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Context Projection Paddle Function-- follow comments #1080

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merged 7 commits into from
Jan 16, 2017
Merged

Context Projection Paddle Function-- follow comments #1080

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86fa8c0
Wei Xu's comments, set up right inouts.
Jan 5, 2017
df66957
clean a little bit code.
Jan 5, 2017
1482ec4
some comments.
Jan 7, 2017
23ac0b7
merge Daoyuan's FuncArgs, pass the ContextProjection test.
Jan 11, 2017
9edfd20
use Daoyuan's SequenceArg.
Jan 11, 2017
8560ce6
Daoyuan's comments about SequenceArg.
Jan 12, 2017
e979421
Address further comments.
Jan 12, 2017
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12 changes: 8 additions & 4 deletions paddle/function/BufferArg.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -20,23 +20,27 @@ limitations under the License. */
namespace paddle {

const SequenceArg& BufferArg::sequence() const {
// CHECK_EQ(bufferType_, TENSOR_SEQUENCE_DATA);
CHECK_EQ(bufferType_, TENSOR_SEQUENCE_DATA);
return dynamic_cast<const SequenceArg&>(*this);
}

const SparseMatrixArg& BufferArg::sparse() const {
// CHECK_EQ(bufferType_, TENSOR_SPARSE);
CHECK_EQ(bufferType_, TENSOR_SPARSE);
return dynamic_cast<const SparseMatrixArg&>(*this);
}

SparseMatrixArg::SparseMatrixArg(const CpuSparseMatrix& sparse, ArgType argType)
: BufferArg(sparse, argType),
row_(reinterpret_cast<void*>(sparse.getRows()), VALUE_TYPE_INT32),
col_(reinterpret_cast<void*>(sparse.getCols()), VALUE_TYPE_INT32) {}
col_(reinterpret_cast<void*>(sparse.getCols()), VALUE_TYPE_INT32) {
bufferType_ = TENSOR_SPARSE;
}

SparseMatrixArg::SparseMatrixArg(const GpuSparseMatrix& sparse, ArgType argType)
: BufferArg(sparse, argType),
row_(reinterpret_cast<void*>(sparse.getRows()), VALUE_TYPE_INT32),
col_(reinterpret_cast<void*>(sparse.getCols()), VALUE_TYPE_INT32) {}
col_(reinterpret_cast<void*>(sparse.getCols()), VALUE_TYPE_INT32) {
bufferType_ = TENSOR_SPARSE;
}

} // namespace paddle
33 changes: 24 additions & 9 deletions paddle/function/BufferArg.h
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Original file line number Diff line number Diff line change
Expand Up @@ -23,10 +23,11 @@ limitations under the License. */
namespace paddle {

enum BufferType {
TENSOR_NORMAL = 0,
TENSOR_SEQUENCE_ID = 1,
TENSOR_SEQUENCE_DATA = 2,
TENSOR_SPARSE = 3
TENSOR_UNKNOWN = 0,
TENSOR_NORMAL = 1,
TENSOR_SEQUENCE_ID = 2,
TENSOR_SEQUENCE_DATA = 3,
TENSOR_SPARSE = 4
};

enum SparseDataType {
Expand Down Expand Up @@ -86,6 +87,7 @@ class BufferArg {
valueType_(DataType<real>::value),
shape_(2),
argType_(argType) {
bufferType_ = TENSOR_NORMAL;
shape_.setDim(0, matrix.getHeight());
shape_.setDim(1, matrix.getWidth());
}
Expand All @@ -98,6 +100,7 @@ class BufferArg {
valueType_(DataType<real>::value),
shape_(shape),
argType_(argType) {
bufferType_ = TENSOR_NORMAL;
CHECK_EQ(matrix.getElementCnt(), shape.getElements());
}

Expand All @@ -107,6 +110,7 @@ class BufferArg {
valueType_(DataType<real>::value),
shape_(1),
argType_(argType) {
bufferType_ = TENSOR_NORMAL;
shape_.setDim(0, vector.getSize());
}

Expand All @@ -116,6 +120,7 @@ class BufferArg {
valueType_(VALUE_TYPE_INT32),
shape_(1),
argType_(argType) {
bufferType_ = TENSOR_NORMAL;
shape_.setDim(0, vector.getSize());
}

Expand Down Expand Up @@ -150,6 +155,8 @@ class BufferArg {
ValueType valueType() const { return valueType_; }
BufferType bufferType() const { return bufferType_; }
const TensorShape& shape() const { return shape_; }
bool isSparse() const { return (TENSOR_SPARSE == bufferType_); }
bool isSequenceArg() const { return TENSOR_SEQUENCE_DATA == bufferType_; }

const SequenceArg& sequence() const;
const SparseMatrixArg& sparse() const;
Expand All @@ -158,8 +165,8 @@ class BufferArg {
void* buf_;
ValueType valueType_;
TensorShape shape_;
BufferType bufferType_;
ArgType argType_ = UNSPECIFIED;
BufferType bufferType_{TENSOR_UNKNOWN};
ArgType argType_{UNSPECIFIED};
// leading dimensions. The size is dims_.size()
// Dims lds_;
};
Expand All @@ -174,11 +181,13 @@ class SequenceIdArg : public BufferArg {
const TensorShape& shape,
ArgType argType = UNSPECIFIED)
: BufferArg(buf, VALUE_TYPE_INT32, shape, argType) {
bufferType_ = TENSOR_SEQUENCE_ID;
CHECK_EQ(shape_.ndims(), (size_t)1);
numSeqs_ = shape_[0] - 1;
}

SequenceIdArg(const IVector& vector) : BufferArg(vector) {
bufferType_ = TENSOR_SEQUENCE_ID;
numSeqs_ = shape_[0] - 1;
}

Expand All @@ -190,7 +199,7 @@ class SequenceIdArg : public BufferArg {
size_t numSeqs_;
};

// sequence data
// sequence data {seqId(vec), buf(matrix)}
class SequenceArg : public BufferArg {
public:
SequenceArg(void* buf,
Expand All @@ -199,17 +208,22 @@ class SequenceArg : public BufferArg {
const SequenceIdArg& startPositions,
ArgType argType = UNSPECIFIED)
: BufferArg(buf, valueType, shape, argType),
startPositions_(startPositions) {}
startPositions_(startPositions) {
bufferType_ = TENSOR_SEQUENCE_DATA;
}

SequenceArg(const Matrix& matrix,
const IVector& vector,
ArgType argType = UNSPECIFIED)
: BufferArg(matrix, argType), startPositions_(vector) {}
: BufferArg(matrix, argType), startPositions_(vector) {
bufferType_ = TENSOR_SEQUENCE_DATA;
}

~SequenceArg() {}

void* getIdBuf() const { return startPositions_.data(); }
size_t numSeqs() const { return startPositions_.numSeqs(); }
const SequenceIdArg& getSequenceIds() const { return startPositions_; }

private:
SequenceIdArg startPositions_;
Expand All @@ -235,6 +249,7 @@ class SparseMatrixArg : public BufferArg {
nnz_(nnz),
format_(format),
type_(type) {
bufferType_ = TENSOR_SPARSE;
CHECK((valueType == VALUE_TYPE_FLOAT) || (valueType == VALUE_TYPE_DOUBLE));
CHECK_EQ(shape_.ndims(), (size_t)2);
CHECK_EQ(row_.shape().ndims(), (size_t)1);
Expand Down
2 changes: 1 addition & 1 deletion paddle/function/CMakeLists.txt
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Expand Up @@ -24,7 +24,7 @@ if(WITH_TESTING)
add_simple_unittest(TensorTypeTest)
add_simple_unittest(BufferArgTest)
add_simple_unittest(FunctionTest)
# add_simple_unittest(ContextProjectionOpTest)
add_simple_unittest(ContextProjectionOpTest)
endif()
endif()

Expand Down
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