Extend support for contraction 6D (#1207)

* Extend support for contraction up to 5D

* Extend contraction bilinear instances

* Fix interface test

* Add 6d support, remove 3d,4d,5d

* Fixes

* Fix readme

* Make defualt dim for contraction instances

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_mkn_instance.cpp → library/src/tensor_operation_instance/gpu/contraction_scale/2D/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_mkn_instance.cpp

 // SPDX-License-Identifier: MIT
-// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
+// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
 
 // This (ifndef) is a hack to use customized behavior for buffer load rather than using default
 // setting Don't use this hack unless absolutely necessary!
@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_mkn_instance =
                                    F32,
                                    PassThrough,
                                    PassThrough,
-                                   Scale>;
+                                   Scale,
+                                   2>;
 
 void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_mkn_instance(
     std::vector<std::unique_ptr<DeviceContractionMultipleD<2,

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_mnn_instance.cpp → library/src/tensor_operation_instance/gpu/contraction_scale/2D/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_mnn_instance.cpp

 // SPDX-License-Identifier: MIT
-// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
+// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
 
 // This (ifndef) is a hack to use customized behavior for buffer load rather than using default
 // setting Don't use this hack unless absolutely necessary!
@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_mnn_instance =
                                    F32,
                                    PassThrough,
                                    PassThrough,
-                                   Scale>;
+                                   Scale,
+                                   2>;
 
 void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f32_f32_f32_mnn_instance(
     std::vector<std::unique_ptr<DeviceContractionMultipleD<2,

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_kkn_instance.cpp → library/src/tensor_operation_instance/gpu/contraction_scale/2D/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_kkn_instance.cpp

 // SPDX-License-Identifier: MIT
-// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
+// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
 
 // This (ifndef) is a hack to use customized behavior for buffer load rather than using default
 // setting Don't use this hack unless absolutely necessary!
@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_kk
                                        F32,
                                        PassThrough,
                                        PassThrough,
-                                       Scale>;
+                                       Scale,
+                                       2>;
 
 void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_kkn_instance(
     std::vector<std::unique_ptr<DeviceContractionMultipleD<2,

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_knn_instance.cpp → library/src/tensor_operation_instance/gpu/contraction_scale/2D/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_knn_instance.cpp

 // SPDX-License-Identifier: MIT
-// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
+// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
 
 // This (ifndef) is a hack to use customized behavior for buffer load rather than using default
 // setting Don't use this hack unless absolutely necessary!
@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_kn
                                        F32,
                                        PassThrough,
                                        PassThrough,
-                                       Scale>;
+                                       Scale,
+                                       2>;
 
 void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_knn_instance(
     std::vector<std::unique_ptr<DeviceContractionMultipleD<2,

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_mkn_instance.cpp → library/src/tensor_operation_instance/gpu/contraction_scale/2D/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_mkn_instance.cpp

 // SPDX-License-Identifier: MIT
-// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
+// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
 
 // This (ifndef) is a hack to use customized behavior for buffer load rather than using default
 // setting Don't use this hack unless absolutely necessary!
@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_mk
                                        F32,
                                        PassThrough,
                                        PassThrough,
-                                       Scale>;
+                                       Scale,
+                                       2>;
 
 void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_mkn_instance(
     std::vector<std::unique_ptr<DeviceContractionMultipleD<2,

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_mnn_instance.cpp → library/src/tensor_operation_instance/gpu/contraction_scale/2D/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_mnn_instance.cpp

 // SPDX-License-Identifier: MIT
-// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
+// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
 
 // This (ifndef) is a hack to use customized behavior for buffer load rather than using default
 // setting Don't use this hack unless absolutely necessary!
@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_mn
                                        F32,
                                        PassThrough,
                                        PassThrough,
-                                       Scale>;
+                                       Scale,
+                                       2>;
 
 void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_mnn_instance(
     std::vector<std::unique_ptr<DeviceContractionMultipleD<2,

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_kkn_instance.cpp → library/src/tensor_operation_instance/gpu/contraction_scale/2D/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_kkn_instance.cpp

 // SPDX-License-Identifier: MIT
-// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
+// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
 
 // This (ifndef) is a hack to use customized behavior for buffer load rather than using default
 // setting Don't use this hack unless absolutely necessary!
@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_kkn_instance =
                                        F64,
                                        PassThrough,
                                        PassThrough,
-                                       Scale>;
+                                       Scale,
+                                       2>;
 
 void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_kkn_instance(
     std::vector<std::unique_ptr<DeviceContractionMultipleD<2,

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_knn_instance.cpp → library/src/tensor_operation_instance/gpu/contraction_scale/2D/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_knn_instance.cpp

 // SPDX-License-Identifier: MIT
-// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
+// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
 
 // This (ifndef) is a hack to use customized behavior for buffer load rather than using default
 // setting Don't use this hack unless absolutely necessary!
@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_knn_instance =
                                        F64,
                                        PassThrough,
                                        PassThrough,
-                                       Scale>;
+                                       Scale,
+                                       2>;
 
 void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_knn_instance(
     std::vector<std::unique_ptr<DeviceContractionMultipleD<2,

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mkn_instance.cpp → library/src/tensor_operation_instance/gpu/contraction_scale/2D/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mkn_instance.cpp

 // SPDX-License-Identifier: MIT
-// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
+// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
 
 // This (ifndef) is a hack to use customized behavior for buffer load rather than using default
 // setting Don't use this hack unless absolutely necessary!
@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mkn_instance =
                                        F64,
                                        PassThrough,
                                        PassThrough,
-                                       Scale>;
+                                       Scale,
+                                       2>;
 
 void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mkn_instance(
     std::vector<std::unique_ptr<DeviceContractionMultipleD<2,

library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mnn_instance.cpp → library/src/tensor_operation_instance/gpu/contraction_scale/2D/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mnn_instance.cpp

 // SPDX-License-Identifier: MIT
-// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
+// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
 
 // This (ifndef) is a hack to use customized behavior for buffer load rather than using default
 // setting Don't use this hack unless absolutely necessary!
@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mnn_instance =
                                        F64,
                                        PassThrough,
                                        PassThrough,
-                                       Scale>;
+                                       Scale,
+                                       2>;
 
 void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mnn_instance(
     std::vector<std::unique_ptr<DeviceContractionMultipleD<2,

library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_kkn_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
+
+// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
+// setting Don't use this hack unless absolutely necessary!
+// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
+#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
+
+#include <cstdlib>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
+// k/k/n/n are the fast changing dimension for A/B/D/E
+using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_kkn_instance =
+    device_contraction_kk_instance<BF16,
+                                   BF16,
+                                   F32,
+                                   BF16,
+                                   Empty_Tuple,
+                                   BF16,
+                                   F32,
+                                   PassThrough,
+                                   PassThrough,
+                                   Scale,
+                                   6>;
+
+void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_kkn_instance(
+    std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
+                                                           6,
+                                                           6,
+                                                           BF16,
+                                                           BF16,
+                                                           Empty_Tuple,
+                                                           BF16,
+                                                           PassThrough,
+                                                           PassThrough,
+                                                           Scale,
+                                                           F32>>>& instances)
+{
+    add_device_operation_instances(
+        instances,
+        device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_kkn_instance{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_knn_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
+
+// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
+// setting Don't use this hack unless absolutely necessary!
+// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
+#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
+
+#include <cstdlib>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
+// k/n/n/n are the fast changing dimension for A/B/D/E
+using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_knn_instance =
+    device_contraction_kn_instance<BF16,
+                                   BF16,
+                                   F32,
+                                   BF16,
+                                   Empty_Tuple,
+                                   BF16,
+                                   F32,
+                                   PassThrough,
+                                   PassThrough,
+                                   Scale,
+                                   6>;
+
+void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_knn_instance(
+    std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
+                                                           6,
+                                                           6,
+                                                           BF16,
+                                                           BF16,
+                                                           Empty_Tuple,
+                                                           BF16,
+                                                           PassThrough,
+                                                           PassThrough,
+                                                           Scale,
+                                                           F32>>>& instances)
+{
+    add_device_operation_instances(
+        instances,
+        device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_knn_instance{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mkn_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
+
+// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
+// setting Don't use this hack unless absolutely necessary!
+// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
+#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
+
+#include <cstdlib>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
+// m/k/n/n are the fast changing dimension for A/B/D/E
+using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mkn_instance =
+    device_contraction_mk_instance<BF16,
+                                   BF16,
+                                   F32,
+                                   BF16,
+                                   Empty_Tuple,
+                                   BF16,
+                                   F32,
+                                   PassThrough,
+                                   PassThrough,
+                                   Scale,
+                                   6>;
+
+void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mkn_instance(
+    std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
+                                                           6,
+                                                           6,
+                                                           BF16,
+                                                           BF16,
+                                                           Empty_Tuple,
+                                                           BF16,
+                                                           PassThrough,
+                                                           PassThrough,
+                                                           Scale,
+                                                           F32>>>& instances)
+{
+    add_device_operation_instances(
+        instances,
+        device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mkn_instance{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mnn_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
+
+// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
+// setting Don't use this hack unless absolutely necessary!
+// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
+#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
+
+#include <cstdlib>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
+// m/n/n/n are the fast changing dimension for A/B/D/E
+using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mnn_instance =
+    device_contraction_mn_instance<BF16,
+                                   BF16,
+                                   F32,
+                                   BF16,
+                                   Empty_Tuple,
+                                   BF16,
+                                   F32,
+                                   PassThrough,
+                                   PassThrough,
+                                   Scale,
+                                   6>;
+
+void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mnn_instance(
+    std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
+                                                           6,
+                                                           6,
+                                                           BF16,
+                                                           BF16,
+                                                           Empty_Tuple,
+                                                           BF16,
+                                                           PassThrough,
+                                                           PassThrough,
+                                                           Scale,
+                                                           F32>>>& instances)
+{
+    add_device_operation_instances(
+        instances,
+        device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mnn_instance{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_kkn_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
+
+// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
+// setting Don't use this hack unless absolutely necessary!
+// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
+#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
+
+#include <cstdlib>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
+// k/k/n/n are the fast changing dimension for A/B/D/E
+using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_kkn_instance =
+    device_contraction_kk_instance<F16,
+                                   F16,
+                                   F32,
+                                   F16,
+                                   Empty_Tuple,
+                                   F16,
+                                   F32,
+                                   PassThrough,
+                                   PassThrough,
+                                   Scale,
+                                   6>;
+
+void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_kkn_instance(
+    std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
+                                                           6,
+                                                           6,
+                                                           F16,
+                                                           F16,
+                                                           Empty_Tuple,
+                                                           F16,
+                                                           PassThrough,
+                                                           PassThrough,
+                                                           Scale,
+                                                           F32>>>& instances)
+{
+    add_device_operation_instances(
+        instances,
+        device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_kkn_instance{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_knn_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
+
+// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
+// setting Don't use this hack unless absolutely necessary!
+// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
+#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
+
+#include <cstdlib>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
+// k/n/n/n are the fast changing dimension for A/B/D/E
+using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_knn_instance =
+    device_contraction_kn_instance<F16,
+                                   F16,
+                                   F32,
+                                   F16,
+                                   Empty_Tuple,
+                                   F16,
+                                   F32,
+                                   PassThrough,
+                                   PassThrough,
+                                   Scale,
+                                   6>;
+
+void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_knn_instance(
+    std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
+                                                           6,
+                                                           6,
+                                                           F16,
+                                                           F16,
+                                                           Empty_Tuple,
+                                                           F16,
+                                                           PassThrough,
+                                                           PassThrough,
+                                                           Scale,
+                                                           F32>>>& instances)
+{
+    add_device_operation_instances(
+        instances,
+        device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_knn_instance{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_mkn_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
+
+// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
+// setting Don't use this hack unless absolutely necessary!
+// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
+#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
+
+#include <cstdlib>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
+// m/k/n/n are the fast changing dimension for A/B/D/E
+using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_mkn_instance =
+    device_contraction_mk_instance<F16,
+                                   F16,
+                                   F32,
+                                   F16,
+                                   Empty_Tuple,
+                                   F16,
+                                   F32,
+                                   PassThrough,
+                                   PassThrough,
+                                   Scale,
+                                   6>;
+
+void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_mkn_instance(
+    std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
+                                                           6,
+                                                           6,
+                                                           F16,
+                                                           F16,
+                                                           Empty_Tuple,
+                                                           F16,
+                                                           PassThrough,
+                                                           PassThrough,
+                                                           Scale,
+                                                           F32>>>& instances)
+{
+    add_device_operation_instances(
+        instances,
+        device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_mkn_instance{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_mnn_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
+
+// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
+// setting Don't use this hack unless absolutely necessary!
+// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
+#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
+
+#include <cstdlib>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
+// m/n/n/n are the fast changing dimension for A/B/D/E
+using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_mnn_instance =
+    device_contraction_mn_instance<F16,
+                                   F16,
+                                   F32,
+                                   F16,
+                                   Empty_Tuple,
+                                   F16,
+                                   F32,
+                                   PassThrough,
+                                   PassThrough,
+                                   Scale,
+                                   6>;
+
+void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_mnn_instance(
+    std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
+                                                           6,
+                                                           6,
+                                                           F16,
+                                                           F16,
+                                                           Empty_Tuple,
+                                                           F16,
+                                                           PassThrough,
+                                                           PassThrough,
+                                                           Scale,
+                                                           F32>>>& instances)
+{
+    add_device_operation_instances(
+        instances,
+        device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_mnn_instance{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_kkn_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
+
+// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
+// setting Don't use this hack unless absolutely necessary!
+// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
+#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
+
+#include <cstdlib>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
+// k/k/n/n are the fast changing dimension for A/B/D/E
+using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_kkn_instance =
+    device_contraction_kk_instance<F32,
+                                   F32,
+                                   F32,
+                                   F32,
+                                   Empty_Tuple,
+                                   F32,
+                                   BF16,
+                                   PassThrough,
+                                   PassThrough,
+                                   Scale,
+                                   6>;
+
+void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_kkn_instance(
+    std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
+                                                           6,
+                                                           6,
+                                                           F32,
+                                                           F32,
+                                                           Empty_Tuple,
+                                                           F32,
+                                                           PassThrough,
+                                                           PassThrough,
+                                                           Scale,
+                                                           BF16>>>& instances)
+{
+    add_device_operation_instances(
+        instances,
+        device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_kkn_instance{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_knn_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
+
+// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
+// setting Don't use this hack unless absolutely necessary!
+// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
+#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
+
+#include <cstdlib>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
+// k/n/n/n are the fast changing dimension for A/B/D/E
+using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_knn_instance =
+    device_contraction_kn_instance<F32,
+                                   F32,
+                                   F32,
+                                   F32,
+                                   Empty_Tuple,
+                                   F32,
+                                   BF16,
+                                   PassThrough,
+                                   PassThrough,
+                                   Scale,
+                                   6>;
+
+void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_knn_instance(
+    std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
+                                                           6,
+                                                           6,
+                                                           F32,
+                                                           F32,
+                                                           Empty_Tuple,
+                                                           F32,
+                                                           PassThrough,
+                                                           PassThrough,
+                                                           Scale,
+                                                           BF16>>>& instances)
+{
+    add_device_operation_instances(
+        instances,
+        device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_knn_instance{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck