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