diff --git a/dsv4/kernels/attention/fmha.py b/dsv4/kernels/attention/fmha.py index a2ff1b4e..f42693d4 100644 --- a/dsv4/kernels/attention/fmha.py +++ b/dsv4/kernels/attention/fmha.py @@ -16,7 +16,7 @@ import math class FmhaKernel: - def __init__(self, head_dim=64, s_k=128, scale_softmax=None, use_smem_p=None, normalize=True, num_query_heads=1, batch_size=1): + def __init__(self, head_dim=64, s_k=128, scale_softmax=None, use_smem_p=None, normalize=True): self.head_dim = head_dim self.s_k = s_k self.n_kv_tiles = s_k // 128 @@ -43,12 +43,6 @@ class FmhaKernel: self.num_c_stage = 1 if head_dim > 256 else 2 # Reduce SMEM at hd=512 self.scale_softmax = scale_softmax if scale_softmax is not None else 1.0 / math.sqrt(self.head_dim) self.scale_softmax_log2 = self.scale_softmax * math.log2(math.e) - self.num_query_heads = num_query_heads - self.batch_size = batch_size - # D2: Multi-CTA grid. Each CTA handles one (head, batch) pair. - # Grid: (1, num_query_heads * batch_size, 1) - # Total CTAs = num_query_heads * batch_size - self.num_ctas = num_query_heads * batch_size def _setup(self, qk_mma, pv_mma): qk_ik = cute.size(qk_mma.shape_mnk, mode=[2]) @@ -135,7 +129,7 @@ class FmhaKernel: # CuTeDSL doesn't support None parameters in @cute.kernel. if const_expr(lse is None): lse = cute.make_tensor(c.iterator, cute.make_layout((1,), stride=(0,))) - self._kernel(qk_mma,pv_mma,tma_q,mQ,tma_k,mK,tma_v,mV,tma_c,mC,self.cluster_layout_vmnk,self.q_smem_s,self.k_smem_s,self.v_smem_s,self.p_tmem_s,self.p_smem_s,self.c_smem_s,self.epi_tile,lse).launch(grid=(1,self.num_ctas,1),block=[self.threads_per_cta,1,1],stream=stream) + self._kernel(qk_mma,pv_mma,tma_q,mQ,tma_k,mK,tma_v,mV,tma_c,mC,self.cluster_layout_vmnk,self.q_smem_s,self.k_smem_s,self.v_smem_s,self.p_tmem_s,self.p_smem_s,self.c_smem_s,self.epi_tile,lse).launch(grid=(1,1,1),block=[self.threads_per_cta,1,1],stream=stream) @cute.kernel def _kernel(self, qk_mma, pv_mma, tma_q, mQ, tma_k, mK, tma_v, mV, tma_c, mC, cl_vmnk, q_smem_s, k_smem_s, v_smem_s, p_tmem_s, p_smem_s, c_smem_s, epi_tile, mLSE):