@ -17,7 +17,7 @@ limitations under the License. */
namespace paddle {
namespace operators {
using framework : : ;
using framework : : LoD Tensor;
class SequenceExpandOp : public framework : : OperatorWithKernel {
public :
@ -25,15 +25,71 @@ class SequenceExpandOp : public framework::OperatorWithKernel {
protected :
void InferShape ( framework : : InferShapeContext * ctx ) const override {
PADDLE_ENFORCE ( ctx - > HasInput ( " X " ) ) ;
PADDLE_ENFORCE ( ctx - > HasOutput ( " Out " ) ) ;
PADDLE_ENFORCE ( ctx - > HasInput ( " Y " ) ) ;
framework : : DDim out_dim ;
auto y_dim = ctx - > GetInputDim ( " Y " ) ;
out_dim = ctx - > GetInputDim ( " X " ) ;
out_dim [ 0 ] = y_dim [ 0 ] ;
ctx - > ShareLoD ( " Y " , " Out " ) ;
ctx - > SetOutputDim ( " Out " , out_dim ) ;
PADDLE_ENFORCE ( ctx - > HasInput ( " X " ) ,
" Input(X) of SequenceExpandOp should not be null. " ) ;
PADDLE_ENFORCE ( ctx - > HasInput ( " Y " ) ,
" Input(Y) of SequenceExpandOp should not be null. " ) ;
PADDLE_ENFORCE ( ctx - > HasOutput ( " Out " ) ,
" Output(Out) of SequenceExpandOp should not be null. " ) ;
auto x_dims = ctx - > GetInputDim ( " X " ) ;
auto out_dims = x_dims ;
int ref_level = ctx - > Attrs ( ) . Get < int > ( " ref_level " ) ;
PADDLE_ENFORCE_GE ( x_dims . size ( ) , 2 ,
" Dimension number of Input(X) should be at least 2. " ) ;
if ( ctx - > IsRuntime ( ) ) {
framework : : Variable * x_var =
boost : : get < framework : : Variable * > ( ctx - > GetInputVarPtrs ( " X " ) [ 0 ] ) ;
framework : : Variable * y_var =
boost : : get < framework : : Variable * > ( ctx - > GetInputVarPtrs ( " Y " ) [ 0 ] ) ;
auto & x_lod = x_var - > Get < LoDTensor > ( ) . lod ( ) ;
auto & y_lod = y_var - > Get < LoDTensor > ( ) . lod ( ) ;
PADDLE_ENFORCE_LE ( x_lod . size ( ) , 1 ,
" Level number of Input(X)'s lod should not be "
" greater than 1. " ) ;
PADDLE_ENFORCE_GT ( y_lod . size ( ) , 0 ,
" Level number of Input(Y)'s lod should be "
" greater than 0. " ) ;
PADDLE_ENFORCE (
ref_level = = - 1 | |
( ref_level > = 0 & & ref_level < static_cast < int > ( y_lod . size ( ) ) ) ,
" Invlid `ref_level`, which should be either equal to -1 "
" or in [0, %d) " ,
y_lod . size ( ) ) ;
if ( ref_level = = - 1 ) ref_level = y_lod . size ( ) - 1 ;
if ( x_lod . size ( ) > 0 ) {
PADDLE_ENFORCE ( x_lod [ 0 ] . size ( ) = = y_lod [ ref_level ] . size ( ) ,
" Level number of Input(X)'s lod could be 0. Otherwise "
" size of Input(X)'s first level lod should be equal to "
" size of Input(Y)'s referred level lod. " ) ;
}
int64_t out_first_dim = 0 ;
if ( y_lod [ ref_level ] . size ( ) < = 1 ) {
out_first_dim = x_dims [ 0 ] ;
} else {
for ( size_t i = 1 ; i < y_lod [ ref_level ] . size ( ) ; + + i ) {
int x_seq_len = 1 ;
if ( x_lod . size ( ) = = 1 ) {
x_seq_len = x_lod [ 0 ] [ i ] - x_lod [ 0 ] [ i - 1 ] ;
}
out_first_dim + =
( y_lod [ ref_level ] [ i ] - y_lod [ ref_level ] [ i - 1 ] ) * x_seq_len ;
}
}
out_dims [ 0 ] = out_first_dim ;
ctx - > SetOutputDim ( " Out " , out_dims ) ;
} else {
out_dims [ 0 ] = - 1 ;
ctx - > SetOutputDim ( " Out " , out_dims ) ;
ctx - > ShareLoD ( " X " , /*->*/ " Out " ) ;
}
}
} ;
@ -42,83 +98,81 @@ class SequenceExpandOpMaker : public framework::OpProtoAndCheckerMaker {
SequenceExpandOpMaker ( OpProto * proto , OpAttrChecker * op_checker )
: OpProtoAndCheckerMaker ( proto , op_checker ) {
AddInput ( " X " ,
" ( Tensor or LoDTensor) The input(X) of this operator can be a "
" LoDTensor or a base Tensor ." ) ;
" ( LoDTensor, default LoDTensor<float>) A 2-D LoDTensor whose lod "
" level is at most 1 ." ) ;
AddInput ( " Y " ,
" (LoDTensor)The reference input(Y) of sequence_expand op. "
" It must be a LoDTensor with k-level(k>0). "
" The input(X) will be expanded according to LOD of input(Y). "
" The element numbers of last level in input(Y) "
" must be equal to dims[0] of input(X). " ) ;
" (LoDTensor, default LoDTensor<float>) Referred LoDTensor whose "
" lod (specified level) is referred by Input(X). " ) ;
AddOutput ( " Out " ,
" (LodTensor)The output of sequence_expand op. "
" The lod of output will be as same as input(Y)'s lod. " ) ;
" (LodTensor, default LoDTensor<float>) Output LoDTensor which is "
" generated from Input(X) by referring lod of Input(Y). " ) ;
AddAttr < int > ( " ref_level " , " Specify lod level of Input(Y). " ) . SetDefault ( - 1 ) ;
AddComment ( R " DOC(
Sequence Expand Operator .
This operator expands input ( X ) according to LOD of input ( Y ) .
This operator expands ` X ` according to specified level lod of ` Y ` . Current
implementation constaints that lod level of ` X ` should be at most 1. Attribute
` ref_level ` is used to specify which level lod of ` Y ` is referred to expand ` X ` .
If set ` ref_level ` to - 1 , then last level lod of ` Y ` would be referred .
Please note , rank of ` X ` should be at least 2 , when the rank exceeds 2 , ` X `
would be viewed as a 2 - D tensor .
Following are cases to better explain how this works :
Case 1 :
Given a 2 - level LoDTensor input ( X )
X . lod = [ [ 0 , 2 , 3 ] ,
[ 0 , 1 , 3 , 4 ] ]
X . data = [ a , b , c , d ]
Given a 1 - level LoDTensor input ( X )
X . lod = [[0, 2, 4]]
X . data = [[a], [b], [c], [d]]
X . dims = [ 4 , 1 ]
and input ( Y )
Y . lod = [ [ 0 , 2 , 4 ] ,
[ 0 , 3 , 6 , 7 , 8 ] ]
with condition len ( Y . lod [ - 1 ] ) - 1 = = X . dims [ 0 ]
then we get 2 - level LoDTensor
Out . lod = [ [ 0 , 2 , 4 ] ,
[ 0 , 3 , 6 , 7 , 8 ] ]
Out . data = [ a , a , a , b , b , b , c , d ]
ref_level : 0
then we get 1 - level LoDTensor
Out . lod = [[0, 2, 4, 6, 8]]
Out . data = [[a], [b], [a], [b], [c], [d], [c], [d]]
Out . dims = [ 8 , 1 ]
Case 2 :
Given 1 - level LoDTensor input ( X )
X . lod = [[0, 1, 4]]
X . data = [[a], [b], [c], [d]]
X . dims = [ 4 , 1 ]
and input ( Y )
Y . lod = [ [ 0 , 2 , 4 ] ,
[ 0 , 3 , 6 , 6 , 8 ] ]
ref_level : 0
then we get 1 - level LoDTensor
Out . lod = [[0, 1, 2, 5, 8]]
Out . data = [[a], [a], [b], [c], [d], [b], [c], [d]]
Out . dims = [ 8 , 1 ]
Case 3 :
Given a common Tensor input ( X )
X . data = [ a , b , c ]
X . data = [[a], [b], [c]
X . dims = [ 3 , 1 ]
and input ( Y )
Y . lod = [[0, 2, 3, 6]]
with condition len ( Y . lod [ - 1 ] ) - 1 = = X . dims [ 0 ]
then we get 1 - level LoDTensor
Out . lod = [[0, 2, 3, 6]]
Out . data = [ a , a , b , c , c , c ]
ref_level : - 1
then we get a common Tensor
Out . data = [[a], [a], [b], [c], [c], [c]]
Out . dims = [ 6 , 1 ]
Case 3 :
Case 4 :
Given a common Tensor input ( X )
X . data = [[a, b], [c, d], [e, f]]
X . dims = [ 3 , 2 ]
and input ( Y )
Y . lod = [[0, 2, 3, 6]]
with condition len ( Y . lod [ - 1 ] ) - 1 = = X . dims [ 0 ]
then we get 1 - level LoDTensor
Out . lod = [[0, 2, 3, 6]]
Out . data = [[a,b], [a,b] [c,d], [e, f], [e, f], [e, f]]
ref_level : 0
then we get a common LoDTensor
Out . data = [[a, b], [a, b] [c, d], [e, f], [e, f], [e, f]]
Out . dims = [ 6 , 2 ]
Case 4 :
Given 2 - level a LoDTensor input ( X )
X . lod = [ [ 0 , 2 , 3 ] ,
[ 0 , 1 , 3 , 4 ] ]
X . data = [ a , b , c , d ]
X . dims = [ 4 , 1 ]
and input ( Y )
Y . lod = [ [ 0 , 2 , 4 ] ,
[ 0 , 3 , 6 , 6 , 8 ] ]
with condition len ( Y . lod [ - 1 ] ) - 1 = = X . dims [ 0 ]
then we get 2 - level LoDTensor
Out . lod = [ [ 0 , 2 , 4 ] ,
[ 0 , 3 , 6 , 6 , 8 ] ]
Out . data = [ a , a , a , b , b , b , d , d ]
Out . dims = [ 8 , 1 ]
) DOC " );
}
} ;
@ -129,12 +183,14 @@ class SequenceExpandOpGrad : public framework::OperatorWithKernel {
protected :
void InferShape ( framework : : InferShapeContext * ctx ) const override {
PADDLE_ENFORCE ( ctx - > HasInput ( " X " ) ;
PADDLE_ENFORCE ( ctx - > HasInput ( " Out " ) ;
PADDLE_ENFORCE ( ctx - > HasInput ( " X " ) , " Input(X) should not be null. " );
PADDLE_ENFORCE ( ctx - > HasInput ( " Out " ) , " Input(Out) should not be null. " );
PADDLE_ENFORCE ( ctx - > HasInput ( framework : : GradVarName ( " Out " ) ) ,
" The input(Out@GRAD) should not be null " ) ;
" Input(Out@GRAD) should not be null. " ) ;
auto x_dims = ctx - > GetInputDim ( " X " ) ;
auto x_grad_name = framework : : GradVarName ( " X " ) ;
if ( ctx - > HasOutput ( x_grad_name ) ) {
ctx - > SetOutputDim ( x_grad_name , x_dims ) ;
}
@ -149,7 +205,13 @@ REGISTER_OP(sequence_expand, ops::SequenceExpandOp, ops::SequenceExpandOpMaker,
sequence_expand_grad , ops : : SequenceExpandOpGrad ) ;
REGISTER_OP_CPU_KERNEL (
sequence_expand ,
ops : : SequenceExpandKernel < paddle : : platform : : CPUDeviceContext , float > ) ;
ops : : SequenceExpandKernel < paddle : : platform : : CPUDeviceContext , float > ,
ops : : SequenceExpandKernel < paddle : : platform : : CPUDeviceContext , double > ,
ops : : SequenceExpandKernel < paddle : : platform : : CPUDeviceContext , int > ,
ops : : SequenceExpandKernel < paddle : : platform : : CPUDeviceContext , int64_t > ) ;
REGISTER_OP_CPU_KERNEL (
sequence_expand_grad ,
ops : : SequenceExpandGradKernel < paddle : : platform : : CPUDeviceContext , float > ) ;
ops : : SequenceExpandGradKernel < paddle : : platform : : CPUDeviceContext , float > ,
ops : : SequenceExpandGradKernel < paddle : : platform : : CPUDeviceContext , double > ,
ops : : SequenceExpandGradKernel < paddle : : platform : : CPUDeviceContext , int > ,
ops : : SequenceExpandGradKernel < paddle : : platform : : CPUDeviceContext , int64_t > ) ;
fengjiayi
7 years ago
