class_docstr: Mixed Grouped Convolution
  
  Based on MDConv and GroupedConv in MixNet impl:
  https://github.com/tensorflow/tpu/blob/master/models/official/mnasnet/mixnet/custom_layers.py
  
  Args:
      in_channels (`int`):
          Number of channels in the input image
      out_channels (`int`):
          Number of channels produced by the convolution.
      kernel_size (`int`):
          Size of the convolving kernel.
      stride (`int`):
          Stride of the convolution.
      padding (`str`):
          Padding added to all four sides of the input.
      dilation (`int`):
          Spacing between kernel elements.
      depthwise (`bool`):
          If True, use depthwise convolution.
code: def forward(self, x: torch.Tensor) -> torch.Tensor:
      x_split = torch.split(x, self.splits, 1)
      x_out = [c(x_split[i]) for i, c in enumerate(self.values())]
      x = torch.cat(x_out, 1)
      return x
  
file_path: towhee/towhee/models/layers/mixed_conv2d.py
imports: from typing import List
  import torch
  from torch import nn
  from towhee.models.utils.create_conv2d_pad import create_conv2d_pad
label_desc: Use image node_id 2 for calling the MixedConv2d obj's underlying member method code with example usage: obj.forward(x) and returns: x