use scale (#363)

example/32_batched_gemm_scale_softmax_gemm/CMakeLists.txt

+add_example_executable(example_batched_gemm_scale_softmax_gemm_xdl_fp16 batched_gemm_scale_softmax_gemm_xdl_fp16.cpp)

example/32_batched_gemm_softmax_gemm/batched_gemm_softmax_gemm_xdl_fp16.cpp → example/32_batched_gemm_scale_softmax_gemm/batched_gemm_scale_softmax_gemm_xdl_fp16.cpp

@@ -51,7 +51,7 @@ using CLayout  = Row;
 
 using AElementOp    = PassThrough;
 using B0ElementOp   = PassThrough;
-using Acc0ElementOp = PassThrough;
+using Acc0ElementOp = ck::tensor_operation::element_wise::Scale;
 using B1ElementOp   = PassThrough;
 using CElementOp    = PassThrough;
 
@@ -122,7 +122,7 @@ using ReferenceGemm0Instance = ck::tensor_operation::host::ReferenceBatchedGemm<
                                                                                 AccDataType,
                                                                                 AElementOp,
                                                                                 B0ElementOp,
-                                                                                CElementOp>;
+                                                                                Acc0ElementOp>;
 
 // Ref Softmax: fp32 in, fp16 out
 using ReferenceSoftmaxInstance =
@@ -157,6 +157,7 @@ int main(int argc, char* argv[])
     ck::index_t BatchStrideB0 = -1;
     ck::index_t BatchStrideB1 = -1;
     ck::index_t BatchStrideC  = -1;
+    float alpha               = 1;
 
     if(argc == 1)
     {
@@ -181,7 +182,7 @@ int main(int argc, char* argv[])
 
         BatchCount = std::stoi(argv[8]);
     }
-    else if(argc == 17)
+    else if(argc == 18)
     {
         do_verification = std::stoi(argv[1]);
         init_method     = std::stoi(argv[2]);
@@ -203,6 +204,8 @@ int main(int argc, char* argv[])
         BatchStrideB0 = std::stoi(argv[14]);
         BatchStrideB1 = std::stoi(argv[15]);
         BatchStrideC  = std::stoi(argv[16]);
+
+        alpha = std::stof(argv[17]);
     }
     else
     {
@@ -211,6 +214,7 @@ int main(int argc, char* argv[])
         printf("arg3: time kernel (0=no, 1=yes)\n");
         printf("arg4 to 17: M, N, K, O, Batch, StrideA, StrideB0, StrideB1, StrideC, BatchStrideA, "
                "BatchStrideB0, BatchStrideB1, BatchStrideC\n");
+        printf("arg18: alpha\n");
         exit(0);
     }
 
@@ -304,7 +308,7 @@ int main(int argc, char* argv[])
 
     auto a_element_op    = AElementOp{};
     auto b0_element_op   = B0ElementOp{};
-    auto acc0_element_op = Acc0ElementOp{};
+    auto acc0_element_op = Acc0ElementOp{alpha};
     auto b1_element_op   = B1ElementOp{};
     auto c_element_op    = CElementOp{};
 
@@ -368,7 +372,7 @@ int main(int argc, char* argv[])
         auto ref_gemm0          = ReferenceGemm0Instance{};
         auto ref_gemm0_invoker  = ref_gemm0.MakeInvoker();
         auto ref_gemm0_argument = ref_gemm0.MakeArgument(
-            a_g_m_k, b0_g_k_n, acc0_g_m_n, a_element_op, b0_element_op, PassThrough{});
+            a_g_m_k, b0_g_k_n, acc0_g_m_n, a_element_op, b0_element_op, acc0_element_op);
 
         ref_gemm0_invoker.Run(ref_gemm0_argument);
 

example/32_batched_gemm_softmax_gemm/CMakeLists.txt

-# TODO: add example batched_gemm_gemm_xdl_fp16
-add_example_executable(example_batched_gemm_softmax_gemm_xdl_fp16 batched_gemm_softmax_gemm_xdl_fp16.cpp)

example/CMakeLists.txt

@@ -46,7 +46,7 @@ add_subdirectory(28_grouped_gemm_bias_e_permute)
 add_subdirectory(29_batched_gemm_bias_e_permute)
 add_subdirectory(30_grouped_convnd_fwd_bias_relu_add)
 add_subdirectory(31_batched_gemm_gemm)
-add_subdirectory(32_batched_gemm_softmax_gemm)
+add_subdirectory(32_batched_gemm_scale_softmax_gemm)
 add_subdirectory(33_multiple_reduce)
 add_subdirectory(34_batchnorm)
 

include/ck/tensor_operation/gpu/grid/gridwise_batched_gemm_softmax_gemm_xdl_cshuffle_v1.hpp

@@ -561,11 +561,11 @@ struct GridwiseBatchedGemmSoftmaxGemm_Xdl_CShuffle
             FloatAB,
             decltype(acc_thread_desc_k0_m_k1),
             decltype(a1_thread_desc_k0_m_k1),
-            decltype(acc_element_op),
+            tensor_operation::element_wise::PassThrough,
             Sequence<A1ThreadSliceK0, A1ThreadSliceM, A1ThreadSliceK1>,
             Sequence<1, 0, 2>,
             2,
-            n4>{acc_element_op};
+            n4>{tensor_operation::element_wise::PassThrough{}};
 
         // B1 matrix blockwise copy
         auto b1_blockwise_copy =
@@ -717,6 +717,11 @@ struct GridwiseBatchedGemmSoftmaxGemm_Xdl_CShuffle
                                                                    blockwise_gemm,
                                                                    acc_thread_buf,
                                                                    num_k_block_main_loop);
+
+            // Acc0 elementwise Op
+            static_for<0, acc_thread_buf.Size(), 1>{}(
+                [&](auto i) { acc_element_op(acc_thread_buf(i), acc_thread_buf[i]); });
+
             // softmax
             SoftmaxBuf& max = blockwise_softmax.max_value_buf;
             SoftmaxBuf& sum = blockwise_softmax.sum_value_buf;