updating formatting

example/44_elementwise_permute/elementwise_permute_5D.cpp

@@ -46,8 +46,6 @@ int main()
     bool do_verification = true;
     bool time_kernel     = true;
 
-    //std::vector<std::size_t> ncdhw = {16, 128, 32, 64, 16};
-    //std::vector<std::size_t> nchwd = {16, 128, 64, 16, 32};
     std::vector<std::size_t> ncdhw = {16, 8, 8, 8, 8};
     std::vector<std::size_t> nchwd = {16, 8, 8, 8, 8};
     Tensor<ADataType> a(ncdhw);
@@ -64,12 +62,14 @@ int main()
     std::array<void*, 1> output      = {b_device_buf.GetDeviceBuffer()};
 
     std::array<ck::index_t, 5> ab_lengths;
-    std::array<ck::index_t, 5> a_strides = {static_cast<int>(ncdhw[1] * ncdhw[2] * ncdhw[3] * ncdhw[4]),
+    std::array<ck::index_t, 5> a_strides = {
+        static_cast<int>(ncdhw[1] * ncdhw[2] * ncdhw[3] * ncdhw[4]),
         static_cast<int>(ncdhw[2] * ncdhw[3] * ncdhw[4]),
         static_cast<int>(ncdhw[3] * ncdhw[4]),
         static_cast<int>(ncdhw[4]),
         1};
-    std::array<ck::index_t, 5> b_strides = {static_cast<int>(nchwd[1] * nchwd[2] * nchwd[3] * nchwd[4]),
+    std::array<ck::index_t, 5> b_strides = {
+        static_cast<int>(nchwd[1] * nchwd[2] * nchwd[3] * nchwd[4]),
         static_cast<int>(nchwd[2] * nchwd[3] * nchwd[4]),
         1,
         static_cast<int>(nchwd[3] * nchwd[4]),
@@ -95,17 +95,15 @@ int main()
         broadcastPermute_invoker_ptr->Run(argument.get(), StreamConfig{nullptr, time_kernel});
     std::size_t flop = std::size_t(2) * ncdhw[0] * ncdhw[1] * ncdhw[2] * ncdhw[3] * ncdhw[4];
 
-    std::size_t num_btype = sizeof(ADataType) * (ncdhw[0] * ncdhw[1] * ncdhw[2] * ncdhw[3] * ncdhw[4]) +
+    std::size_t num_btype =
+        sizeof(ADataType) * (ncdhw[0] * ncdhw[1] * ncdhw[2] * ncdhw[3] * ncdhw[4]) +
         sizeof(BDataType) * (ncdhw[0] * ncdhw[1] * ncdhw[2] * ncdhw[3] * ncdhw[4]);
 
     float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
 
     float gb_per_sec = num_btype / 1.E6 / ave_time;
 
-    //LogRangeAsType<float>(std::cout << "A  : ", a.mData, ",") << std::endl;
-    //LogRangeAsType<float>(std::cout << "B  : ", b.mData, ",") << std::endl;
-    //std::cout << "A: " << a.mData.data() << std::endl;
-
+    // LogRangeAsType<float>(std::cout << "A  : ", a.mData, ",") << std::endl;
     std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s"
               << std::endl;
 
@@ -117,8 +115,8 @@ int main()
         Tensor<BDataType> host_b(nchwd);
         host_elementwise4D(host_b, a, PassThrough{});
 
-	//LogRangeAsType<float>(std::cout << "B  : ", b.mData, ",") << std::endl;
-	//LogRangeAsType<float>(std::cout << "Host B  : ", host_b.mData, ",") << std::endl;
+        // LogRangeAsType<float>(std::cout << "B  : ", b.mData, ",") << std::endl;
+        // LogRangeAsType<float>(std::cout << "Host B  : ", host_b.mData, ",") << std::endl;
 
         pass &=
             ck::utils::check_err(b.mData, host_b.mData, "Error: Incorrect results b", 1e-3, 1e-3);