Merge branch 'develop' into barkocot/grouped-conv-fwd-multiple-ab

library/include/ck/library/reference_tensor_operation/cpu/reference_layernorm.hpp

@@ -28,7 +28,8 @@ template <typename XDataType,
 struct ReferenceLayernorm : public device::BaseOperator
 {
     // TODO - support generic layernorm
-    static_assert((Rank == 2 && NumReduceDim == 1), "Only support 2D version so far");
+    static_assert((Rank == 2 && NumReduceDim == 1) || (Rank == 4 && NumReduceDim == 3),
+                  "Only support 2D & 4D version so far");
 
     // Argument
     struct Argument : public device::BaseArgument
@@ -71,7 +72,7 @@ struct ReferenceLayernorm : public device::BaseOperator
     // Invoker
     struct Invoker : public device::BaseInvoker
     {
-        float Run(const Argument& arg)
+        float Run2D(const Argument& arg)
         {
             int M = arg.lengths_[0];
             int N = arg.lengths_[1];
@@ -117,6 +118,71 @@ struct ReferenceLayernorm : public device::BaseOperator
             return 0;
         }
 
+        float Run4D(const Argument& arg)
+        {
+            int N = arg.lengths_[0];
+            int H = arg.lengths_[1];
+            int W = arg.lengths_[2];
+            int C = arg.lengths_[3];
+
+            Tensor<ComputeDataType> mean({N});
+            Tensor<ComputeDataType> var({N});
+
+            int reduce_length = H * W * C;
+
+            for(int n = 0; n < N; ++n)
+            {
+                mean(n) = 0;
+                var(n)  = 0;
+
+                for(int h = 0; h < H; ++h)
+                    for(int w = 0; w < W; ++w)
+                        for(int c = 0; c < C; ++c)
+                        {
+                            auto x_val = ck::type_convert<ComputeDataType>(arg.x_m_n_(n, h, w, c));
+                            mean(n) += x_val;
+                            var(n) += x_val * x_val;
+                        }
+
+                mean(n) = mean(n) / reduce_length;
+                var(n)  = (var(n) / reduce_length) - (mean(n) * mean(n));
+            }
+
+            for(int n = 0; n < N; ++n)
+            {
+                ComputeDataType divisor =
+                    static_cast<ComputeDataType>(1) / ck::math::sqrt(var(n) + arg.epsilon_);
+
+                for(int h = 0; h < H; ++h)
+                    for(int w = 0; w < W; ++w)
+                        for(int c = 0; c < C; ++c)
+                        {
+                            auto x_val = ck::type_convert<ComputeDataType>(arg.x_m_n_(n, h, w, c));
+                            auto gamma_val =
+                                ck::type_convert<ComputeDataType>(arg.gamma_n_(h, w, c));
+                            auto beta_val = ck::type_convert<ComputeDataType>(arg.beta_n_(h, w, c));
+                            auto y_val    = (x_val - mean(n)) * divisor;
+                            y_val         = (y_val * gamma_val) + beta_val;
+                            arg.y_elementwise_op_(y_val, y_val);
+                            arg.y_m_n_(n, h, w, c) = ck::type_convert<YDataType>(y_val);
+                        }
+                arg.save_mean_m_(n)    = ck::type_convert<SaveMeanInvStdDataType>(mean(n));
+                arg.save_inv_std_m_(n) = ck::type_convert<SaveMeanInvStdDataType>(divisor);
+            }
+
+            return 0;
+        }
+
+        float Run(const Argument& arg)
+        {
+            if(arg.lengths_.size() == 2)
+                return Run2D(arg);
+            else if(arg.lengths_.size() == 4)
+                return Run4D(arg);
+
+            return 0;
+        }
+
         float Run(const device::BaseArgument* p_arg,
                   const StreamConfig& /* stream_config */ = StreamConfig{}) override
         {
@@ -134,17 +200,16 @@ struct ReferenceLayernorm : public device::BaseOperator
     {
         const Argument* p_arg_ = dynamic_cast<const Argument*>(p_arg);
 
-        // TODO - support generic layernorm
-        if(p_arg_->lengths_.size() != 2)
-            return false;
-
-        if(p_arg_->reduceDims_.size() != 1)
-            return false;
+        if(p_arg_->lengths_.size() == 2 && p_arg_->reduceDims_.size() == 1 &&
+           p_arg_->reduceDims_[0] == 1)
+            return true;
 
-        if(p_arg_->reduceDims_[0] != 1)
-            return false;
+        else if(p_arg_->lengths_.size() == 4 && p_arg_->reduceDims_.size() == 3 &&
+                p_arg_->reduceDims_[0] == 1 && p_arg_->reduceDims_[1] == 2 &&
+                p_arg_->reduceDims_[2] == 3)
+            return true;
 
-        return true;
+        return false;
     }
 
     static auto MakeArgument(const Tensor<XDataType>& x_m_n,

library/include/ck/library/tensor_operation_instance/gpu/normalization.hpp → library/include/ck/library/tensor_operation_instance/gpu/normalization_fwd.hpp

@@ -7,7 +7,7 @@
 #include <memory>
 #include "ck/ck.hpp"
 #include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
-#include "ck/tensor_operation/gpu/device/device_normalization.hpp"
+#include "ck/tensor_operation/gpu/device/device_normalization_fwd.hpp"
 #include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
 
 #include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
@@ -18,25 +18,31 @@ namespace device {
 namespace instance {
 #ifdef CK_ENABLE_FP16
 // FP16
-void add_device_normalization_rank_2_1_f16_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F16, F32, PassThrough, 2, 1>>>&);
+void add_device_normalization_fwd_rank_2_1_f16_instances(
+    std::vector<
+        std::unique_ptr<DeviceNormalizationFwd<F16, F16, F16, F16, F32, PassThrough, 2, 1>>>&);
 
-void add_device_normalization_rank_4_3_f16_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F16, F32, PassThrough, 4, 3>>>&);
+void add_device_normalization_fwd_rank_4_3_f16_instances(
+    std::vector<
+        std::unique_ptr<DeviceNormalizationFwd<F16, F16, F16, F16, F32, PassThrough, 4, 3>>>&);
 
-void add_device_normalization_rank_5_3_f16_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F16, F32, PassThrough, 5, 3>>>&);
+void add_device_normalization_fwd_rank_5_3_f16_instances(
+    std::vector<
+        std::unique_ptr<DeviceNormalizationFwd<F16, F16, F16, F16, F32, PassThrough, 5, 3>>>&);
 #endif
 #ifdef CK_ENABLE_FP32
 // FP32
-void add_device_normalization_rank_2_1_f32_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F32, F32, F32, F32, F32, PassThrough, 2, 1>>>&);
+void add_device_normalization_fwd_rank_2_1_f32_instances(
+    std::vector<
+        std::unique_ptr<DeviceNormalizationFwd<F32, F32, F32, F32, F32, PassThrough, 2, 1>>>&);
 
-void add_device_normalization_rank_4_3_f32_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F32, F32, F32, F32, F32, PassThrough, 4, 3>>>&);
+void add_device_normalization_fwd_rank_4_3_f32_instances(
+    std::vector<
+        std::unique_ptr<DeviceNormalizationFwd<F32, F32, F32, F32, F32, PassThrough, 4, 3>>>&);
 
-void add_device_normalization_rank_5_3_f32_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F32, F32, F32, F32, F32, PassThrough, 5, 3>>>&);
+void add_device_normalization_fwd_rank_5_3_f32_instances(
+    std::vector<
+        std::unique_ptr<DeviceNormalizationFwd<F32, F32, F32, F32, F32, PassThrough, 5, 3>>>&);
 #endif
 template <typename XDataType,
           typename GammaDataType,
@@ -45,7 +51,7 @@ template <typename XDataType,
           typename SaveMeanInvStdDataType,
           index_t Rank,
           index_t NumReduceDim>
-struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceNormalization<
+struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceNormalizationFwd<
     XDataType,
     GammaDataType,
     BetaDataType,
@@ -55,14 +61,14 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceNormal
     Rank,
     NumReduceDim>>
 {
-    using DeviceOp = DeviceNormalization<XDataType,
-                                         GammaDataType,
-                                         BetaDataType,
-                                         YDataType,
-                                         SaveMeanInvStdDataType,
-                                         ck::tensor_operation::element_wise::PassThrough,
-                                         Rank,
-                                         NumReduceDim>;
+    using DeviceOp = DeviceNormalizationFwd<XDataType,
+                                            GammaDataType,
+                                            BetaDataType,
+                                            YDataType,
+                                            SaveMeanInvStdDataType,
+                                            ck::tensor_operation::element_wise::PassThrough,
+                                            Rank,
+                                            NumReduceDim>;
 
     static auto GetInstances()
     {
@@ -74,15 +80,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceNormal
         {
             if constexpr(Rank == 2 && NumReduceDim == 1)
             {
-                add_device_normalization_rank_2_1_f16_instances(op_ptrs);
+                add_device_normalization_fwd_rank_2_1_f16_instances(op_ptrs);
             }
             else if constexpr(Rank == 4 && NumReduceDim == 3)
             {
-                add_device_normalization_rank_4_3_f16_instances(op_ptrs);
+                add_device_normalization_fwd_rank_4_3_f16_instances(op_ptrs);
             }
             else if constexpr(Rank == 5 && NumReduceDim == 3)
             {
-                add_device_normalization_rank_5_3_f16_instances(op_ptrs);
+                add_device_normalization_fwd_rank_5_3_f16_instances(op_ptrs);
             }
         }
 #endif
@@ -93,15 +99,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceNormal
         {
             if constexpr(Rank == 2 && NumReduceDim == 1)
             {
-                add_device_normalization_rank_2_1_f32_instances(op_ptrs);
+                add_device_normalization_fwd_rank_2_1_f32_instances(op_ptrs);
             }
             else if constexpr(Rank == 4 && NumReduceDim == 3)
             {
-                add_device_normalization_rank_4_3_f32_instances(op_ptrs);
+                add_device_normalization_fwd_rank_4_3_f32_instances(op_ptrs);
             }
             else if constexpr(Rank == 5 && NumReduceDim == 3)
             {
-                add_device_normalization_rank_5_3_f32_instances(op_ptrs);
+                add_device_normalization_fwd_rank_5_3_f32_instances(op_ptrs);
             }
         }
 #endif

library/include/ck/library/tensor_operation_instance/gpu/normalization_swish.hpp → library/include/ck/library/tensor_operation_instance/gpu/normalization_fwd_swish.hpp

@@ -7,7 +7,7 @@
 
 #include "ck/ck.hpp"
 #include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
-#include "ck/tensor_operation/gpu/device/device_normalization.hpp"
+#include "ck/tensor_operation/gpu/device/device_normalization_fwd.hpp"
 #include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
 
 #include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
@@ -18,16 +18,16 @@ namespace device {
 namespace instance {
 
 // FP16
-void add_device_normalization_rank_5_3_swish_f16_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F16, F32, Swish, 5, 3>>>&);
+void add_device_normalization_fwd_rank_5_3_swish_f16_instances(
+    std::vector<std::unique_ptr<DeviceNormalizationFwd<F16, F16, F16, F16, F32, Swish, 5, 3>>>&);
 
 // FP32
-void add_device_normalization_rank_5_3_swish_f32_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F32, F32, F32, F32, F32, Swish, 5, 3>>>&);
+void add_device_normalization_fwd_rank_5_3_swish_f32_instances(
+    std::vector<std::unique_ptr<DeviceNormalizationFwd<F32, F32, F32, F32, F32, Swish, 5, 3>>>&);
 
 // [x, gamma, beta, y] = [f16, f32, f32, f16]
-void add_device_normalization_rank_5_3_swish_f16_f32_f32_f16_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F16, F32, F32, F16, F32, Swish, 5, 3>>>&);
+void add_device_normalization_fwd_rank_5_3_swish_f16_f32_f32_f16_instances(
+    std::vector<std::unique_ptr<DeviceNormalizationFwd<F16, F32, F32, F16, F32, Swish, 5, 3>>>&);
 
 template <typename XDataType,
           typename GammaDataType,
@@ -37,23 +37,23 @@ template <typename XDataType,
           index_t Rank,
           index_t NumReduceDim>
 struct DeviceOperationInstanceFactory<
-    ck::tensor_operation::device::DeviceNormalization<XDataType,
-                                                      GammaDataType,
-                                                      BetaDataType,
-                                                      YDataType,
-                                                      SaveMeanInvStdDataType,
-                                                      ck::tensor_operation::element_wise::Swish,
-                                                      Rank,
-                                                      NumReduceDim>>
+    ck::tensor_operation::device::DeviceNormalizationFwd<XDataType,
+                                                         GammaDataType,
+                                                         BetaDataType,
+                                                         YDataType,
+                                                         SaveMeanInvStdDataType,
+                                                         ck::tensor_operation::element_wise::Swish,
+                                                         Rank,
+                                                         NumReduceDim>>
 {
-    using DeviceOp = DeviceNormalization<XDataType,
-                                         GammaDataType,
-                                         BetaDataType,
-                                         YDataType,
-                                         SaveMeanInvStdDataType,
-                                         ck::tensor_operation::element_wise::Swish,
-                                         Rank,
-                                         NumReduceDim>;
+    using DeviceOp = DeviceNormalizationFwd<XDataType,
+                                            GammaDataType,
+                                            BetaDataType,
+                                            YDataType,
+                                            SaveMeanInvStdDataType,
+                                            ck::tensor_operation::element_wise::Swish,
+                                            Rank,
+                                            NumReduceDim>;
 
     static auto GetInstances()
     {
@@ -65,7 +65,7 @@ struct DeviceOperationInstanceFactory<
         {
             if constexpr(Rank == 5 && NumReduceDim == 3)
             {
-                add_device_normalization_rank_5_3_swish_f16_instances(op_ptrs);
+                add_device_normalization_fwd_rank_5_3_swish_f16_instances(op_ptrs);
             }
         }
         else if constexpr(is_same_v<XDataType, F32> && is_same_v<GammaDataType, F32> &&
@@ -74,7 +74,7 @@ struct DeviceOperationInstanceFactory<
         {
             if constexpr(Rank == 5 && NumReduceDim == 3)
             {
-                add_device_normalization_rank_5_3_swish_f32_instances(op_ptrs);
+                add_device_normalization_fwd_rank_5_3_swish_f32_instances(op_ptrs);
             }
         }
         else if constexpr(is_same_v<XDataType, F16> && is_same_v<GammaDataType, F32> &&
@@ -83,7 +83,7 @@ struct DeviceOperationInstanceFactory<
         {
             if constexpr(Rank == 5 && NumReduceDim == 3)
             {
-                add_device_normalization_rank_5_3_swish_f16_f32_f32_f16_instances(op_ptrs);
+                add_device_normalization_fwd_rank_5_3_swish_f16_f32_f32_f16_instances(op_ptrs);
             }
         }
 

library/include/ck/library/tensor_operation_instance/gpu/transpose/device_transpose_instance.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/impl/device_elementwise_3d_impl.hpp"
+
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+using F16 = ck::half_t;
+using F32 = float;
+
+using PassThrough = ck::tensor_operation::element_wise::PassThrough;
+
+template <ck::index_t... Is>
+using S = ck::Sequence<Is...>;
+
+using device_transpose_f16_instances = std::tuple<
+    // FOR 16, 32, 16, 32, 16
+    // clang-format off
+    DeviceElementwise3dImpl<ck::Tuple<F16>, ck::Tuple<F16>, PassThrough, 2, 2, 1, 8, 8, 8, ck::Sequence<1>, ck::Sequence<1>>,
+    DeviceElementwise3dImpl<ck::Tuple<F16>, ck::Tuple<F16>, PassThrough, 2, 2, 1, 8, 1, 1, ck::Sequence<1>, ck::Sequence<1>>,
+    DeviceElementwise3dImpl<ck::Tuple<F16>, ck::Tuple<F16>, PassThrough, 2, 2, 1, 8, 4, 4, ck::Sequence<1>, ck::Sequence<1>>
+    // clang-format on
+    >;
+
+using device_transpose_f32_instances = std::tuple<
+    // for 16, 8, 16, 32, 8 -> test with instances for fp16
+    // clang-format off
+    DeviceElementwise3dImpl<ck::Tuple<F32>, ck::Tuple<F32>, PassThrough, 2, 2, 1, 4, 4, 4, ck::Sequence<1>, ck::Sequence<1>>,
+    DeviceElementwise3dImpl<ck::Tuple<F32>, ck::Tuple<F32>, PassThrough, 2, 2, 1, 4, 8, 4, ck::Sequence<1>, ck::Sequence<1>>,
+    DeviceElementwise3dImpl<ck::Tuple<F32>, ck::Tuple<F32>, PassThrough, 2, 2, 1, 4, 8, 8, ck::Sequence<1>, ck::Sequence<1>>
+    // clang-format on
+    >;
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/include/ck/library/tensor_operation_instance/gpu/transpose_3d.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include <vector>
+#include <memory>
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/device_elementwise.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+using F16 = ck::half_t;
+using F32 = float;
+
+using PassThrough = ck::tensor_operation::element_wise::PassThrough;
+
+void add_device_transpose_f16_instances(
+    std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, PassThrough, 5>>>&
+        instances);
+
+void add_device_transpose_f32_instances(
+    std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, PassThrough, 5>>>&
+        instances);
+
+template <typename InDataTypeTuple,
+          typename OutDataTypeTuple,
+          typename ElementwiseOperation,
+          index_t NumDim>
+struct DeviceOperationInstanceFactory<
+    ck::tensor_operation::device::
+        DeviceElementwise<InDataTypeTuple, OutDataTypeTuple, ElementwiseOperation, NumDim>>
+{
+    using DeviceOp =
+        DeviceElementwise<InDataTypeTuple, OutDataTypeTuple, ElementwiseOperation, NumDim>;
+
+    static auto GetInstances()
+    {
+        std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
+        if constexpr(is_same_v<InDataTypeTuple, ck::Tuple<F32>> &&
+                     is_same_v<OutDataTypeTuple, ck::Tuple<F32>>)
+        {
+            add_device_transpose_f32_instances(op_ptrs);
+        }
+        else if constexpr(is_same_v<InDataTypeTuple, ck::Tuple<F16>> &&
+                          is_same_v<OutDataTypeTuple, ck::Tuple<F16>>)
+        {
+            add_device_transpose_f16_instances(op_ptrs);
+        }
+        return op_ptrs;
+    }
+};
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/normalization/CMakeLists.txt

-set(DEVICE_NORMALIZATION_INSTANCES)
-
-list(APPEND DEVICE_NORMALIZATION_INSTANCES 
-    device_layernorm2d_f16_instance.cpp
-    device_layernorm4d_f16_instance.cpp
-    device_groupnorm_f16_instance.cpp
-    device_groupnorm_swish_f16_instance.cpp
-    device_groupnorm_swish_f16_f32_f32_f16_instance.cpp
-    device_layernorm2d_f32_instance.cpp
-    device_layernorm4d_f32_instance.cpp
-    device_groupnorm_f32_instance.cpp
-    device_groupnorm_swish_f32_instance.cpp)
-
-add_instance_library(device_normalization_instance ${DEVICE_NORMALIZATION_INSTANCES})

library/src/tensor_operation_instance/gpu/normalization_fwd/CMakeLists.txt

+set(DEVICE_NORMALIZATION_FWD_INSTANCES)
+
+list(APPEND DEVICE_NORMALIZATION_FWD_INSTANCES
+    device_layernorm2d_fwd_f16_instance.cpp
+    device_layernorm4d_fwd_f16_instance.cpp
+    device_groupnorm_fwd_f16_instance.cpp
+    device_groupnorm_fwd_swish_f16_instance.cpp
+    device_groupnorm_fwd_swish_f16_f32_f32_f16_instance.cpp
+    device_layernorm2d_fwd_f32_instance.cpp
+    device_layernorm4d_fwd_f32_instance.cpp
+    device_groupnorm_fwd_f32_instance.cpp
+    device_groupnorm_fwd_swish_f32_instance.cpp)
+
+add_instance_library(device_normalization_fwd_instance ${DEVICE_NORMALIZATION_FWD_INSTANCES})

library/src/tensor_operation_instance/gpu/normalization/device_groupnorm_f16_instance.cpp → library/src/tensor_operation_instance/gpu/normalization_fwd/device_groupnorm_fwd_f16_instance.cpp

 // SPDX-License-Identifier: MIT
 // Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
 
-#include "normalization_instance_common.hpp"
+#include "normalization_fwd_instance_common.hpp"
 
 namespace ck {
 namespace tensor_operation {
@@ -10,8 +10,8 @@ namespace instance {
 
 using Pass = ck::tensor_operation::element_wise::PassThrough;
 
-void add_device_normalization_rank_5_3_f16_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F16, F32, Pass, 5, 3>>>&
+void add_device_normalization_fwd_rank_5_3_f16_instances(
+    std::vector<std::unique_ptr<DeviceNormalizationFwd<F16, F16, F16, F16, F32, Pass, 5, 3>>>&
         instances)
 {
     add_device_operation_instances(instances,

library/src/tensor_operation_instance/gpu/normalization/device_groupnorm_f32_instance.cpp → library/src/tensor_operation_instance/gpu/normalization_fwd/device_groupnorm_fwd_f32_instance.cpp

 // SPDX-License-Identifier: MIT
 // Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
 
-#include "normalization_instance_common.hpp"
+#include "normalization_fwd_instance_common.hpp"
 
 namespace ck {
 namespace tensor_operation {
@@ -10,8 +10,8 @@ namespace instance {
 
 using Pass = ck::tensor_operation::element_wise::PassThrough;
 
-void add_device_normalization_rank_5_3_f32_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F32, F32, F32, F32, F32, Pass, 5, 3>>>&
+void add_device_normalization_fwd_rank_5_3_f32_instances(
+    std::vector<std::unique_ptr<DeviceNormalizationFwd<F32, F32, F32, F32, F32, Pass, 5, 3>>>&
         instances)
 {
     add_device_operation_instances(instances,

library/src/tensor_operation_instance/gpu/normalization/device_groupnorm_swish_f16_f32_f32_f16_instance.cpp → library/src/tensor_operation_instance/gpu/normalization_fwd/device_groupnorm_fwd_swish_f16_f32_f32_f16_instance.cpp

 // SPDX-License-Identifier: MIT
 // Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
 
-#include "normalization_instance_common.hpp"
+#include "normalization_fwd_instance_common.hpp"
 
 namespace ck {
 namespace tensor_operation {
@@ -10,8 +10,8 @@ namespace instance {
 
 using Swish = ck::tensor_operation::element_wise::Swish;
 
-void add_device_normalization_rank_5_3_swish_f16_f32_f32_f16_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F16, F32, F32, F16, F32, Swish, 5, 3>>>&
+void add_device_normalization_fwd_rank_5_3_swish_f16_f32_f32_f16_instances(
+    std::vector<std::unique_ptr<DeviceNormalizationFwd<F16, F32, F32, F16, F32, Swish, 5, 3>>>&
         instances)
 {
     add_device_operation_instances(

library/src/tensor_operation_instance/gpu/normalization/device_groupnorm_swish_f16_instance.cpp → library/src/tensor_operation_instance/gpu/normalization_fwd/device_groupnorm_fwd_swish_f16_instance.cpp

 // SPDX-License-Identifier: MIT
 // Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
 
-#include "normalization_instance_common.hpp"
+#include "normalization_fwd_instance_common.hpp"
 
 namespace ck {
 namespace tensor_operation {
@@ -10,8 +10,8 @@ namespace instance {
 
 using Swish = ck::tensor_operation::element_wise::Swish;
 
-void add_device_normalization_rank_5_3_swish_f16_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F16, F32, Swish, 5, 3>>>&
+void add_device_normalization_fwd_rank_5_3_swish_f16_instances(
+    std::vector<std::unique_ptr<DeviceNormalizationFwd<F16, F16, F16, F16, F32, Swish, 5, 3>>>&
         instances)
 {
     add_device_operation_instances(instances,

library/src/tensor_operation_instance/gpu/normalization/device_groupnorm_swish_f32_instance.cpp → library/src/tensor_operation_instance/gpu/normalization_fwd/device_groupnorm_fwd_swish_f32_instance.cpp

 // SPDX-License-Identifier: MIT
 // Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
 
-#include "normalization_instance_common.hpp"
+#include "normalization_fwd_instance_common.hpp"
 
 namespace ck {
 namespace tensor_operation {
@@ -10,8 +10,8 @@ namespace instance {
 
 using Swish = ck::tensor_operation::element_wise::Swish;
 
-void add_device_normalization_rank_5_3_swish_f32_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F32, F32, F32, F32, F32, Swish, 5, 3>>>&
+void add_device_normalization_fwd_rank_5_3_swish_f32_instances(
+    std::vector<std::unique_ptr<DeviceNormalizationFwd<F32, F32, F32, F32, F32, Swish, 5, 3>>>&
         instances)
 {
     add_device_operation_instances(instances,

library/src/tensor_operation_instance/gpu/normalization/device_layernorm2d_f16_instance.cpp → library/src/tensor_operation_instance/gpu/normalization_fwd/device_layernorm2d_fwd_f16_instance.cpp

 // SPDX-License-Identifier: MIT
 // Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
 
-#include "normalization_instance_common.hpp"
+#include "normalization_fwd_instance_common.hpp"
 
 namespace ck {
 namespace tensor_operation {
@@ -10,8 +10,8 @@ namespace instance {
 
 using Pass = ck::tensor_operation::element_wise::PassThrough;
 
-void add_device_normalization_rank_2_1_f16_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F16, F32, Pass, 2, 1>>>&
+void add_device_normalization_fwd_rank_2_1_f16_instances(
+    std::vector<std::unique_ptr<DeviceNormalizationFwd<F16, F16, F16, F16, F32, Pass, 2, 1>>>&
         instances)
 {
     add_device_operation_instances(instances,

library/src/tensor_operation_instance/gpu/normalization/device_layernorm2d_f32_instance.cpp → library/src/tensor_operation_instance/gpu/normalization_fwd/device_layernorm2d_fwd_f32_instance.cpp

 // SPDX-License-Identifier: MIT
 // Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
 
-#include "normalization_instance_common.hpp"
+#include "normalization_fwd_instance_common.hpp"
 
 namespace ck {
 namespace tensor_operation {
@@ -10,8 +10,8 @@ namespace instance {
 
 using Pass = ck::tensor_operation::element_wise::PassThrough;
 
-void add_device_normalization_rank_2_1_f32_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F32, F32, F32, F32, F32, Pass, 2, 1>>>&
+void add_device_normalization_fwd_rank_2_1_f32_instances(
+    std::vector<std::unique_ptr<DeviceNormalizationFwd<F32, F32, F32, F32, F32, Pass, 2, 1>>>&
         instances)
 {
     add_device_operation_instances(instances,

library/src/tensor_operation_instance/gpu/normalization/device_layernorm4d_f16_instance.cpp → library/src/tensor_operation_instance/gpu/normalization_fwd/device_layernorm4d_fwd_f16_instance.cpp

 // SPDX-License-Identifier: MIT
 // Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
 
-#include "normalization_instance_common.hpp"
+#include "normalization_fwd_instance_common.hpp"
 
 namespace ck {
 namespace tensor_operation {
@@ -10,8 +10,8 @@ namespace instance {
 
 using Pass = ck::tensor_operation::element_wise::PassThrough;
 
-void add_device_normalization_rank_4_3_f16_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F16, F16, F16, F16, F32, Pass, 4, 3>>>&
+void add_device_normalization_fwd_rank_4_3_f16_instances(
+    std::vector<std::unique_ptr<DeviceNormalizationFwd<F16, F16, F16, F16, F32, Pass, 4, 3>>>&
         instances)
 {
     add_device_operation_instances(instances,

library/src/tensor_operation_instance/gpu/normalization/device_layernorm4d_f32_instance.cpp → library/src/tensor_operation_instance/gpu/normalization_fwd/device_layernorm4d_fwd_f32_instance.cpp

 // SPDX-License-Identifier: MIT
 // Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
 
-#include "normalization_instance_common.hpp"
+#include "normalization_fwd_instance_common.hpp"
 
 namespace ck {
 namespace tensor_operation {
@@ -10,8 +10,8 @@ namespace instance {
 
 using Pass = ck::tensor_operation::element_wise::PassThrough;
 
-void add_device_normalization_rank_4_3_f32_instances(
-    std::vector<std::unique_ptr<DeviceNormalization<F32, F32, F32, F32, F32, Pass, 4, 3>>>&
+void add_device_normalization_fwd_rank_4_3_f32_instances(
+    std::vector<std::unique_ptr<DeviceNormalizationFwd<F32, F32, F32, F32, F32, Pass, 4, 3>>>&
         instances)
 {
     add_device_operation_instances(instances,

library/src/tensor_operation_instance/gpu/transpose/CMakeLists.txt

+add_instance_library(device_transpose_instance 
+	device_transpose_instances_3d.cpp
+)

library/src/tensor_operation_instance/gpu/transpose/device_transpose_instances_3d.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "ck/ck.hpp"
+#include "ck/library/tensor_operation_instance/gpu/transpose/device_transpose_instance.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace instance {
+
+using F16         = ck::half_t;
+using F32         = float;
+using PassThrough = ck::tensor_operation::element_wise::PassThrough;
+
+void add_device_transpose_f16_instances(
+    std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F16>, ck::Tuple<F16>, PassThrough, 5>>>&
+        instances)
+{
+#ifdef CK_ENABLE_FP16
+    add_device_operation_instances(instances, device_transpose_f16_instances{});
+#else
+    ignore = instances;
+#endif
+}
+
+void add_device_transpose_f32_instances(
+    std::vector<std::unique_ptr<DeviceElementwise<ck::Tuple<F32>, ck::Tuple<F32>, PassThrough, 5>>>&
+        instances)
+{
+#ifdef CK_ENABLE_FP32
+    add_device_operation_instances(instances, device_transpose_f32_instances{});
+#else
+    ignore = instances;
+#endif
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck