clean

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

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
 #pragma once
 
 #include "ck/utility/common_header.hpp"

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

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
 #pragma once
 
 #include "ck/utility/common_header.hpp"
@@ -5,13 +8,13 @@
 #include "ck/tensor_description/tensor_descriptor.hpp"
 #include "ck/tensor_description/tensor_descriptor_helper.hpp"
 #include "ck/tensor_operation/gpu/grid/block_to_ctile_map.hpp"
-#include "ck/tensor_operation/gpu/grid/gridwise_gemm_pipeline_v1.hpp"
+#include "ck/tensor_operation/gpu/grid/gridwise_gemm_waveletmodel.hpp"
 #include "ck/tensor_operation/gpu/block/blockwise_gemm_xdlops.hpp"
 #include "ck/tensor_operation/gpu/block/thread_group_tensor_slice_transfer_v4r1.hpp"
 #include "ck/tensor_operation/gpu/block/thread_group_tensor_slice_transfer_v6r1.hpp"
 #include "ck/tensor_operation/gpu/thread/threadwise_tensor_slice_transfer.hpp"
 #include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
-#include "ck/tensor_operation/gpu/grid/gridwise_gemm_waveletmodel.hpp"
+
 namespace ck {
 
 template <typename GridwiseGemm,
@@ -156,7 +159,9 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdl_waveletmodel_cshuffle
 
         __device__ static index_t GetThreadId() { return get_thread_local_1d_id(); }
     };
+
     using CShuffleBlockTransferThreadGroup = ThisThreadBlock<TileMathThreadGroupSize>;
+
     // load and math+store Wave pipelines.
     // TODO: build pipelines blocks scheduling parallel tasks
     using GridwiseGemmLoad = GridwiseGemmLoadWave<TileLoadThreadGroup, NumGemmKPrefetchStage>;
@@ -220,6 +225,7 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdl_waveletmodel_cshuffle
                              sizeof(FloatAB),
                          c_block_size * sizeof(FloatCShuffle));
     }
+
     // block_id to matrix tile idx (m0, n0) mapping are controlled by {M01, N01}
     __host__ __device__ static constexpr bool
     CheckValidity(const AGridDesc_AK0_M_AK1& a_grid_desc_ak0_m_ak1,
@@ -251,6 +257,7 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdl_waveletmodel_cshuffle
         // TODO: also check validity of all components (blockwise-copy, threadwise-copy, etc)
         return true;
     }
+
     __host__ __device__ static constexpr index_t
     CalculateGridSize(const CGridDesc_M_N& c_grid_desc_m_n)
     {
@@ -377,6 +384,7 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdl_waveletmodel_cshuffle
         const index_t num_k_block_main_loop = __builtin_amdgcn_readfirstlane(
             (a_grid_desc_ak0_m_ak1.GetLength(I0) * a_grid_desc_ak0_m_ak1.GetLength(I2)) /
             KPerBlock);
+
         // divide block work by [M, N]
         const auto block_work_idx =
             block_2_ctile_map.CalculateBottomIndex(make_multi_index(get_block_1d_id()));
@@ -479,7 +487,6 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdl_waveletmodel_cshuffle
         }
         else if(TileMathThreadGroup::IsBelong())
         {
-
             // branch early for math wave
             constexpr index_t KPack =
                 math::max(math::lcm(AK1, BK1),