code: def mx_model(n_hidden: int, input_size: int, X: Array2d):
      import mxnet as mx
  
      mx_model = mx.gluon.nn.Sequential()
      mx_model.add(
          mx.gluon.nn.Dense(n_hidden),
          mx.gluon.nn.LayerNorm(),
          mx.gluon.nn.Dense(n_hidden, activation="relu"),
          mx.gluon.nn.LayerNorm(),
          mx.gluon.nn.Dense(10, activation="softrelu"),
      )
      mx_model.initialize()
      return mx_model
  
imports: from typing import cast
  import numpy
  import pytest
  from thinc.api import Adam, ArgsKwargs, Model, MXNetWrapper, Ops, get_current_ops, mxnet2xp, xp2mxnet
  from thinc.compat import has_cupy_gpu, has_mxnet
  from thinc.types import Array1d, Array2d, IntsXd
  from thinc.util import to_categorical
  from ..util import check_input_converters, make_tempdir
label_desc: Use image node_id 7 for calling a global function with example usage: mx_model(n_hidden, input_size, X) and returns: mx_model