Stage C: add validation harness with real softmax reference (C1)
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@@ -381,3 +381,41 @@ class FmhaV3Softmax:
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c_pipe.producer_tail()
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tmem.relinquish_alloc_permit()
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tmem.free(tmem_ptr)
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def test():
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"""C1 validation harness: real softmax reference."""
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import math
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torch.manual_seed(42)
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for n in [128, 256, 384]:
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m, hd = 128, HEAD_DIM
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q = torch.randn(m, hd, 1, dtype=torch.bfloat16, device='cuda')
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k = torch.randn(n, hd, 1, dtype=torch.bfloat16, device='cuda')
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v = torch.randn(n, hd, dtype=torch.bfloat16, device='cuda')
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v_kernel = v.unsqueeze(-1)
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c = torch.zeros(m, hd, 1, dtype=torch.bfloat16, device='cuda')
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# Real softmax reference
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qf = q[:,:,0].float()
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kf = k[:,:,0].float()
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attn = qf @ kf.T / math.sqrt(hd)
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ref = torch.softmax(attn, dim=-1) @ v.float()
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mQ = ct.from_dlpack(q).mark_layout_dynamic(leading_dim=ct.get_leading_dim(q))
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mK = ct.from_dlpack(k).mark_layout_dynamic(leading_dim=ct.get_leading_dim(k))
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mV = ct.from_dlpack(v_kernel).mark_layout_dynamic(leading_dim=ct.get_leading_dim(v_kernel))
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mC = ct.from_dlpack(c).mark_layout_dynamic(leading_dim=ct.get_leading_dim(c))
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stream = cuda.CUstream(torch.cuda.current_stream().cuda_stream)
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kernel = FmhaV3Softmax()
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print(f'n={n}: Compiling...', flush=True)
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compiled = cute.compile(kernel, mQ, mK, mV, mC, stream)
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print(f'n={n}: tmem: s0={kernel.tmem_s0_offset} p0={kernel.tmem_p0_offset} o0={kernel.tmem_o0_offset} alloc={kernel.num_tmem_alloc_cols}', flush=True)
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print(f'n={n}: Running...', flush=True)
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compiled(mQ, mK, mV, mC, stream)
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torch.cuda.synchronize()
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out = c[:,:,0].float()
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cos = torch.nn.functional.cosine_similarity(out.flatten().unsqueeze(0), ref.flatten().unsqueeze(0)).item()
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max_err = (out - ref).abs().max().item()
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print(f'FMHA softmax n={n}: cosine {cos:.6f} max_err {max_err:.6f} {"PASS" if cos >= 0.999 else "FAIL"}', flush=True)
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if cos < 0.999:
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print(f' out[0,:4]={out[0,:4].tolist()} ref[0,:4]={ref[0,:4].tolist()}')
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if __name__ == '__main__':
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test()
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