class ConvEncoder(nn.Module):
 """
 Implementation of ConvEncoder with 3*3 and 1*1 convolutions.
 Input: tensor with shape [B, C, H, W]
 Output: tensor with shape [B, C, H, W]
 """
 def __init__(
 self, dim, hidden_dim=64, kernel_size=3, drop_path=0.0, use_layer_scale=True
 ):
 super().__init__()
 self.dwconv = nn.Conv2d(
 dim, dim, kernel_size=kernel_size, padding=kernel_size // 2, groups=dim
 )
 self.norm = nn.BatchNorm2d(dim)
 self.pwconv1 = nn.Conv2d(dim, hidden_dim, kernel_size=1)
 self.act = nn.GELU()
 self.pwconv2 = nn.Conv2d(hidden_dim, dim, kernel_size=1)
 self.drop_path = DropPath(drop_path) if drop_path > 0.0 else nn.Identity()
 self.use_layer_scale = use_layer_scale
 if use_layer_scale:
 self.layer_scale = nn.Parameter(
 torch.ones(dim).unsqueeze(-1).unsqueeze(-1), requires_grad=True
 )
 self.apply(self._init_weights)

 for node in model.graph.nodes:
 if node.op == "get_attr":
 if prefix:
 sub_name = prefix + "--" + node.target
 else:
 sub_name = node.target
 if not hasattr(model, node.target):
 continue
 if "scale" in node.target: #### This condition is not suitable
 tune_cfg["get_attr"][sub_name] = float(getattr(model, node.target))
 elif "zero_point" in node.target:
 tune_cfg["get_attr"][sub_name] = int(getattr(model, node.target))
 else:
 pass

 File "/root/.pyenv/versions/3.11.11/lib/python3.11/site-packages/neural_compressor/utils/utility.py", line 347, in fi
 res = func(*args, **kwargs)
 ^^^^^^^^^^^^^^^^^^^^^
 File "/root/.pyenv/versions/3.11.11/lib/python3.11/site-packages/neural_compressor/adaptor/pytorch.py", line 3658, in quantize
 self._get_scale_zeropoint(q_model._model, q_model.q_config)
 File "/root/.pyenv/versions/3.11.11/lib/python3.11/site-packages/neural_compressor/adaptor/pytorch.py", line 4217, in _get_scale_zeropoint
 self._get_sub_module_scale_zeropoint(model, tune_cfg)
 File "/root/.pyenv/versions/3.11.11/lib/python3.11/site-packages/neural_compressor/adaptor/pytorch.py", line 4199, in _get_sub_module_scale_zeropoint
 self._get_sub_module_scale_zeropoint(module, tune_cfg, op_name)
 File "/root/.pyenv/versions/3.11.11/lib/python3.11/site-packages/neural_compressor/adaptor/pytorch.py", line 4199, in _get_sub_module_scale_zeropoint
 self._get_sub_module_scale_zeropoint(module, tune_cfg, op_name)
 File "/root/.pyenv/versions/3.11.11/lib/python3.11/site-packages/neural_compressor/adaptor/pytorch.py", line 4199, in _get_sub_module_scale_zeropoint
 self._get_sub_module_scale_zeropoint(module, tune_cfg, op_name)
 File "/root/.pyenv/versions/3.11.11/lib/python3.11/site-packages/neural_compressor/adaptor/pytorch.py", line 4197, in _get_sub_module_scale_zeropoint
 self._get_module_scale_zeropoint(module, tune_cfg, op_name)
 File "/root/.pyenv/versions/3.11.11/lib/python3.11/site-packages/neural_compressor/adaptor/pytorch.py", line 4175, in _get_module_scale_zeropoint
 tune_cfg["get_attr"][sub_name] = float(getattr(model, node.target))
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: only one element tensors can be converted to Python scalars

feature_extractor.patch_embed--0_input_scale_0 tensor(0.0355)
feature_extractor.network.0.0--dwconv_input_scale_0 tensor(0.0338)
feature_extractor.network.0.0--pwconv2_input_scale_0 tensor(0.2263)
feature_extractor.network.0.0--layer_scale Parameter containing:
tensor([[[ 0.0336]],
 [[ 0.0153]],
 [[ 0.0214]],
 [[ 0.0068]],
 [[ 0.0229]],
 [[ 0.0136]],
 [[ 0.0491]],
 [[ 0.0202]],
 [[ 0.0420]],
 [[ 0.0495]],
 [[ 0.0060]],
 [[ 0.0225]],
 [[ 0.0311]],
 [[ 0.0303]],
 [[ 0.0556]],
 [[ 0.0290]],
 [[ 0.0222]],
 [[ 0.0153]],
 [[ 0.0332]],
 [[ 0.0667]],
 [[ 0.0168]],
 [[ 0.0416]],
 [[ 0.0258]],
 [[ 0.0200]],
 [[ 0.0259]],
 [[ 0.0044]],
 [[ 0.0514]],
 [[ 0.0190]],
 [[ 0.0545]],
 [[ 0.0119]],
 [[ 0.0220]],
 [[ 0.0481]],
 [[ 0.0115]],
 [[ 0.0707]],
 [[ 0.0299]],
 [[ 0.0105]],
 [[ 0.0266]],
 [[ 0.0156]],
 [[ 0.0380]],
 [[ 0.0160]],
 [[ 0.0521]],
 [[ 0.0094]],
 [[-0.0133]],
 [[ 0.0585]],
 [[ 0.0216]],
 [[ 0.0102]],
 [[ 0.0297]],
 [[ 0.0104]]], requires_grad=True)

if "scale" in node.target and "layer_scale" not in node.target: