class_docstr: MobileNetV2 model from the
  `"Inverted Residuals and Linear Bottlenecks:
    Mobile Networks for Classification, Detection and Segmentation"
  <https://arxiv.org/abs/1801.04381>`_ paper.
  Parameters
  ----------
  multiplier : float, default 1.0
      The width multiplier for controlling the model size. The actual number of channels
      is equal to the original channel size multiplied by this multiplier.
  classes : int, default 1000
      Number of classes for the output layer.
  norm_layer : object
      Normalization layer used (default: :class:`mxnet.gluon.nn.BatchNorm`)
      Can be :class:`mxnet.gluon.nn.BatchNorm` or :class:`mxnet.gluon.contrib.nn.SyncBatchNorm`.
  norm_kwargs : dict
      Additional `norm_layer` arguments, for example `num_devices=4`
      for :class:`mxnet.gluon.contrib.nn.SyncBatchNorm`.
class_docstr_tok: ["MobileNetV2","model","from","the","`","``","Inverted","Residuals","and","Linear","Bottlenecks",":","Mobile","Networks","for","Classification",",","Detection","and","Segmentation","''","<","https",":","\/\/arxiv.org\/abs\/1801.04381",">","`","_","paper",".","Parameters","--","--","--","--","--","multiplier",":","float",",","default","1.0","The","width","multiplier","for","controlling","the","model","size",".","The","actual","number","of","channels","is","equal","to","the","original","channel","size","multiplied","by","this","multiplier",".","classes",":","int",",","default","1000","Number","of","classes","for","the","output","layer",".","norm_layer",":","object","Normalization","layer","used","(","default",":",":","class",":","`","mxnet.gluon.nn.BatchNorm","`",")","Can","be",":","class",":","`","mxnet.gluon.nn.BatchNorm","`","or",":","class",":","`","mxnet.gluon.contrib.nn.SyncBatchNorm","`",".","norm_kwargs",":","dict","Additional","`","norm_layer","`","arguments",",","for","example","`","num_devices=4","`","for",":","class",":","`","mxnet.gluon.contrib.nn.SyncBatchNorm","`","."]
code: def hybrid_forward(self, F, x):
      x = self.features(x)
      x = self.output(x)
      return x
  
imports: from mxnet.gluon import nn
  from mxnet.gluon.nn import BatchNorm
  from mxnet.context import cpu
  from mxnet.gluon.block import HybridBlock
  from ..nn import ReLU6
label_desc: Use image node_id 2 for calling the MobileNetV2 obj's underlying member method code with example usage: obj.hybrid_forward(F, x) and returns: x