class_docstr: ResNe(X)t 3D basic stem module. Assume a single pathway.
  Performs spatiotemporal Convolution, BN, and Relu following by a
      spatiotemporal pooling.
code: def _construct_stem(self, dim_in, dim_out):
      self.conv = nn.Conv3d(
          dim_in,
          dim_out,
          self.kernel,
          stride=self.stride,
          padding=self.padding,
          bias=False,
      )
      self.bn = nn.BatchNorm3d(
          dim_out, eps=self.bn_eps, momentum=self.bn_mmt
      )
      self.relu = nn.ReLU(self.inplace_relu)
      if self.maxpool:
          self.pool_layer = nn.MaxPool3d(
              kernel_size=[1, 3, 3], stride=[1, 2, 2], padding=[0, 1, 1]
          )
  
imports: from typing import Sequence
  import torch.nn
  from .r2plus1_util import r2plus1_unit
label_desc: Use image node_id 2 for calling the ResNeXt3DStemSinglePathway obj's underlying member method code with example usage: obj._construct_stem(dim_in, dim_out) without return types