merge develop

library/include/ck/library/tensor_operation_instance/gpu/device_gemm_mean_squaremean_instance.hpp

@@ -10,12 +10,12 @@
 #include "ck/tensor_operation/gpu/device/device_gemm_reduce.hpp"
 #include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
 
-#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
 
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_gemm_instance {
+namespace instance {
 
 using DeviceGemmAddAddMeanSquareMeanPtr = ck::tensor_operation::device::DeviceGemmReducePtr<1, 2>;
 
@@ -45,7 +45,7 @@ auto get_device_gemm_add_add_mean_squaremean_instances()
                      is_same<BLayout, tensor_layout::gemm::RowMajor>::value &&
                      is_same<CLayout, tensor_layout::gemm::RowMajor>::value)
         {
-            ck::tensor_operation::device::device_gemm_instance::
+            ck::tensor_operation::device::instance::
                 add_device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_mk_kn_mn_instances(
                     op_ptrs);
         }
@@ -53,7 +53,7 @@ auto get_device_gemm_add_add_mean_squaremean_instances()
                           is_same<BLayout, tensor_layout::gemm::ColumnMajor>::value &&
                           is_same<CLayout, tensor_layout::gemm::RowMajor>::value)
         {
-            ck::tensor_operation::device::device_gemm_instance::
+            ck::tensor_operation::device::instance::
                 add_device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_mk_nk_mn_instances(
                     op_ptrs);
         }
@@ -61,7 +61,7 @@ auto get_device_gemm_add_add_mean_squaremean_instances()
                           is_same<BLayout, tensor_layout::gemm::RowMajor>::value &&
                           is_same<CLayout, tensor_layout::gemm::RowMajor>::value)
         {
-            ck::tensor_operation::device::device_gemm_instance::
+            ck::tensor_operation::device::instance::
                 add_device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_km_kn_mn_instances(
                     op_ptrs);
         }
@@ -69,7 +69,7 @@ auto get_device_gemm_add_add_mean_squaremean_instances()
                           is_same<BLayout, tensor_layout::gemm::ColumnMajor>::value &&
                           is_same<CLayout, tensor_layout::gemm::RowMajor>::value)
         {
-            ck::tensor_operation::device::device_gemm_instance::
+            ck::tensor_operation::device::instance::
                 add_device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_km_nk_mn_instances(
                     op_ptrs);
         }
@@ -78,7 +78,7 @@ auto get_device_gemm_add_add_mean_squaremean_instances()
     return op_ptrs;
 }
 
-} // namespace device_gemm_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/gemm.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include <cstdlib>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_gemm.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+
+#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+void add_device_gemm_dl_f16_f16_f16_km_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Row, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_dl_f16_f16_f16_km_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Col, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_dl_f16_f16_f16_mk_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Row, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_dl_f16_f16_f16_mk_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Col, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_dl_f32_f32_f32_km_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Row, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
+
+        instances);
+
+void add_device_gemm_dl_f32_f32_f32_km_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Col, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_dl_f32_f32_f32_mk_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Row, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_dl_f32_f32_f32_mk_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Col, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_dl_i8_i8_i8_km_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Row, Row, int8_t, int8_t, int8_t, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_dl_i8_i8_i8_km_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Col, Row, int8_t, int8_t, int8_t, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_dl_i8_i8_i8_mk_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Row, Row, int8_t, int8_t, int8_t, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_dl_i8_i8_i8_mk_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Col, Row, int8_t, int8_t, int8_t, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_2_stage_f16_f16_f16_mk_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Col, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Row, Row, BF16, BF16, BF16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Col, Row, BF16, BF16, BF16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_mk_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Row, Row, BF16, BF16, BF16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_mk_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Col, Row, BF16, BF16, BF16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_f16_f16_f16_km_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Row, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Col, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_f16_f16_f16_mk_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Row, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_f16_f16_f16_mk_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Col, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_f32_f32_f32_km_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Row, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_f32_f32_f32_km_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Col, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_f32_f32_f32_mk_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Row, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_f32_f32_f32_mk_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Col, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_i8_i8_i8_km_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Row, Row, int8_t, int8_t, int8_t, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_i8_i8_i8_km_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Col, Row, int8_t, int8_t, int8_t, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_i8_i8_i8_mk_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Row, Row, int8_t, int8_t, int8_t, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_c_shuffle_i8_i8_i8_mk_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Col, Row, int8_t, int8_t, int8_t, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_f16_f16_f16_km_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Row, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_f16_f16_f16_km_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Col, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_f16_f16_f16_mk_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Row, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_f16_f16_f16_mk_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Col, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_f32_f32_f32_km_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Row, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_f32_f32_f32_km_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Col, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_f32_f32_f32_mk_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Row, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_f32_f32_f32_mk_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Col, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_f64_f64_f64_km_kn_mn_instances(
+    std::vector<std::unique_ptr<
+
+        DeviceGemm<Col, Row, Row, F64, F64, F64, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_f64_f64_f64_km_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Col, Col, Row, F64, F64, F64, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_f64_f64_f64_mk_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Row, Row, F64, F64, F64, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_f64_f64_f64_mk_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemm<Row, Col, Row, F64, F64, F64, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+template <typename ALayout,
+          typename BLayout,
+          typename CLayout,
+          typename ADataType,
+          typename BDataType,
+          typename CDataType>
+struct DeviceOperationInstanceFactory<
+    ck::tensor_operation::device::DeviceGemm<ALayout,
+                                             BLayout,
+                                             CLayout,
+                                             ADataType,
+                                             BDataType,
+                                             CDataType,
+                                             ck::tensor_operation::element_wise::PassThrough,
+                                             ck::tensor_operation::element_wise::PassThrough,
+                                             ck::tensor_operation::element_wise::PassThrough>>
+{
+    using DeviceOp = DeviceGemm<ALayout,
+                                BLayout,
+                                CLayout,
+                                ADataType,
+                                BDataType,
+                                CDataType,
+                                ck::tensor_operation::element_wise::PassThrough,
+                                ck::tensor_operation::element_wise::PassThrough,
+                                ck::tensor_operation::element_wise::PassThrough>;
+
+    static auto GetInstances()
+    {
+        std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
+
+        if constexpr(is_same_v<ADataType, float> && is_same_v<BDataType, float> &&
+                     is_same_v<CDataType, float>)
+        {
+            if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
+                         is_same_v<CLayout, Row>)
+            {
+                add_device_gemm_xdl_f32_f32_f32_mk_kn_mn_instances(op_ptrs);
+                add_device_gemm_dl_f32_f32_f32_mk_kn_mn_instances(op_ptrs);
+                add_device_gemm_xdl_c_shuffle_f32_f32_f32_mk_kn_mn_instances(op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
+                              is_same_v<CLayout, Row>)
+            {
+                add_device_gemm_xdl_f32_f32_f32_mk_nk_mn_instances(op_ptrs);
+                add_device_gemm_dl_f32_f32_f32_mk_nk_mn_instances(op_ptrs);
+                add_device_gemm_xdl_c_shuffle_f32_f32_f32_mk_nk_mn_instances(op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> &&
+                              is_same_v<CLayout, Row>)
+            {
+                add_device_gemm_xdl_f32_f32_f32_km_kn_mn_instances(op_ptrs);
+                add_device_gemm_dl_f32_f32_f32_km_kn_mn_instances(op_ptrs);
+                add_device_gemm_xdl_c_shuffle_f32_f32_f32_km_kn_mn_instances(op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Col> &&
+                              is_same_v<CLayout, Row>)
+            {
+                add_device_gemm_xdl_f32_f32_f32_km_nk_mn_instances(op_ptrs);
+                add_device_gemm_dl_f32_f32_f32_km_nk_mn_instances(op_ptrs);
+                add_device_gemm_xdl_c_shuffle_f32_f32_f32_km_nk_mn_instances(op_ptrs);
+            }
+        }
+        else if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
+                          is_same_v<CDataType, half_t>)
+        {
+            if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
+                         is_same_v<CLayout, Row>)
+            {
+                add_device_gemm_xdl_f16_f16_f16_mk_kn_mn_instances(op_ptrs);
+                add_device_gemm_dl_f16_f16_f16_mk_kn_mn_instances(op_ptrs);
+                add_device_gemm_xdl_c_shuffle_f16_f16_f16_mk_kn_mn_instances(op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
+                              is_same_v<CLayout, Row>)
+            {
+                add_device_gemm_xdl_f16_f16_f16_mk_nk_mn_instances(op_ptrs);
+                add_device_gemm_dl_f16_f16_f16_mk_nk_mn_instances(op_ptrs);
+                add_device_gemm_xdl_c_shuffle_f16_f16_f16_mk_nk_mn_instances(op_ptrs);
+                add_device_gemm_xdl_c_shuffle_2_stage_f16_f16_f16_mk_nk_mn_instances(op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> &&
+                              is_same_v<CLayout, Row>)
+            {
+                add_device_gemm_xdl_f16_f16_f16_km_kn_mn_instances(op_ptrs);
+                add_device_gemm_dl_f16_f16_f16_km_kn_mn_instances(op_ptrs);
+                add_device_gemm_xdl_c_shuffle_f16_f16_f16_km_kn_mn_instances(op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Col> &&
+                              is_same_v<CLayout, Row>)
+            {
+                add_device_gemm_xdl_f16_f16_f16_km_nk_mn_instances(op_ptrs);
+                add_device_gemm_dl_f16_f16_f16_km_nk_mn_instances(op_ptrs);
+                add_device_gemm_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instances(op_ptrs);
+            }
+        }
+        else if constexpr(is_same_v<ADataType, ck::bhalf_t> && is_same_v<BDataType, ck::bhalf_t> &&
+                          is_same_v<CDataType, ck::bhalf_t>)
+        {
+            if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
+                         is_same_v<CLayout, Row>)
+            {
+                add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_mk_kn_mn_instances(op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
+                              is_same_v<CLayout, Row>)
+            {
+                add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_mk_nk_mn_instances(op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> &&
+                              is_same_v<CLayout, Row>)
+            {
+                add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_kn_mn_instances(op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Col> &&
+                              is_same_v<CLayout, Row>)
+            {
+                add_device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_nk_mn_instances(op_ptrs);
+            }
+        }
+        else if constexpr(is_same_v<ADataType, int8_t> && is_same_v<BDataType, int8_t> &&
+                          is_same_v<CDataType, int8_t>)
+        {
+            if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
+                         is_same_v<CLayout, Row>)
+            {
+                add_device_gemm_xdl_c_shuffle_i8_i8_i8_mk_kn_mn_instances(op_ptrs);
+                add_device_gemm_dl_i8_i8_i8_mk_kn_mn_instances(op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
+                              is_same_v<CLayout, Row>)
+            {
+                add_device_gemm_xdl_c_shuffle_i8_i8_i8_mk_nk_mn_instances(op_ptrs);
+                add_device_gemm_dl_i8_i8_i8_mk_nk_mn_instances(op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> &&
+                              is_same_v<CLayout, Row>)
+            {
+                add_device_gemm_xdl_c_shuffle_i8_i8_i8_km_kn_mn_instances(op_ptrs);
+                add_device_gemm_dl_i8_i8_i8_km_kn_mn_instances(op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Col> &&
+                              is_same_v<CLayout, Row>)
+            {
+                add_device_gemm_xdl_c_shuffle_i8_i8_i8_km_nk_mn_instances(op_ptrs);
+                add_device_gemm_dl_i8_i8_i8_km_nk_mn_instances(op_ptrs);
+            }
+        }
+
+        return op_ptrs;
+    }
+};
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/gemm_add_add_fastgelu.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include <cstdlib>
+#include <vector>
+#include <memory>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_gemm_multiple_d.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+
+#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+void add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_mk_kn_mn_instances(
+    std::vector<std::unique_ptr<DeviceGemmMultipleD<Row,
+                                                    Row,
+                                                    Row,
+                                                    F16,
+                                                    F16,
+                                                    F16_F16_TUPLE,
+                                                    F16,
+                                                    PassThrough,
+                                                    PassThrough,
+                                                    AddAddFastGelu>>>&);
+
+void add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_mk_nk_mn_instances(
+    std::vector<std::unique_ptr<DeviceGemmMultipleD<Row,
+                                                    Col,
+                                                    Row,
+                                                    F16,
+                                                    F16,
+                                                    F16_F16_TUPLE,
+                                                    F16,
+                                                    PassThrough,
+                                                    PassThrough,
+                                                    AddAddFastGelu>>>&);
+
+void add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_km_kn_mn_instances(
+    std::vector<std::unique_ptr<DeviceGemmMultipleD<Col,
+                                                    Row,
+                                                    Row,
+                                                    F16,
+                                                    F16,
+                                                    F16_F16_TUPLE,
+                                                    F16,
+                                                    PassThrough,
+                                                    PassThrough,
+                                                    AddAddFastGelu>>>&);
+
+void add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instances(
+    std::vector<std::unique_ptr<DeviceGemmMultipleD<Col,
+                                                    Col,
+                                                    Row,
+                                                    F16,
+                                                    F16,
+                                                    F16_F16_TUPLE,
+                                                    F16,
+                                                    PassThrough,
+                                                    PassThrough,
+                                                    AddAddFastGelu>>>&);
+
+// GEMM + Add + Add + FastGelu
+template <typename ALayout,
+          typename BLayout,
+          typename DELayout,
+          typename ADataType,
+          typename BDataType,
+          typename D0DataType,
+          typename D1DataType,
+          typename EDataType>
+struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMultipleD<
+    ALayout,
+    BLayout,
+    DELayout,
+    ADataType,
+    BDataType,
+    ck::Tuple<D0DataType, D1DataType>,
+    EDataType,
+    ck::tensor_operation::element_wise::PassThrough,
+    ck::tensor_operation::element_wise::PassThrough,
+    ck::tensor_operation::element_wise::AddAddFastGelu>>
+{
+    using DeviceOp = DeviceGemmMultipleD<ALayout,
+                                         BLayout,
+                                         DELayout,
+                                         ADataType,
+                                         BDataType,
+                                         ck::Tuple<D0DataType, D1DataType>,
+                                         EDataType,
+                                         ck::tensor_operation::element_wise::PassThrough,
+                                         ck::tensor_operation::element_wise::PassThrough,
+                                         ck::tensor_operation::element_wise::AddAddFastGelu>;
+
+    static auto GetInstances()
+    {
+        std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
+
+        if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
+                     is_same_v<D0DataType, half_t> && is_same_v<D1DataType, half_t> &&
+                     is_same_v<EDataType, half_t>)
+        {
+            if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
+                         is_same_v<DELayout, Row>)
+            {
+                add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_mk_kn_mn_instances(
+                    op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
+                              is_same_v<DELayout, Row>)
+            {
+                add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_mk_nk_mn_instances(
+                    op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> &&
+                              is_same_v<DELayout, Row>)
+            {
+                add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_km_kn_mn_instances(
+                    op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Col> &&
+                              is_same_v<DELayout, Row>)
+            {
+                add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instances(
+                    op_ptrs);
+            }
+        }
+
+        return op_ptrs;
+    }
+};
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/gemm_bilinear.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include <cstdlib>
+#include <vector>
+#include <memory>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_gemm_multiple_d.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+
+#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+void add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_km_kn_mn_instances(
+    std::vector<std::unique_ptr<DeviceGemmMultipleD<Col,
+                                                    Row,
+                                                    Row,
+                                                    F16,
+                                                    F16,
+                                                    F16_TUPLE,
+                                                    F16,
+                                                    PassThrough,
+                                                    PassThrough,
+                                                    Bilinear>>>& instances);
+
+void add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instances(
+    std::vector<std::unique_ptr<DeviceGemmMultipleD<Col,
+                                                    Col,
+                                                    Row,
+                                                    F16,
+                                                    F16,
+                                                    F16_TUPLE,
+                                                    F16,
+                                                    PassThrough,
+                                                    PassThrough,
+                                                    Bilinear>>>& instances);
+
+void add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_mk_kn_mn_instances(
+    std::vector<std::unique_ptr<DeviceGemmMultipleD<Row,
+                                                    Row,
+                                                    Row,
+                                                    F16,
+                                                    F16,
+                                                    F16_TUPLE,
+                                                    F16,
+                                                    PassThrough,
+                                                    PassThrough,
+                                                    Bilinear>>>& instances);
+
+void add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_mk_nk_mn_instances(
+    std::vector<std::unique_ptr<DeviceGemmMultipleD<Row,
+                                                    Col,
+                                                    Row,
+                                                    F16,
+                                                    F16,
+                                                    F16_TUPLE,
+                                                    F16,
+                                                    PassThrough,
+                                                    PassThrough,
+                                                    Bilinear>>>& instances);
+
+// GEMM + Bilinear
+template <typename ALayout,
+          typename BLayout,
+          typename DELayout,
+          typename ADataType,
+          typename BDataType,
+          typename DDataType,
+          typename EDataType>
+struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMultipleD<
+    ALayout,
+    BLayout,
+    DELayout,
+    ADataType,
+    BDataType,
+    ck::Tuple<DDataType>,
+    EDataType,
+    ck::tensor_operation::element_wise::PassThrough,
+    ck::tensor_operation::element_wise::PassThrough,
+    ck::tensor_operation::element_wise::Bilinear>>
+{
+    using DeviceOp = DeviceGemmMultipleD<ALayout,
+                                         BLayout,
+                                         DELayout,
+                                         ADataType,
+                                         BDataType,
+                                         ck::Tuple<DDataType>,
+                                         EDataType,
+                                         ck::tensor_operation::element_wise::PassThrough,
+                                         ck::tensor_operation::element_wise::PassThrough,
+                                         ck::tensor_operation::element_wise::Bilinear>;
+
+    static auto GetInstances()
+    {
+        std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
+
+        if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
+                     is_same_v<DDataType, half_t> && is_same_v<EDataType, half_t>)
+        {
+            if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
+                         is_same_v<DELayout, Row>)
+            {
+                add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_mk_kn_mn_instances(op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
+                              is_same_v<DELayout, Row>)
+            {
+                add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_mk_nk_mn_instances(op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> &&
+                              is_same_v<DELayout, Row>)
+            {
+                add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_km_kn_mn_instances(op_ptrs);
+            }
+            else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Col> &&
+                              is_same_v<DELayout, Row>)
+            {
+                add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instances(op_ptrs);
+            }
+        }
+
+        return op_ptrs;
+    }
+};
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/device_gemm_splitk_instance.hpp → library/include/ck/library/tensor_operation_instance/gpu/gemm_splitk.hpp

@@ -10,35 +10,52 @@
 #include "ck/tensor_operation/gpu/device/device_gemm_splitk.hpp"
 #include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
 
-#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
+#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
 
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_gemm_instance {
+namespace instance {
 
-using DeviceGemmSplitKNoOpPtr = ck::tensor_operation::device::DeviceGemmSplitKPtr<
-    ck::tensor_operation::element_wise::PassThrough,
-    ck::tensor_operation::element_wise::PassThrough,
-    ck::tensor_operation::element_wise::PassThrough>;
+void add_device_gemm_xdl_splitk_f16_f16_f16_km_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemmSplitK<Col, Row, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
 
-void add_device_gemm_xdl_splitk_f32_f32_f32_mk_kn_mn_instances(
-    std::vector<DeviceGemmSplitKNoOpPtr>&);
-void add_device_gemm_xdl_splitk_f32_f32_f32_mk_nk_mn_instances(
-    std::vector<DeviceGemmSplitKNoOpPtr>&);
-void add_device_gemm_xdl_splitk_f32_f32_f32_km_kn_mn_instances(
-    std::vector<DeviceGemmSplitKNoOpPtr>&);
-void add_device_gemm_xdl_splitk_f32_f32_f32_km_nk_mn_instances(
-    std::vector<DeviceGemmSplitKNoOpPtr>&);
+void add_device_gemm_xdl_splitk_f16_f16_f16_km_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemmSplitK<Col, Col, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
 
 void add_device_gemm_xdl_splitk_f16_f16_f16_mk_kn_mn_instances(
-    std::vector<DeviceGemmSplitKNoOpPtr>&);
+    std::vector<std::unique_ptr<
+        DeviceGemmSplitK<Row, Row, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
 void add_device_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_instances(
-    std::vector<DeviceGemmSplitKNoOpPtr>&);
-void add_device_gemm_xdl_splitk_f16_f16_f16_km_kn_mn_instances(
-    std::vector<DeviceGemmSplitKNoOpPtr>&);
-void add_device_gemm_xdl_splitk_f16_f16_f16_km_nk_mn_instances(
-    std::vector<DeviceGemmSplitKNoOpPtr>&);
+    std::vector<std::unique_ptr<
+        DeviceGemmSplitK<Row, Col, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_splitk_f32_f32_f32_km_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemmSplitK<Col, Row, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_splitk_f32_f32_f32_km_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemmSplitK<Col, Col, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_splitk_f32_f32_f32_mk_kn_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemmSplitK<Row, Row, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
+        instances);
+
+void add_device_gemm_xdl_splitk_f32_f32_f32_mk_nk_mn_instances(
+    std::vector<std::unique_ptr<
+        DeviceGemmSplitK<Row, Col, Row, F32, F32, F32, PassThrough, PassThrough, PassThrough>>>&
+        instances);
 
 template <typename ADataType,
           typename BDataType,
@@ -46,79 +63,85 @@ template <typename ADataType,
           typename ALayout,
           typename BLayout,
           typename CLayout>
-auto get_device_gemm_splitk_instances()
+struct DeviceOperationInstanceFactory<
+    ck::tensor_operation::device::DeviceGemmSplitK<ALayout,
+                                                   BLayout,
+                                                   CLayout,
+                                                   ADataType,
+                                                   BDataType,
+                                                   CDataType,
+                                                   ck::tensor_operation::element_wise::PassThrough,
+                                                   ck::tensor_operation::element_wise::PassThrough,
+                                                   ck::tensor_operation::element_wise::PassThrough>>
 {
-    std::vector<DeviceGemmSplitKNoOpPtr> op_ptrs;
+    using DeviceOp = DeviceGemmSplitK<ALayout,
+                                      BLayout,
+                                      CLayout,
+                                      ADataType,
+                                      BDataType,
+                                      CDataType,
+                                      ck::tensor_operation::element_wise::PassThrough,
+                                      ck::tensor_operation::element_wise::PassThrough,
+                                      ck::tensor_operation::element_wise::PassThrough>;
 
-    if constexpr(is_same<ADataType, float>::value && is_same<BDataType, float>::value &&
-                 is_same<CDataType, float>::value)
+    static auto GetInstances()
     {
-        if constexpr(is_same<ALayout, tensor_layout::gemm::RowMajor>::value &&
-                     is_same<BLayout, tensor_layout::gemm::RowMajor>::value &&
-                     is_same<CLayout, tensor_layout::gemm::RowMajor>::value)
+        std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
+
+        if constexpr(is_same_v<ADataType, float> && is_same_v<BDataType, float> &&
+                     is_same_v<CDataType, float>)
         {
-            ck::tensor_operation::device::device_gemm_instance::
+            if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
+                         is_same_v<CLayout, Row>)
+            {
                 add_device_gemm_xdl_splitk_f32_f32_f32_mk_kn_mn_instances(op_ptrs);
-        }
-        else if constexpr(is_same<ALayout, tensor_layout::gemm::RowMajor>::value &&
-                          is_same<BLayout, tensor_layout::gemm::ColumnMajor>::value &&
-                          is_same<CLayout, tensor_layout::gemm::RowMajor>::value)
-        {
-            ck::tensor_operation::device::device_gemm_instance::
+            }
+            else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
+                              is_same_v<CLayout, Row>)
+            {
                 add_device_gemm_xdl_splitk_f32_f32_f32_mk_nk_mn_instances(op_ptrs);
-        }
-        else if constexpr(is_same<ALayout, tensor_layout::gemm::ColumnMajor>::value &&
-                          is_same<BLayout, tensor_layout::gemm::RowMajor>::value &&
-                          is_same<CLayout, tensor_layout::gemm::RowMajor>::value)
-        {
-            ck::tensor_operation::device::device_gemm_instance::
+            }
+            else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> &&
+                              is_same_v<CLayout, Row>)
+            {
                 add_device_gemm_xdl_splitk_f32_f32_f32_km_kn_mn_instances(op_ptrs);
-        }
-        else if constexpr(is_same<ALayout, tensor_layout::gemm::ColumnMajor>::value &&
-                          is_same<BLayout, tensor_layout::gemm::ColumnMajor>::value &&
-                          is_same<CLayout, tensor_layout::gemm::RowMajor>::value)
-        {
-            ck::tensor_operation::device::device_gemm_instance::
+            }
+            else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Col> &&
+                              is_same_v<CLayout, Row>)
+            {
                 add_device_gemm_xdl_splitk_f32_f32_f32_km_nk_mn_instances(op_ptrs);
+            }
         }
-    }
-    else if constexpr(is_same<ADataType, half_t>::value && is_same<BDataType, half_t>::value &&
-                      is_same<CDataType, half_t>::value)
-    {
-        if constexpr(is_same<ALayout, tensor_layout::gemm::RowMajor>::value &&
-                     is_same<BLayout, tensor_layout::gemm::RowMajor>::value &&
-                     is_same<CLayout, tensor_layout::gemm::RowMajor>::value)
+        else if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
+                          is_same_v<CDataType, half_t>)
         {
-            ck::tensor_operation::device::device_gemm_instance::
+            if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
+                         is_same_v<CLayout, Row>)
+            {
                 add_device_gemm_xdl_splitk_f16_f16_f16_mk_kn_mn_instances(op_ptrs);
-        }
-        else if constexpr(is_same<ALayout, tensor_layout::gemm::RowMajor>::value &&
-                          is_same<BLayout, tensor_layout::gemm::ColumnMajor>::value &&
-                          is_same<CLayout, tensor_layout::gemm::RowMajor>::value)
-        {
-            ck::tensor_operation::device::device_gemm_instance::
+            }
+            else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
+                              is_same_v<CLayout, Row>)
+            {
                 add_device_gemm_xdl_splitk_f16_f16_f16_mk_nk_mn_instances(op_ptrs);
-        }
-        else if constexpr(is_same<ALayout, tensor_layout::gemm::ColumnMajor>::value &&
-                          is_same<BLayout, tensor_layout::gemm::RowMajor>::value &&
-                          is_same<CLayout, tensor_layout::gemm::RowMajor>::value)
-        {
-            ck::tensor_operation::device::device_gemm_instance::
+            }
+            else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> &&
+                              is_same_v<CLayout, Row>)
+            {
                 add_device_gemm_xdl_splitk_f16_f16_f16_km_kn_mn_instances(op_ptrs);
-        }
-        else if constexpr(is_same<ALayout, tensor_layout::gemm::ColumnMajor>::value &&
-                          is_same<BLayout, tensor_layout::gemm::ColumnMajor>::value &&
-                          is_same<CLayout, tensor_layout::gemm::RowMajor>::value)
-        {
-            ck::tensor_operation::device::device_gemm_instance::
+            }
+            else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Col> &&
+                              is_same_v<CLayout, Row>)
+            {
                 add_device_gemm_xdl_splitk_f16_f16_f16_km_nk_mn_instances(op_ptrs);
+            }
         }
-    }
 
-    return op_ptrs;
-}
+        return op_ptrs;
+    }
+};
 
-} // namespace device_gemm_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_blockwise.hpp

@@ -10,7 +10,7 @@
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_reduce_instance {
+namespace instance {
 
 using reduce_configuration_1_instances_blockwise = std::tuple<
     // clang-format off
@@ -174,7 +174,7 @@ void add_device_reduce_instance_blockwise(
                                    Rank,                                    \
                                    NumReduceDim)
 
-} // namespace device_reduce_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_blockwise_b16_f32_b16.hpp

@@ -10,7 +10,7 @@
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_reduce_instance {
+namespace instance {
 
 // clang-format off
 // InDataType | AccDataType | OutDataType | ReduceOpId | NanPropaOpt | IndicesOpt | Rank | NumReduceDim 
@@ -53,7 +53,7 @@ ADD_BLOCKWISE_INST_REF_BY_ID(bhalf_t, float, bhalf_t, 4, 0, 1, 4, 1);
 ADD_BLOCKWISE_INST_REF_BY_ID(bhalf_t, float, bhalf_t, 4, 0, 1, 2, 1);
 // clang-format on
 
-} // namespace device_reduce_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_blockwise_f16_f16_f16.hpp

@@ -10,7 +10,7 @@
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_reduce_instance {
+namespace instance {
 
 // clang-format off
 // InDataType | AccDataType | OutDataType | ReduceOpId | NanPropaOpt | IndicesOpt | Rank | NumReduceDim 
@@ -40,7 +40,7 @@ ADD_BLOCKWISE_INST_REF_BY_ID(half_t, half_t, half_t, 4, 0, 1, 4, 1);
 ADD_BLOCKWISE_INST_REF_BY_ID(half_t, half_t, half_t, 4, 0, 1, 2, 1);
 // clang-format on
 
-} // namespace device_reduce_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_blockwise_f16_f32_f16.hpp

@@ -10,7 +10,7 @@
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_reduce_instance {
+namespace instance {
 
 // clang-format off
 // InDataType | AccDataType | OutDataType | ReduceOpId | NanPropaOpt | IndicesOpt | Rank | NumReduceDim 
@@ -28,7 +28,7 @@ ADD_BLOCKWISE_INST_REF_BY_ID(half_t, float, half_t, 7, 0, 0, 4, 1);
 ADD_BLOCKWISE_INST_REF_BY_ID(half_t, float, half_t, 7, 0, 0, 2, 1);
 // clang-format on
 
-} // namespace device_reduce_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_blockwise_f32_f32_f32.hpp

@@ -10,7 +10,7 @@
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_reduce_instance {
+namespace instance {
 
 // clang-format off
 // InDataType | AccDataType | OutDataType | ReduceOpId | NanPropaOpt | IndicesOpt | Rank | NumReduceDim 
@@ -52,7 +52,7 @@ ADD_BLOCKWISE_INST_REF_BY_ID(float, float, float, 4, 0, 1, 4, 1);
 ADD_BLOCKWISE_INST_REF_BY_ID(float, float, float, 4, 0, 1, 2, 1);
 // clang-format on
 
-} // namespace device_reduce_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_blockwise_f32_f64_f32.hpp

@@ -10,7 +10,7 @@
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_reduce_instance {
+namespace instance {
 
 // clang-format off
 // InDataType | AccDataType | OutDataType | ReduceOpId | NanPropaOpt | IndicesOpt | Rank | NumReduceDim 
@@ -28,7 +28,7 @@ ADD_BLOCKWISE_INST_REF_BY_ID(float, double, float, 7, 0, 0, 4, 1);
 ADD_BLOCKWISE_INST_REF_BY_ID(float, double, float, 7, 0, 0, 2, 1);
 // clang-format on
 
-} // namespace device_reduce_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_blockwise_f64_f64_f64.hpp

@@ -10,7 +10,7 @@
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_reduce_instance {
+namespace instance {
 
 // clang-format off
 // InDataType | AccDataType | OutDataType | ReduceOpId | NanPropaOpt | IndicesOpt | Rank | NumReduceDim 
@@ -52,7 +52,7 @@ ADD_BLOCKWISE_INST_REF_BY_ID(double, double, double, 4, 0, 1, 4, 1);
 ADD_BLOCKWISE_INST_REF_BY_ID(double, double, double, 4, 0, 1, 2, 1);
 // clang-format on
 
-} // namespace device_reduce_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_blockwise_i8_i32_i8.hpp

@@ -10,7 +10,7 @@
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_reduce_instance {
+namespace instance {
 
 // clang-format off
 // InDataType | AccDataType | OutDataType | ReduceOpId | NanPropaOpt | IndicesOpt | Rank | NumReduceDim 
@@ -24,7 +24,7 @@ ADD_BLOCKWISE_INST_REF_BY_ID(int8_t, int32_t, int8_t, 5, 0, 0, 4, 1);
 ADD_BLOCKWISE_INST_REF_BY_ID(int8_t, int32_t, int8_t, 5, 0, 0, 2, 1);
 // clang-format on
 
-} // namespace device_reduce_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_blockwise_i8_i8_i8.hpp

@@ -10,7 +10,7 @@
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_reduce_instance {
+namespace instance {
 
 // clang-format off
 // InDataType | AccDataType | OutDataType | ReduceOpId | NanPropaOpt | IndicesOpt | Rank | NumReduceDim 
@@ -40,7 +40,7 @@ ADD_BLOCKWISE_INST_REF_BY_ID(int8_t, int8_t, int8_t, 4, 0, 1, 4, 1);
 ADD_BLOCKWISE_INST_REF_BY_ID(int8_t, int8_t, int8_t, 4, 0, 1, 2, 1);
 // clang-format on
 
-} // namespace device_reduce_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_impl_common.hpp

@@ -6,7 +6,7 @@
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_reduce_instance {
+namespace instance {
 
 template <int BlockSize, int MThreadClusterSize, int KThreadClusterSize>
 struct ReductionConfiguration_1
@@ -34,7 +34,7 @@ struct ReductionConfiguration_2
 
 #define QUICK_REDUCE_TEST 1
 
-} // namespace device_reduce_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_multiblock_atomic_add.hpp

@@ -11,7 +11,7 @@
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_reduce_instance {
+namespace instance {
 
 using reduce_configuration_1_instances_multiblock_atomic_add = std::tuple<
     // clang-format off
@@ -193,7 +193,7 @@ void add_device_reduce_instance_multiblock_atomic_add(
                                                Rank,                                    \
                                                NumReduceDim)
 
-} // namespace device_reduce_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_multiblock_atomic_add_b16_f32_f32.hpp

@@ -10,7 +10,7 @@
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_reduce_instance {
+namespace instance {
 
 // clang-format off
 // InDataType | AccDataType | OutDataType | ReduceOpId | NanPropaOpt | IndicesOpt | Rank | NumReduceDim 
@@ -24,7 +24,7 @@ ADD_MULTIBLOCK_ATOMIC_ADD_INST_REF_BY_ID(bhalf_t, float, float, 5, 0, 0, 4, 1);
 ADD_MULTIBLOCK_ATOMIC_ADD_INST_REF_BY_ID(bhalf_t, float, float, 5, 0, 0, 2, 1);
 // clang-format on
 
-} // namespace device_reduce_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_multiblock_atomic_add_f16_f32_f32.hpp

@@ -10,7 +10,7 @@
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_reduce_instance {
+namespace instance {
 
 // clang-format off
 // InDataType | AccDataType | OutDataType | ReduceOpId | NanPropaOpt | IndicesOpt | Rank | NumReduceDim 
@@ -24,7 +24,7 @@ ADD_MULTIBLOCK_ATOMIC_ADD_INST_REF_BY_ID(half_t, float, float, 5, 0, 0, 4, 1);
 ADD_MULTIBLOCK_ATOMIC_ADD_INST_REF_BY_ID(half_t, float, float, 5, 0, 0, 2, 1);
 // clang-format on
 
-} // namespace device_reduce_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_multiblock_atomic_add_f32_f32_f32.hpp

@@ -10,7 +10,7 @@
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_reduce_instance {
+namespace instance {
 
 // clang-format off
 // InDataType | AccDataType | OutDataType | ReduceOpId | NanPropaOpt | IndicesOpt | Rank | NumReduceDim 
@@ -24,7 +24,7 @@ ADD_MULTIBLOCK_ATOMIC_ADD_INST_REF_BY_ID(float, float, float, 5, 0, 0, 4, 1);
 ADD_MULTIBLOCK_ATOMIC_ADD_INST_REF_BY_ID(float, float, float, 5, 0, 0, 2, 1);
 // clang-format on
 
-} // namespace device_reduce_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_multiblock_atomic_add_f32_f64_f32.hpp

@@ -10,7 +10,7 @@
 namespace ck {
 namespace tensor_operation {
 namespace device {
-namespace device_reduce_instance {
+namespace instance {
 
 // clang-format off
 // InDataType | AccDataType | OutDataType | ReduceOpId | NanPropaOpt | IndicesOpt | Rank | NumReduceDim 
@@ -24,7 +24,7 @@ ADD_MULTIBLOCK_ATOMIC_ADD_INST_REF_BY_ID(float, double, float, 5, 0, 0, 4, 1);
 ADD_MULTIBLOCK_ATOMIC_ADD_INST_REF_BY_ID(float, double, float, 5, 0, 0, 2, 1);
 // clang-format on
 
-} // namespace device_reduce_instance
+} // namespace instance
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck