cleanup.

Author: trivialfis

Diff for: src/common/ranking_utils.cc

@@ -43,10 +43,6 @@ void RankingCache::InitOnCPU(Context const* ctx, MetaInfo const& info) {
     sum_weights += weight[k];
   }
   weight_norm_ = static_cast<double>(n_groups) / sum_weights;
-
-  auto const& h_label = info.labels.HostView().Slice(linalg::All(), 0);
-  is_binary_ = IsBinaryRel(
-      h_label, [ctx](auto beg, auto end, auto op) { return common::AllOf(ctx, beg, end, op); });
 }
 
 common::Span<std::size_t const> RankingCache::MakeRankOnCPU(Context const* ctx,

Diff for: src/common/ranking_utils.cu

@@ -173,9 +173,6 @@ void RankingCache::InitOnCUDA(Context const* ctx, MetaInfo const& info) {
   auto w_it =
       dh::MakeTransformIterator<double>(thrust::make_counting_iterator(0ul), WeightOp{weight});
   weight_norm_ = static_cast<double>(n_groups) / thrust::reduce(w_it, w_it + n_groups);
-
-  auto const d_label = info.labels.View(ctx->gpu_id).Slice(linalg::All(), 0);
-  is_binary_ = IsBinaryRel(d_label, CheckMAPOp{ctx->CUDACtx()});
 }
 
 common::Span<std::size_t const> RankingCache::MakeRankOnCUDA(Context const* ctx,

Diff for: src/common/ranking_utils.h

@@ -162,8 +162,6 @@ class RankingCache {
   std::size_t max_group_size_{0};
   // Normalization for weight
   double weight_norm_{1.0};
-  // Whether label is binary
-  bool is_binary_{false};
   /**
    * CUDA cache
    */
@@ -227,7 +225,6 @@ class RankingCache {
   [[nodiscard]] auto const& Param() const { return param_; }
   [[nodiscard]] std::size_t Groups() const { return group_ptr_.Size() - 1; }
   [[nodiscard]] double WeightNorm() const { return weight_norm_; }
-  [[nodiscard]] bool IsBinary() const { return is_binary_; }
 
   // Create a rank list by model prediction
   common::Span<std::size_t const> SortedIdx(Context const* ctx, common::Span<float const> predt) {