class_docstr: ConvBlock3D
class_docstr_tok: ["ConvBlock3D"]
code: def _setup_activation(self, input_shape: Tuple[float, ...]) -> None:
      assert self.dim_pad > 0
      self.activation = torch.zeros(
          *input_shape[:2],  # type: ignore
          self.dim_pad,
          *input_shape[3:],
      )
  
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 6 for calling the ConvBlock3D obj's underlying member method code with example usage: obj._setup_activation(input_shape) without return types