code: def __init__(
      self, inp, oup, t, strides, kernel=3, same_shape=True, **kwargs
  ):
      super(ExpandedConv, self).__init__(**kwargs)
  
      self.same_shape = same_shape
      self.strides = strides
      with self.name_scope():
          self.bottleneck = nn.HybridSequential()
          self.bottleneck.add(
              Conv1x1(inp * t, prefix="expand_"),
              DWise(inp * t, self.strides, kernel, prefix="dwise_"),
              Conv1x1(oup, is_linear=True, prefix="linear_"),
          )
  
imports: import sys
  import os
  import mxnet
  import mxnet.ndarray
  import mxnet.gluon
  import mxnet.gluon.nn
  import mxnet.autograd
  import symbol_utils
  from config import config
label_desc: Use image node_id 1 to create a new ExpandedConv object from inherited base classes: nn with example: obj = ExpandedConv(inp, oup, t, strides, kernel, same_shape)