class_docstr: X3D model builder. It builds a X3D network backbone, which is a ResNet.
  
  Christoph Feichtenhofer.
  "X3D: Expanding Architectures for Efficient Video Recognition."
  https://arxiv.org/abs/2004.04730
class_docstr_tok: ["X3D","model","builder",".","It","builds","a","X3D","network","backbone",",","which","is","a","ResNet",".","Christoph","Feichtenhofer",".","``","X3D",":","Expanding","Architectures","for","Efficient","Video","Recognition",".","''","https",":","\/\/arxiv.org\/abs\/2004.04730"]
code: def forward(self, x, bboxes=None):
      for module in self.children():
          x = module(x)
      return x
  
imports: import math
  from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.init import trunc_normal_
  import slowfast.utils.logging
  import slowfast.utils.weight_init_helper
  from slowfast.models.attention import MultiScaleBlock
  from slowfast.models.batchnorm_helper import get_norm
  from slowfast.models.common import TwoStreamFusion
  from slowfast.models.reversible_mvit import ReversibleMViT
  from slowfast.models.utils import calc_mvit_feature_geometry, get_3d_sincos_pos_embed, round_width, validate_checkpoint_wrapper_import
  from .None import head_helper, operators, resnet_helper, stem_helper
  from .build import MODEL_REGISTRY
label_desc: Use image node_id 4 for calling the X3D obj's underlying member method code with example usage: obj.forward(x, bboxes) and returns: x