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0b21b854
编写于
9月 14, 2017
作者:
L
Liu Yiqun
浏览文件
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电子邮件补丁
差异文件
Make the weights of FCOp a fixed 2-D matrix and refine some comments in FCOp.
上级
af2eb949
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
49 addition
and
35 deletion
+49
-35
paddle/operators/fc_op.cc
paddle/operators/fc_op.cc
+44
-26
python/paddle/v2/framework/tests/test_fc_op.py
python/paddle/v2/framework/tests/test_fc_op.py
+5
-9
未找到文件。
paddle/operators/fc_op.cc
浏览文件 @
0b21b854
...
...
@@ -41,21 +41,16 @@ class FCOp : public NetOp {
"The size of inputs X(%d) should be no less than 1."
,
n
);
auto
x_num_col_dims
=
Attr
<
std
::
vector
<
int
>>
(
"xNumColDims"
);
auto
w_num_col_dims
=
Attr
<
std
::
vector
<
int
>>
(
"wNumColDims"
);
PADDLE_ENFORCE_EQ
(
x_num_col_dims
.
size
(),
n
,
"The size of attribute xNumColDims(%d) should be the "
"same as that of inputs X(%d)."
,
x_num_col_dims
.
size
(),
n
);
PADDLE_ENFORCE_EQ
(
w_num_col_dims
.
size
(),
n
,
"The size of attribute wNumColDims(%d) should be the "
"same as that of inputs X(%d)."
,
w_num_col_dims
.
size
(),
n
)
// mul_out[i] = X[i] * W[i]
for
(
size_t
i
=
0
;
i
<
n
;
i
++
)
{
framework
::
AttributeMap
mul_attr
;
mul_attr
[
"x_num_col_dims"
]
=
static_cast
<
int
>
(
x_num_col_dims
[
i
]);
mul_attr
[
"y_num_col_dims"
]
=
static_cast
<
int
>
(
w_num_col_dims
[
i
]
);
mul_attr
[
"y_num_col_dims"
]
=
static_cast
<
int
>
(
1
);
AppendOp
(
framework
::
OpRegistry
::
CreateOp
(
"mul"
,
{{
"X"
,
{
x
[
i
]}},
{
"Y"
,
{
w
[
i
]}}},
{{
"Out"
,
{
mul_out
[
i
]}}},
mul_attr
));
...
...
@@ -95,30 +90,54 @@ class FCOpMaker : public framework::OpProtoAndCheckerMaker {
public:
FCOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"The inputs of FC operator, a ordered vector of 2-D matrix."
)
AddInput
(
"X"
,
"(A vector of Tensors) each input Tensor can be of arbitrary "
"dimension, and will be reshaped to a 2-D matrix of size "
"(minibatch, number_of_input_features) according to attribute "
"xNumColDims."
)
.
AsDuplicable
();
AddInput
(
"W"
,
"The weights of FC operator, a ordered vector of 2-D matrix."
)
AddInput
(
"W"
,
"(A vector of Tensors) the weights of FC operator, a "
"vector of 2-D matrix of size "
"(number_of_input_features, number_of_neurons)."
)
.
AsDuplicable
();
AddInput
(
"B"
,
"The 1-D bias vector of FC operator"
);
AddInput
(
"B"
,
"(Tensor) the bias of FC operator, a 1-D vector of size "
"number_of_neurons."
);
AddOutput
(
"Y"
,
"The activated output matrix of FC operator"
);
AddOutput
(
"Y"
,
"(Tensor) the activated output matrix of FC operator, a 2-D "
"matrix of size (minibatch, number_of_neurons)."
);
AddOutput
(
"MulOut"
,
"
T
he intermediate outputs of FC operator, "
"
saving the product of X[i] * W[i]
"
)
"
(A vector of Tensors) t
he intermediate outputs of FC operator, "
"
each Tensor saving the product of X_i * W_i.
"
)
.
AsIntermediate
()
.
AsDuplicable
();
AddOutput
(
"SumOut"
,
"The intermediate output of FC operator, "
"saving the sum of products, sum(X[i] * W[i])"
)
AddOutput
(
"SumOut"
,
"(Tensor) the intermediate output of FC operator, "
"saving the sum of the products of X and W, that is sum{X_i * W_i}."
)
.
AsIntermediate
();
AddOutput
(
"AddOut"
,
"The non-actived output of FC operator, saving X * W + b"
)
"(Tensor) the non-actived output of FC operator, "
"saving sum{X_i * W_i} + B."
)
.
AsIntermediate
();
AddAttr
<
std
::
string
>
(
"activation"
,
"The activation type of FC operator."
)
AddAttr
<
std
::
string
>
(
"activation"
,
"(string, default identity) the activation type of FC operator."
)
.
SetDefault
(
"identity"
)
.
InEnum
({
"identity"
,
"sigmoid"
,
"softmax"
});
AddAttr
<
std
::
vector
<
int
>>
(
"xNumColDims"
,
""
);
AddAttr
<
std
::
vector
<
int
>>
(
"wNumColDims"
,
""
);
AddAttr
<
std
::
vector
<
int
>>
(
"xNumColDims"
,
"(std::vector<int>) The inputs Tensors of FC operator can be of "
"more than 2 dimensions. In that case, each input Tensor `X_i` will be "
"reshaped to a 2-D matrix. The matrix's first dimension "
"(the length of column) will be the product of `X_i`'s last "
"`xNumColDims_i` dimensions, that is "
"`X_i.dims[0] x ... x X_i.dims[xNumColDims_i - 1]`. "
"The matrix's second dimension (the length of row) will be the product "
"of `X_i`'s first `rank - xNumColDims_i` dimensions, that is "
"`X_i.dims[xNumColDims_i] x ... x X_i.dims[rank - 1]`)"
);
AddComment
(
R"DOC(
Fully Connected Operator, known as Fully Connected Layer or Inner Product Layer
...
...
@@ -129,15 +148,14 @@ learned weights with a matrix multiplication followed by a bias offset
(optionally).
Equation:
Y = Act(sum_n{X_i * W_i} +
b
)
Y = Act(sum_n{X_i * W_i} +
B
)
where X_i is a 2D matrix of size (M x K), usually M is the minibatch size and
K is the number of features. W_i is also a 2D matrix of size (K x N),
where N means the number of neurons in the fully connected layer.
b is a 1D vector of size N. Thus, the output Y is a 2D matrix of size (M x N).
where X_i is Tensor that will be reshaped to a 2-D matrix of size (M x K),
usually M is the minibatch size and K is the number of input features.
W_i is a 2-D matrix of size (K x N), where N means the number of neurons
in the fully connected layer. B is a 1-D vector of size N.
Thus, the output Y is a 2-D matrix of size (M x N).
Activation type can be set to `identity` (default), `sigmoid` or `softmax`.
The config api is `paddle.v2.layer.fc`.
)DOC"
);
}
};
...
...
python/paddle/v2/framework/tests/test_fc_op.py
浏览文件 @
0b21b854
...
...
@@ -22,7 +22,7 @@ class TestFCOp1(OpTest):
"AddOut"
:
add_out
,
"Y"
:
identity_out
}
self
.
attrs
=
{
"xNumColDims"
:
[
1
]
,
"wNumColDims"
:
[
1
]
}
self
.
attrs
=
{
"xNumColDims"
:
[
1
]}
def
test_check_output
(
self
):
self
.
check_output
()
...
...
@@ -34,13 +34,13 @@ class TestFCOp1(OpTest):
class
TestFCOp2
(
OpTest
):
def
setUp
(
self
):
x0
=
np
.
random
.
random
((
16
,
4
,
8
)).
astype
(
"float32"
)
x1
=
np
.
random
.
random
((
16
,
32
)).
astype
(
"float32"
)
x1
=
np
.
random
.
random
((
4
,
4
,
32
)).
astype
(
"float32"
)
w0
=
np
.
random
.
random
((
32
,
10
)).
astype
(
"float32"
)
w1
=
np
.
random
.
random
((
4
,
8
,
10
)).
astype
(
"float32"
)
w1
=
np
.
random
.
random
((
32
,
10
)).
astype
(
"float32"
)
b
=
np
.
random
.
random
(
10
).
astype
(
"float32"
)
mul_out0
=
np
.
dot
(
x0
.
reshape
(
16
,
4
*
8
),
w0
)
mul_out1
=
np
.
dot
(
x1
,
w1
.
reshape
(
4
*
8
,
10
)
)
mul_out1
=
np
.
dot
(
x1
.
reshape
(
4
*
4
,
32
),
w1
)
sum_out
=
mul_out0
+
mul_out1
add_out
=
np
.
add
(
sum_out
,
b
)
sigmoid_out
=
1
/
(
1
+
np
.
exp
(
-
add_out
))
...
...
@@ -51,11 +51,7 @@ class TestFCOp2(OpTest):
"W"
:
[(
"W0"
,
w0
),
(
"W1"
,
w1
)],
"B"
:
b
}
self
.
attrs
=
{
"xNumColDims"
:
[
1
,
1
],
"wNumColDims"
:
[
1
,
2
],
"activation"
:
"sigmoid"
}
self
.
attrs
=
{
"xNumColDims"
:
[
1
,
2
],
"activation"
:
"sigmoid"
}
self
.
outputs
=
{
"MulOut"
:
[(
"MulOut0"
,
mul_out0
),
(
"MulOut1"
,
mul_out1
)],
"SumOut"
:
sum_out
,
...
...
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