class_docstr: The conv vision transformer stem as per https://arxiv.org/abs/2106.14881.
class_docstr_tok: ["The","conv","vision","transformer","stem","as","per","https",":","\/\/arxiv.org\/abs\/2106.14881","."]
code: def complexity(cx, w_in, ks, ws, ss):
      for i, (k, w_out, stride) in enumerate(zip(ks, ws, ss)):
          if i < len(ks) - 1:
              cx = conv2d_cx(cx, w_in, w_out, 3, stride=stride)
              cx = norm2d_cx(cx, w_out)
          else:
              cx = conv2d_cx(
                  cx, w_in, w_out, k, stride=stride, bias=True
              )
          w_in = w_out
      return cx
  
imports: import math
  import numpy
  import torch
  from pycls.core.config import cfg
  from pycls.models.blocks import activation, conv2d, conv2d_cx, layernorm, layernorm_cx, linear, linear_cx, MultiheadAttention, norm2d, norm2d_cx, patchify2d, patchify2d_cx
  from torch.nn import init, Module, Parameter
label_desc: Use image node_id 3 for calling the ViTStemConv obj's underlying member method code with example usage: obj.complexity(cx, w_in, ks, ws, ss) and returns: cx