Kmcuda for windows bugfixes

src/kmcuda.cc

@@ -51,7 +51,7 @@ static KMCUDAResult check_kmeans_args(
   if (yinyang_t < 0 || yinyang_t > 0.5) {
     return kmcudaInvalidArguments;
   }
-#if CUDA_ARCH < 60
+#if defined(__CUDA_ARCH__) &&  CUDA_ARCH < 60
   if (fp16x2) {
     INFO("CUDA device arch %d does not support fp16\n", CUDA_ARCH);
     return kmcudaInvalidArguments;
@@ -83,14 +83,18 @@ static std::vector<int> setup_devices(uint32_t device, int device_ptrs, int verb
              dev, cudaGetErrorString(err));
         devs.pop_back();
       }
-      if (props.major != (CUDA_ARCH / 10) || props.minor != (CUDA_ARCH % 10)) {
-        INFO("compute capability mismatch for device %d: wanted %d.%d, have "
-             "%d.%d\n>>>> you may want to build kmcuda with -DCUDA_ARCH=%d "
-             "(refer to \"Building\" in README.md)\n",
-             dev, CUDA_ARCH / 10, CUDA_ARCH % 10, props.major, props.minor,
-             props.major * 10 + props.minor);
-        devs.pop_back();
-      }
+
+#if defined(__CUDA_ARCH__)
+	  if (props.major != (CUDA_ARCH / 10) || props.minor != (CUDA_ARCH % 10)) {
+		  INFO("compute capability mismatch for device %d: wanted %d.%d, have "
+			  "%d.%d\n>>>> you may want to build kmcuda with -DCUDA_ARCH=%d "
+			  "(refer to \"Building\" in README.md)\n",
+			  dev, CUDA_ARCH / 10, CUDA_ARCH % 10, props.major, props.minor,
+			  props.major * 10 + props.minor);
+		  devs.pop_back();
+	}
+#endif
+
     }
     device >>= 1;
   }
@@ -559,7 +563,7 @@ static KMCUDAResult check_knn_args(
       neighbors == nullptr) {
     return kmcudaInvalidArguments;
   }
-#if CUDA_ARCH < 60
+#if defined(__CUDA_ARCH__) && CUDA_ARCH < 60
   if (fp16x2) {
     INFO("CUDA device arch %d does not support fp16\n", CUDA_ARCH);
     return kmcudaInvalidArguments;

src/kmcuda.h

@@ -37,6 +37,8 @@
 
 #include <stdint.h>
 
+#include<device_launch_parameters.h>
+
 /// All possible error codes in public API.
 typedef enum {
   /// Everything's all right.

src/knn.cu

@@ -1,4 +1,5 @@
 #include <cfloat>
+#include <algorithm>
 
 #include "private.h"
 #include "metric_abstraction.h"

src/metric_abstraction.h

@@ -2,6 +2,9 @@
 // distance and normalization functions.
 //
 
+#define _USE_MATH_DEFINES
+#include <math.h>
+
 #ifndef KMCUDA_METRIC_ABSTRACTION_H
 #define KMCUDA_METRIC_ABSTRACTION_H
 
@@ -169,7 +172,7 @@ struct METRIC<kmcudaDistanceMetricCosine, F> {
   }
 
   FPATTR static typename HALF<F>::type distance(
-      F sqr1 __attribute__((unused)), F sqr2 __attribute__((unused)), F prod) {
+      F sqr1, F sqr2, F prod) {
     float fp = _float(_fin(prod));
     if (fp >= 1.f) return _half<F>(0.f);
     if (fp <= -1.f) return _half<F>(M_PI);
@@ -252,7 +255,7 @@ struct METRIC<kmcudaDistanceMetricCosine, F> {
     return acos(partial);
   }
 
-  FPATTR static void normalize(uint32_t count __attribute__((unused)), float *vec) {
+  FPATTR static void normalize(uint32_t count, float *vec) {
     // Kahan summation with inverted c
     float norm = 0, corr = 0;
     #pragma unroll 4
@@ -272,7 +275,7 @@ struct METRIC<kmcudaDistanceMetricCosine, F> {
   }
 
   #if CUDA_ARCH >= 60
-  FPATTR static void normalize(uint32_t count __attribute__((unused)), half2 *vec) {
+  FPATTR static void normalize(uint32_t count, half2 *vec) {
     // We really have to calculate norm in 32-bit floats because the maximum
     // value which 16-bit float may represent is 2^16.
     float norm = 0, corr = 0;

src/wrappers.h

@@ -17,7 +17,10 @@ template <typename T>
 class unique_devptr : public unique_devptr_parent<T> {
  public:
   explicit unique_devptr(T *ptr, bool fake = false) : unique_devptr_parent<T>(
-      ptr, fake? [](T*){} : [](T *p){ cudaFree(p); }) {}
+	  ptr,
+	  (fake == true)
+	  ? (std::function<void(T*)>)([](T*) {})
+	  : [](T *p) { cudaFree(p); }) {}
 };
 
 /// std::vector of unique_devptr-s. Used to pass device arrays inside .cu