Remove save mean and inv std

example/ck_tile/02_layernorm2d/example_layernorm2d_fwd.cpp

@@ -52,11 +52,6 @@ bool run(const ck_tile::ArgParser& arg_parser)
     ck_tile::HostTensor<MeanDataType> mean_host_ref({M});
     ck_tile::HostTensor<InvStdDataType> invStd_host_ref({M});
 
-// TODO - move SAVE_MEAN_INV_STD to user args
-#ifdef SAVE_MEAN_INV_STD
-    ck_tile::HostTensor<MeanDataType> mean_host_dev({M});
-    ck_tile::HostTensor<InvStdDataType> invStd_host_dev({M});
-#endif
 
     ck_tile::FillUniformDistribution<XDataType>{-.5f, .5f}(x_host);
     ck_tile::FillUniformDistribution<GammaDataType>{-.5f, .5f}(gamma_host);
@@ -66,10 +61,6 @@ bool run(const ck_tile::ArgParser& arg_parser)
     ck_tile::DeviceMem gamma_buf(gamma_host.get_element_space_size_in_bytes());
     ck_tile::DeviceMem beta_buf(beta_host.get_element_space_size_in_bytes());
     ck_tile::DeviceMem y_buf(y_host_dev.get_element_space_size_in_bytes());
-#ifdef SAVE_MEAN_INV_STD
-    ck_tile::DeviceMem mean_buf(mean_host_dev.get_element_space_size_in_bytes());
-    ck_tile::DeviceMem invStd_buf(invStd_host_dev.get_element_space_size_in_bytes());
-#endif
 
     x_buf.ToDevice(x_host.data());
     gamma_buf.ToDevice(gamma_host.data());
@@ -81,13 +72,8 @@ bool run(const ck_tile::ArgParser& arg_parser)
                               gamma_buf.GetDeviceBuffer(),
                               beta_buf.GetDeviceBuffer(),
                               y_buf.GetDeviceBuffer(),
-#ifdef SAVE_MEAN_INV_STD
-                              mean_buf.GetDeviceBuffer(),
-                              invStd_buf.GetDeviceBuffer(),
-#else
                               nullptr,
                               nullptr,
-#endif
                               epsilon,
                               M,
                               N};

example/ck_tile/02_layernorm2d/layernorm2d_fwd.hpp

@@ -8,11 +8,6 @@
 #include "ck_tile/ops/layernorm2d.hpp"
 #include <string>
 
-struct layernorm2d_fwd_traits
-{
-    std::string data_type;
-};
-
 template <typename DataType>
 struct LayerNormTypeConfig;
 
@@ -23,13 +18,8 @@ struct LayerNormTypeConfig<ck_tile::half_t>
     using YDataType       = ck_tile::half_t;
     using GammaDataType   = ck_tile::half_t;
     using BetaDataType    = ck_tile::half_t;
-#ifdef SAVE_MEAN_INV_STD
     using MeanDataType    = ck_tile::half_t;
     using InvStdDataType  = ck_tile::half_t;
-#else
-    using MeanDataType   = ck_tile::null_type;
-    using InvStdDataType = ck_tile::null_type;
-#endif
     using ComputeDataType = float;
 };
 
@@ -40,16 +30,12 @@ struct LayerNormTypeConfig<float>
     using YDataType       = float;
     using GammaDataType   = float;
     using BetaDataType    = float;
-#ifdef SAVE_MEAN_INV_STD
     using MeanDataType    = float;
     using InvStdDataType  = float;
-#else
-    using MeanDataType   = ck_tile::null_type;
-    using InvStdDataType = ck_tile::null_type;
-#endif
     using ComputeDataType = float;
 };
 
+// runtime args
 struct layernorm2d_fwd_args
 {
     const void* p_x;
@@ -63,5 +49,10 @@ struct layernorm2d_fwd_args
     ck_tile::index_t N;
 };
 
-// host API
+// This is the public API, will be generated by script
+struct layernorm2d_fwd_traits
+{
+    std::string data_type;
+};
+
 float layernorm2d_fwd(layernorm2d_fwd_traits, layernorm2d_fwd_args, const ck_tile::stream_config&);

example/ck_tile/02_layernorm2d/layernorm_dispatch.hpp

@@ -14,6 +14,7 @@ template <typename InOutDataType,
           ck_tile::index_t NThread,
           ck_tile::index_t VectorAccessSize,
           bool kPadN,
+          bool kSaveMeanInvStd,
           bool kTwoPass>
 struct layernorm_dispatch
 {
@@ -38,6 +39,7 @@ struct layernorm_dispatch
         typename LayerNormTypeConfig<InOutDataType>::InvStdDataType,
         Shape,
         kPadN,
+        kSaveMeanInvStd,
         kTwoPass>;
 
     using Kernel = ck_tile::Layernorm2dFwd<PipelineProblem>;
@@ -75,6 +77,13 @@ template <typename InOutDataType,
           bool kTwoPass = false>
 float run_layernorm(const layernorm2d_fwd_args& param, ck_tile::stream_config stream)
 {
-    return layernorm_dispatch<InOutDataType, NRepeat, NThread, VectorAccessSize, kPadN, kTwoPass>::
-        Run(param, stream);
+    // TODO - Add SaveMeanInvStd instance
+    constexpr bool kSaveMeanInvStd = false;
+    return layernorm_dispatch<InOutDataType,
+                              NRepeat,
+                              NThread,
+                              VectorAccessSize,
+                              kSaveMeanInvStd,
+                              kPadN,
+                              kTwoPass>::Run(param, stream);
 };

include/ck_tile/ops/layernorm2d/kernel/layernorm2d_fwd_kernel.hpp

@@ -26,8 +26,8 @@ struct Layernorm2dFwd
 
     static constexpr bool kHasGamma   = !std::is_same_v<GammaDataType, ck_tile::null_type>;
     static constexpr bool kHasBeta    = !std::is_same_v<BetaDataType, ck_tile::null_type>;
-    static constexpr bool kSaveMean   = !std::is_same_v<MeanDataType, ck_tile::null_type>;
-    static constexpr bool kSaveInvStd = !std::is_same_v<InvStdDataType, ck_tile::null_type>;
+    static constexpr bool kSaveMean   = Problem::kSaveMeanInvStd;
+    static constexpr bool kSaveInvStd = Problem::kSaveMeanInvStd;
 
     static constexpr ck_tile::index_t kMPerBlock = Problem::BlockShape::kMPerBlock;
     static constexpr ck_tile::index_t kNPerBlock = Problem::BlockShape::kNPerBlock;

include/ck_tile/ops/layernorm2d/pipeline/block_layernorm2d_fwd_problem.hpp

@@ -16,6 +16,7 @@ template <typename XDataType_,
           typename InvStdDataType_,
           typename BlockShape_,
           bool kPadN_,
+          bool kSaveMeanInvStd_,
           bool kTwoPass_>
 struct BlockLayernorm2dFwdProblem
 {
@@ -27,7 +28,9 @@ struct BlockLayernorm2dFwdProblem
     using MeanDataType    = remove_cvref_t<MeanDataType_>;
     using InvStdDataType  = remove_cvref_t<InvStdDataType_>;
     using BlockShape      = remove_cvref_t<BlockShape_>;
+
     static constexpr bool kPadN           = kPadN_;
+    static constexpr bool kSaveMeanInvStd = kSaveMeanInvStd_;
     static constexpr bool kTwoPass        = kTwoPass_;
 };