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#ifndef CAFFE2_OPERATORS_HALF_FLOAT_OPS_H_
#define CAFFE2_OPERATORS_HALF_FLOAT_OPS_H_
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
namespace caffe2 {
template <class Context>
class FloatToHalfOp : public Operator<Context> {
public:
explicit FloatToHalfOp(const OperatorDef& operator_def, Workspace* ws)
: Operator<Context>(operator_def, ws),
clip_(this->template GetSingleArgument<bool>("clip", false)) {}
USE_OPERATOR_CONTEXT_FUNCTIONS;
bool RunOnDevice() override;
private:
bool clip_;
};
template <class Context>
class HalfToFloatOp : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
USE_SIMPLE_CTOR_DTOR(HalfToFloatOp);
bool RunOnDevice() override;
};
class Float16ConstantFillOp : public Operator<CPUContext> {
public:
template <class... Args>
explicit Float16ConstantFillOp(Args&&... args)
: Operator<CPUContext>(std::forward<Args>(args)...),
shape_(this->template GetRepeatedArgument<int64_t>("shape")) {}
USE_OPERATOR_FUNCTIONS(CPUContext);
virtual ~Float16ConstantFillOp() {}
bool RunOnDevice() override;
private:
vector<int64_t> shape_;
};
template <class Context>
class Float16UniformFillOp : public Operator<Context> {
public:
template <class... Args>
explicit Float16UniformFillOp(Args&&... args)
: Operator<Context>(std::forward<Args>(args)...),
shape_(this->template GetRepeatedArgument<int64_t>("shape")),
min_(this->template GetSingleArgument<float>("min", 0)),
max_(this->template GetSingleArgument<float>("max", 1)) {
if (InputSize() == 3) {
CAFFE_ENFORCE(
!this->template HasSingleArgumentOfType<float>("min"),
"Cannot set both min arg and min input blob");
CAFFE_ENFORCE(
!this->template HasSingleArgumentOfType<float>("max"),
"Cannot set both max arg and max input blob");
} else {
CAFFE_ENFORCE_LT(
min_, max_, "Max value should be bigger than min value.");
}
}
USE_OPERATOR_CONTEXT_FUNCTIONS;
virtual ~Float16UniformFillOp() {}
bool RunOnDevice() override;
private:
vector<int64_t> shape_;
float min_;
float max_;
Tensor temp_data_buffer_;
};
inline std::vector<TensorShape> Float16FillerTensorInference(
const OperatorDef& def,
const vector<TensorShape>& in) {
vector<TensorShape> out(1);
ArgumentHelper helper(def);
out[0].set_data_type(static_cast<TensorProto_DataType>(
helper.GetSingleArgument<int>("dtype", TensorProto_DataType_FLOAT16)));
auto shape = helper.GetRepeatedArgument<int>("shape");
for (int d : shape) {
out[0].add_dims(d);
}
return out;
}
} // namespace caffe2
#endif // CAFFE2_OPERATORS_HALF_FLOAT_OPS_H_
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