[CK Tile] Fix FMHA LSE calculation and potential division by zero

This commit addresses numerical stability issues in the BlockFmhaPipelineQRKSVS pipeline when bias has -inf masking values:
1. Explicitly handle the case where the accumulated exponential sum (l) is zero. In this case, the LSE is now correctly set to negative infinity, preventing log(0) errors.
2. Extend the zero-check protection in the normalization step to cover the ELEMENTWISE_BIAS case, preventing potential division by zero.
This commit is contained in:
Jeff Huang
2025-11-28 11:30:10 +08:00
committed by Ye Wang
parent 1aa93ef551
commit 8537a356a3

View File

@@ -655,26 +655,35 @@ struct BlockFmhaPipelineQRKSVS
constexpr auto lse_spans = decltype(lse)::get_distributed_spans();
sweep_tile_span(lse_spans[number<0>{}], [&, m_ = m, l_ = l](auto idx0) {
constexpr auto i_idx = make_tuple(idx0);
#if CK_TILE_FMHA_FWD_FAST_EXP2
if constexpr(BiasEnum == BlockAttentionBiasEnum::ELEMENTWISE_BIAS ||
BiasEnum == BlockAttentionBiasEnum::ALIBI)
// In the masked biased case, the entire row can be suppressed and the accumulated
// softmax denominator becomes zero; treat it as log(0) = -inf to avoid NaNs.
if(l_[i_idx] == 0.0f)
{
lse(i_idx) = m_[i_idx] / C_LOG2E + log(l_[i_idx]);
lse(i_idx) = -numeric<LSEDataType>::infinity();
}
else
{
if constexpr(kHasLogitsSoftCap)
#if CK_TILE_FMHA_FWD_FAST_EXP2
if constexpr(BiasEnum == BlockAttentionBiasEnum::ELEMENTWISE_BIAS ||
BiasEnum == BlockAttentionBiasEnum::ALIBI)
{
lse(i_idx) = m_[i_idx] / C_LOG2E + log(l_[i_idx]);
}
else
{
lse(i_idx) = m_[i_idx] * scale_s / C_LOG2E + log(l_[i_idx]);
if constexpr(kHasLogitsSoftCap)
{
lse(i_idx) = m_[i_idx] / C_LOG2E + log(l_[i_idx]);
}
else
{
lse(i_idx) = m_[i_idx] * scale_s / C_LOG2E + log(l_[i_idx]);
}
}
}
#else
lse(i_idx) = m_[i_idx] + log(l_[i_idx]);
lse(i_idx) = m_[i_idx] + log(l_[i_idx]);
#endif
}
});
store_tile(lse_dram_window_tmp, tile_elementwise_in(lse_element_func, lse));
@@ -686,7 +695,10 @@ struct BlockFmhaPipelineQRKSVS
sweep_tile_span(o_spans[number<0>{}], [&](auto idx0) {
constexpr auto i_idx = make_tuple(idx0);
const auto tmp = [&]() {
if constexpr(FmhaMask::IsMasking)
// When bias carries -inf masks the denominator can be zero; guard the normalization
// so we do not divide by zero after a fully masked row.
if constexpr(FmhaMask::IsMasking ||
BiasEnum == BlockAttentionBiasEnum::ELEMENTWISE_BIAS)
{
return l[i_idx] == 0.f ? 0.f : 1 / l[i_idx];
}