update eigen

1 files changed, 22 insertions, 92 deletions

diff --git a/eigen/unsupported/test/cxx11_tensor_broadcast_sycl.cpp b/eigen/unsupported/test/cxx11_tensor_broadcast_sycl.cpp
index 21fdfca..7201bfe 100644
--- a/eigen/unsupported/test/cxx11_tensor_broadcast_sycl.cpp
+++ b/eigen/unsupported/test/cxx11_tensor_broadcast_sycl.cpp
@@ -14,7 +14,7 @@
 #define EIGEN_TEST_NO_LONGDOUBLE
 #define EIGEN_TEST_NO_COMPLEX
 #define EIGEN_TEST_FUNC cxx11_tensor_broadcast_sycl
-#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int64_t
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
 #define EIGEN_USE_SYCL
 
 #include "main.h"
@@ -25,99 +25,39 @@ using Eigen::SyclDevice;
 using Eigen::Tensor;
 using Eigen::TensorMap;
 
-template <typename DataType, int DataLayout, typename IndexType>
-static void test_broadcast_sycl_fixed(const Eigen::SyclDevice &sycl_device){
-
-  // BROADCAST test:
-  IndexType inDim1=2;
-  IndexType inDim2=3;
-  IndexType inDim3=5;
-  IndexType inDim4=7;
-  IndexType bDim1=2;
-  IndexType bDim2=3;
-  IndexType bDim3=1;
-  IndexType bDim4=4;
-  array<IndexType, 4> in_range   = {{inDim1, inDim2, inDim3, inDim4}};
-  array<IndexType, 4> broadcasts = {{bDim1, bDim2, bDim3, bDim4}};
-  array<IndexType, 4> out_range;  // = in_range * broadcasts
-  for (size_t i = 0; i < out_range.size(); ++i)
-    out_range[i] = in_range[i] * broadcasts[i];
-
-  Tensor<DataType, 4, DataLayout, IndexType>  input(in_range);
-  Tensor<DataType, 4, DataLayout, IndexType> out(out_range);
-
-  for (size_t i = 0; i < in_range.size(); ++i)
-    VERIFY_IS_EQUAL(out.dimension(i), out_range[i]);
-
-
-  for (IndexType i = 0; i < input.size(); ++i)
-    input(i) = static_cast<DataType>(i);
-
-  DataType * gpu_in_data  = static_cast<DataType*>(sycl_device.allocate(input.dimensions().TotalSize()*sizeof(DataType)));
-  DataType * gpu_out_data  = static_cast<DataType*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(DataType)));
-
-  TensorMap<TensorFixedSize<DataType, Sizes<2, 3, 5, 7>, DataLayout, IndexType>> gpu_in(gpu_in_data, in_range);
-  TensorMap<Tensor<DataType, 4, DataLayout, IndexType>> gpu_out(gpu_out_data, out_range);
-  sycl_device.memcpyHostToDevice(gpu_in_data, input.data(),(input.dimensions().TotalSize())*sizeof(DataType));
-  gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts);
-  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(DataType));
-
-  for (IndexType i = 0; i < inDim1*bDim1; ++i) {
-    for (IndexType j = 0; j < inDim2*bDim2; ++j) {
-      for (IndexType k = 0; k < inDim3*bDim3; ++k) {
-        for (IndexType l = 0; l < inDim4*bDim4; ++l) {
-          VERIFY_IS_APPROX(input(i%2,j%3,k%5,l%7), out(i,j,k,l));
-        }
-      }
-    }
-  }
-  printf("Broadcast Test with fixed size Passed\n");
-  sycl_device.deallocate(gpu_in_data);
-  sycl_device.deallocate(gpu_out_data);
-}
-
-template <typename DataType, int DataLayout, typename IndexType>
 static void test_broadcast_sycl(const Eigen::SyclDevice &sycl_device){
 
   // BROADCAST test:
-  IndexType inDim1=2;
-  IndexType inDim2=3;
-  IndexType inDim3=5;
-  IndexType inDim4=7;
-  IndexType bDim1=2;
-  IndexType bDim2=3;
-  IndexType bDim3=1;
-  IndexType bDim4=4;
-  array<IndexType, 4> in_range   = {{inDim1, inDim2, inDim3, inDim4}};
-  array<IndexType, 4> broadcasts = {{bDim1, bDim2, bDim3, bDim4}};
-  array<IndexType, 4> out_range;  // = in_range * broadcasts
+  array<int, 4> in_range   = {{2, 3, 5, 7}};
+  array<int, 4> broadcasts = {{2, 3, 1, 4}};
+  array<int, 4> out_range;  // = in_range * broadcasts
   for (size_t i = 0; i < out_range.size(); ++i)
     out_range[i] = in_range[i] * broadcasts[i];
 
-  Tensor<DataType, 4, DataLayout, IndexType>  input(in_range);
-  Tensor<DataType, 4, DataLayout, IndexType> out(out_range);
+  Tensor<float, 4>  input(in_range);
+  Tensor<float, 4> out(out_range);
 
   for (size_t i = 0; i < in_range.size(); ++i)
     VERIFY_IS_EQUAL(out.dimension(i), out_range[i]);
 
 
-  for (IndexType i = 0; i < input.size(); ++i)
-    input(i) = static_cast<DataType>(i);
+  for (int i = 0; i < input.size(); ++i)
+    input(i) = static_cast<float>(i);
 
-  DataType * gpu_in_data  = static_cast<DataType*>(sycl_device.allocate(input.dimensions().TotalSize()*sizeof(DataType)));
-  DataType * gpu_out_data  = static_cast<DataType*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(DataType)));
+  float * gpu_in_data  = static_cast<float*>(sycl_device.allocate(input.dimensions().TotalSize()*sizeof(float)));
+  float * gpu_out_data  = static_cast<float*>(sycl_device.allocate(out.dimensions().TotalSize()*sizeof(float)));
 
-  TensorMap<Tensor<DataType, 4, DataLayout, IndexType>>  gpu_in(gpu_in_data, in_range);
-  TensorMap<Tensor<DataType, 4, DataLayout, IndexType>> gpu_out(gpu_out_data, out_range);
-  sycl_device.memcpyHostToDevice(gpu_in_data, input.data(),(input.dimensions().TotalSize())*sizeof(DataType));
+  TensorMap<Tensor<float, 4>>  gpu_in(gpu_in_data, in_range);
+  TensorMap<Tensor<float, 4>> gpu_out(gpu_out_data, out_range);
+  sycl_device.memcpyHostToDevice(gpu_in_data, input.data(),(input.dimensions().TotalSize())*sizeof(float));
   gpu_out.device(sycl_device) = gpu_in.broadcast(broadcasts);
-  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(DataType));
+  sycl_device.memcpyDeviceToHost(out.data(), gpu_out_data,(out.dimensions().TotalSize())*sizeof(float));
 
-  for (IndexType i = 0; i < inDim1*bDim1; ++i) {
-    for (IndexType j = 0; j < inDim2*bDim2; ++j) {
-      for (IndexType k = 0; k < inDim3*bDim3; ++k) {
-        for (IndexType l = 0; l < inDim4*bDim4; ++l) {
-          VERIFY_IS_APPROX(input(i%inDim1,j%inDim2,k%inDim3,l%inDim4), out(i,j,k,l));
+  for (int i = 0; i < 4; ++i) {
+    for (int j = 0; j < 9; ++j) {
+      for (int k = 0; k < 5; ++k) {
+        for (int l = 0; l < 28; ++l) {
+          VERIFY_IS_APPROX(input(i%2,j%3,k%5,l%7), out(i,j,k,l));
         }
       }
     }
@@ -127,18 +67,8 @@ static void test_broadcast_sycl(const Eigen::SyclDevice &sycl_device){
   sycl_device.deallocate(gpu_out_data);
 }
 
-template<typename DataType> void sycl_broadcast_test_per_device(const cl::sycl::device& d){
-  std::cout << "Running on " << d.template get_info<cl::sycl::info::device::name>() << std::endl;
-  QueueInterface queueInterface(d);
-  auto sycl_device = Eigen::SyclDevice(&queueInterface);
-  test_broadcast_sycl<DataType, RowMajor, int64_t>(sycl_device);
-  test_broadcast_sycl<DataType, ColMajor, int64_t>(sycl_device);
-  test_broadcast_sycl_fixed<DataType, RowMajor, int64_t>(sycl_device);
-  test_broadcast_sycl_fixed<DataType, ColMajor, int64_t>(sycl_device);
-}
-
 void test_cxx11_tensor_broadcast_sycl() {
-  for (const auto& device :Eigen::get_sycl_supported_devices()) {
-    CALL_SUBTEST(sycl_broadcast_test_per_device<float>(device));
-  }
+  cl::sycl::gpu_selector s;
+  Eigen::SyclDevice sycl_device(s);
+  CALL_SUBTEST(test_broadcast_sycl(sycl_device));
 }