code: def __init__(
      self,
      stage_idx,
      dim_in,
      dim_out,
      dim_inner,
      temporal_kernel_basis,
      temporal_conv_1x1,
      temporal_stride,
      spatial_stride,
      num_blocks,
      num_groups,
  ):
      super(ResStageBase, self).__init__()
  
      assert (
          len(
              {
                  len(dim_in),
                  len(dim_out),
                  len(temporal_kernel_basis),
                  len(temporal_conv_1x1),
                  len(temporal_stride),
                  len(spatial_stride),
                  len(num_blocks),
                  len(dim_inner),
                  len(num_groups),
              }
          )
          == 1
      )
  
      self.stage_idx = stage_idx
      self.num_blocks = num_blocks
      self.num_pathways = len(self.num_blocks)
  
      self.temporal_kernel_sizes = [
          (temporal_kernel_basis[i] * num_blocks[i])[: num_blocks[i]]
          for i in range(len(temporal_kernel_basis))
      ]
  
file_path: ClassyVision/classy_vision/models/resnext3d_stage.py
imports: from collections import OrderedDict
  import torch.nn
  from .resnext3d_block import ResBlock
label_desc: Use image node_id 1 to create a new ResStageBase object from inherited base classes: nn with example: obj = ResStageBase(stage_idx, dim_in, dim_out, dim_inner, temporal_kernel_basis, temporal_conv_1x1, temporal_stride, spatial_stride, num_blocks, num_groups)