"""Minimal test: CUTLASS reference FMHA, n=256 only."""
import sys
sys.path.insert(0, '/root/cutlass/examples/python/CuTeDSL')

import torch, math, cutlass, cutlass.cute as cute, cuda.bindings.driver as cuda
from cute.blackwell.kernel.attention.fmha.fmha import BlackwellFusedMultiHeadAttentionForward, FMHA_OperandMajorMode

HEAD_DIM = 64
n = 256
torch.manual_seed(42)
m = 128; batch = 1
q = torch.randn(batch, 1, m, HEAD_DIM, dtype=torch.bfloat16, device='cuda')
k = torch.randn(batch, 1, n, HEAD_DIM, dtype=torch.bfloat16, device='cuda')
v = torch.randn(batch, 1, n, HEAD_DIM, dtype=torch.bfloat16, device='cuda')
c = torch.zeros(batch, 1, m, HEAD_DIM, dtype=torch.bfloat16, device='cuda')

qf = q[0,0].float(); kf = k[0,0].float(); vf = v[0,0].float()
scale = 1.0/math.sqrt(HEAD_DIM)
ref = torch.softmax(qf @ kf.T * scale, dim=-1) @ vf

stream = cuda.CUstream(torch.cuda.current_stream().cuda_stream)
kernel = BlackwellFusedMultiHeadAttentionForward(
    q_major_mode=FMHA_OperandMajorMode.K, k_major_mode=FMHA_OperandMajorMode.K,
    v_major_mode=FMHA_OperandMajorMode.MN, o_major_mode=FMHA_OperandMajorMode.K,
    q_head_dim=HEAD_DIM, kv_head_dim=HEAD_DIM, num_q_heads=1, num_kv_heads=1,
    q_dtype=cutlass.BFloat16, k_dtype=cutlass.BFloat16, v_dtype=cutlass.BFloat16,
    o_dtype=cutlass.BFloat16, acc_dtype=cutlass.Float32, epilogue_dtype=cutlass.Float32,
    use_2cta_instrs=False,
)
print(f'n={n}: Compiling reference FMHA...', flush=True)
try:
    kernel.run(q, k, v, c, stream)
    torch.cuda.synchronize()
    out = c[0,0].float()
    cos = torch.nn.functional.cosine_similarity(out.flatten().unsqueeze(0), ref.flatten().unsqueeze(0)).item()
    print(f'Reference FMHA n={n} (2 tiles): cos {cos:.6f}  {"PASS" if cos >= 0.99 else "FAIL"}')
    if cos < 0.99:
        print(f'  out[0,:4]={out[0,:4].tolist()}')
        print(f'  ref[0,:4]={ref[0,:4].tolist()}')
except Exception as e:
    import traceback; traceback.print_exc()