updated new dropout for attn fwd

example/32_batched_gemm_scale_softmax_gemm/batched_multihead_attention_forward.cpp

@@ -103,17 +103,17 @@ using DeviceGemmInstance =
         TensorSpecC,
         1,
         256,
-        256,         // MPerBlock
+        128,         // MPerBlock
         128,         // NPerBlock
-        32,          // KPerBlock
+        64,          // KPerBlock
         64,          // Gemm1NPerBlock
-        32,          // Gemm1KPerBlock
+        64,          // Gemm1KPerBlock
         8,           // AK1
         8,           // BK1
         2,           // B1K1
         32,          // MPerXDL
         32,          // NPerXDL
-        2,           // MXdlPerWave
+        1,           // MXdlPerWave
         4,           // NXdlPerWave
         2,           // Gemm1NXdlPerWave
         S<4, 64, 1>, // ABlockTransfer
@@ -130,11 +130,11 @@ using DeviceGemmInstance =
         8,
         8,
         true,
-        S<16, 16, 1>, // B1BlockTransfer
+        S<8, 32, 1>, // B1BlockTransfer
         S<0, 2, 1>,
         S<0, 2, 1>,
         1,
-        4,
+        2,
         2,
         false,
         1,              // CShuffleMXdlPerWavePerShuffle

example/32_batched_gemm_scale_softmax_gemm/batched_multihead_attention_forward_bf16.cpp

@@ -99,17 +99,17 @@ using DeviceGemmInstance =
         TensorSpecC,
         1,
         256,
-        256,         // MPerBlock
+        128,         // MPerBlock
         128,         // NPerBlock
-        32,          // KPerBlock
+        64,          // KPerBlock
         64,          // Gemm1NPerBlock
-        32,          // Gemm1KPerBlock
+        64,          // Gemm1KPerBlock
         8,           // AK1
         8,           // BK1
         2,           // B1K1
         32,          // MPerXDL
         32,          // NPerXDL
-        2,           // MXdlPerWave
+        1,           // MXdlPerWave
         4,           // NXdlPerWave
         2,           // Gemm1NXdlPerWave
         S<4, 64, 1>, // ABlockTransfer
@@ -126,11 +126,11 @@ using DeviceGemmInstance =
         8,
         8,
         true,
-        S<16, 16, 1>, // B1BlockTransfer
+        S<8, 32, 1>, // B1BlockTransfer
         S<0, 2, 1>,
         S<0, 2, 1>,
         1,
-        4,
+        2,
         2,
         false,
         1,              // CShuffleMXdlPerWavePerShuffle

example/32_batched_gemm_scale_softmax_gemm/grouped_multihead_attention_forward.cpp

@@ -105,8 +105,8 @@ using DeviceGemmInstance =
         256,
         128,         // MPerBlock
         128,         // NPerBlock
-        32,          // KPerBlock
-        128,         // Gemm1NPerBlock
+        64,          // KPerBlock
+        64,          // Gemm1NPerBlock
         64,          // Gemm1KPerBlock
         8,           // AK1
         8,           // BK1
@@ -115,7 +115,7 @@ using DeviceGemmInstance =
         32,          // NPerXDL
         1,           // MXdlPerWave
         4,           // NXdlPerWave
-        4,           // Gemm1NXdlPerWave
+        2,           // Gemm1NXdlPerWave
         S<4, 64, 1>, // ABlockTransfer
         S<1, 0, 2>,
         S<1, 0, 2>,
@@ -130,11 +130,11 @@ using DeviceGemmInstance =
         8,
         8,
         true,
-        S<16, 16, 1>, // B1BlockTransfer
+        S<8, 32, 1>, // B1BlockTransfer
         S<0, 2, 1>,
         S<0, 2, 1>,
         1,
-        4,
+        2,
         2,
         false,
         1,              // CShuffleMXdlPerWavePerShuffle

example/32_batched_gemm_scale_softmax_gemm/grouped_multihead_attention_forward_bf16.cpp

@@ -101,8 +101,8 @@ using DeviceGemmInstance =
         256,
         128,         // MPerBlock
         128,         // NPerBlock
-        32,          // KPerBlock
-        128,         // Gemm1NPerBlock
+        64,          // KPerBlock
+        64,          // Gemm1NPerBlock
         64,          // Gemm1KPerBlock
         8,           // AK1
         8,           // BK1
@@ -111,7 +111,7 @@ using DeviceGemmInstance =
         32,          // NPerXDL
         1,           // MXdlPerWave
         4,           // NXdlPerWave
-        4,           // Gemm1NXdlPerWave
+        2,           // Gemm1NXdlPerWave
         S<4, 64, 1>, // ABlockTransfer
         S<1, 0, 2>,
         S<1, 0, 2>,
@@ -126,11 +126,11 @@ using DeviceGemmInstance =
         8,
         8,
         true,
-        S<16, 16, 1>, // B1BlockTransfer
+        S<8, 32, 1>, // B1BlockTransfer
         S<0, 2, 1>,
         S<0, 2, 1>,
         1,
-        4,
+        2,
         2,
         false,
         1,              // CShuffleMXdlPerWavePerShuffle

example/32_batched_gemm_scale_softmax_gemm/run_batched_multihead_attention_forward.inc

@@ -9,8 +9,8 @@ int run(int argc, char* argv[])
 
     // GEMM shape for A/B0/B1/C
     // C_g_m_o = A_g_m_k * B0_g_k_n * B1_g_n_o
-    ck::index_t M = 1000; // 120
-    ck::index_t N = 1000; // 1000
+    ck::index_t M = 512; // 120
+    ck::index_t N = 512; // 1000
     ck::index_t K = 64;
     ck::index_t O = 64;
 
@@ -97,7 +97,7 @@ int run(int argc, char* argv[])
 
     std::vector<ck::index_t> z_gs_ms_ns_lengths{G0, G1, M, N};
     std::vector<ck::index_t> z_gs_ms_ns_strides =
-        output_permute
+        input_permute
             ? std::vector<ck::index_t>{M * G1 * N, N, G1 * N, 1} // Z layout [G0, M, G1, N]
             : std::vector<ck::index_t>{G1 * M * N, M * N, N, 1}; // Z layout [G0, G1, M, N]
 

example/32_batched_gemm_scale_softmax_gemm/run_grouped_multihead_attention_forward.inc

@@ -10,8 +10,7 @@ int run(int argc, char* argv[])
     bool input_permute  = false;
     bool output_permute = true;
 
-
-    float p_drop                    = 0.2;
+    float p_drop                    = 0.1;
     float p_dropout                 = 1 - p_drop;
     uint16_t p_dropout_in_16bits    = uint16_t(std::floor(p_dropout * 65535.0));
     float rp_dropout                = 1.0 / p_dropout;
@@ -84,8 +83,8 @@ int run(int argc, char* argv[])
 
         int M  = 128 * (rand() % 8 + 1);
         int N  = 128 * (rand() % 8 + 1);
-        int K  = 128;
-        int O  = 128;
+        int K  = 64;
+        int O  = 64;
         int G0 = rand() % 3 + 1;
         int G1 = rand() % 5 + 1;
 
@@ -117,7 +116,7 @@ int run(int argc, char* argv[])
 
         std::vector<ck::index_t> z_gs_ms_ns_lengths{G0, G1, M, N};
         std::vector<ck::index_t> z_gs_ms_ns_strides =
-            output_permute
+            input_permute
                 ? std::vector<ck::index_t>{M * G1 * N, N, G1 * N, 1} // Z layout [G0, M, G1, N]
                 : std::vector<ck::index_t>{G1 * M * N, M * N, N, 1}; // Z layout [G0, G1, M, N]
 

include/ck/tensor_operation/gpu/grid/gridwise_batched_multihead_attention_forward_xdl_cshuffle.hpp

@@ -274,11 +274,11 @@ struct GridwiseBatchedMultiheadAttentionForward_Xdl_CShuffle
         const auto K = a_grid_desc_ak0_m_ak1.GetLength(I0) * a_grid_desc_ak0_m_ak1.GetLength(I2);
         const auto Gemm1N = b1_grid_desc_bk0_n_bk1.GetLength(I1);
 
-        // if(Gemm1N != K)
-        //{
-        //    std::cout << "SizeK must be equal to SizeO (equal attention head size)" << '\n';
-        //    return false;
-        //}
+        if(Gemm1N != K)
+        {
+            std::cout << "SizeK must be equal to SizeO (equal attention head size)" << '\n';
+            return false;
+        }
 
         if(!(M == c_grid_desc_m_n.GetLength(I0) && Gemm1N == c_grid_desc_m_n.GetLength(I1)))
         {
@@ -852,7 +852,7 @@ struct GridwiseBatchedMultiheadAttentionForward_Xdl_CShuffle
             make_naive_tensor_descriptor_packed(make_tuple(I1,   // MBlockId
                                                            I1,   // NBlockID
                                                            m0,   // MRepeat
-                                                           n0,   // NRepeat
+                                                           I1,   // n0,   // NRepeat
                                                            m1,   // MWaveId
                                                            n1,   // NWaveId
                                                            m2,   // MPerXdl
@@ -883,7 +883,7 @@ struct GridwiseBatchedMultiheadAttentionForward_Xdl_CShuffle
             Sequence<I1, // MBlockId
                      I1, // NBlockID
                      m0, // MRepeat
-                     n0, // NRepeat
+                     I1, // NRepeat
                      m1, // MWaveId
                      n1, // NWaveId
                      m2, // MPerXdl
@@ -1006,10 +1006,12 @@ struct GridwiseBatchedMultiheadAttentionForward_Xdl_CShuffle
                 // save z to global
                 if(p_z_grid)
                 {
-                    // P_dropped
+                    static_for<0, n0, 1>{}([&](auto i) {
                         blockwise_dropout.template ApplyDropout<decltype(acc_thread_buf),
                                                                 decltype(z_tenor_buffer),
-                                                            false>(
+                                                                false,
+                                                                decltype(n0),
+                                                                decltype(i)>(
                             acc_thread_buf, ph, z_tenor_buffer);
 
                         z_thread_copy_vgpr_to_global.Run(
@@ -1018,13 +1020,20 @@ struct GridwiseBatchedMultiheadAttentionForward_Xdl_CShuffle
                             z_tenor_buffer,
                             z_grid_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5,
                             z_grid_buf);
-
+                        z_thread_copy_vgpr_to_global.MoveDstSliceWindow(
+                            z_grid_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5,
+                            make_multi_index(0, 0, 0, 1, 0, 0, 0, 0, 0, 0));
+                    });
+                    z_thread_copy_vgpr_to_global.MoveDstSliceWindow(
+                        z_grid_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5,
+                        make_multi_index(0, 0, 0, -(n0.value), 0, 0, 0, 0, 0, 0));
                     z_thread_copy_vgpr_to_global.MoveDstSliceWindow(
                         z_grid_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5,
                         make_multi_index(0, 1, 0, 0, 0, 0, 0, 0, 0, 0));
                 }
                 else
                 {
+                    // ignore = z_grid_buf;
                     // P_dropped
                     blockwise_dropout.template ApplyDropout<decltype(acc_thread_buf), false>(
                         acc_thread_buf, ph);