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体验新版 GitCode,发现更多精彩内容 >>
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ca41e552
编写于
5月 15, 2020
作者:
L
lilong12
提交者:
GitHub
5月 15, 2020
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电子邮件补丁
差异文件
[Cherry-pick 1.8] Improving error reporting messages for ops #24438 (#24534)
* improve error reporting messages
上级
56eead24
变更
12
隐藏空白更改
内联
并排
Showing
12 changed file
with
324 addition
and
144 deletion
+324
-144
paddle/fluid/operators/crop_op.cc
paddle/fluid/operators/crop_op.cc
+14
-10
paddle/fluid/operators/crop_op.h
paddle/fluid/operators/crop_op.h
+43
-12
paddle/fluid/operators/crop_tensor_op.cc
paddle/fluid/operators/crop_tensor_op.cc
+28
-23
paddle/fluid/operators/crop_tensor_op.h
paddle/fluid/operators/crop_tensor_op.h
+78
-32
paddle/fluid/operators/expand_op.cc
paddle/fluid/operators/expand_op.cc
+31
-17
paddle/fluid/operators/expand_op.h
paddle/fluid/operators/expand_op.h
+41
-19
paddle/fluid/operators/merge_selected_rows_op.cc
paddle/fluid/operators/merge_selected_rows_op.cc
+12
-10
paddle/fluid/operators/shard_index_op.cc
paddle/fluid/operators/shard_index_op.cc
+10
-6
paddle/fluid/operators/shard_index_op.cu
paddle/fluid/operators/shard_index_op.cu
+23
-4
paddle/fluid/operators/shard_index_op.h
paddle/fluid/operators/shard_index_op.h
+33
-7
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+3
-4
python/paddle/fluid/tests/unittests/test_layers.py
python/paddle/fluid/tests/unittests/test_layers.py
+8
-0
未找到文件。
paddle/fluid/operators/crop_op.cc
浏览文件 @
ca41e552
...
...
@@ -27,16 +27,18 @@ class CropOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of CropOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of CropOp should not be null."
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"X"
),
"Input"
,
"X"
,
"Crop"
);
OP_INOUT_CHECK
(
ctx
->
HasOutput
(
"Out"
),
"Output"
,
"Out"
,
"Crop"
);
auto
x_dim
=
ctx
->
GetInputDim
(
"X"
);
if
(
!
ctx
->
HasInput
(
"Y"
))
{
auto
shape
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"shape"
);
PADDLE_ENFORCE_EQ
(
int64_t
(
shape
.
size
()),
x_dim
.
size
(),
"Shape size should be equal to dimension size of input tensor."
);
platform
::
errors
::
InvalidArgument
(
"The number of elements (%d) of CropOp's "
"'shape' attribute should be equal to the number of dimensions "
"(%d) of the Input(X)."
,
shape
.
size
(),
x_dim
.
size
()));
std
::
vector
<
int64_t
>
tensor_shape
(
shape
.
size
());
for
(
size_t
i
=
0
;
i
<
shape
.
size
();
++
i
)
{
tensor_shape
[
i
]
=
static_cast
<
int64_t
>
(
shape
[
i
]);
...
...
@@ -45,8 +47,10 @@ class CropOp : public framework::OperatorWithKernel {
}
else
{
auto
y_dim
=
ctx
->
GetInputDim
(
"Y"
);
PADDLE_ENFORCE_EQ
(
framework
::
arity
(
x_dim
),
framework
::
arity
(
y_dim
),
"Tensor rank of both CropOp's "
"inputs must be same."
);
platform
::
errors
::
InvalidArgument
(
"The number of dimensions (%d) of CropOp's input(X)"
" must be equal to that (%d) of input(Y)."
,
framework
::
arity
(
x_dim
),
framework
::
arity
(
y_dim
)));
ctx
->
SetOutputDim
(
"Out"
,
y_dim
);
}
}
...
...
@@ -163,9 +167,9 @@ class CropOpGrad : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) should not be null
"
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
))
,
"Input(Out@GRAD) should not be null
"
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"X"
),
"Input"
,
"X"
,
"CropGrad
"
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
"Input"
,
framework
::
GradVarName
(
"Out"
),
"CropGrad
"
);
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
auto
x_grad_name
=
framework
::
GradVarName
(
"X"
);
if
(
ctx
->
HasOutput
(
x_grad_name
))
{
...
...
paddle/fluid/operators/crop_op.h
浏览文件 @
ca41e552
...
...
@@ -31,14 +31,23 @@ static std::vector<int> GetOffsets(const framework::ExecutionContext& ctx) {
std
::
vector
<
int
>
res
;
int
rank
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
().
size
();
if
(
ctx
.
HasInput
(
"Offsets"
))
{
PADDLE_ENFORCE
(
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"offsets"
).
empty
(),
"Input 'Offsets' and attribute 'offsets' should not be used "
"at the same time."
);
PADDLE_ENFORCE_EQ
(
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"offsets"
).
empty
(),
true
,
platform
::
errors
::
InvalidArgument
(
"Input 'Offsets' and attribute 'offsets' "
"should not be used at the same time for CropOp."
));
const
auto
*
offsets_tensor
=
ctx
.
Input
<
Tensor
>
(
"Offsets"
);
PADDLE_ENFORCE_EQ
(
offsets_tensor
->
dims
().
size
(),
1
);
PADDLE_ENFORCE_EQ
(
offsets_tensor
->
dims
().
size
(),
1
,
platform
::
errors
::
InvalidArgument
(
"The number of dimensions of input 'Offsets' for "
"CropOp must be 1, but the value received is %d."
,
offsets_tensor
->
dims
().
size
()));
PADDLE_ENFORCE_EQ
(
rank
,
offsets_tensor
->
dims
()[
0
],
"Offsets size should be equal to dimension size of input tensor."
);
platform
::
errors
::
InvalidArgument
(
"The number of elements (%d) for "
"input 'Offsets' must be equal to "
"the number of dimensions (%d) "
"of the input tensor."
,
offsets_tensor
->
dims
()[
0
],
rank
));
const
int
*
offsets_data
;
framework
::
Tensor
cpu_tmp_tensor
;
if
(
platform
::
is_cpu_place
(
offsets_tensor
->
place
()))
{
...
...
@@ -53,7 +62,11 @@ static std::vector<int> GetOffsets(const framework::ExecutionContext& ctx) {
res
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"offsets"
);
PADDLE_ENFORCE_EQ
(
rank
,
static_cast
<
int
>
(
res
.
size
()),
"Offsets size should be equal to dimension size of input tensor."
);
platform
::
errors
::
InvalidArgument
(
"The number of elements (%d) for "
"input 'Offsets' must be equal to "
"the number of dimensions (%d) "
"of the input tensor."
,
res
.
size
(),
rank
));
}
return
res
;
}
...
...
@@ -92,6 +105,18 @@ class CropKernel : public framework::OpKernel<T> {
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
int
rank
=
context
.
Input
<
Tensor
>
(
"X"
)
->
dims
().
size
();
PADDLE_ENFORCE_GE
(
rank
,
1
,
platform
::
errors
::
InvalidArgument
(
"The number of dimensions of the Input(X) for CropOp must be "
"greater than or equal to 1, but the value received is %d."
,
rank
));
PADDLE_ENFORCE_LE
(
rank
,
6
,
platform
::
errors
::
InvalidArgument
(
"The number of dimensions of the Input(X) for CropOp must be "
"less than or equal to 6, but the value received is %d."
,
rank
));
switch
(
rank
)
{
case
1
:
CropFunction
<
DeviceContext
,
T
,
1
>
(
context
);
...
...
@@ -111,9 +136,6 @@ class CropKernel : public framework::OpKernel<T> {
case
6
:
CropFunction
<
DeviceContext
,
T
,
6
>
(
context
);
break
;
default:
PADDLE_THROW
(
"CropOp only support tensors with no more than 6 dimensions."
);
}
}
};
...
...
@@ -145,6 +167,18 @@ class CropGradKernel : public framework::OpKernel<T> {
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
size_t
rank
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
))
->
dims
().
size
();
PADDLE_ENFORCE_GE
(
rank
,
1
,
platform
::
errors
::
InvalidArgument
(
"The number of dimensions of the input 'Out@GRAD' for "
"CropGrad must be greater than or equal "
"to 1, but the value received is %d."
,
rank
));
PADDLE_ENFORCE_LE
(
rank
,
6
,
platform
::
errors
::
InvalidArgument
(
"The number of dimensions of the input 'Out@GRAD' for "
"CropGrad must be less than or equal "
"to 6, but the value received is %d."
,
rank
));
switch
(
rank
)
{
case
1
:
CropGradFunction
<
DeviceContext
,
T
,
1
>
(
context
);
...
...
@@ -164,9 +198,6 @@ class CropGradKernel : public framework::OpKernel<T> {
case
6
:
CropGradFunction
<
DeviceContext
,
T
,
6
>
(
context
);
break
;
default:
PADDLE_THROW
(
"CropOp only support tensors with no more than 6 dimensions."
);
}
}
};
...
...
paddle/fluid/operators/crop_tensor_op.cc
浏览文件 @
ca41e552
...
...
@@ -27,10 +27,8 @@ class CropTensorOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"X"
),
true
,
"Input(X) of Op(crop_tensor) should not be null."
);
PADDLE_ENFORCE_EQ
(
ctx
->
HasOutput
(
"Out"
),
true
,
"Output(Out) of Op(crop_tensor) should not be null."
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"X"
),
"Input"
,
"X"
,
"CropTensor"
);
OP_INOUT_CHECK
(
ctx
->
HasOutput
(
"Out"
),
"Output"
,
"Out"
,
"CropTensor"
);
auto
x_dim
=
ctx
->
GetInputDim
(
"X"
);
auto
shape
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"shape"
);
auto
offsets
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"offsets"
);
...
...
@@ -39,9 +37,11 @@ class CropTensorOp : public framework::OperatorWithKernel {
auto
inputs_name
=
ctx
->
Inputs
(
"ShapeTensor"
);
PADDLE_ENFORCE_GT
(
inputs_name
.
size
(),
0
,
"Input(ShapeTensor)'size of Op(crop_tensor) can't be zero. "
"Please check the Attr(shape)'s size of "
"Op(fluid.layers.crop_tensor)."
);
platform
::
errors
::
InvalidArgument
(
"The number of elements of the input 'ShapeTensor' for "
"CropTensor must be greater than zero, "
"but the value received is %d."
,
inputs_name
.
size
()));
auto
out_dims
=
std
::
vector
<
int
>
(
inputs_name
.
size
(),
-
1
);
for
(
size_t
i
=
0
;
i
<
shape
.
size
();
++
i
)
{
if
(
shape
[
i
]
>
0
)
{
...
...
@@ -59,16 +59,18 @@ class CropTensorOp : public framework::OperatorWithKernel {
if
(
ctx
->
HasInput
(
"Shape"
))
{
auto
shape_dim
=
ctx
->
GetInputDim
(
"Shape"
);
PADDLE_ENFORCE_EQ
(
shape_dim
.
size
(),
1
,
"Input(Shape)'s dimension size of Op(crop_tensor) must be 1. "
"Please check the Attr(shape)'s dimension size of "
"Op(fluid.layers.crop_tensor)."
);
PADDLE_ENFORCE_EQ
(
shape_dim
.
size
(),
1
,
platform
::
errors
::
InvalidArgument
(
"The number of dimensions of the input "
"'Shape' for CropTensor must be 1, "
"but the value received is %d."
,
shape_dim
.
size
()));
PADDLE_ENFORCE_EQ
(
shape_dim
[
0
],
x_dim
.
size
(),
"Input(Shape)'s size of Op(crop_tensor) must be equal "
"to dimension size of input tensor. "
"Please check the Attr(shape)'s size of "
"Op(fluid.layers.crop_tensor)."
);
platform
::
errors
::
InvalidArgument
(
"The number of elements (%d) of the input 'Shape' "
"for CropTensor must be equal to the number of"
" dimensions (%d) of the input."
,
shape_dim
[
0
],
x_dim
.
size
()));
if
(
ctx
->
IsRuntime
())
{
// If true, set the shape of Output(Out) according to Input(Shape) in
// CropTensorKernel with ExecutionContext. Also check LoD in
...
...
@@ -80,9 +82,13 @@ class CropTensorOp : public framework::OperatorWithKernel {
}
return
;
}
PADDLE_ENFORCE_EQ
(
int64_t
(
shape
.
size
()),
x_dim
.
size
(),
"Attr(shape)'size of Op(crop_tensor) should be equal to "
"dimension size of input tensor."
);
PADDLE_ENFORCE_EQ
(
int64_t
(
shape
.
size
()),
x_dim
.
size
(),
platform
::
errors
::
InvalidArgument
(
"The number of elements (%d) of attribute 'shape' for "
"CropTensor must be equal to the number of "
"dimensions (%d) of the input."
,
shape
.
size
(),
x_dim
.
size
()));
std
::
vector
<
int64_t
>
out_shape
(
shape
.
size
(),
-
1
);
for
(
size_t
i
=
0
;
i
<
shape
.
size
();
++
i
)
{
if
(
shape
[
i
]
>
0
)
{
...
...
@@ -242,10 +248,9 @@ class CropTensorOpGrad : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"X"
),
true
,
"Input(X) of Op(crop_tensor) should not be null."
);
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
true
,
"Input(Out@GRAD) of Op(crop_tensor) should not be null."
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"X"
),
"Input"
,
"X"
,
"CropTensorGrad"
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
"Input"
,
framework
::
GradVarName
(
"Out"
),
"CropTensorGrad"
);
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
auto
x_grad_name
=
framework
::
GradVarName
(
"X"
);
if
(
ctx
->
HasOutput
(
x_grad_name
))
{
...
...
paddle/fluid/operators/crop_tensor_op.h
浏览文件 @
ca41e552
...
...
@@ -35,7 +35,10 @@ inline std::vector<int> get_new_data(
auto
tensor
=
list_new_tensor
[
i
];
PADDLE_ENFORCE_EQ
(
tensor
->
dims
(),
framework
::
make_ddim
({
1
}),
"The tensor's shape in list of Op(crop_tensor) should be [1]."
);
platform
::
errors
::
InvalidArgument
(
"The tensor's shape in list of Op(crop_tensor) should be [1], "
"but the value received is %d."
,
tensor
->
dims
()));
if
(
platform
::
is_gpu_place
(
tensor
->
place
()))
{
framework
::
Tensor
temp
;
TensorCopySync
(
*
tensor
,
platform
::
CPUPlace
(),
&
temp
);
...
...
@@ -56,18 +59,23 @@ static framework::DDim ValidateShape(const std::vector<int> shape,
auto
shape_size
=
shape
.
size
();
PADDLE_ENFORCE_EQ
(
in_dim_size
,
shape_size
,
"Attr(shape)'s size of Op(crop_tensor) should be equal "
"to that of input Tensor. "
"Please check the Attr(shape)'s size of Op(fluid.layers.crop_tensor)."
);
platform
::
errors
::
InvalidArgument
(
"The number of elements (%d) for shape of Op(crop_tensor) should be "
"equal to the number of dimensions (%d) of the input tensor."
,
shape_size
,
in_dim_size
));
std
::
vector
<
int64_t
>
output_shape
(
shape
.
size
(),
0
);
for
(
size_t
i
=
0
;
i
<
shape
.
size
();
++
i
)
{
if
(
shape
[
i
]
<=
0
&&
in_dims
[
i
]
>
0
)
{
PADDLE_ENFORCE_NE
(
shape
[
i
],
0
,
"The element in Attr(shape) of Op(crop_tensor) should not be zero."
);
PADDLE_ENFORCE_EQ
(
shape
[
i
],
-
1
,
"When the element in Attr(shape) of Op(crop_tensor) is "
"negative, only -1 is supported."
);
PADDLE_ENFORCE_NE
(
shape
[
i
],
0
,
platform
::
errors
::
InvalidArgument
(
"The value (%d) of the %uth element for shape of "
"Op(crop_tensor) should not be zero."
,
shape
[
i
],
i
));
PADDLE_ENFORCE_EQ
(
shape
[
i
],
-
1
,
platform
::
errors
::
InvalidArgument
(
"When the value (%d) of the %uth "
"element for shape of Op(crop_tensor)"
" is negative, only -1 is supported."
,
shape
[
i
],
i
));
output_shape
[
i
]
=
in_dims
[
i
]
-
offsets
[
i
];
}
else
{
output_shape
[
i
]
=
static_cast
<
int64_t
>
(
shape
[
i
]);
...
...
@@ -83,9 +91,13 @@ static std::vector<int> GetShape(const framework::ExecutionContext& ctx) {
auto
list_new_shape_tensor
=
ctx
.
MultiInput
<
framework
::
Tensor
>
(
"ShapeTensor"
);
if
(
list_new_shape_tensor
.
size
()
>
0
)
{
// have offsets tensor list
PADDLE_ENFORCE_EQ
(
list_new_shape_tensor
.
size
(),
rank
,
"Input(ShapeTensor)'s length of Op(crop_tensor) should "
"be equal to dimension size of input tensor."
);
PADDLE_ENFORCE_EQ
(
list_new_shape_tensor
.
size
(),
rank
,
platform
::
errors
::
InvalidArgument
(
"The number of tensors (%d) for the input ShapeTensor of "
"Op(crop_tensor) must be equal to the number of "
"dimensions (%d) of the input."
,
list_new_shape_tensor
.
size
(),
rank
));
res
=
get_new_data
(
list_new_shape_tensor
);
return
res
;
...
...
@@ -122,13 +134,21 @@ static std::vector<int> GetOffsets(const framework::ExecutionContext& ctx) {
if
(
ctx
.
HasInput
(
"Offsets"
))
{
PADDLE_ENFORCE_EQ
(
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"offsets"
).
empty
(),
true
,
"Input 'Offsets' and attribute 'offsets' should not be used "
"at the same time."
);
platform
::
errors
::
InvalidArgument
(
"Input 'Offsets' and attribute 'offsets' for Op(crop_tensor) "
"cannot be used at the same time."
));
const
auto
*
offsets_tensor
=
ctx
.
Input
<
Tensor
>
(
"Offsets"
);
PADDLE_ENFORCE_EQ
(
offsets_tensor
->
dims
().
size
(),
1
);
PADDLE_ENFORCE_EQ
(
rank
,
offsets_tensor
->
dims
()[
0
],
"Offsets size should be equal to dimension size of input tensor."
);
PADDLE_ENFORCE_EQ
(
offsets_tensor
->
dims
().
size
(),
1
,
platform
::
errors
::
InvalidArgument
(
"The number of dimensions of input 'Offsets' must "
"be 1, but the value received is: %d."
,
offsets_tensor
->
dims
().
size
()));
PADDLE_ENFORCE_EQ
(
rank
,
offsets_tensor
->
dims
()[
0
],
platform
::
errors
::
InvalidArgument
(
"The number of elements (%d) for "
"input 'Offsets' must be equal to "
"the number of dimensions (%d) of the input tensor."
,
offsets_tensor
->
dims
()[
0
],
rank
));
const
int
*
offsets_data
;
framework
::
Tensor
cpu_tmp_tensor
;
if
(
platform
::
is_cpu_place
(
offsets_tensor
->
place
()))
{
...
...
@@ -143,7 +163,11 @@ static std::vector<int> GetOffsets(const framework::ExecutionContext& ctx) {
res
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"offsets"
);
PADDLE_ENFORCE_EQ
(
rank
,
static_cast
<
int
>
(
res
.
size
()),
"Offsets size should be equal to dimension size of input tensor."
);
platform
::
errors
::
InvalidArgument
(
"The number of elements (%d) for "
"input 'Offsets' must be equal to "
"the number of dimensions (%d) "
"of the input tensor."
,
static_cast
<
int
>
(
res
.
size
()),
rank
));
}
return
res
;
}
...
...
@@ -168,10 +192,13 @@ void CropTensorFunction(const framework::ExecutionContext& context) {
out_dims
=
ValidateShape
(
shape
,
offsets
,
x
->
dims
());
out
->
mutable_data
<
T
>
(
out_dims
,
context
.
GetPlace
());
for
(
size_t
i
=
0
;
i
<
offsets
.
size
();
++
i
)
{
PADDLE_ENFORCE_LE
(
offsets
[
i
]
+
shape
[
i
],
x_dims
[
i
],
"The sum of the Attr(offsets) and Attr(shape) of Op(crop_tensor) "
"should be less than or equal to corresponding input dimension size."
);
PADDLE_ENFORCE_LE
(
offsets
[
i
]
+
shape
[
i
],
x_dims
[
i
],
platform
::
errors
::
InvalidArgument
(
"The sum of the %uth elements of "
"offsets (%d) and shape (%d) of Op(crop_tensor) "
"should be less than or "
"equal to the size of %uth dimension of the input."
,
i
,
offsets
[
i
],
shape
[
i
],
i
));
}
auto
x_tensor
=
EigenTensor
<
T
,
D
>::
From
(
*
x
);
...
...
@@ -192,6 +219,19 @@ class CropTensorKernel : public framework::OpKernel<T> {
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
int
rank
=
context
.
Input
<
Tensor
>
(
"X"
)
->
dims
().
size
();
PADDLE_ENFORCE_GE
(
rank
,
1
,
platform
::
errors
::
InvalidArgument
(
"The number of dimensions of the input 'x' for "
"Op(crop_tensor) must be greater than or equal to 1, but the "
"value received is %d."
,
rank
));
PADDLE_ENFORCE_LE
(
rank
,
6
,
platform
::
errors
::
InvalidArgument
(
"The number of dimensions of the input 'x' for "
"Op(crop_tensor) must be less than or equal to 6, but the "
"value received is %d."
,
rank
));
switch
(
rank
)
{
case
1
:
CropTensorFunction
<
DeviceContext
,
T
,
1
>
(
context
);
...
...
@@ -211,10 +251,6 @@ class CropTensorKernel : public framework::OpKernel<T> {
case
6
:
CropTensorFunction
<
DeviceContext
,
T
,
6
>
(
context
);
break
;
default:
PADDLE_THROW
(
"CropTensorOp only support tensors with no more than 6 "
"dimensions."
);
}
}
};
...
...
@@ -246,6 +282,20 @@ class CropTensorGradKernel : public framework::OpKernel<T> {
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
size_t
rank
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
))
->
dims
().
size
();
PADDLE_ENFORCE_GE
(
rank
,
1
,
platform
::
errors
::
InvalidArgument
(
"The number of dimensions of the input 'Out@GRAD' for "
"Op(crop_tensor_grad) must be greater than or equal to 1, but the "
"value received is %d."
,
rank
));
PADDLE_ENFORCE_LE
(
rank
,
6
,
platform
::
errors
::
InvalidArgument
(
"The number of dimensions of the input 'Out@GRAD' for "
"Op(crop_tensor_grad) must be less than or equal to 6, but the "
"value received is %d."
,
rank
));
switch
(
rank
)
{
case
1
:
CropTensorGradFunction
<
DeviceContext
,
T
,
1
>
(
context
);
...
...
@@ -265,10 +315,6 @@ class CropTensorGradKernel : public framework::OpKernel<T> {
case
6
:
CropTensorGradFunction
<
DeviceContext
,
T
,
6
>
(
context
);
break
;
default:
PADDLE_THROW
(
"CropTensorOp only support tensors with no more than 6 "
"dimensions."
);
}
}
};
...
...
paddle/fluid/operators/expand_op.cc
浏览文件 @
ca41e552
...
...
@@ -28,9 +28,8 @@ class ExpandOp : public framework::OperatorWithKernel {
protected:
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"X"
),
true
,
"Input(X) should not be null."
);
PADDLE_ENFORCE_EQ
(
ctx
->
HasOutput
(
"Out"
),
true
,
"Output(Out) should not be null."
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"X"
),
"Input"
,
"X"
,
"Expand"
);
OP_INOUT_CHECK
(
ctx
->
HasOutput
(
"Out"
),
"Output"
,
"Out"
,
"Expand"
);
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
auto
expand_times
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"expand_times"
);
...
...
@@ -38,11 +37,19 @@ class ExpandOp : public framework::OperatorWithKernel {
expand_times
=
std
::
vector
<
int
>
(
x_dims
.
size
(),
-
1
);
}
PADDLE_ENFORCE_EQ
(
static_cast
<
size_t
>
(
x_dims
.
size
()),
expand_times
.
size
(),
"The number of Attr(expand_times)'s value must be equal "
"to the rank of Input(X)."
);
PADDLE_ENFORCE_LE
(
x_dims
.
size
(),
6
,
"The rank of Input(X) must not be greater than 6."
);
PADDLE_ENFORCE_EQ
(
static_cast
<
size_t
>
(
x_dims
.
size
()),
expand_times
.
size
(),
platform
::
errors
::
InvalidArgument
(
"The number of elements (%d) of 'expand_times' for "
"Op(expand) must be equal to the number of dimensions "
"(%d) of the input."
,
expand_times
.
size
(),
static_cast
<
size_t
>
(
x_dims
.
size
())));
PADDLE_ENFORCE_LE
(
x_dims
.
size
(),
6
,
platform
::
errors
::
InvalidArgument
(
"The number of dimensions of the input for Op(expand) "
"must not be greater than 6, but the value received is %d."
,
x_dims
.
size
()));
std
::
vector
<
int64_t
>
out_shape
(
x_dims
.
size
());
for
(
size_t
i
=
0
;
i
<
expand_times
.
size
();
++
i
)
{
...
...
@@ -51,7 +58,10 @@ class ExpandOp : public framework::OperatorWithKernel {
}
else
{
PADDLE_ENFORCE_GT
(
expand_times
[
i
],
0
,
"The element of Attr(expand_times) must greater than 0."
);
platform
::
errors
::
InvalidArgument
(
"The %uth element of 'expand_times' for Op(expand) must be "
"greater than 0, but the value given is %d."
,
i
,
expand_times
[
i
]));
out_shape
[
i
]
=
x_dims
[
i
]
*
expand_times
[
i
];
}
}
...
...
@@ -139,9 +149,9 @@ class ExpandGradOp : public framework::OperatorWithKernel {
protected:
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"X"
),
true
,
"Input(X) should not be null.
"
);
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
true
,
"Input(Out@GRAD) should not be null.
"
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"X"
),
"Input"
,
"X"
,
"ExpandGrad
"
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
"Input"
,
framework
::
GradVarName
(
"Out"
),
"ExpandGrad
"
);
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
std
::
vector
<
int
>
expand_times
=
...
...
@@ -153,8 +163,10 @@ class ExpandGradOp : public framework::OperatorWithKernel {
if
(
!
ctx
->
IsRuntime
()
&&
x_dims
[
0
]
<
0
)
{
PADDLE_ENFORCE_EQ
(
x_dims
[
0
],
out_dims
[
0
],
"The first dimension size of Input(Out@GRAD) should be "
"equal to the crroresponding dimension size of Input(X)"
);
platform
::
errors
::
InvalidArgument
(
"The first dimension size (%d) of Input(Out@GRAD) should be "
"equal to the crroresponding dimension size (%d) of Input(X)"
,
out_dims
[
0
],
x_dims
[
0
]));
start_pos
=
1u
;
}
...
...
@@ -165,9 +177,11 @@ class ExpandGradOp : public framework::OperatorWithKernel {
if
(
ctx
->
IsRuntime
())
{
PADDLE_ENFORCE_EQ
(
x_dims
[
i
]
*
expand_times
[
i
],
out_dims
[
i
],
"Each dimension size of Input(Out@GRAD) should be "
"equal to multiplication of crroresponding dimension "
"size of Input(X) and Attr(expand_times) value."
);
platform
::
errors
::
InvalidArgument
(
"The %uth dimension size (%d) of Input(Out@GRAD) should be "
"equal to the multiplication of the crroresponding dimension "
"sizes of Input(X) (%d) and expand_times (%d)."
,
i
,
out_dims
[
i
],
x_dims
[
i
],
expand_times
[
i
]));
}
}
}
...
...
paddle/fluid/operators/expand_op.h
浏览文件 @
ca41e552
...
...
@@ -96,12 +96,19 @@ class ExpandKernel : public framework::OpKernel<T> {
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
rank
=
context
.
Input
<
Tensor
>
(
"X"
)
->
dims
().
size
();
switch
(
rank
)
{
REP_EXPAND_TEMPLATE
(
MAX_RANK_SUPPORTED
)
default:
PADDLE_ENFORCE
(
false
,
"Only support tensor with rank being between 1 and 6."
);
}
PADDLE_ENFORCE_GE
(
rank
,
1
,
platform
::
errors
::
InvalidArgument
(
"The number of dimensions of the input 'x' for Op(expand) "
"must be greater than or equal to 1, but the value received is %d."
,
rank
));
PADDLE_ENFORCE_LE
(
rank
,
MAX_RANK_SUPPORTED
,
platform
::
errors
::
InvalidArgument
(
"The number of dimensions of the input 'x' for Op(expand) "
"must be less than or equal to %d, but the value received is %d."
,
MAX_RANK_SUPPORTED
,
rank
));
switch
(
rank
)
{
REP_EXPAND_TEMPLATE
(
MAX_RANK_SUPPORTED
)
}
}
protected:
...
...
@@ -111,9 +118,13 @@ class ExpandKernel : public framework::OpKernel<T> {
auto
in_dims
=
in0
->
dims
();
auto
expand_times
=
get_expand_times
(
context
);
PADDLE_ENFORCE_EQ
(
static_cast
<
size_t
>
(
in_dims
.
size
()),
expand_times
.
size
(),
"The number of Attr(expand_times)'s value must be equal "
"to the rank of Input(X)."
);
PADDLE_ENFORCE_EQ
(
static_cast
<
size_t
>
(
in_dims
.
size
()),
expand_times
.
size
(),
platform
::
errors
::
InvalidArgument
(
"The number of elements (%d) of 'expand_times' for "
"Op(expand) must be equal to the number "
"of dimensions (%d) of the input."
,
expand_times
.
size
(),
static_cast
<
size_t
>
(
in_dims
.
size
())));
auto
*
out0
=
context
.
Output
<
Tensor
>
(
"Out"
);
Eigen
::
DSizes
<
int
,
Rank
>
bcast_dims
;
for
(
size_t
i
=
0
;
i
<
expand_times
.
size
();
++
i
)
{
...
...
@@ -172,12 +183,19 @@ class ExpandGradKernel : public framework::OpKernel<T> {
framework
::
TensorCopy
(
*
in0
,
context
.
GetPlace
(),
context
.
device_context
(),
out0
);
}
else
{
switch
(
dims
)
{
REP_EXPAND_GRAD_TEMPLATE
(
MAX_RANK_SUPPORTED
)
default:
PADDLE_ENFORCE
(
false
,
"Only support tensor with rank being between 1 and 6."
);
}
PADDLE_ENFORCE_GE
(
dims
,
1
,
platform
::
errors
::
InvalidArgument
(
"The number of dimensions of the input "
"'Out@GRAD' for Op(expand_grad)"
" must be greater than or equal to 1, but "
"the value received is %d."
,
dims
));
PADDLE_ENFORCE_LE
(
dims
,
MAX_RANK_SUPPORTED
,
platform
::
errors
::
InvalidArgument
(
"The number of dimensions of the input 'Out@GRAD' "
"for Op(expand_grad) must be less than or equal "
"to %d, but the value received is %d."
,
MAX_RANK_SUPPORTED
,
dims
));
switch
(
dims
)
{
REP_EXPAND_GRAD_TEMPLATE
(
MAX_RANK_SUPPORTED
)
}
}
}
...
...
@@ -189,11 +207,15 @@ class ExpandGradKernel : public framework::OpKernel<T> {
size_t
reshape_size
=
reshape_dims_vec
.
size
();
size_t
reduce_size
=
reduce_dims_vec
.
size
();
PADDLE_ENFORCE_EQ
(
reshape_size
,
reshape_dims_vec
.
size
(),
"Inconsistent size between template Dims and "
"reshape dimensions."
);
platform
::
errors
::
InvalidArgument
(
"Inconsistent size between template Dims (%d) and "
"reshape dimensions (%d)."
,
reshape_size
,
reshape_dims_vec
.
size
()));
PADDLE_ENFORCE_EQ
(
reduce_size
,
reduce_dims_vec
.
size
(),
"Inconsistent size between template Dims and "
"reduce dimensions."
);
platform
::
errors
::
InvalidArgument
(
"Inconsistent size between template Dims (%d) and "
"reduce dimensions (%d)."
,
reduce_size
,
reduce_dims_vec
.
size
()));
auto
*
in0
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
out0
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
out0
->
mutable_data
<
T
>
(
context
.
GetPlace
());
...
...
paddle/fluid/operators/merge_selected_rows_op.cc
浏览文件 @
ca41e552
...
...
@@ -23,16 +23,18 @@ class MergeSelectedRowsOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of MergeSelectedRowsOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of MergeSelectedRowsOp should not be null."
);
PADDLE_ENFORCE_EQ
(
ctx
->
GetInputsVarType
(
"X"
).
front
(),
framework
::
proto
::
VarType
::
SELECTED_ROWS
,
"Input X only should be SelectedRows."
);
PADDLE_ENFORCE_EQ
(
ctx
->
GetOutputsVarType
(
"Out"
).
front
(),
framework
::
proto
::
VarType
::
SELECTED_ROWS
,
"Output Y only should be SelectedRows."
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"X"
),
"Input"
,
"X"
,
"MergeSelectedRows"
);
OP_INOUT_CHECK
(
ctx
->
HasOutput
(
"Out"
),
"Output"
,
"Out"
,
"MergeSelectedRows"
);
PADDLE_ENFORCE_EQ
(
ctx
->
GetInputsVarType
(
"X"
).
front
(),
framework
::
proto
::
VarType
::
SELECTED_ROWS
,
platform
::
errors
::
InvalidArgument
(
"Input(X) of MergeSelectedRowsOp "
"should be of type SelectedRows."
));
PADDLE_ENFORCE_EQ
(
ctx
->
GetOutputsVarType
(
"Out"
).
front
(),
framework
::
proto
::
VarType
::
SELECTED_ROWS
,
platform
::
errors
::
InvalidArgument
(
"Output(Out) of MergeSelectedRowsOp "
"should be of type SelectedRows."
));
ctx
->
ShareDim
(
"X"
,
/*->*/
"Out"
);
}
...
...
paddle/fluid/operators/shard_index_op.cc
浏览文件 @
ca41e552
...
...
@@ -21,17 +21,21 @@ class ShardIndexOp : public framework::OperatorWithKernel {
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of ShardIndexOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of ShardIndexOp should not be null."
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"X"
),
"Input"
,
"X"
,
"ShardIndex"
);
OP_INOUT_CHECK
(
ctx
->
HasOutput
(
"Out"
),
"Output"
,
"Out"
,
"ShardIndex"
);
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
PADDLE_ENFORCE_GE
(
x_dims
.
size
(),
2
,
"Rank of Input(X) should be at least 2."
);
platform
::
errors
::
InvalidArgument
(
"Rank of Input(X) should be at least 2, "
"but the value given is %d."
,
x_dims
.
size
()));
if
(
ctx
->
IsRuntime
()
||
x_dims
[
x_dims
.
size
()
-
1
]
>
0
)
{
PADDLE_ENFORCE_GE
(
x_dims
[
x_dims
.
size
()
-
1
],
1U
,
"Last dimension of Input(X) should be 1."
);
platform
::
errors
::
InvalidArgument
(
"The last dimension of Input(X) should be 1, "
"but the value given is %d."
,
x_dims
[
x_dims
.
size
()
-
1
]));
}
ctx
->
SetOutputDim
(
"Out"
,
x_dims
);
...
...
paddle/fluid/operators/shard_index_op.cu
浏览文件 @
ca41e552
...
...
@@ -50,10 +50,29 @@ class ShardIndexCUDAKernel : public framework::OpKernel<T> {
int
nshards
=
context
.
Attr
<
int
>
(
"nshards"
);
int
shard_id
=
context
.
Attr
<
int
>
(
"shard_id"
);
int
ignore_value
=
context
.
Attr
<
int
>
(
"ignore_value"
);
PADDLE_ENFORCE_GT
(
index_num
,
0
);
PADDLE_ENFORCE_GT
(
nshards
,
0
);
PADDLE_ENFORCE
(
shard_id
>=
0
&&
shard_id
<
nshards
,
"shard_id(%d) is not in range [0, %d)"
,
shard_id
,
nshards
);
PADDLE_ENFORCE_GT
(
index_num
,
0
,
platform
::
errors
::
InvalidArgument
(
"The value 'index_num' for Op(shard_index) must be greater than 0, "
"but the value given is %d."
,
index_num
));
PADDLE_ENFORCE_GT
(
nshards
,
0
,
platform
::
errors
::
InvalidArgument
(
"The value 'nshard' for Op(shard_index) must be "
"greater than 0, but the value given is %d."
,
nshards
));
PADDLE_ENFORCE_GE
(
shard_id
,
0
,
platform
::
errors
::
InvalidArgument
(
"The value 'shard_id' for Op(shard_index) must be greater or "
"equal to 0, but the value given is %d."
,
shard_id
));
PADDLE_ENFORCE_LT
(
shard_id
,
nshards
,
platform
::
errors
::
InvalidArgument
(
"The value 'shard_id' for Op(shard_index) must be less than "
"nshards (%d), but the value given is %d."
,
nshards
,
shard_id
));
out
->
Resize
(
in
->
dims
());
out
->
set_lod
(
in
->
lod
());
...
...
paddle/fluid/operators/shard_index_op.h
浏览文件 @
ca41e552
...
...
@@ -29,10 +29,29 @@ class ShardIndexCPUKernel : public framework::OpKernel<T> {
int
nshards
=
context
.
Attr
<
int
>
(
"nshards"
);
int
shard_id
=
context
.
Attr
<
int
>
(
"shard_id"
);
int
ignore_value
=
context
.
Attr
<
int
>
(
"ignore_value"
);
PADDLE_ENFORCE_GT
(
index_num
,
0
);
PADDLE_ENFORCE_GT
(
nshards
,
0
);
PADDLE_ENFORCE
(
shard_id
>=
0
&&
shard_id
<
nshards
,
"shard_id(%d) is not in range [0, %d)"
,
shard_id
,
nshards
);
PADDLE_ENFORCE_GT
(
index_num
,
0
,
platform
::
errors
::
InvalidArgument
(
"The value 'index_num' for Op(shard_index) must be greater than 0, "
"but the value given is %d."
,
index_num
));
PADDLE_ENFORCE_GT
(
nshards
,
0
,
platform
::
errors
::
InvalidArgument
(
"The value 'nshard' for Op(shard_index) must be "
"greater than 0, but the value given is %d."
,
nshards
));
PADDLE_ENFORCE_GE
(
shard_id
,
0
,
platform
::
errors
::
InvalidArgument
(
"The value 'shard_id' for Op(shard_index) must be greater or "
"equal to 0, but the value given is %d."
,
shard_id
));
PADDLE_ENFORCE_LT
(
shard_id
,
nshards
,
platform
::
errors
::
InvalidArgument
(
"The value 'shard_id' for Op(shard_index) must be less than "
"nshards (%d), but the value given is %d."
,
nshards
,
shard_id
));
int
shard_size
=
(
index_num
+
nshards
-
1
)
/
nshards
;
...
...
@@ -42,9 +61,16 @@ class ShardIndexCPUKernel : public framework::OpKernel<T> {
auto
*
out_data
=
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
int64_t
numel
=
in
->
numel
();
for
(
int64_t
i
=
0
;
i
<
numel
;
++
i
)
{
PADDLE_ENFORCE
(
in_data
[
i
]
>=
0
&&
in_data
[
i
]
<
index_num
,
"Input index(%d) is out of range [0,%d)"
,
in_data
[
i
],
index_num
);
PADDLE_ENFORCE_GE
(
in_data
[
i
],
0
,
platform
::
errors
::
InvalidArgument
(
"The input_index for Op(shard_index) must be "
"greater or equal to 0, but the value given is %d."
,
in_data
[
i
]));
PADDLE_ENFORCE_LT
(
in_data
[
i
],
index_num
,
platform
::
errors
::
InvalidArgument
(
"The input_index for Op(shard_index) must be less "
"than index_num (%d), but the value given is %d."
,
index_num
,
in_data
[
i
]));
if
(
in_data
[
i
]
/
shard_size
==
shard_id
)
{
out_data
[
i
]
=
in_data
[
i
]
%
shard_size
;
}
else
{
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
ca41e552
...
...
@@ -9913,12 +9913,10 @@ def crop(x, shape=None, offsets=None, name=None):
crop = fluid.layers.crop(z, shape=[2, 2, 3])
"""
check_variable_and_dtype(x, 'x', ['float32'], 'crop')
check_type(shape, 'shape', (list, tuple, Variable), 'crop')
helper = LayerHelper('crop', **locals())
if not (isinstance(shape, list) or isinstance(shape, tuple) or \
isinstance(shape, Variable)):
raise ValueError("The shape should be a list, tuple or Variable.")
if offsets is None:
offsets = [0] * len(x.shape)
...
...
@@ -15580,6 +15578,7 @@ def shard_index(input, index_num, nshards, shard_id, ignore_value=-1):
nshards=2,
shard_id=0)
"""
check_variable_and_dtype(input, 'input', ['int64'], 'shard_index')
op_type = 'shard_index'
helper = LayerHelper(op_type, **locals())
if shard_id < 0 or shard_id >= nshards:
...
...
python/paddle/fluid/tests/unittests/test_layers.py
浏览文件 @
ca41e552
...
...
@@ -1840,6 +1840,14 @@ class TestLayer(LayerTest):
self
.
assertIsNotNone
(
out2
)
self
.
assertIsNotNone
(
out3
)
def
test_shard_index
(
self
):
with
self
.
static_graph
():
x
=
fluid
.
layers
.
data
(
name
=
"label"
,
shape
=
[
4
,
1
],
dtype
=
'int64'
)
shard_label
=
fluid
.
layers
.
shard_index
(
input
=
x
,
index_num
=
20
,
nshards
=
2
,
shard_id
=
0
)
self
.
assertIsNotNone
(
shard_label
)
def
test_accuracy
(
self
):
x
=
np
.
random
.
rand
(
3
,
32
,
32
).
astype
(
"float32"
)
y
=
np
.
array
([[
1
],
[
0
],
[
1
]])
...
...
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