Add (#677)

client_example/18_groupnorm/groupnorm_swish.cpp

@@ -13,8 +13,8 @@
 #include "ck/library/tensor_operation_instance/gpu/normalization_swish.hpp"
 
 using XDataType       = ck::half_t;
-using GammaDataType   = ck::half_t;
-using BetaDataType    = ck::half_t;
+using GammaDataType   = float;
+using BetaDataType    = float;
 using YDataType       = ck::half_t;
 using ComputeDataType = float;
 using Swish           = ck::tensor_operation::element_wise::Swish;

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

@@ -25,6 +25,10 @@ void add_device_normalization_rank_5_3_swish_f16_instances(
 void add_device_normalization_rank_5_3_swish_f32_instances(
     std::vector<std::unique_ptr<DeviceNormalization<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, F32, F16, Swish, 5, 3>>>&);
+
 template <typename XDataType,
           typename GammaDataType,
           typename BetaDataType,
@@ -70,6 +74,14 @@ struct DeviceOperationInstanceFactory<
                 add_device_normalization_rank_5_3_swish_f32_instances(op_ptrs);
             }
         }
+        else if constexpr(is_same_v<XDataType, F16> && is_same_v<GammaDataType, F32> &&
+                          is_same_v<BetaDataType, F32> && is_same_v<YDataType, F16>)
+        {
+            if constexpr(Rank == 5 && NumReduceDim == 3)
+            {
+                add_device_normalization_rank_5_3_swish_f16_f32_f32_f16_instances(op_ptrs);
+            }
+        }
 
         return op_ptrs;
     }

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

@@ -7,4 +7,5 @@ add_instance_library(device_normalization_instance
     device_groupnorm_f32_instance.cpp
     device_groupnorm_swish_f16_instance.cpp
     device_groupnorm_swish_f32_instance.cpp
+    device_groupnorm_swish_f16_f32_f32_f16_instance.cpp
 )

library/src/tensor_operation_instance/gpu/normalization/device_groupnorm_swish_f16_f32_f32_f16_instance.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "normalization_instance_common.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+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, F32, F16, Swish, 5, 3>>>&
+        instances)
+{
+    add_device_operation_instances(instances,
+                                   device_normalization_f16_f32_f32_f16_instances<Swish, 5, 3>{});
+}
+
+} // namespace instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

library/src/tensor_operation_instance/gpu/normalization/normalization_instance_common.hpp

@@ -69,6 +69,32 @@ using device_normalization_f32_instances = std::tuple<
     // clang-format on
     >;
 
+template <typename OutElementwise, index_t Rank, index_t Reduce>
+using device_normalization_f16_f32_f32_f16_instances = std::tuple<
+    // clang-format off
+        // XDataType, GammaDataType, BetaDataType, ComputeDataType, YDataType, Rank, NumReduceDim, BlockSize, MThreadClusterSize, KThreadClusterSize, MThreadSliceSize, KThreadSliceSize, XYSrcVectorDim, XSrcVectorSize, GammaSrcVectorSize, BetaSrcVectorSize, YDstVectorSize>
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 128, 1, 128, 1, 1, 1, 1, 1, 1, 1, 1, 1>,   // irregular size
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 256, 1, 256, 1, 1, 1, 1, 1, 1, 1, 1, 1>,   // irregular size
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 512, 1, 512, 1, 1, 1, 1, 1, 1, 1, 1, 1>,   // irregular size
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 1024, 1, 1024, 1, 1, 1, 1, 1, 1, 1, 1, 1>, // irregular size
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 256, 1, 256, 1, 2, 1, 2, 1, 2, 1, 2, 2>,   // irregular size
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 128, 1, 128, 1, 4, 1, 4, 1, 4, 1, 4, 4>,
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 128, 1, 128, 1, 8, 1, 4, 1, 4, 1, 4, 4>,
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 128, 1, 128, 1, 16, 1, 4, 1, 4, 1, 4, 4>,
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 128, 1, 128, 1, 32, 1, 4, 1, 4, 1, 4, 4>,
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 256, 1, 256, 1, 4, 1, 4, 1, 4, 1, 4, 4>,
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 256, 1, 256, 1, 8, 1, 4, 1, 4, 1, 4, 4>,
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 256, 1, 256, 1, 16, 1, 4, 1, 4, 1, 4, 4>,
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 256, 1, 256, 2, 16, 1, 4, 1, 4, 1, 4, 4>,
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 256, 1, 256, 1, 32, 1, 4, 1, 4, 1, 4, 4>,
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 512, 1, 512, 1, 4, 1, 4, 1, 4, 1, 4, 4>,
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 512, 1, 512, 1, 8, 1, 4, 1, 4, 1, 4, 4>,
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 512, 1, 512, 2, 8, 1, 4, 1, 4, 1, 4, 4>,
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 1024, 1, 1024, 1, 4, 1, 4, 1, 4, 1, 4, 4>,
+        DeviceNormalizationImpl<F16, F32, F32, F32, F16, OutElementwise, Rank, Reduce, 1024, 1, 1024, 1, 8, 1, 4, 1, 4, 1, 4, 4>
+    // clang-format on
+    >;
+
 } // namespace instance
 } // namespace device
 } // namespace tensor_operation