SNNWrapper(
  (model): VisionTransformer(
    (patch_embed): PatchEmbed(
      (proj): save_module_inout(
        (m): Sequential(
          (0): LLConv2d(
            (conv): QuanConv2d(
              3, 384, kernel_size=(16, 16), stride=(16, 16)
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.025305096060037613)
            )
          )
          (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.15667758882045746)
        )
      )
      (norm): Identity()
    )
    (pos_drop): Dropout(p=0.0, inplace=False)
    (blocks): Sequential(
      (0): Block(
        (norm1): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.15645596385002136)
          )
        )
        (attn): SAttention(
          (qkv): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=1152, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.024404320865869522)
            )
          )
          (q_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.474159836769104)
          (k_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.442491739988327)
          (v_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.23857834935188293)
          (attn_drop): Dropout(p=0.0, inplace=False)
          (attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=2.0540571212768555)
          (attn_softmax_IF): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.0042631798423826694)
          (after_attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.050137244164943695)
          (proj): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=384, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.02799963392317295)
            )
          )
          (proj_drop): Dropout(p=0.0, inplace=False)
          (proj_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.05917580425739288)
          (Ssoftmax): spiking_softmax()
          (multi): AttentionMulti()
          (multi1): AttentionMulti1()
        )
        (drop_path): Identity()
        (norm2): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.3849744200706482)
          )
        )
        (mlp): Mlp(
          (fc1): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=384, out_features=1536, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.02344435267150402)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.6427932381629944)
            )
          )
          (act): Identity()
          (drop1): Dropout(p=0.0, inplace=False)
          (fc2): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=1536, out_features=384, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.011265595443546772)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.29549145698547363)
            )
          )
          (drop2): Dropout(p=0.0, inplace=False)
        )
        (addition1): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.16290001571178436)
          )
        )
        (addition2): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.2983298599720001)
          )
        )
      )
      (1): Block(
        (norm1): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.21835462749004364)
          )
        )
        (attn): SAttention(
          (qkv): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=1152, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.03216549754142761)
            )
          )
          (q_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.5228611826896667)
          (k_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.49831122159957886)
          (v_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.4515444040298462)
          (attn_drop): Dropout(p=0.0, inplace=False)
          (attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=2.009047269821167)
          (attn_softmax_IF): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.010984851978719234)
          (after_attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.10922417044639587)
          (proj): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=384, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.018830405548214912)
            )
          )
          (proj_drop): Dropout(p=0.0, inplace=False)
          (proj_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.13141082227230072)
          (Ssoftmax): spiking_softmax()
          (multi): AttentionMulti()
          (multi1): AttentionMulti1()
        )
        (drop_path): DropPath()
        (norm2): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.25774261355400085)
          )
        )
        (mlp): Mlp(
          (fc1): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=384, out_features=1536, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.020486975088715553)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.35453489422798157)
            )
          )
          (act): Identity()
          (drop1): Dropout(p=0.0, inplace=False)
          (fc2): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=1536, out_features=384, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.01627502776682377)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.20709264278411865)
            )
          )
          (drop2): Dropout(p=0.0, inplace=False)
        )
        (addition1): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.27861443161964417)
          )
        )
        (addition2): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.2785472571849823)
          )
        )
      )
      (2): Block(
        (norm1): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.2807318866252899)
          )
        )
        (attn): SAttention(
          (qkv): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=1152, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.023782555013895035)
            )
          )
          (q_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.5208654999732971)
          (k_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.4813345670700073)
          (v_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.47070905566215515)
          (attn_drop): Dropout(p=0.0, inplace=False)
          (attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=1.3396556377410889)
          (attn_softmax_IF): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.024587981402873993)
          (after_attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.14195336401462555)
          (proj): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=384, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.017246754840016365)
            )
          )
          (proj_drop): Dropout(p=0.0, inplace=False)
          (proj_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.14861644804477692)
          (Ssoftmax): spiking_softmax()
          (multi): AttentionMulti()
          (multi1): AttentionMulti1()
        )
        (drop_path): DropPath()
        (norm2): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.28619489073753357)
          )
        )
        (mlp): Mlp(
          (fc1): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=384, out_features=1536, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.017810281366109848)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.3807090222835541)
            )
          )
          (act): Identity()
          (drop1): Dropout(p=0.0, inplace=False)
          (fc2): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=1536, out_features=384, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.016555435955524445)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.18985188007354736)
            )
          )
          (drop2): Dropout(p=0.0, inplace=False)
        )
        (addition1): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.30047154426574707)
          )
        )
        (addition2): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.30392715334892273)
          )
        )
      )
      (3): Block(
        (norm1): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.3016557991504669)
          )
        )
        (attn): SAttention(
          (qkv): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=1152, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.01792910508811474)
            )
          )
          (q_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.4808667004108429)
          (k_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.46265166997909546)
          (v_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.5114502906799316)
          (attn_drop): Dropout(p=0.0, inplace=False)
          (attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.9453734755516052)
          (attn_softmax_IF): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.01132669672369957)
          (after_attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.14330759644508362)
          (proj): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=384, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.017501795664429665)
            )
          )
          (proj_drop): Dropout(p=0.0, inplace=False)
          (proj_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.1855776607990265)
          (Ssoftmax): spiking_softmax()
          (multi): AttentionMulti()
          (multi1): AttentionMulti1()
        )
        (drop_path): DropPath()
        (norm2): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.29478320479393005)
          )
        )
        (mlp): Mlp(
          (fc1): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=384, out_features=1536, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.018179956823587418)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.3865627348423004)
            )
          )
          (act): Identity()
          (drop1): Dropout(p=0.0, inplace=False)
          (fc2): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=1536, out_features=384, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.016108784824609756)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.1914384365081787)
            )
          )
          (drop2): Dropout(p=0.0, inplace=False)
        )
        (addition1): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.3272383213043213)
          )
        )
        (addition2): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.30542293190956116)
          )
        )
      )
      (4): Block(
        (norm1): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.32519128918647766)
          )
        )
        (attn): SAttention(
          (qkv): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=1152, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.019642286002635956)
            )
          )
          (q_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.4642670750617981)
          (k_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.4547576904296875)
          (v_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.5011751651763916)
          (attn_drop): Dropout(p=0.0, inplace=False)
          (attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.7508196830749512)
          (attn_softmax_IF): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.01619039848446846)
          (after_attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.16195720434188843)
          (proj): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=384, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.016353530809283257)
            )
          )
          (proj_drop): Dropout(p=0.0, inplace=False)
          (proj_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.1833721548318863)
          (Ssoftmax): spiking_softmax()
          (multi): AttentionMulti()
          (multi1): AttentionMulti1()
        )
        (drop_path): DropPath()
        (norm2): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.2878575026988983)
          )
        )
        (mlp): Mlp(
          (fc1): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=384, out_features=1536, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.017213577404618263)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.3993522524833679)
            )
          )
          (act): Identity()
          (drop1): Dropout(p=0.0, inplace=False)
          (fc2): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=1536, out_features=384, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.0164443738758564)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.19180674850940704)
            )
          )
          (drop2): Dropout(p=0.0, inplace=False)
        )
        (addition1): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.3332865238189697)
          )
        )
        (addition2): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.3156069219112396)
          )
        )
      )
      (5): Block(
        (norm1): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.2990875840187073)
          )
        )
        (attn): SAttention(
          (qkv): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=1152, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.017228038981556892)
            )
          )
          (q_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.46348610520362854)
          (k_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.4409554898738861)
          (v_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.484670490026474)
          (attn_drop): Dropout(p=0.0, inplace=False)
          (attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.6679416298866272)
          (attn_softmax_IF): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.01295850332826376)
          (after_attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.15587376058101654)
          (proj): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=384, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.015992233529686928)
            )
          )
          (proj_drop): Dropout(p=0.0, inplace=False)
          (proj_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.17274357378482819)
          (Ssoftmax): spiking_softmax()
          (multi): AttentionMulti()
          (multi1): AttentionMulti1()
        )
        (drop_path): DropPath()
        (norm2): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.30515575408935547)
          )
        )
        (mlp): Mlp(
          (fc1): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=384, out_features=1536, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.017113419249653816)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.4464282989501953)
            )
          )
          (act): Identity()
          (drop1): Dropout(p=0.0, inplace=False)
          (fc2): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=1536, out_features=384, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.016238421201705933)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.19351473450660706)
            )
          )
          (drop2): Dropout(p=0.0, inplace=False)
        )
        (addition1): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.34283220767974854)
          )
        )
        (addition2): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.3476502299308777)
          )
        )
      )
      (6): Block(
        (norm1): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.3143277168273926)
          )
        )
        (attn): SAttention(
          (qkv): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=1152, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.017791640013456345)
            )
          )
          (q_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.4765688478946686)
          (k_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.4472537338733673)
          (v_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.5458303093910217)
          (attn_drop): Dropout(p=0.0, inplace=False)
          (attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.7722600102424622)
          (attn_softmax_IF): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.012629646807909012)
          (after_attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.1705537587404251)
          (proj): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=384, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.01735755056142807)
            )
          )
          (proj_drop): Dropout(p=0.0, inplace=False)
          (proj_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.22012630105018616)
          (Ssoftmax): spiking_softmax()
          (multi): AttentionMulti()
          (multi1): AttentionMulti1()
        )
        (drop_path): DropPath()
        (norm2): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.3495614528656006)
          )
        )
        (mlp): Mlp(
          (fc1): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=384, out_features=1536, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.01850946806371212)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.5743505358695984)
            )
          )
          (act): Identity()
          (drop1): Dropout(p=0.0, inplace=False)
          (fc2): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=1536, out_features=384, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.019224368035793304)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.25915539264678955)
            )
          )
          (drop2): Dropout(p=0.0, inplace=False)
        )
        (addition1): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.4195225238800049)
          )
        )
        (addition2): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.45861974358558655)
          )
        )
      )
      (7): Block(
        (norm1): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.3001748323440552)
          )
        )
        (attn): SAttention(
          (qkv): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=1152, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.0185929574072361)
            )
          )
          (q_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.48491379618644714)
          (k_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.47693488001823425)
          (v_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.549017071723938)
          (attn_drop): Dropout(p=0.0, inplace=False)
          (attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.8592156767845154)
          (attn_softmax_IF): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.014251191169023514)
          (after_attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.19911609590053558)
          (proj): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=384, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.01872020587325096)
            )
          )
          (proj_drop): Dropout(p=0.0, inplace=False)
          (proj_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.2604525685310364)
          (Ssoftmax): spiking_softmax()
          (multi): AttentionMulti()
          (multi1): AttentionMulti1()
        )
        (drop_path): DropPath()
        (norm2): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.43807733058929443)
          )
        )
        (mlp): Mlp(
          (fc1): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=384, out_features=1536, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.02178165502846241)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.8488224744796753)
            )
          )
          (act): Identity()
          (drop1): Dropout(p=0.0, inplace=False)
          (fc2): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=1536, out_features=384, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.022806871682405472)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.35374099016189575)
            )
          )
          (drop2): Dropout(p=0.0, inplace=False)
        )
        (addition1): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.5388374328613281)
          )
        )
        (addition2): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.6315375566482544)
          )
        )
      )
      (8): Block(
        (norm1): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.2586710751056671)
          )
        )
        (attn): SAttention(
          (qkv): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=1152, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.021189190447330475)
            )
          )
          (q_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.4714939296245575)
          (k_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.493221253156662)
          (v_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.5643364191055298)
          (attn_drop): Dropout(p=0.0, inplace=False)
          (attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.8630113005638123)
          (attn_softmax_IF): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.012573694810271263)
          (after_attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.21653205156326294)
          (proj): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=384, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.02292521484196186)
            )
          )
          (proj_drop): Dropout(p=0.0, inplace=False)
          (proj_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.30853548645973206)
          (Ssoftmax): spiking_softmax()
          (multi): AttentionMulti()
          (multi1): AttentionMulti1()
        )
        (drop_path): DropPath()
        (norm2): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.9033029079437256)
          )
        )
        (mlp): Mlp(
          (fc1): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=384, out_features=1536, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.027214685454964638)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=2.0269696712493896)
            )
          )
          (act): Identity()
          (drop1): Dropout(p=0.0, inplace=False)
          (fc2): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=1536, out_features=384, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.02773165889084339)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.49609753489494324)
            )
          )
          (drop2): Dropout(p=0.0, inplace=False)
        )
        (addition1): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.7161394953727722)
          )
        )
        (addition2): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.8399077653884888)
          )
        )
      )
      (9): Block(
        (norm1): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.21777956187725067)
          )
        )
        (attn): SAttention(
          (qkv): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=1152, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.02911793813109398)
            )
          )
          (q_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.4516143798828125)
          (k_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.575655996799469)
          (v_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.6442452073097229)
          (attn_drop): Dropout(p=0.0, inplace=False)
          (attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.778500497341156)
          (attn_softmax_IF): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.010727607645094395)
          (after_attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.24904119968414307)
          (proj): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=384, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.03350652754306793)
            )
          )
          (proj_drop): Dropout(p=0.0, inplace=False)
          (proj_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.5194981694221497)
          (Ssoftmax): spiking_softmax()
          (multi): AttentionMulti()
          (multi1): AttentionMulti1()
        )
        (drop_path): DropPath()
        (norm2): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=1.428245186805725)
          )
        )
        (mlp): Mlp(
          (fc1): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=384, out_features=1536, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.0373680479824543)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=4.144067287445068)
            )
          )
          (act): Identity()
          (drop1): Dropout(p=0.0, inplace=False)
          (fc2): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=1536, out_features=384, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.04169498011469841)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.8362968564033508)
            )
          )
          (drop2): Dropout(p=0.0, inplace=False)
        )
        (addition1): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=1.0315347909927368)
          )
        )
        (addition2): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=1.1786693334579468)
          )
        )
      )
      (10): Block(
        (norm1): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.16312237083911896)
          )
        )
        (attn): SAttention(
          (qkv): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=1152, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.046822164207696915)
            )
          )
          (q_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.4125945568084717)
          (k_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.5589931607246399)
          (v_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.841540515422821)
          (attn_drop): Dropout(p=0.0, inplace=False)
          (attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.7531548738479614)
          (attn_softmax_IF): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.007715407758951187)
          (after_attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.31620335578918457)
          (proj): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=384, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.06014649569988251)
            )
          )
          (proj_drop): Dropout(p=0.0, inplace=False)
          (proj_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=1.1672593355178833)
          (Ssoftmax): spiking_softmax()
          (multi): AttentionMulti()
          (multi1): AttentionMulti1()
        )
        (drop_path): DropPath()
        (norm2): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=3.5136351585388184)
          )
        )
        (mlp): Mlp(
          (fc1): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=384, out_features=1536, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.05244287848472595)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=12.93521499633789)
            )
          )
          (act): Identity()
          (drop1): Dropout(p=0.0, inplace=False)
          (fc2): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=1536, out_features=384, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.05251264572143555)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=2.4582149982452393)
            )
          )
          (drop2): Dropout(p=0.0, inplace=False)
        )
        (addition1): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=1.8265680074691772)
          )
        )
        (addition2): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=1.9670727252960205)
          )
        )
      )
      (11): Block(
        (norm1): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.09470207244157791)
          )
        )
        (attn): SAttention(
          (qkv): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=1152, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.07745865732431412)
            )
          )
          (q_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.31094878911972046)
          (k_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.42446956038475037)
          (v_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=1.1014759540557861)
          (attn_drop): Dropout(p=0.0, inplace=False)
          (attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.46543946862220764)
          (attn_softmax_IF): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=0.005158567801117897)
          (after_attn_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.3532934784889221)
          (proj): LLLinear(
            (linear): QuanLinear(
              in_features=384, out_features=384, bias=True
              (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.10939797013998032)
            )
          )
          (proj_drop): Dropout(p=0.0, inplace=False)
          (proj_IF): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=2.5630290508270264)
          (Ssoftmax): spiking_softmax()
          (multi): AttentionMulti()
          (multi1): AttentionMulti1()
        )
        (drop_path): DropPath()
        (norm2): save_module_inout(
          (m): Sequential(
            (0): Spiking_LayerNorm(
              (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
            )
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.17150342464447021)
          )
        )
        (mlp): Mlp(
          (fc1): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=384, out_features=1536, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.06351862102746964)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=False, pos_max=6.0, neg_min=0.0, q_threshold=1.2497397661209106)
            )
          )
          (act): Identity()
          (drop1): Dropout(p=0.0, inplace=False)
          (fc2): save_module_inout(
            (m): Sequential(
              (0): LLLinear(
                (linear): QuanLinear(
                  in_features=1536, out_features=384, bias=True
                  (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.060112059116363525)
                )
              )
              (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.9357426166534424)
            )
          )
          (drop2): Dropout(p=0.0, inplace=False)
        )
        (addition1): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=3.9341444969177246)
          )
        )
        (addition2): save_module_inout(
          (m): Sequential(
            (0): Addition()
            (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=3.81054425239563)
          )
        )
      )
    )
    (norm): save_module_inout(
      (m): Sequential(
        (0): Spiking_LayerNorm(
          (layernorm): LayerNorm((384,), eps=1e-05, elementwise_affine=True)
        )
        (1): ST-BIFNeuron(level=14, sym=True, pos_max=6.0, neg_min=-7.0, q_threshold=0.0772123858332634)
      )
    )
    (pre_logits): Identity()
    (head): LLLinear(
      (linear): QuanLinear(
        in_features=384, out_features=1000, bias=True
        (quan_w_fn): MyQuan(level=16, sym=True, pos_max=7.0, neg_min=-8.0, s=0.03369053825736046)
      )
    )
  )
)