add binary logloss metric for new cuda version

src/metric/cuda/cuda_binary_metric.hpp

@@ -0,0 +1,55 @@
+/*!
+ * Copyright (c) 2022 Microsoft Corporation. All rights reserved.
+ * Licensed under the MIT License. See LICENSE file in the project root for
+ * license information.
+ */
+
+#ifndef LIGHTGBM_METRIC_CUDA_CUDA_BINARY_METRIC_HPP_
+#define LIGHTGBM_METRIC_CUDA_CUDA_BINARY_METRIC_HPP_
+
+#ifdef USE_CUDA_EXP
+
+#include <LightGBM/cuda/cuda_metric.hpp>
+#include <LightGBM/cuda/cuda_utils.h>
+
+#include <vector>
+
+#include "cuda_regression_metric.hpp"
+#include "../binary_metric.hpp"
+
+namespace LightGBM {
+
+template <typename HOST_METRIC, typename CUDA_METRIC>
+class CUDABinaryMetricInterface: public CUDARegressionMetricInterface<HOST_METRIC, CUDA_METRIC> {
+ public:
+  explicit CUDABinaryMetricInterface(const Config& config): CUDARegressionMetricInterface<HOST_METRIC, CUDA_METRIC>(config) {}
+
+  virtual ~CUDABinaryMetricInterface() {}
+};
+
+class CUDABinaryLoglossMetric: public CUDABinaryMetricInterface<BinaryLoglossMetric, CUDABinaryLoglossMetric> {
+ public:
+  explicit CUDABinaryLoglossMetric(const Config& config);
+
+  virtual ~CUDABinaryLoglossMetric() {}
+
+  __device__ static double MetricOnPointCUDA(label_t label, double score) {
+    // score should have been converted to probability
+    if (label <= 0) {
+      if (1.0f - score > kEpsilon) {
+        return -log(1.0f - score);
+      }
+    } else {
+      if (score > kEpsilon) {
+        return -log(score);
+      }
+    }
+    return -log(kEpsilon);
+  }
+};
+
+}  // namespace LightGBM
+
+#endif  // USE_CUDA_EXP
+
+#endif  // LIGHTGBM_METRIC_CUDA_CUDA_BINARY_METRIC_HPP_

src/metric/metric.cpp

@@ -11,6 +11,7 @@
 #include "regression_metric.hpp"
 #include "xentropy_metric.hpp"
 
+#include "cuda/cuda_binary_metric.hpp"
 #include "cuda/cuda_regression_metric.hpp"
 
 namespace LightGBM {
@@ -39,8 +40,7 @@ Metric* Metric::CreateMetric(const std::string& type, const Config& config) {
       Log::Warning("Metric poisson is not implemented in cuda_exp version. Fall back to evaluation on CPU.");
       return new PoissonMetric(config);
     } else if (type == std::string("binary_logloss")) {
-      Log::Warning("Metric binary_logloss is not implemented in cuda_exp version. Fall back to evaluation on CPU.");
-      return new BinaryLoglossMetric(config);
+      return new CUDABinaryLoglossMetric(config);
     } else if (type == std::string("binary_error")) {
       Log::Warning("Metric binary_error is not implemented in cuda_exp version. Fall back to evaluation on CPU.");
       return new BinaryErrorMetric(config);