"""D1: Test SMEM-P at hd=128 with debug prints.""" import torch, math import cutlass.cute as cute import cutlass.torch as ct import cuda.bindings.driver as cuda from dsv4.kernels.attention.fmha import FmhaKernel def test_smem_p(hd, n_kv=128): m = 128 torch.manual_seed(42) q = torch.randn(m, hd, 1, dtype=torch.bfloat16, device='cuda') k = torch.randn(n_kv, hd, 1, dtype=torch.bfloat16, device='cuda') v = torch.randn(n_kv, hd, dtype=torch.bfloat16, device='cuda') qf = q[:, :, 0].float() kf = k[:, :, 0].float() scale = 1.0 / math.sqrt(hd) attn_max = (qf @ kf.T * scale).max(dim=-1, keepdim=True)[0] attn_exp = torch.exp(qf @ kf.T * scale - attn_max) attn_sum = attn_exp.sum(dim=-1, keepdim=True) ref_unnorm = attn_exp @ v.float() lse_tensor = torch.zeros(m, 1, 1, dtype=torch.float32, device='cuda') kernel = FmhaKernel(head_dim=hd, s_k=n_kv, use_smem_p=True) pv_n_tile = kernel.pv_n_tile stream = cuda.CUstream(torch.cuda.current_stream().cuda_stream) v_tile = v[:, 0:pv_n_tile].contiguous().unsqueeze(-1) c_tile = torch.zeros(m, pv_n_tile, 1, dtype=torch.bfloat16, device='cuda') mQ = ct.from_dlpack(q).mark_layout_dynamic(leading_dim=ct.get_leading_dim(q)) mK = ct.from_dlpack(k).mark_layout_dynamic(leading_dim=ct.get_leading_dim(k)) mV = ct.from_dlpack(v_tile).mark_layout_dynamic(leading_dim=ct.get_leading_dim(v_tile)) mC = ct.from_dlpack(c_tile).mark_layout_dynamic(leading_dim=ct.get_leading_dim(c_tile)) mLSE = ct.from_dlpack(lse_tensor).mark_layout_dynamic(leading_dim=ct.get_leading_dim(lse_tensor)) print(f'hd={hd} SMEM-P: Compiling...', flush=True) compiled = cute.compile(kernel, mQ, mK, mV, mC, stream, mLSE) compiled(mQ, mK, mV, mC, stream, mLSE) torch.cuda.synchronize() out = c_tile[:, :, 0].float() cos = torch.nn.functional.cosine_similarity(out.flatten().unsqueeze(0), ref_unnorm.flatten().unsqueeze(0)).item() print(f'hd={hd} SMEM-P: cos={cos:.6f} {"PASS" if cos >= 0.99 else "FAIL"}') return cos if __name__ == '__main__': test_smem_p(128)