(
ctx
->
HasInput
(
"InsideWeight"
))
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"OutsideWeight"
),
"If weights are provided, must specify both "
"inside and outside weights."
);
PADDLE_ENFORCE_EQ
(
ctx
->
GetInputDim
(
"InsideWeight"
),
x_dims
);
PADDLE_ENFORCE_EQ
(
ctx
->
GetInputDim
(
"OutsideWeight"
),
x_dims
);
auto
dims
=
ctx
->
GetInputDim
(
"InsideWeight"
);
bool
check
=
true
;
if
((
!
ctx
->
IsRuntime
())
&&
(
framework
::
product
(
dims
)
<=
0
||
framework
::
product
(
x_dims
)
<=
0
))
{
check
=
false
;
}
if
(
check
)
{
PADDLE_ENFORCE_EQ
(
dims
,
x_dims
);
}
dims
=
ctx
->
GetInputDim
(
"OutsideWeight"
);
check
=
true
;
if
((
!
ctx
->
IsRuntime
())
&&
(
framework
::
product
(
dims
)
<=
0
||
framework
::
product
(
x_dims
)
<=
0
))
{
check
=
false
;
}
if
(
check
)
{
PADDLE_ENFORCE_EQ
(
dims
,
x_dims
);
}
}
ctx
->
SetOutputDim
(
"Diff"
,
x_dims
);
...
...
@@ -110,11 +135,11 @@ class SmoothL1LossGradOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE_GE
(
out_dims
.
size
(),
2
,
"The tensor rank of Input(Out@Grad) should be 2."
);
PADDLE_
ENFORCE_EQ
(
out_dims
[
0
],
in_dims
[
0
],
"The 1st dimension of Input(Out@Grad) must be "
"same as input."
);
PADDLE_
ENFORCE_EQ
(
out_dims
[
1
],
1
,
"The 2nd dimension of Input(Out@Grad) must be 1."
);
PADDLE_
INFERSHAPE_ENFORCE_EQ
(
ctx
,
out_dims
[
0
],
in_dims
[
0
],
"The 1st dimension of Input(Out@Grad) must be "
"same as input."
);
PADDLE_
INFERSHAPE_ENFORCE_EQ
(
ctx
,
out_dims
[
1
],
1
,
"The 2nd dimension of Input(Out@Grad) must be 1."
);
auto
x_grad_name
=
framework
::
GradVarName
(
"X"
);
auto
y_grad_name
=
framework
::
GradVarName
(
"Y"
);
...
...
paddle/fluid/operators/squared_l2_distance_op.cc
浏览文件 @
baf60e3a
...
...
@@ -45,13 +45,26 @@ class SquaredL2DistanceOp : public framework::OperatorWithKernel {
int
rank
=
framework
::
arity
(
x_dims
);
PADDLE_ENFORCE_GE
(
rank
,
2
,
"Tensor rank should be at least equal to 2."
);
PADDLE_ENFORCE_EQ
(
product
(
x_dims
)
/
x_dims
[
0
],
product
(
y_dims
)
/
y_dims
[
0
],
"Product of dimensions expcet the first dimension of "
"input and target must be equal."
);
PADDLE_ENFORCE
(
y_dims
[
0
]
==
1
||
y_dims
[
0
]
==
x_dims
[
0
],
"First dimension of target must be equal to input "
"or to 1."
);
bool
check
=
true
;
if
((
!
ctx
->
IsRuntime
())
&&
(
framework
::
product
(
x_dims
)
<=
0
||
framework
::
product
(
y_dims
)
<=
0
))
{
check
=
false
;
}
if
(
check
)
{
PADDLE_ENFORCE_EQ
(
product
(
x_dims
)
/
x_dims
[
0
],
product
(
y_dims
)
/
y_dims
[
0
],
"Product of dimensions expcet the first dimension of "
"input and target must be equal."
);
}
check
=
true
;
if
((
!
ctx
->
IsRuntime
())
&&
(
y_dims
[
0
]
<=
0
||
x_dims
[
0
]
<=
0
))
{
check
=
false
;
}
if
(
check
)
{
PADDLE_ENFORCE
(
y_dims
[
0
]
==
1
||
y_dims
[
0
]
==
x_dims
[
0
],
"First dimension of target must be equal to input "
"or to 1."
);
}
ctx
->
SetOutputDim
(
"sub_result"
,
{
x_dims
[
0
],
product
(
x_dims
)
/
x_dims
[
0
]});
ctx
->
SetOutputDim
(
"Out"
,
{
x_dims
[
0
],
1
});
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
...
...
@@ -124,12 +137,12 @@ class SquaredL2DistanceGradOp : public framework::OperatorWithKernel {
auto
out_dims
=
ctx
->
GetInputDim
(
framework
::
GradVarName
(
"Out"
));
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
auto
y_dims
=
ctx
->
GetInputDim
(
"Y"
);
PADDLE_
ENFORCE_EQ
(
out_dims
[
0
],
x_dims
[
0
],
"First dimension of output gradient and "
"input value must be equal."
);
PADDLE_
ENFORCE_EQ
(
out_dims
[
1
],
1
,
"Second dimension of output gradient "
"must be 1."
);
PADDLE_
INFERSHAPE_ENFORCE_EQ
(
ctx
,
out_dims
[
0
],
x_dims
[
0
],
"First dimension of output gradient and "
"input value must be equal."
);
PADDLE_
INFERSHAPE_ENFORCE_EQ
(
ctx
,
out_dims
[
1
],
1
,
"Second dimension of output gradient "
"must be 1."
);
auto
x_grad_name
=
framework
::
GradVarName
(
"X"
);
auto
y_grad_name
=
framework
::
GradVarName
(
"Y"
);
if
(
ctx
->
HasOutput
(
x_grad_name
))
ctx
->
SetOutputDim
(
x_grad_name
,
x_dims
);
...
...
paddle/fluid/platform/enforce.h
浏览文件 @
baf60e3a
...
...
@@ -356,5 +356,46 @@ using CommonType2 = typename std::add_lvalue_reference<
#define PADDLE_ENFORCE_LE(__VAL0, __VAL1, ...) \
__PADDLE_BINARY_COMPARE(__VAL0, __VAL1, <=, >, __VA_ARGS__)
#define __PADDLE_INFERSHAPE_BINARY_COMPARE(__CTX, __VAL1, __VAL2, __CMP, \
__INV_CMP, ...) \
do { \
auto __val1 = (__VAL1); \
auto __val2 = (__VAL2); \
if (!__CTX->IsRuntime()) { \
if (__val1 == -1 || __val2 == -1) { \
break; \
} \
} \
using __TYPE1__ = decltype(__val1); \
using __TYPE2__ = decltype(__val2); \
using __COMMON_TYPE1__ = \
::paddle::platform::details::CommonType1<__TYPE1__, __TYPE2__>; \
using __COMMON_TYPE2__ = \
::paddle::platform::details::CommonType2<__TYPE1__, __TYPE2__>; \
bool __is_not_error = (static_cast<__COMMON_TYPE1__>(__val1))__CMP( \
static_cast<__COMMON_TYPE2__>(__val2)); \
if (UNLIKELY(!__is_not_error)) { \
PADDLE_THROW("Enforce failed. Expected %s " #__CMP \
" %s, but received %s:%s " #__INV_CMP " %s:%s.\n%s", \
#__VAL1, #__VAL2, #__VAL1, \
::paddle::string::to_string(__val1), #__VAL2, \
::paddle::string::to_string(__val2), \
::paddle::string::Sprintf(__VA_ARGS__)); \
} \
} while (0)
#define PADDLE_INFERSHAPE_ENFORCE_EQ(__CTX, __VAL0, __VAL1, ...) \
__PADDLE_INFERSHAPE_BINARY_COMPARE(__CTX, __VAL0, __VAL1, ==, !=, __VA_ARGS__)
#define PADDLE_INFERSHAPE_ENFORCE_NE(__CTX, __VAL0, __VAL1, ...) \
__PADDLE_INFERSHAPE_BINARY_COMPARE(__CTX, __VAL0, __VAL1, !=, ==, __VA_ARGS__)
#define PADDLE_INFERSHAPE_ENFORCE_GT(__CTX, __VAL0, __VAL1, ...) \
__PADDLE_INFERSHAPE_BINARY_COMPARE(__CTX, __VAL0, __VAL1, >, <=, __VA_ARGS__)
#define PADDLE_INFERSHAPE_ENFORCE_GE(__CTX, __VAL0, __VAL1, ...) \
__PADDLE_INFERSHAPE_BINARY_COMPARE(__CTX, __VAL0, __VAL1, >=, <, __VA_ARGS__)
#define PADDLE_INFERSHAPE_ENFORCE_LT(__CTX, __VAL0, __VAL1, ...) \
__PADDLE_INFERSHAPE_BINARY_COMPARE(__CTX, __VAL0, __VAL1, <, >=, __VA_ARGS__)
#define PADDLE_INFERSHAPE_ENFORCE_LE(__CTX, __VAL0, __VAL1, ...) \
__PADDLE_INFERSHAPE_BINARY_COMPARE(__CTX, __VAL0, __VAL1, <=, >, __VA_ARGS__)
}
// namespace platform
}
// namespace paddle
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