binary_log_loss.hpp

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#ifndef STAN_MATH_REV_FUN_BINARY_LOG_LOSS_HPP
#define STAN_MATH_REV_FUN_BINARY_LOG_LOSS_HPP
 
#include <stan/math/rev/meta.hpp>
#include <stan/math/rev/core.hpp>
#include <stan/math/prim/fun/log1p.hpp>
#include <cmath>
 
namespace stan {
namespace math {
 
inline var binary_log_loss(int y, const var& y_hat) {
  if (y == 0) {
    return make_callback_var(-log1p(-y_hat.val()), [y_hat](auto& vi) mutable {
      y_hat.adj() += vi.adj() / (1.0 - y_hat.val());
    });
  } else {
    return make_callback_var(-std::log(y_hat.val()), [y_hat](auto& vi) mutable {
      y_hat.adj() -= vi.adj() / y_hat.val();
    });
  }
}
 
template <typename Mat, require_eigen_t<Mat>* = nullptr>
inline auto binary_log_loss(int y, const var_value<Mat>& y_hat) {
  if (y == 0) {
    return make_callback_var(
        -(-y_hat.val().array()).log1p(), [y_hat](auto& vi) mutable {
          y_hat.adj().array() += vi.adj().array() / (1.0 - y_hat.val().array());
        });
  } else {
    return make_callback_var(
        -y_hat.val().array().log(), [y_hat](auto& vi) mutable {
          y_hat.adj().array() -= vi.adj().array() / y_hat.val().array();
        });
  }
}
 
template <typename StdVec, typename Mat, require_eigen_t<Mat>* = nullptr,
          require_st_integral<StdVec>* = nullptr>
inline auto binary_log_loss(const StdVec& y, const var_value<Mat>& y_hat) {
  auto arena_y = to_arena(as_array_or_scalar(y).template cast<bool>());
  auto ret_val
      = -(arena_y == 0)
             .select((-y_hat.val().array()).log1p(), y_hat.val().array().log());
  return make_callback_var(ret_val, [y_hat, arena_y](auto& vi) mutable {
    y_hat.adj().array()
        += vi.adj().array()
           / (arena_y == 0)
                 .select((1.0 - y_hat.val().array()), -y_hat.val().array());
  });
}
 
}  // namespace math
}  // namespace stan
#endif