class_docstr: SlowFast networks (SlowFast) from
  `"SlowFast Networks for Video Recognition"
  <https://arxiv.org/abs/1812.03982>`_ paper.
code: def _make_layer_fast(
      self,
      inplanes,
      planes,
      num_blocks,
      num_block_temp_kernel_fast=None,
      block=Bottleneck,
      strides=1,
      head_conv=1,
      norm_layer=BatchNorm3d,
      norm_kwargs=None,
      layer_name="",
  ):
      downsample = None
      if strides != 1 or inplanes != planes * block.expansion:
          downsample = nn.Sequential(
              nn.Conv3d(
                  in_channels=inplanes,
                  out_channels=planes * block.expansion,
                  kernel_size=1,
                  stride=(1, strides, strides),
                  bias=False,
              ),
              norm_layer(
                  num_features=planes * block.expansion,
                  **({} if norm_kwargs is None else norm_kwargs),
              ),
          )
  
      layers = []
      cnt = 0
      layers.append(
          block(
              inplanes=inplanes,
              planes=planes,
              strides=strides,
              downsample=downsample,
              head_conv=head_conv,
              layer_name="block%d_" % cnt,
          )
      )
      inplanes = planes * block.expansion
      cnt += 1
      for _ in range(1, num_blocks):
          if num_block_temp_kernel_fast is not None:
              if cnt < num_block_temp_kernel_fast:
                  layers.append(
                      block(
                          inplanes=inplanes,
                          planes=planes,
                          head_conv=head_conv,
                          layer_name="block%d_" % cnt,
                      )
                  )
              else:
                  layers.append(
                      block(
                          inplanes=inplanes,
                          planes=planes,
                          head_conv=1,
                          layer_name="block%d_" % cnt,
                      )
                  )
          else:
              layers.append(
                  block(
                      inplanes=inplanes,
                      planes=planes,
                      head_conv=head_conv,
                      layer_name="block%d_" % cnt,
                  )
              )
          cnt += 1
      return nn.Sequential(*layers)
  
imports: import torch
  import torch.nn
  from torch.nn import BatchNorm3d
label_desc: Use image node_id 5 for calling the SlowFast obj's underlying member method code with example usage: obj._make_layer_fast(inplanes, planes, num_blocks, num_block_temp_kernel_fast, block, strides, head_conv, norm_layer, norm_kwargs, layer_name) and returns: nn