class_docstr: Appearance-Free Link Model.
class_docstr_tok: ["Appearance-Free","Link","Model","."]
code: def __init__(
      self,
      temporal_module_channels: list = [1, 32, 64, 128, 256],
      fusion_module_channels: list = [256, 256],
      classifier_channels: list = [256, 2],
  ):
      super(AFLinkModel, self).__init__()
      self.TemporalModule_1 = nn.Sequential(
          *[
              TemporalBlock(
                  temporal_module_channels[i],
                  temporal_module_channels[i + 1],
              )
              for i in range(len(temporal_module_channels) - 1)
          ]
      )
  
      self.TemporalModule_2 = nn.Sequential(
          *[
              TemporalBlock(
                  temporal_module_channels[i],
                  temporal_module_channels[i + 1],
              )
              for i in range(len(temporal_module_channels) - 1)
          ]
      )
  
      self.FusionBlock_1 = FusionBlock(*fusion_module_channels)
      self.FusionBlock_2 = FusionBlock(*fusion_module_channels)
  
      self.pooling = nn.AdaptiveAvgPool2d((1, 1))
      self.classifier = Classifier(*classifier_channels)
  
imports: from collections import defaultdict
  from typing import Tuple
  import numpy
  import torch
  from mmengine.model import BaseModule
  from mmengine.runner.checkpoint import load_checkpoint
  from scipy.optimize import linear_sum_assignment
  from torch import Tensor, nn
  from mmdet.registry import TASK_UTILS
label_desc: Use image node_id 1 to create a new AFLinkModel object from inherited base classes: BaseModule with example: obj = AFLinkModel(temporal_module_channels, fusion_module_channels, classifier_channels)