Bugfixes on gfx1101 architecture.

example/32_batched_gemm_scale_softmax_gemm/run_batched_gemm_scale_softmax_gemm_permute_wmma.inc

@@ -153,7 +153,7 @@ int run(int argc, char* argv[])
         b1_gs_os_ns.GenerateTensorValue(GeneratorTensor_2<B1DataType>{-2, 2});
         break;
     default:
-        a_gs_ms_ks.GenerateTensorValue(GeneratorTensor_Sequential<2>{});
+        a_gs_ms_ks.GenerateTensorValue(GeneratorTensor_Sequential<ADataType, 2>{});
         b0_gs_ns_ks.GenerateTensorValue(GeneratorTensor_Diagonal<B0DataType>{});
         b1_gs_os_ns.GenerateTensorValue(GeneratorTensor_Diagonal<B1DataType>{});
     }

example/32_batched_gemm_scale_softmax_gemm/run_cross_attention_wmma.inc

@@ -178,7 +178,7 @@ int run(int argc, char* argv[])
         b1_gs_os_ns.GenerateTensorValue(GeneratorTensor_2<B1DataType>{-2, 2});
         break;
     default:
-        a_gs_ms_ks.GenerateTensorValue(GeneratorTensor_Sequential<2>{});
+        a_gs_ms_ks.GenerateTensorValue(GeneratorTensor_Sequential<ADataType, 2>{});
         b0_gs_ns_ks.GenerateTensorValue(GeneratorTensor_Diagonal<B0DataType>{});
         b1_gs_os_ns.GenerateTensorValue(GeneratorTensor_Diagonal<B1DataType>{});
     }

example/32_batched_gemm_scale_softmax_gemm/run_grouped_query_attention_forward_wmma.inc

@@ -156,7 +156,7 @@ int run(int argc, char* argv[])
         b1_gs_os_ns.GenerateTensorValue(GeneratorTensor_2<B1DataType>{-2, 2});
         break;
     default:
-        a_gs_ms_ks.GenerateTensorValue(GeneratorTensor_Sequential<2>{});
+        a_gs_ms_ks.GenerateTensorValue(GeneratorTensor_Sequential<ADataType, 2>{});
         b0_gs_ns_ks.GenerateTensorValue(GeneratorTensor_Diagonal<B0DataType>{});
         b1_gs_os_ns.GenerateTensorValue(GeneratorTensor_Diagonal<B1DataType>{});
     }

example/32_batched_gemm_scale_softmax_gemm/run_multi_query_attention_forward_wmma.inc

@@ -156,7 +156,7 @@ int run(int argc, char* argv[])
         b1_gs_os_ns.GenerateTensorValue(GeneratorTensor_2<B1DataType>{-2, 2});
         break;
     default:
-        a_gs_ms_ks.GenerateTensorValue(GeneratorTensor_Sequential<2>{});
+        a_gs_ms_ks.GenerateTensorValue(GeneratorTensor_Sequential<ADataType, 2>{});
         b0_gs_ns_ks.GenerateTensorValue(GeneratorTensor_Diagonal<B0DataType>{});
         b1_gs_os_ns.GenerateTensorValue(GeneratorTensor_Diagonal<B1DataType>{});
     }

example/32_batched_gemm_scale_softmax_gemm/run_self_attention_wmma.inc

@@ -173,7 +173,7 @@ int run(int argc, char* argv[])
         b1_gs_os_ns.GenerateTensorValue(GeneratorTensor_2<B1DataType>{-2, 2});
         break;
     default:
-        a_gs_ms_ks.GenerateTensorValue(GeneratorTensor_Sequential<2>{});
+        a_gs_ms_ks.GenerateTensorValue(GeneratorTensor_Sequential<ADataType, 2>{});
         b0_gs_ns_ks.GenerateTensorValue(GeneratorTensor_Diagonal<B0DataType>{});
         b1_gs_os_ns.GenerateTensorValue(GeneratorTensor_Diagonal<B1DataType>{});
     }

library/include/ck/library/utility/host_tensor.hpp

@@ -326,7 +326,7 @@ struct Tensor
 
     std::size_t GetElementSpaceSizeInBytes() const { return sizeof(T) * GetElementSpaceSize(); }
 
-    void SetZero() { ck::ranges::fill<T>(mData, 0); }
+    void SetZero() { ck::ranges::fill<T>(mData, T{0}); }
 
     template <typename F>
     void ForEach_impl(F&& f, std::vector<size_t>& idx, size_t rank)

profiler/include/profiler/profile_gemm_impl.hpp

@@ -74,8 +74,8 @@ int profile_gemm_impl(int do_verification,
     switch(init_method)
     {
     case 0:
-        ck::utils::FillConstant<ADataType>{static_cast<ADataType>(1.f)}(a_m_k);
-        ck::utils::FillConstant<BDataType>{static_cast<BDataType>(1.f)}(b_k_n);
+        ck::utils::FillConstant<ADataType>{type_convert<ADataType>(1.f)}(a_m_k);
+        ck::utils::FillConstant<BDataType>{type_convert<BDataType>(1.f)}(b_k_n);
         break;
     case 1:
         ck::utils::FillUniformDistributionIntegerValue<ADataType>{-5.f, 5.f}(a_m_k);