From b109516455631ff8fd6dce99cf7c14bf8e323ebb Mon Sep 17 00:00:00 2001
From: Chao Liu <chao.liu2@amd.com>
Date: Wed, 25 May 2022 19:01:02 +0000
Subject: [PATCH] debugging conv

---
 example/09_convnd_fwd/convnd_fwd_xdl_fp16.cpp | 53 ++++++++++++++++++-
 1 file changed, 52 insertions(+), 1 deletion(-)

diff --git a/example/09_convnd_fwd/convnd_fwd_xdl_fp16.cpp b/example/09_convnd_fwd/convnd_fwd_xdl_fp16.cpp
index 7ad83d5ad6..022a24d073 100644
--- a/example/09_convnd_fwd/convnd_fwd_xdl_fp16.cpp
+++ b/example/09_convnd_fwd/convnd_fwd_xdl_fp16.cpp
@@ -8,6 +8,7 @@
 #include "conv_util.hpp"
 #include "device.hpp"
 #include "device_tensor.hpp"
+#include "device_conv2d_fwd_xdl_c_shuffle_nhwc_kyxc_nhwk.hpp"
 #include "device_convnd_fwd_xdl_nhwc_kyxc_nhwk.hpp"
 #include "element_wise_operation.hpp"
 #include "host_tensor.hpp"
@@ -78,6 +79,52 @@ using DeviceConvNDFwdInstance = ck::tensor_operation::device::
         7,                  // CThreadTransferSrcDstVectorDim
         1>;                 // CThreadTransferDstScalarPerVector
 
+#if 1
+using DeviceConv2DFwdInstance = ck::tensor_operation::device::DeviceConv2dFwdXdl_C_Shuffle_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K<
+    ck::half_t,
+    ck::half_t,
+    ck::half_t,
+    float,
+    ck::tensor_operation::element_wise::PassThrough,
+    ck::tensor_operation::element_wise::PassThrough,
+    ck::tensor_operation::element_wise::PassThrough,
+    ck::tensor_operation::device::ConvolutionForwardSpecialization::Default,
+
+    256, // block_size
+    128, // m_per_block
+    64, // n_per_block
+    4, // k_per_block
+    8, // k1
+    32, // m_per_xdl
+    32, // n_per_xdl
+    2, // m_xdl_per_wave
+    1, // n_xdl_per_wave
+
+
+    S<4,64,1>, // thread_cluster_length
+    S<1,0,2>, // thread_cluster_arrange_order
+    S<1,0,2>, // src_access_order
+    2, // src_vector_dim
+    8, // src_scalar_per_vector
+    8, // dst_scalar_per_vector
+    true, // add_extra_dim
+
+    S<4,64,1>, // thread_cluster_length
+    S<1,0,2>, // thread_cluster_arrange_order
+    S<1,0,2>, // src_access_order
+    2, // src_vector_dim
+    8, // src_scalar_per_vector
+    8, // dst_scalar_per_vector
+    true, // add_extra_dim
+
+    1, // m_xdl_per_wave
+    1, // n_xdl_per_wave
+    S<1,1,32,1,1,8>, // m_n_block_wave_per_xdl
+    8 // scalar_per_vector
+
+    >;
+#endif
+
 template <ck::index_t NumDimSpatial>
 using ReferenceConvNDFwdInstance = ck::tensor_operation::host::ReferenceConvFwd<InDataType,
                                                                                 WeiDataType,
@@ -95,7 +142,11 @@ DeviceConvFwdBasePtr get_conv_instance(int num_dim_spatial)
         return std::make_unique<DeviceConvNDFwdInstance<3>>();
     }
     case 2: {
+#if 0
         return std::make_unique<DeviceConvNDFwdInstance<2>>();
+#else
+        return std::make_unique<DeviceConv2DFwdInstance>();
+#endif
     }
     case 1: {
         return std::make_unique<DeviceConvNDFwdInstance<1>>();
@@ -291,7 +342,7 @@ int main(int argc, char* argv[])
 
     float tflops     = static_cast<float>(flop) / 1.E9 / ave_time;
     float gb_per_sec = num_btype / 1.E6 / ave_time;
-    std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s"
+    std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s, " << conv->GetTypeString() 
               << std::endl;
 
     if(do_verification)