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体验新版 GitCode,发现更多精彩内容 >>
提交
544458e0
编写于
9月 07, 2017
作者:
F
fengjiayi
提交者:
GitHub
9月 07, 2017
浏览文件
操作
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差异文件
Merge pull request #3888 from Canpio/dev_add_axis
Add axis for `mul_op` and `rowwise_add_op`
上级
d7079cea
856611cc
变更
14
隐藏空白更改
内联
并排
Showing
14 changed file
with
301 addition
and
52 deletion
+301
-52
paddle/framework/attribute.h
paddle/framework/attribute.h
+18
-1
paddle/framework/ddim.cc
paddle/framework/ddim.cc
+9
-0
paddle/framework/ddim.h
paddle/framework/ddim.h
+6
-0
paddle/framework/eigen.h
paddle/framework/eigen.h
+20
-5
paddle/framework/eigen_test.cc
paddle/framework/eigen_test.cc
+19
-0
paddle/framework/tensor.h
paddle/framework/tensor.h
+3
-0
paddle/framework/tensor_impl.h
paddle/framework/tensor_impl.h
+8
-0
paddle/framework/tensor_test.cc
paddle/framework/tensor_test.cc
+13
-0
paddle/operators/mul_op.cc
paddle/operators/mul_op.cc
+50
-14
paddle/operators/mul_op.h
paddle/operators/mul_op.h
+40
-12
paddle/operators/rowwise_add_op.cc
paddle/operators/rowwise_add_op.cc
+25
-13
paddle/operators/rowwise_add_op.h
paddle/operators/rowwise_add_op.h
+11
-6
python/paddle/v2/framework/tests/test_mul_op.py
python/paddle/v2/framework/tests/test_mul_op.py
+49
-1
python/paddle/v2/framework/tests/test_rowwise_add_op.py
python/paddle/v2/framework/tests/test_rowwise_add_op.py
+30
-0
未找到文件。
paddle/framework/attribute.h
浏览文件 @
544458e0
...
...
@@ -45,7 +45,19 @@ class GreaterThanChecker {
public:
explicit
GreaterThanChecker
(
T
lower_bound
)
:
lower_bound_
(
lower_bound
)
{}
void
operator
()(
T
&
value
)
const
{
PADDLE_ENFORCE
(
value
>
lower_bound_
,
"larger_than check fail"
);
PADDLE_ENFORCE
(
value
>
lower_bound_
,
"larger_than check fails."
);
}
private:
T
lower_bound_
;
};
template
<
typename
T
>
class
EqualGreaterThanChecker
{
public:
explicit
EqualGreaterThanChecker
(
T
lower_bound
)
:
lower_bound_
(
lower_bound
)
{}
void
operator
()(
T
&
value
)
const
{
PADDLE_ENFORCE_GE
(
value
,
lower_bound_
,
"equal_larger_than check fails."
);
}
private:
...
...
@@ -115,6 +127,11 @@ class TypedAttrChecker {
return
*
this
;
}
TypedAttrChecker
&
EqualGreaterThan
(
const
T
&
lower_bound
)
{
value_checkers_
.
push_back
(
EqualGreaterThanChecker
<
T
>
(
lower_bound
));
return
*
this
;
}
// we can add more common limits, like LessThan(), Between()...
TypedAttrChecker
&
SetDefault
(
const
T
&
default_value
)
{
...
...
paddle/framework/ddim.cc
浏览文件 @
544458e0
...
...
@@ -283,5 +283,14 @@ std::ostream& operator<<(std::ostream& os, const DDim& ddim) {
DDim
::
DDim
(
std
::
initializer_list
<
int64_t
>
init_list
)
{
*
this
=
make_ddim
(
init_list
);
}
DDim
flatten_to_2d
(
const
DDim
&
src
,
int
num_col_dims
)
{
int
rank
=
src
.
size
();
return
make_ddim
({
product
(
slice_ddim
(
src
,
0
,
num_col_dims
)),
product
(
slice_ddim
(
src
,
num_col_dims
,
rank
))});
}
DDim
flatten_to_1d
(
const
DDim
&
src
)
{
return
make_ddim
({
product
(
src
)});
}
}
// namespace framework
}
// namespace paddle
paddle/framework/ddim.h
浏览文件 @
544458e0
...
...
@@ -115,6 +115,12 @@ int arity(const DDim& ddim);
std
::
ostream
&
operator
<<
(
std
::
ostream
&
,
const
DDim
&
);
// Reshape a tensor to a matrix. The matrix's first dimension(column length)
// will be the product of tensor's first `num_col_dims` dimensions.
DDim
flatten_to_2d
(
const
DDim
&
src
,
int
num_col_dims
);
DDim
flatten_to_1d
(
const
DDim
&
src
);
}
// namespace framework
}
// namespace paddle
...
...
paddle/framework/eigen.h
浏览文件 @
544458e0
...
...
@@ -63,20 +63,35 @@ struct EigenTensor {
template
<
typename
T
,
int
MajorType
=
Eigen
::
RowMajor
,
typename
IndexType
=
Eigen
::
DenseIndex
>
struct
EigenMatrix
:
public
EigenTensor
<
T
,
2
,
MajorType
,
IndexType
>
{};
struct
EigenMatrix
:
public
EigenTensor
<
T
,
2
,
MajorType
,
IndexType
>
{
static
typename
EigenMatrix
::
Type
Reshape
(
Tensor
&
tensor
,
int
num_col_dims
)
{
int
rank
=
tensor
.
dims_
.
size
();
PADDLE_ENFORCE
(
num_col_dims
>
0
&&
num_col_dims
<
rank
,
"`num_col_dims` must be between (0, rank_of_tensor)."
);
return
EigenMatrix
::
From
(
tensor
,
flatten_to_2d
(
tensor
.
dims
(),
num_col_dims
));
}
static
typename
EigenMatrix
::
ConstType
Reshape
(
const
Tensor
&
tensor
,
int
num_col_dims
)
{
int
rank
=
tensor
.
dims_
.
size
();
PADDLE_ENFORCE
(
num_col_dims
>
0
&&
num_col_dims
<
rank
,
"`num_col_dims` must be between (0, rank_of_tensor)."
);
return
EigenMatrix
::
From
(
tensor
,
flatten_to_2d
(
tensor
.
dims
(),
num_col_dims
));
}
};
template
<
typename
T
,
int
MajorType
=
Eigen
::
RowMajor
,
typename
IndexType
=
Eigen
::
DenseIndex
>
struct
EigenVector
:
public
EigenTensor
<
T
,
1
,
MajorType
,
IndexType
>
{
// Flatten reshapes a Tensor into an EigenVector.
static
typename
EigenVector
::
Type
Flatten
(
Tensor
&
tensor
)
{
return
EigenVector
::
From
(
tensor
,
make_ddim
({
static_cast
<
int
>
(
product
(
tensor
.
dims_
))}));
return
EigenVector
::
From
(
tensor
,
{
product
(
tensor
.
dims_
)});
}
static
typename
EigenVector
::
ConstType
Flatten
(
const
Tensor
&
tensor
)
{
return
EigenVector
::
From
(
tensor
,
make_ddim
({
static_cast
<
int
>
(
product
(
tensor
.
dims_
))}));
return
EigenVector
::
From
(
tensor
,
{
product
(
tensor
.
dims_
)});
}
};
...
...
paddle/framework/eigen_test.cc
浏览文件 @
544458e0
...
...
@@ -108,5 +108,24 @@ TEST(Eigen, Matrix) {
}
}
TEST
(
Eigen
,
MatrixReshape
)
{
Tensor
t
;
float
*
p
=
t
.
mutable_data
<
float
>
({
2
,
3
,
6
,
4
},
platform
::
CPUPlace
());
for
(
int
i
=
0
;
i
<
2
*
3
*
6
*
4
;
++
i
)
{
p
[
i
]
=
static_cast
<
float
>
(
i
);
}
EigenMatrix
<
float
>::
Type
em
=
EigenMatrix
<
float
>::
Reshape
(
t
,
2
);
ASSERT_EQ
(
2
*
3
,
em
.
dimension
(
0
));
ASSERT_EQ
(
6
*
4
,
em
.
dimension
(
1
));
for
(
int
i
=
0
;
i
<
2
*
3
;
i
++
)
{
for
(
int
j
=
0
;
j
<
6
*
4
;
j
++
)
{
ASSERT_NEAR
(
i
*
6
*
4
+
j
,
em
(
i
,
j
),
1e-6
f
);
}
}
}
}
// namespace framework
}
// namespace paddle
paddle/framework/tensor.h
浏览文件 @
544458e0
...
...
@@ -43,6 +43,9 @@ class Tensor {
template
<
typename
T
,
size_t
D
,
int
MajorType
,
typename
IndexType
>
friend
struct
EigenTensor
;
template
<
typename
T
,
int
MajorType
,
typename
IndexType
>
friend
struct
EigenMatrix
;
template
<
typename
T
,
int
MajorType
,
typename
IndexType
>
friend
struct
EigenVector
;
...
...
paddle/framework/tensor_impl.h
浏览文件 @
544458e0
...
...
@@ -148,5 +148,13 @@ inline Tensor& Tensor::Resize(const DDim& dims) {
inline
const
DDim
&
Tensor
::
dims
()
const
{
return
dims_
;
}
template
<
typename
T
>
inline
Tensor
ReshapeToMatrix
(
const
Tensor
&
src
,
int
num_col_dims
)
{
Tensor
res
;
res
.
ShareDataWith
<
T
>
(
src
);
res
.
Resize
(
flatten_to_2d
(
src
.
dims
(),
num_col_dims
));
return
res
;
}
}
// namespace framework
}
// namespace paddle
paddle/framework/tensor_test.cc
浏览文件 @
544458e0
...
...
@@ -262,3 +262,16 @@ TEST(Tensor, CopyFrom) {
}
#endif
}
TEST
(
Tensor
,
ReshapeToMatrix
)
{
using
namespace
paddle
::
framework
;
using
namespace
paddle
::
platform
;
Tensor
src
;
int
*
src_ptr
=
src
.
mutable_data
<
int
>
({
2
,
3
,
4
,
9
},
CPUPlace
());
for
(
int
i
=
0
;
i
<
2
*
3
*
4
*
9
;
++
i
)
{
src_ptr
[
i
]
=
i
;
}
Tensor
res
=
ReshapeToMatrix
<
int
>
(
src
,
2
);
ASSERT_EQ
(
res
.
dims
()[
0
],
2
*
3
);
ASSERT_EQ
(
res
.
dims
()[
1
],
4
*
9
);
}
\ No newline at end of file
paddle/operators/mul_op.cc
浏览文件 @
544458e0
...
...
@@ -25,18 +25,27 @@ class MulOp : public framework::OperatorWithKernel {
protected:
void
InferShape
(
const
framework
::
InferShapeContext
&
ctx
)
const
override
{
auto
dim0
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
auto
dim1
=
ctx
.
Input
<
Tensor
>
(
"Y"
)
->
dims
();
PADDLE_ENFORCE_EQ
(
dim0
.
size
(),
2
,
"input X(%s) should be a tensor with 2 dims, a matrix"
,
ctx
.
op
().
Input
(
"X"
));
PADDLE_ENFORCE_EQ
(
dim1
.
size
(),
2
,
"input Y(%s) should be a tensor with 2 dims, a matrix"
,
ctx
.
op
().
Input
(
"Y"
));
auto
x_dims
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
auto
y_dims
=
ctx
.
Input
<
Tensor
>
(
"Y"
)
->
dims
();
int
x_num_col_dims
=
Attr
<
int
>
(
"x_num_col_dims"
);
int
y_num_col_dims
=
Attr
<
int
>
(
"y_num_col_dims"
);
PADDLE_ENFORCE
(
x_dims
.
size
()
>
x_num_col_dims
,
"The rank of input tensor X(%s) should be larger than "
"`mul_op`'s `x_num_col_dims`."
,
ctx
.
op
().
Input
(
"X"
));
PADDLE_ENFORCE
(
y_dims
.
size
()
>
y_num_col_dims
,
"The rank of input tensor Y(%s) should be larger than "
"`mul_op`'s `y_num_col_dims`."
,
ctx
.
op
().
Input
(
"Y"
));
auto
x_mat_dims
=
framework
::
flatten_to_2d
(
x_dims
,
x_num_col_dims
);
auto
y_mat_dims
=
framework
::
flatten_to_2d
(
y_dims
,
y_num_col_dims
);
PADDLE_ENFORCE_EQ
(
dim0
[
1
],
dim1
[
0
],
x_mat_dims
[
1
],
y_mat_dims
[
0
],
"First matrix's width must be equal with second matrix's height."
);
ctx
.
Output
<
Tensor
>
(
"Out"
)
->
Resize
({
dim0
[
0
],
dim1
[
1
]});
ctx
.
Output
<
Tensor
>
(
"Out"
)
->
Resize
({
x_mat_dims
[
0
],
y_mat_dims
[
1
]});
}
};
...
...
@@ -47,6 +56,23 @@ class MulOpMaker : public framework::OpProtoAndCheckerMaker {
AddInput
(
"X"
,
"The first input of mul op"
);
AddInput
(
"Y"
,
"The second input of mul op"
);
AddOutput
(
"Out"
,
"The output of mul op"
);
AddAttr
<
int
>
(
"x_num_col_dims"
,
R"DOC(mul_op can take tensors with more than two dimensions as input `X`,
in that case, tensors will be reshaped to a matrix. The matrix's first
dimension(column length) will be the product of tensor's last
`num_col_dims` dimensions, and the matrix's second dimension(row length)
will be the product of tensor's first `rank - num_col_dims` dimensions.
)DOC"
)
.
SetDefault
(
1
)
.
EqualGreaterThan
(
1
);
AddAttr
<
int
>
(
"y_num_col_dims"
,
R"DOC(mul_op can take tensors with more than two dimensions as input `Y`,
in that case, tensors will be reshaped to a matrix. Just like input `X`.
)DOC"
)
.
SetDefault
(
1
)
.
EqualGreaterThan
(
1
);
AddComment
(
R"DOC(
Two Element Mul Operator.
...
...
@@ -70,10 +96,20 @@ class MulOpGrad : public framework::OperatorWithKernel {
auto
out_dims
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
))
->
dims
();
auto
*
x_grad
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
y_grad
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
PADDLE_ENFORCE
(
x_dims
[
0
]
==
out_dims
[
0
],
"Out@GRAD M X N must equal to X dims 0, M "
);
PADDLE_ENFORCE
(
y_dims
[
1
]
==
out_dims
[
1
],
"Out@GRAD M X N must equal to Y dims 1, N "
);
auto
x_mat_dims
=
framework
::
flatten_to_2d
(
x_dims
,
Attr
<
int
>
(
"x_num_col_dims"
));
auto
y_mat_dims
=
framework
::
flatten_to_2d
(
y_dims
,
Attr
<
int
>
(
"y_num_col_dims"
));
PADDLE_ENFORCE_EQ
(
x_mat_dims
[
0
],
out_dims
[
0
],
"The first dimension of Out@GRAD must equal to the first dimension of "
"the first operand."
);
PADDLE_ENFORCE_EQ
(
y_mat_dims
[
1
],
out_dims
[
1
],
"The second dimension of Out@GRAD must equal to the second "
"dimension of the second operand."
);
if
(
x_grad
)
x_grad
->
Resize
(
x_dims
);
if
(
y_grad
)
y_grad
->
Resize
(
y_dims
);
...
...
paddle/operators/mul_op.h
浏览文件 @
544458e0
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
y
ou may not use this file except in compliance with the License.
Y
ou 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
...
...
@@ -31,13 +31,25 @@ template <typename Place, typename T>
class
MulKernel
:
public
framework
::
OpKernel
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
*
x
=
context
.
Input
<
Tensor
>
(
"X"
);
auto
*
y
=
context
.
Input
<
Tensor
>
(
"Y"
);
auto
*
z
=
context
.
Output
<
Tensor
>
(
"Out"
);
const
Tensor
*
x
=
context
.
Input
<
Tensor
>
(
"X"
);
const
Tensor
*
y
=
context
.
Input
<
Tensor
>
(
"Y"
);
Tensor
*
z
=
context
.
Output
<
Tensor
>
(
"Out"
);
const
Tensor
x_matrix
=
x
->
dims
().
size
()
>
2
?
framework
::
ReshapeToMatrix
<
T
>
(
*
x
,
context
.
template
Attr
<
int
>(
"x_num_col_dims"
))
:
*
x
;
const
Tensor
y_matrix
=
y
->
dims
().
size
()
>
2
?
framework
::
ReshapeToMatrix
<
T
>
(
*
y
,
context
.
template
Attr
<
int
>(
"y_num_col_dims"
))
:
*
y
;
z
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
*
device_context
=
const_cast
<
platform
::
DeviceContext
*>
(
context
.
device_context_
);
math
::
matmul
<
Place
,
T
>
(
*
x
,
false
,
*
y
,
false
,
1
,
z
,
0
,
device_context
);
math
::
matmul
<
Place
,
T
>
(
x_matrix
,
false
,
y_matrix
,
false
,
1
,
z
,
0
,
device_context
);
}
};
...
...
@@ -45,23 +57,39 @@ template <typename Place, typename T>
class
MulGradKernel
:
public
framework
::
OpKernel
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
*
x
=
ctx
.
Input
<
Tensor
>
(
"X"
);
auto
*
y
=
ctx
.
Input
<
Tensor
>
(
"Y"
);
auto
*
dout
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
int
x_num_col_dims
=
ctx
.
template
Attr
<
int
>(
"x_num_col_dims"
);
int
y_num_col_dims
=
ctx
.
template
Attr
<
int
>(
"y_num_col_dims"
);
const
Tensor
*
x
=
ctx
.
Input
<
Tensor
>
(
"X"
);
const
Tensor
*
y
=
ctx
.
Input
<
Tensor
>
(
"Y"
);
const
Tensor
x_matrix
=
x
->
dims
().
size
()
>
2
?
framework
::
ReshapeToMatrix
<
T
>
(
*
x
,
x_num_col_dims
)
:
*
x
;
const
Tensor
y_matrix
=
y
->
dims
().
size
()
>
2
?
framework
::
ReshapeToMatrix
<
T
>
(
*
y
,
y_num_col_dims
)
:
*
y
;
const
Tensor
*
dout
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
dx
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
dy
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
Tensor
*
dx
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
Tensor
*
dy
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
auto
*
device_context
=
const_cast
<
platform
::
DeviceContext
*>
(
ctx
.
device_context_
);
if
(
dx
)
{
dx
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
Tensor
dx_matrix
=
dx
->
dims
().
size
()
>
2
?
framework
::
ReshapeToMatrix
<
T
>
(
*
dx
,
x_num_col_dims
)
:
*
dx
;
// dx = dout * y'. dx: M x K, dout : M x N, y : K x N
math
::
matmul
<
Place
,
T
>
(
*
dout
,
false
,
*
y
,
true
,
1
,
dx
,
0
,
device_context
);
math
::
matmul
<
Place
,
T
>
(
*
dout
,
false
,
y_matrix
,
true
,
1
,
&
dx_matrix
,
0
,
device_context
);
}
if
(
dy
)
{
dy
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
Tensor
dy_matrix
=
dy
->
dims
().
size
()
>
2
?
framework
::
ReshapeToMatrix
<
T
>
(
*
dy
,
y_num_col_dims
)
:
*
dy
;
// dy = x' * dout. dy K x N, dout : M x N, x : M x K
math
::
matmul
<
Place
,
T
>
(
*
x
,
true
,
*
dout
,
false
,
1
,
dy
,
0
,
device_context
);
math
::
matmul
<
Place
,
T
>
(
x_matrix
,
true
,
*
dout
,
false
,
1
,
&
dy_matrix
,
0
,
device_context
);
}
}
};
...
...
paddle/operators/rowwise_add_op.cc
浏览文件 @
544458e0
...
...
@@ -25,14 +25,19 @@ class RowwiseAddOp : public framework::OperatorWithKernel {
protected:
void
InferShape
(
const
framework
::
InferShapeContext
&
ctx
)
const
override
{
auto
dim0
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
auto
dim1
=
ctx
.
Input
<
Tensor
>
(
"b"
)
->
dims
();
PADDLE_ENFORCE
(
dim0
.
size
()
==
2
,
"Input 0 must be matrix"
);
PADDLE_ENFORCE
(
dim1
.
size
()
==
1
,
"The second input must be vector"
);
PADDLE_ENFORCE
(
dim0
[
1
]
==
dim1
[
0
],
"The width of two input must be same"
);
PADDLE_ENFORCE
(
ctx
.
OutputSize
(
"Out"
)
==
1
,
"The output size must be 1"
);
ctx
.
Output
<
Tensor
>
(
"Out"
)
->
Resize
(
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
());
auto
x_dims
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
auto
b_dims
=
ctx
.
Input
<
Tensor
>
(
"b"
)
->
dims
();
PADDLE_ENFORCE_GT
(
x_dims
.
size
(),
b_dims
.
size
(),
"The rank of input `X` must be larger than the one of input `b`."
);
int
num_col_dims
=
x_dims
.
size
()
-
b_dims
.
size
();
PADDLE_ENFORCE_EQ
(
framework
::
slice_ddim
(
x_dims
,
num_col_dims
,
x_dims
.
size
()),
b_dims
,
"The width of two operands must be same"
);
PADDLE_ENFORCE_EQ
(
ctx
.
OutputSize
(
"Out"
),
1
,
"The output size must be 1"
);
ctx
.
Output
<
Tensor
>
(
"Out"
)
->
Resize
(
x_dims
);
}
};
...
...
@@ -61,13 +66,20 @@ class RowwiseAddGradOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
InputVar
(
"b"
),
"b should not be null"
);
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
InputVar
(
framework
::
GradVarName
(
"Out"
)),
"Input(Out@GRAD) should not be null"
);
auto
dims0
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
auto
dims1
=
ctx
.
Input
<
Tensor
>
(
"b"
)
->
dims
();
PADDLE_ENFORCE_EQ
(
1
,
dims1
.
size
(),
"b dims should be 1"
)
auto
x_dims
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
auto
b_dims
=
ctx
.
Input
<
Tensor
>
(
"b"
)
->
dims
();
PADDLE_ENFORCE_GT
(
x_dims
.
size
(),
b_dims
.
size
(),
"The rank of input `X` must be larger than the one of input `b`."
);
int
num_col_dims
=
x_dims
.
size
()
-
b_dims
.
size
();
PADDLE_ENFORCE_EQ
(
framework
::
slice_ddim
(
x_dims
,
num_col_dims
,
x_dims
.
size
()),
b_dims
,
"The width of two operands must be same"
);
auto
*
dx
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
db
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"b"
));
if
(
dx
)
dx
->
Resize
(
dims0
);
if
(
db
)
db
->
Resize
(
dims1
);
if
(
dx
)
dx
->
Resize
(
x_dims
);
if
(
db
)
db
->
Resize
(
b_dims
);
}
};
...
...
paddle/operators/rowwise_add_op.h
浏览文件 @
544458e0
...
...
@@ -33,10 +33,12 @@ class RowwiseAddKernel : public framework::OpKernel {
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
out
=
context
.
Output
<
Tensor
>
(
"Out"
);
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
input
=
EigenMatrix
<
T
>::
From
(
*
context
.
Input
<
Tensor
>
(
"X"
));
auto
bias
=
EigenVector
<
T
>::
From
(
*
context
.
Input
<
Tensor
>
(
"b"
));
auto
output
=
EigenMatrix
<
T
>::
From
(
*
out
);
int
num_col_dims
=
context
.
Input
<
Tensor
>
(
"X"
)
->
dims
().
size
()
-
context
.
Input
<
Tensor
>
(
"b"
)
->
dims
().
size
();
auto
input
=
EigenMatrix
<
T
>::
Reshape
(
*
context
.
Input
<
Tensor
>
(
"X"
),
num_col_dims
);
auto
bias
=
EigenVector
<
T
>::
Flatten
(
*
context
.
Input
<
Tensor
>
(
"b"
));
auto
output
=
EigenMatrix
<
T
>::
Reshape
(
*
out
,
num_col_dims
);
const
int
bias_size
=
bias
.
dimension
(
0
);
const
int
rest_size
=
input
.
size
()
/
bias_size
;
...
...
@@ -54,12 +56,15 @@ class RowwiseAddGradKernel : public framework::OpKernel {
auto
*
dout
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
dx
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
db
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"b"
));
int
num_col_dims
=
context
.
Input
<
Tensor
>
(
"X"
)
->
dims
().
size
()
-
context
.
Input
<
Tensor
>
(
"b"
)
->
dims
().
size
();
auto
out_grad
=
EigenMatrix
<
T
>::
From
(
*
dout
);
auto
out_grad
=
EigenMatrix
<
T
>::
Reshape
(
*
dout
,
num_col_dims
);
auto
place
=
context
.
GetEigenDevice
<
Place
>
();
if
(
dx
)
{
dx
->
mutable_data
<
T
>
(
context
.
GetPlace
());
EigenMatrix
<
T
>::
From
(
*
dx
).
device
(
place
)
=
out_grad
;
EigenMatrix
<
T
>::
Reshape
(
*
dx
,
num_col_dims
).
device
(
place
)
=
out_grad
;
}
if
(
db
)
{
...
...
python/paddle/v2/framework/tests/test_mul_op.py
浏览文件 @
544458e0
...
...
@@ -2,6 +2,7 @@ import unittest
import
numpy
as
np
from
gradient_checker
import
GradientChecker
,
create_op
from
op_test_util
import
OpTestMeta
from
paddle.v2.framework.op
import
Operator
class
TestMulOp
(
unittest
.
TestCase
):
...
...
@@ -16,6 +17,22 @@ class TestMulOp(unittest.TestCase):
self
.
outputs
=
{
'Out'
:
np
.
dot
(
self
.
inputs
[
'X'
],
self
.
inputs
[
'Y'
])}
class
TestMulOp2
(
unittest
.
TestCase
):
__metaclass__
=
OpTestMeta
def
setUp
(
self
):
self
.
type
=
"mul"
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
15
,
4
,
12
,
10
)).
astype
(
"float32"
),
'Y'
:
np
.
random
.
random
((
4
,
30
,
8
,
2
,
9
)).
astype
(
"float32"
)
}
self
.
attrs
=
{
'x_num_col_dims'
:
2
,
'y_num_col_dims'
:
2
}
self
.
outputs
=
{
'Out'
:
np
.
dot
(
self
.
inputs
[
'X'
].
reshape
(
15
*
4
,
12
*
10
),
self
.
inputs
[
'Y'
].
reshape
(
4
*
30
,
8
*
2
*
9
))
}
class
TestMulGradOp
(
GradientChecker
):
def
setUp
(
self
):
self
.
op
=
create_op
(
"mul"
)
...
...
@@ -49,7 +66,38 @@ class TestMulGradOp(GradientChecker):
no_grad_set
=
{
"Y"
})
# TODO(dzh,qijun) : mulgrad test case need transpose feature of blas library
class
TestMulGradTest2
(
GradientChecker
):
def
setUp
(
self
):
self
.
op
=
Operator
(
"mul"
,
X
=
"X"
,
Y
=
"Y"
,
Out
=
"Out"
,
x_num_col_dims
=
2
,
y_num_col_dims
=
2
)
self
.
inputs
=
{
"X"
:
np
.
random
.
random
((
15
,
4
,
12
,
10
)).
astype
(
"float32"
),
"Y"
:
np
.
random
.
random
((
4
,
30
,
8
,
2
,
9
)).
astype
(
"float32"
)
}
def
test_cpu_gpu_compare
(
self
):
self
.
compare_grad
(
self
.
op
,
self
.
inputs
)
def
test_normal
(
self
):
self
.
check_grad
(
self
.
op
,
self
.
inputs
,
[
"X"
,
"Y"
],
"Out"
,
max_relative_error
=
0.5
)
def
test_ignore_x
(
self
):
self
.
check_grad
(
self
.
op
,
self
.
inputs
,
[
"Y"
],
"Out"
,
max_relative_error
=
0.5
,
no_grad_set
=
{
"X"
})
def
test_ignore_y
(
self
):
self
.
check_grad
(
self
.
op
,
self
.
inputs
,
[
"X"
],
"Out"
,
max_relative_error
=
0.5
,
no_grad_set
=
{
"Y"
})
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/v2/framework/tests/test_rowwise_add_op.py
浏览文件 @
544458e0
...
...
@@ -16,6 +16,18 @@ class TestRowwiseAddOp(unittest.TestCase):
self
.
outputs
=
{
'Out'
:
np
.
add
(
self
.
inputs
[
'X'
],
self
.
inputs
[
'b'
])}
class
TestRowwiseAddOp2
(
unittest
.
TestCase
):
__metaclass__
=
OpTestMeta
def
setUp
(
self
):
self
.
type
=
"rowwise_add"
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
13
,
6
,
7
,
8
)).
astype
(
"float32"
),
'b'
:
np
.
random
.
random
((
7
,
8
)).
astype
(
"float32"
)
}
self
.
outputs
=
{
'Out'
:
np
.
add
(
self
.
inputs
[
'X'
],
self
.
inputs
[
'b'
])}
class
TestRowwiseAddGradOp
(
GradientChecker
):
def
setUp
(
self
):
self
.
op
=
create_op
(
"rowwise_add"
)
...
...
@@ -34,5 +46,23 @@ class TestRowwiseAddGradOp(GradientChecker):
self
.
check_grad
(
self
.
op
,
self
.
inputs
,
[
"b"
],
"Out"
,
no_grad_set
=
{
"X"
})
class
TestRowwiseAddGradOp2
(
GradientChecker
):
def
setUp
(
self
):
self
.
op
=
create_op
(
"rowwise_add"
)
self
.
inputs
=
{
"X"
:
np
.
random
.
uniform
(
0.1
,
1
,
[
2
,
3
,
2
,
5
]).
astype
(
"float32"
),
"b"
:
np
.
random
.
uniform
(
0.1
,
1
,
[
2
,
5
]).
astype
(
"float32"
)
}
def
test_normal
(
self
):
self
.
check_grad
(
self
.
op
,
self
.
inputs
,
[
"X"
,
"b"
],
"Out"
)
def
test_ignore_b
(
self
):
self
.
check_grad
(
self
.
op
,
self
.
inputs
,
[
"X"
],
"Out"
,
no_grad_set
=
{
"b"
})
def
test_ignore_x
(
self
):
self
.
check_grad
(
self
.
op
,
self
.
inputs
,
[
"b"
],
"Out"
,
no_grad_set
=
{
"X"
})
if
__name__
==
'__main__'
:
unittest
.
main
()
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