class_docstr: SqueezeExcitation
class_docstr_tok: ["SqueezeExcitation"]
code: def forward(self, input_tensor: Tensor) -> Tensor:
      scale = self._scale(input_tensor)
      return scale * input_tensor
  
imports: from typing import Any, Callable, Optional, Tuple, Union
  from einops import rearrange
  import torch
  from torch.nn.modules.utils import _triple
  import torch.nn.functional
  from torch import nn, Tensor
  from towhee.models.utils.general_utils import make_divisible
  from towhee.models.utils.causal_module import CausalModule
  from towhee.models.layers.activations import HardSigmoid
  from towhee.models.layers.conv_bn_activation import Conv2dBNActivation, Conv3DBNActivation
  from towhee.models.layers.padding_functions import same_padding
  from towhee.models.layers.tf_avgpool3d import TfAvgPool3D
  from towhee.models.layers.temporal_cg_avgpool3d import TemporalCGAvgPool3D
label_desc: Use image node_id 3 for calling the SqueezeExcitation obj's underlying member method code with example usage: obj.forward(input_tensor) and returns: unknown