class_docstr: Initializes weights with random values sampled from a normal distribution
  with a custom mean and standard deviation of `sigma`.
class_docstr_tok: ["Initializes","weights","with","random","values","sampled","from","a","normal","distribution","with","a","custom","mean","and","standard","deviation","of","`","sigma","`","."]
code: def _init_weight(self, _, arr):
      mx.np.random.normal(
          self.mean, self.sigma, arr.shape, dtype=arr.dtype, out=arr
      )
      if self.bounded:
          mx.np.abs(arr, out=arr)
  
imports: import mxnet
  import numpy
  import unittest
  import pytest
  import ctypes
  import copy
  from mxnet.contrib import quantization
  from mxnet.gluon import nn
  from mxnet.test_utils import assert_almost_equal, assert_almost_equal_with_err
label_desc: Use image node_id 2 for calling the CustomNormalInit obj's underlying member method code with example usage: obj._init_weight(_, arr) without return types