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Commit 0999070d authored by danyao12's avatar danyao12
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Merge branch 'attn-train-develop-qloop' into mha-train-develop

parents 5ba30232 68e3bb6d
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Showing with 182 additions and 144 deletions
include/ck/tensor_operation/gpu/device/impl/device_batched_mha_bwd_xdl_cshuffle_kloop_v1.hpp
View file @ 0999070d
......@@ -1047,7 +1047,7 @@ struct DeviceBatchedMultiheadAttentionBackward_Kloop_Xdl_CShuffle_V1
static bool IsSupportedArgument(const Argument& arg)
{
#if 0
#if DEBUG_LOG
arg.Print();
#endif
......
include/ck/tensor_operation/gpu/device/impl/device_batched_mha_bwd_xdl_cshuffle_kloop_v2.hpp
View file @ 0999070d
......@@ -1048,7 +1048,7 @@ struct DeviceBatchedMultiheadAttentionBackward_Kloop_Xdl_CShuffle_V2
static bool IsSupportedArgument(const Argument& arg)
{
#if 0
#if DEBUG_LOG
arg.Print();
#endif
......
include/ck/tensor_operation/gpu/device/impl/device_batched_mha_bwd_xdl_cshuffle_qloop_phased_v1.hpp
View file @ 0999070d
......@@ -1041,7 +1041,7 @@ struct DeviceBatchedMultiheadAttentionBackward_Qloop_Phased_Xdl_CShuffle_V1
static bool IsSupportedArgument(const Argument& arg)
{
#if 0
#if DEBUG_LOG
arg.Print();
#endif
......
include/ck/tensor_operation/gpu/device/impl/device_batched_mha_bwd_xdl_cshuffle_qloop_v1.hpp
View file @ 0999070d
......@@ -48,6 +48,7 @@ template <typename GridwiseGemm,
typename ComputeBasePtrOfStridedBatch,
typename C0MatrixMask,
bool HasMainKBlockLoop,
bool IsDropout,
bool Deterministic>
__global__ void
#if CK_USE_LAUNCH_BOUNDS
......@@ -120,7 +121,7 @@ __global__ void
{
for(index_t i = 0; i < nblock; i++)
{
GridwiseGemm::template Run<HasMainKBlockLoop>(
GridwiseGemm::template Run<HasMainKBlockLoop, IsDropout>(
p_a_grid + a_batch_offset,
p_b_grid + b_batch_offset,
z_matrix_ptr,
......@@ -155,36 +156,36 @@ __global__ void
}
else
{
GridwiseGemm::template Run<HasMainKBlockLoop>(p_a_grid + a_batch_offset,
p_b_grid + b_batch_offset,
z_matrix_ptr,
p_b1_grid + b1_batch_offset,
p_c_grid + c_batch_offset,
p_lse_grid + lse_batch_offset,
p_ygrad_grid + c_batch_offset,
p_qgrad_grid + a_batch_offset,
p_kgrad_grid + b_batch_offset,
p_vgrad_grid + b1_batch_offset,
p_shared,
a_element_op,
b_element_op,
acc_element_op,
b1_element_op,
c_element_op,
a_grid_desc_ak0_m_ak1,
b_grid_desc_bk0_n_bk1,
c_grid_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5,
b1_grid_desc_bk0_n_bk1,
c_grid_desc_mblock_mperblock_nblock_nperblock,
lse_grid_desc_m,
ygrad_grid_desc_o0_m_o1,
block_2_ctile_map,
c0_matrix_mask,
p_drop,
ph,
z_random_matrix_offset,
raw_n_padded,
0);
GridwiseGemm::template Run<HasMainKBlockLoop, IsDropout>(p_a_grid + a_batch_offset,
p_b_grid + b_batch_offset,
z_matrix_ptr,
p_b1_grid + b1_batch_offset,
p_c_grid + c_batch_offset,
p_lse_grid + lse_batch_offset,
p_ygrad_grid + c_batch_offset,
p_qgrad_grid + a_batch_offset,
p_kgrad_grid + b_batch_offset,
p_vgrad_grid + b1_batch_offset,
p_shared,
a_element_op,
b_element_op,
acc_element_op,
b1_element_op,
c_element_op,
a_grid_desc_ak0_m_ak1,
b_grid_desc_bk0_n_bk1,
c_grid_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5,
b1_grid_desc_bk0_n_bk1,
c_grid_desc_mblock_mperblock_nblock_nperblock,
lse_grid_desc_m,
ygrad_grid_desc_o0_m_o1,
block_2_ctile_map,
c0_matrix_mask,
p_drop,
ph,
z_random_matrix_offset,
raw_n_padded,
0);
}
#else
ignore = p_a_grid;
......@@ -933,7 +934,7 @@ struct DeviceBatchedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V1
float ave_time = 0;
auto launch_kernel = [&](auto has_main_k_block_loop_) {
auto launch_kernel = [&](auto has_main_k_block_loop_, auto is_dropout_) {
const auto kernel =
kernel_batched_multihead_attention_backward_qloop_xdl_cshuffle_v1<
GridwiseGemm,
......@@ -957,6 +958,7 @@ struct DeviceBatchedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V1
ComputeBasePtrOfStridedBatch,
C0MatrixMask,
has_main_k_block_loop_,
is_dropout_,
Deterministic>;
return launch_and_time_kernel(
......@@ -998,9 +1000,11 @@ struct DeviceBatchedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V1
arg.m_raw_padded_,
arg.n_raw_padded_);
};
ave_time = launch_kernel(integral_constant<bool, false>{});
if(arg.p_drop_ > 0.0){
ave_time = launch_kernel(integral_constant<bool, false>{}, integral_constant<bool, true>{});
}else{
ave_time = launch_kernel(integral_constant<bool, false>{}, integral_constant<bool, false>{});
}
return ave_time;
}
......@@ -1020,6 +1024,9 @@ struct DeviceBatchedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V1
static bool IsSupportedArgument(const Argument& arg)
{
#if DEBUG_LOG
arg.Print();
#endif
if(!(ck::get_device_name() == "gfx908" || ck::get_device_name() == "gfx90a" ||
ck::get_device_name() == "gfx940" || ck::get_device_name() == "gfx941" ||
......
include/ck/tensor_operation/gpu/device/impl/device_batched_mha_bwd_xdl_cshuffle_qloop_v2.hpp
View file @ 0999070d
......@@ -47,6 +47,7 @@ template <typename GridwiseGemm,
typename ComputeBasePtrOfStridedBatch,
typename C0MatrixMask,
bool HasMainKBlockLoop,
bool IsDropout,
bool Deterministic>
__global__ void
#if CK_USE_LAUNCH_BOUNDS
......@@ -119,7 +120,7 @@ __global__ void
{
for(index_t i = 0; i < nblock; i++)
{
GridwiseGemm::template Run<HasMainKBlockLoop>(
GridwiseGemm::template Run<HasMainKBlockLoop, IsDropout>(
p_a_grid + a_batch_offset,
p_b_grid + b_batch_offset,
z_matrix_ptr,
......@@ -154,7 +155,7 @@ __global__ void
}
else
{
GridwiseGemm::template Run<HasMainKBlockLoop>(p_a_grid + a_batch_offset,
GridwiseGemm::template Run<HasMainKBlockLoop, IsDropout>(p_a_grid + a_batch_offset,
p_b_grid + b_batch_offset,
z_matrix_ptr,
p_b1_grid + b1_batch_offset,
......@@ -950,7 +951,7 @@ struct DeviceBatchedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V2
float ave_time = 0;
auto launch_kernel = [&](auto has_main_k_block_loop_) {
auto launch_kernel = [&](auto has_main_k_block_loop_, auto is_dropout_) {
const auto kernel =
kernel_batched_multihead_attention_backward_qloop_xdl_cshuffle_v2<
GridwiseGemm,
......@@ -974,6 +975,7 @@ struct DeviceBatchedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V2
ComputeBasePtrOfStridedBatch,
C0MatrixMask,
has_main_k_block_loop_,
is_dropout_,
Deterministic>;
return launch_and_time_kernel(
......@@ -1021,11 +1023,17 @@ struct DeviceBatchedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V2
if(GridwiseGemm::CalculateHasMainKBlockLoop(K))
{
ave_time = launch_kernel(integral_constant<bool, true>{});
if(arg.p_drop_ > 0.0)
ave_time = launch_kernel(integral_constant<bool, true>{}, integral_constant<bool, true>{});
else
ave_time = launch_kernel(integral_constant<bool, true>{}, integral_constant<bool, false>{});
}
else
{
ave_time = launch_kernel(integral_constant<bool, false>{});
if(arg.p_drop_ > 0.0)
ave_time = launch_kernel(integral_constant<bool, false>{}, integral_constant<bool, true>{});
else
ave_time = launch_kernel(integral_constant<bool, false>{}, integral_constant<bool, false>{});
}
return ave_time;
......@@ -1047,6 +1055,9 @@ struct DeviceBatchedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V2
static bool IsSupportedArgument(const Argument& arg)
{
#if DEBUG_LOG
arg.Print();
#endif
if(!(ck::get_device_name() == "gfx908" || ck::get_device_name() == "gfx90a" ||
ck::get_device_name() == "gfx940" || ck::get_device_name() == "gfx941" ||
......
include/ck/tensor_operation/gpu/device/impl/device_grouped_mha_bwd_xdl_cshuffle_qloop_v1.hpp
View file @ 0999070d
......@@ -35,6 +35,7 @@ template <typename GridwiseGemm,
typename B1ElementwiseOperation,
typename CElementwiseOperation,
bool HasMainKBlockLoop,
bool IsDropout,
bool Deterministic>
__global__ void
#if CK_USE_LAUNCH_BOUNDS
......@@ -105,7 +106,7 @@ __global__ void
{
for(index_t i = 0; i < num_blocks_per_batch; i++)
{
GridwiseGemm::template Run<HasMainKBlockLoop>(
GridwiseGemm::template Run<HasMainKBlockLoop, IsDropout>(
arg_ptr[group_id].p_a_grid_ + a_batch_offset,
arg_ptr[group_id].p_b_grid_ + b_batch_offset,
z_matrix_ptr,
......@@ -141,7 +142,7 @@ __global__ void
}
else
{
GridwiseGemm::template Run<HasMainKBlockLoop>(
GridwiseGemm::template Run<HasMainKBlockLoop, IsDropout>(
arg_ptr[group_id].p_a_grid_ + a_batch_offset,
arg_ptr[group_id].p_b_grid_ + b_batch_offset,
z_matrix_ptr,
......@@ -961,7 +962,7 @@ struct DeviceGroupedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V1
float ave_time = 0;
auto launch_kernel = [&](auto has_main_k_block_loop_) {
auto launch_kernel = [&](auto has_main_k_block_loop_, auto is_dropout_) {
const auto kernel =
kernel_grouped_multihead_attention_backward_qloop_xdl_cshuffle_v1<
GridwiseGemm,
......@@ -972,6 +973,7 @@ struct DeviceGroupedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V1
B1ElementwiseOperation,
CElementwiseOperation,
has_main_k_block_loop_,
is_dropout_,
Deterministic>;
return launch_and_time_kernel(
......@@ -996,11 +998,17 @@ struct DeviceGroupedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V1
// to concern Gemm0's loop
if(all_has_main_k_block_loop)
{
ave_time = launch_kernel(integral_constant<bool, true>{});
if(arg.p_dropout_ > 0.0)
ave_time = launch_kernel(integral_constant<bool, true>{}, integral_constant<bool, true>{});
else
ave_time = launch_kernel(integral_constant<bool, true>{}, integral_constant<bool, false>{});
}
else if(!some_has_main_k_block_loop)
{
ave_time = launch_kernel(integral_constant<bool, false>{});
if(arg.p_dropout_ > 0.0)
ave_time = launch_kernel(integral_constant<bool, false>{}, integral_constant<bool, true>{});
else
ave_time = launch_kernel(integral_constant<bool, false>{}, integral_constant<bool, false>{});
}
else
{
......
include/ck/tensor_operation/gpu/device/impl/device_grouped_mha_bwd_xdl_cshuffle_qloop_v2.hpp
View file @ 0999070d
......@@ -35,6 +35,7 @@ template <typename GridwiseGemm,
typename B1ElementwiseOperation,
typename CElementwiseOperation,
bool HasMainKBlockLoop,
bool IsDropout,
bool Deterministic>
__global__ void
#if CK_USE_LAUNCH_BOUNDS
......@@ -105,7 +106,7 @@ __global__ void
{
for(index_t i = 0; i < num_blocks_per_batch; i++)
{
GridwiseGemm::template Run<HasMainKBlockLoop>(
GridwiseGemm::template Run<HasMainKBlockLoop, IsDropout>(
arg_ptr[group_id].p_a_grid_ + a_batch_offset,
arg_ptr[group_id].p_b_grid_ + b_batch_offset,
z_matrix_ptr,
......@@ -141,7 +142,7 @@ __global__ void
}
else
{
GridwiseGemm::template Run<HasMainKBlockLoop>(
GridwiseGemm::template Run<HasMainKBlockLoop, IsDropout>(
arg_ptr[group_id].p_a_grid_ + a_batch_offset,
arg_ptr[group_id].p_b_grid_ + b_batch_offset,
z_matrix_ptr,
......@@ -968,7 +969,7 @@ struct DeviceGroupedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V2
float ave_time = 0;
auto launch_kernel = [&](auto has_main_k_block_loop_) {
auto launch_kernel = [&](auto has_main_k_block_loop_, auto is_dropout_) {
const auto kernel =
kernel_grouped_multihead_attention_backward_qloop_xdl_cshuffle_v2<
GridwiseGemm,
......@@ -979,6 +980,7 @@ struct DeviceGroupedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V2
B1ElementwiseOperation,
CElementwiseOperation,
has_main_k_block_loop_,
is_dropout_,
Deterministic>;
return launch_and_time_kernel(
......@@ -1003,11 +1005,17 @@ struct DeviceGroupedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V2
// to concern Gemm0's loop
if(all_has_main_k_block_loop)
{
ave_time = launch_kernel(integral_constant<bool, true>{});
if(arg.p_dropout_ > 0.0)
ave_time = launch_kernel(integral_constant<bool, true>{}, integral_constant<bool, true>{});
else
ave_time = launch_kernel(integral_constant<bool, true>{}, integral_constant<bool, false>{});
}
else if(!some_has_main_k_block_loop)
{
ave_time = launch_kernel(integral_constant<bool, false>{});
if(arg.p_dropout_ > 0.0)
ave_time = launch_kernel(integral_constant<bool, false>{}, integral_constant<bool, true>{});
else
ave_time = launch_kernel(integral_constant<bool, false>{}, integral_constant<bool, false>{});
}
else
{
......
include/ck/tensor_operation/gpu/grid/gridwise_batched_mha_bwd_xdl_cshuffle_qloop_b2t_v1.hpp
View file @ 0999070d
......@@ -1222,6 +1222,7 @@ struct GridwiseBatchedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V1
}
template <bool HasMainKBlockLoop,
bool IsDropout,
typename Block2CTileMap,
typename C0MatrixMask,
typename YGradGridDesc_O0_M_O1>
......@@ -1947,56 +1948,57 @@ struct GridwiseBatchedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V1
constexpr auto position_offset = M3 * M4;
// save z to global
if(p_z_grid)
{
if constexpr(IsDropout){
if(p_z_grid)
{
auto acc0_thread_idx = Acc0TileIterator::GetIndex(I0) + acc0_thread_origin;
auto m_local = block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I0];
auto n_local = block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I1];
auto m_global = m_local + m_block_data_idx_on_grid;
auto n_global = n_local + n_block_data_idx_on_grid;
auto global_elem_id_raw = z_random_matrix_offset + m_global * raw_n_padded +
n_global; // unique element global 1d id
auto global_elem_id =
(global_elem_id_raw % M4) * raw_n_padded + (global_elem_id_raw / M4) * M4;
blockwise_dropout.template ApplyDropoutAttnBwdSaveZ<decltype(s_slash_p_thread_buf),
decltype(z_tenor_buffer),
decltype(position_offset),
true>(
s_slash_p_thread_buf, ph, global_elem_id, z_tenor_buffer, raw_n_padded);
z_thread_copy_vgpr_to_global.Run(z_thread_desc_m0_n0_m1_n1_m2_n2_m3_m4_m5_n3,
make_tuple(I0, I0, I0, I0, I0, I0, I0, I0, I0, I0),
z_tenor_buffer,
z_grid_desc_m0_n0_m1_n1_m2_n2_m3_m4_m5_n3,
z_grid_buf);
}
else
{
ignore = z_grid_buf;
auto acc0_thread_idx = Acc0TileIterator::GetIndex(I0) + acc0_thread_origin;
auto m_local = block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I0];
auto n_local = block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I1];
auto m_global = m_local + m_block_data_idx_on_grid;
auto n_global = n_local + n_block_data_idx_on_grid;
auto global_elem_id_raw = z_random_matrix_offset + m_global * raw_n_padded +
n_global; // unique element global 1d id
auto global_elem_id =
(global_elem_id_raw % M4) * raw_n_padded + (global_elem_id_raw / M4) * M4;
blockwise_dropout.template ApplyDropoutAttnBwdSaveZ<decltype(s_slash_p_thread_buf),
decltype(z_tenor_buffer),
decltype(position_offset),
true>(
s_slash_p_thread_buf, ph, global_elem_id, z_tenor_buffer, raw_n_padded);
z_thread_copy_vgpr_to_global.Run(z_thread_desc_m0_n0_m1_n1_m2_n2_m3_m4_m5_n3,
make_tuple(I0, I0, I0, I0, I0, I0, I0, I0, I0, I0),
z_tenor_buffer,
z_grid_desc_m0_n0_m1_n1_m2_n2_m3_m4_m5_n3,
z_grid_buf);
}
else
{
ignore = z_grid_buf;
auto acc0_thread_idx = Acc0TileIterator::GetIndex(I0) + acc0_thread_origin;
auto m_local = block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I0];
auto n_local = block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I1];
auto m_global = m_local + m_block_data_idx_on_grid;
auto n_global = n_local + n_block_data_idx_on_grid;
auto acc0_thread_idx = Acc0TileIterator::GetIndex(I0) + acc0_thread_origin;
auto m_local = block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I0];
auto n_local = block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I1];
auto m_global = m_local + m_block_data_idx_on_grid;
auto n_global = n_local + n_block_data_idx_on_grid;
auto global_elem_id_raw = z_random_matrix_offset + m_global * raw_n_padded +
n_global; // unique element global 1d id
auto global_elem_id_raw = z_random_matrix_offset + m_global * raw_n_padded +
n_global; // unique element global 1d id
auto global_elem_id =
(global_elem_id_raw % M4) * raw_n_padded + (global_elem_id_raw / M4) * M4;
auto global_elem_id =
(global_elem_id_raw % M4) * raw_n_padded + (global_elem_id_raw / M4) * M4;
// P_dropped
blockwise_dropout.template ApplyDropoutAttnBwd<decltype(s_slash_p_thread_buf),
decltype(position_offset),
true>(
s_slash_p_thread_buf, ph, global_elem_id, raw_n_padded);
// P_dropped
blockwise_dropout.template ApplyDropoutAttnBwd<decltype(s_slash_p_thread_buf),
decltype(position_offset),
true>(
s_slash_p_thread_buf, ph, global_elem_id, raw_n_padded);
}
}
block_sync_lds(); // wait for gemm1 LDS read
// dS = P * (dP - Y_dot_dY)
......
include/ck/tensor_operation/gpu/grid/gridwise_batched_mha_bwd_xdl_cshuffle_qloop_b2t_v2.hpp
View file @ 0999070d
......@@ -1154,6 +1154,7 @@ struct GridwiseBatchedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V2
}
template <bool HasMainKBlockLoop,
bool IsDropout,
typename Block2CTileMap,
typename C0MatrixMask,
typename YGradGridDesc_M0_O_M1>
......@@ -1863,55 +1864,56 @@ struct GridwiseBatchedMultiheadAttentionBackward_Qloop_Xdl_CShuffle_V2
constexpr auto position_offset = M3 * M4;
// save z to global
if(p_z_grid)
{
if constexpr(IsDropout){
if(p_z_grid)
{
auto acc0_thread_idx = Acc0TileIterator::GetIndex(I0) + acc0_thread_origin;
auto m_local = block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I0];
auto n_local = block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I1];
auto m_global = m_local + m_block_data_idx_on_grid;
auto n_global = n_local + n_block_data_idx_on_grid;
auto global_elem_id_raw = z_random_matrix_offset + m_global * raw_n_padded +
n_global; // unique element global 1d id
auto global_elem_id =
(global_elem_id_raw % M4) * raw_n_padded + (global_elem_id_raw / M4) * M4;
blockwise_dropout.template ApplyDropoutAttnBwdSaveZ<decltype(s_slash_p_thread_buf),
decltype(z_tenor_buffer),
decltype(position_offset),
true>(
s_slash_p_thread_buf, ph, global_elem_id, z_tenor_buffer, raw_n_padded);
z_thread_copy_vgpr_to_global.Run(z_thread_desc_m0_n0_m1_n1_m2_n2_m3_m4_m5_n3,
make_tuple(I0, I0, I0, I0, I0, I0, I0, I0, I0, I0),
z_tenor_buffer,
z_grid_desc_m0_n0_m1_n1_m2_n2_m3_m4_m5_n3,
z_grid_buf);
}
else
{
ignore = z_grid_buf;
auto acc0_thread_idx = Acc0TileIterator::GetIndex(I0) + acc0_thread_origin;
auto m_local = block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I0];
auto n_local = block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I1];
auto m_global = m_local + m_block_data_idx_on_grid;
auto n_global = n_local + n_block_data_idx_on_grid;
auto global_elem_id_raw = z_random_matrix_offset + m_global * raw_n_padded +
n_global; // unique element global 1d id
auto global_elem_id =
(global_elem_id_raw % M4) * raw_n_padded + (global_elem_id_raw / M4) * M4;
// P_dropped
blockwise_dropout.template ApplyDropoutAttnBwd<decltype(s_slash_p_thread_buf),
decltype(position_offset),
true>(
s_slash_p_thread_buf, ph, global_elem_id, raw_n_padded);
auto acc0_thread_idx = Acc0TileIterator::GetIndex(I0) + acc0_thread_origin;
auto m_local = block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I0];
auto n_local = block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I1];
auto m_global = m_local + m_block_data_idx_on_grid;
auto n_global = n_local + n_block_data_idx_on_grid;
auto global_elem_id_raw = z_random_matrix_offset + m_global * raw_n_padded +
n_global; // unique element global 1d id
auto global_elem_id =
(global_elem_id_raw % M4) * raw_n_padded + (global_elem_id_raw / M4) * M4;
blockwise_dropout.template ApplyDropoutAttnBwdSaveZ<decltype(s_slash_p_thread_buf),
decltype(z_tenor_buffer),
decltype(position_offset),
true>(
s_slash_p_thread_buf, ph, global_elem_id, z_tenor_buffer, raw_n_padded);
z_thread_copy_vgpr_to_global.Run(z_thread_desc_m0_n0_m1_n1_m2_n2_m3_m4_m5_n3,
make_tuple(I0, I0, I0, I0, I0, I0, I0, I0, I0, I0),
z_tenor_buffer,
z_grid_desc_m0_n0_m1_n1_m2_n2_m3_m4_m5_n3,
z_grid_buf);
}
else
{
ignore = z_grid_buf;
auto acc0_thread_idx = Acc0TileIterator::GetIndex(I0) + acc0_thread_origin;
auto m_local = block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I0];
auto n_local = block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I1];
auto m_global = m_local + m_block_data_idx_on_grid;
auto n_global = n_local + n_block_data_idx_on_grid;
auto global_elem_id_raw = z_random_matrix_offset + m_global * raw_n_padded +
n_global; // unique element global 1d id
auto global_elem_id =
(global_elem_id_raw % M4) * raw_n_padded + (global_elem_id_raw / M4) * M4;
// P_dropped
blockwise_dropout.template ApplyDropoutAttnBwd<decltype(s_slash_p_thread_buf),
decltype(position_offset),
true>(
s_slash_p_thread_buf, ph, global_elem_id, raw_n_padded);
}
}
block_sync_lds(); // wait for gemm1 LDS read
// gemm dV
......
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