docstr: Test complex BottleneckBlock with different dimensions.
code: def test_create_complex_bottleneck_block(self):
      """
      Test complex BottleneckBlock with different dimensions.
      """
      for dim_in, dim_inner, dim_out in itertools.product(
          (4, 8, 16), (2, 4), (4, 8, 16)
      ):
          model = BottleneckBlock(
              conv_a=nn.Conv3d(
                  dim_in,
                  dim_inner,
                  kernel_size=[3, 1, 1],
                  stride=[2, 1, 1],
                  padding=[1, 0, 0],
                  bias=False,
              ),
              norm_a=nn.BatchNorm3d(dim_inner),
              act_a=nn.ReLU(),
              conv_b=nn.Conv3d(
                  dim_inner,
                  dim_inner,
                  kernel_size=[1, 3, 3],
                  stride=[1, 2, 2],
                  padding=[0, 1, 1],
                  groups=1,
                  dilation=[1, 1, 1],
                  bias=False,
              ),
              norm_b=nn.BatchNorm3d(dim_inner),
              act_b=nn.ReLU(),
              conv_c=nn.Conv3d(
                  dim_inner,
                  dim_out,
                  kernel_size=[1, 1, 1],
                  stride=[1, 1, 1],
                  padding=[0, 0, 0],
                  bias=False,
              ),
              norm_c=nn.BatchNorm3d(dim_out),
          )
  
          # Test forwarding.
          for input_tensor in TestBottleneckBlock._get_inputs(dim_in):
              if input_tensor.shape[1] != dim_in:
                  with self.assertRaises(Exception):
                      output_tensor = model(input_tensor)
                  continue
  
              output_tensor = model(input_tensor)
              input_shape = input_tensor.shape
              output_shape = output_tensor.shape
  
              output_shape_gt = (
                  input_shape[0],
                  dim_out,
                  (input_shape[2] - 1) // 2 + 1,
                  (input_shape[3] - 1) // 2 + 1,
                  (input_shape[4] - 1) // 2 + 1,
              )
  
              self.assertEqual(
                  output_shape,
                  output_shape_gt,
                  "Output shape {} is different from expected shape {}".format(
                      output_shape, output_shape_gt
                  ),
              )
  
imports: import itertools
  import os
  import unittest
  import numpy
  import torch
  from pytorchvideo.models.head import ResNetBasicHead
  from pytorchvideo.models.net import Net
  from pytorchvideo.models.resnet import BottleneckBlock, create_acoustic_bottleneck_block, create_acoustic_resnet, create_bottleneck_block, create_res_block, create_res_stage, create_resnet, create_resnet_with_roi_head, ResBlock, ResStage, SeparableBottleneckBlock
  from pytorchvideo.models.stem import ResNetBasicStem
  from torch import nn
label_desc: Use image node_id 3 for calling the TestBottleneckBlock obj's underlying member method code with example usage: obj.test_create_complex_bottleneck_block() without return types