code: def _get_initializer(
      initializer: tp.Optional[types.InitializerSpec],
  ) -> types.AbstractInitializer:
      if initializer is None:
          return LeCunNormal()
      if isinstance(
          initializer, chainer.get_array_types()
      ) or numpy.isscalar(initializer):
          return Constant(initializer)
  
      if not callable(initializer):
          raise TypeError(
              "invalid type of initializer: %s" % type(initializer)
          )
      return initializer
  
imports: import typing
  import numpy
  import chainer
  from chainer import backend
  from chainer.backends import _chainerx
  from chainer.initializers.constant import Constant
  from chainer.initializers.constant import Identity
  from chainer.initializers.constant import NaN
  from chainer.initializers.constant import One
  from chainer.initializers.constant import Zero
  from chainer.initializers.normal import GlorotNormal
  from chainer.initializers.normal import HeNormal
  from chainer.initializers.normal import LeCunNormal
  from chainer.initializers.normal import Normal
  from chainer.initializers.orthogonal import Orthogonal
  from chainer.initializers.sampling import DownsamplingConvFilter
  from chainer.initializers.sampling import UpsamplingDeconvFilter
  from chainer.initializers.uniform import GlorotUniform
  from chainer.initializers.uniform import HeUniform
  from chainer.initializers.uniform import LeCunUniform
  from chainer.initializers.uniform import Uniform
  from chainer import types
label_desc: Use image node_id 2 for calling a global function with example usage: _get_initializer(initializer) and returns: initializer, LeCunNormal, Constant