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// Copyright 2004-present Facebook. All Rights Reserved.
#pragma once
#include "caffe2/core/context.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
template <typename T, class Context>
class LambdaRankNdcgOp final : public Operator<Context> {
public:
template <class... Args>
explicit LambdaRankNdcgOp(Args&&... args)
: Operator<Context>(std::forward<Args>(args)...),
use_ndcg_as_loss_(
this->template GetSingleArgument<bool>("use_ndcg_as_loss", false)),
use_idcg_normalization_(this->template GetSingleArgument<bool>(
"use_idcg_normalization",
true)),
use_exp_gain_(
this->template GetSingleArgument<bool>("use_exp_gain", true)) {}
USE_OPERATOR_CONTEXT_FUNCTIONS;
bool RunOnDevice() override;
private:
INPUT_TAGS(PRED, REL, SESSION_LENS);
OUTPUT_TAGS(LOSS, DPRED);
void ResizeInvLogITensor(int);
void ComputeDiscounts(int*, int);
float LambdaRankNdcgSession(
int start_index,
int end_index,
const Tensor& y,
const Tensor& r,
Tensor** dy);
bool use_ndcg_as_loss_;
bool use_idcg_normalization_;
bool use_exp_gain_;
Tensor gain_;
Tensor discount_;
Tensor rank_idx_;
Tensor ideal_idx_;
Tensor lambda_;
Tensor inv_log_i_;
};
template <typename T, class Context>
class LambdaRankNdcgGradientOp final : public Operator<Context> {
public:
USE_SIMPLE_CTOR_DTOR(LambdaRankNdcgGradientOp);
USE_OPERATOR_CONTEXT_FUNCTIONS;
bool RunOnDevice() override;
private:
INPUT_TAGS(Y, SESSION_LENS, DY_CACHE, DLOSS);
OUTPUT_TAGS(DY);
};
} // namespace caffe2
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