code: def twins_svt_base(pretrained=False, **kwargs) -> Twins:
      model_args = dict(
          patch_size=4,
          embed_dims=[96, 192, 384, 768],
          num_heads=[3, 6, 12, 24],
          mlp_ratios=[4, 4, 4, 4],
          depths=[2, 2, 18, 2],
          wss=[7, 7, 7, 7],
          sr_ratios=[8, 4, 2, 1],
      )
      return _create_twins(
          "twins_svt_base",
          pretrained=pretrained,
          **dict(model_args, **kwargs),
      )
  
imports: import math
  from functools import partial
  from typing import Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import Mlp, DropPath, to_2tuple, trunc_normal_, use_fused_attn
  from ._builder import build_model_with_cfg
  from ._features_fx import register_notrace_module
  from ._registry import register_model, generate_default_cfgs
  from .vision_transformer import Attention
label_desc: Use image node_id 7 for calling a global function with example usage: twins_svt_base(pretrained) and returns: _create_twins