class_docstr: Apply instance normalization to the n-dimensional input tensor.
  
  Parameters
  ----------
  x: tensor<[n,C,*D], T>  (Required)
      * ``3 <= rank(x) <= 4``.
      * ``*D`` refers to the spatial dimensions, ``1 <= rank(*D) <= 2``.
      * ``n`` is the batch dimension.
  gamma: const tensor<[C], T> (Optional)
      * Optional scale applied to normalized tensor.
      * Default to all ones.
  beta: const tensor<[C], T> (Optional)
      * Optional offset applied to normalized tensor.
      * Default to all zeros.
  epsilon: const f32 (Optional)
      * Default to ``1e-5``.
  
  Returns
  -------
  tensor<[n,C,*D], T>
      * Output tensor has the same shape and type as the input ``x``.
  
  Attributes
  ----------
  T: fp16, fp32
class_docstr_tok: ["Apply","instance","normalization","to","the","n-dimensional","input","tensor",".","Parameters","--","--","--","--","--","x",":","tensor","<","[","n",",","C",",","*","D","]",",","T",">","(","Required",")","*","``","3","<","=","rank","(","x",")","<","=","4","``",".","*","``","*","D","``","refers","to","the","spatial","dimensions",",","``","1","<","=","rank","(","*","D",")","<","=","2","``",".","*","``","n","``","is","the","batch","dimension",".","gamma",":","const","tensor","<","[","C","]",",","T",">","(","Optional",")","*","Optional","scale","applied","to","normalized","tensor",".","*","Default","to","all","ones",".","beta",":","const","tensor","<","[","C","]",",","T",">","(","Optional",")","*","Optional","offset","applied","to","normalized","tensor",".","*","Default","to","all","zeros",".","epsilon",":","const","f32","(","Optional",")","*","Default","to","``","1e-5","``",".","Returns","--","--","--","-","tensor","<","[","n",",","C",",","*","D","]",",","T",">","*","Output","tensor","has","the","same","shape","and","type","as","the","input","``","x","``",".","Attributes","--","--","--","--","--","T",":","fp16",",","fp32"]
code: def default_inputs(self):
      return DefaultInputs(
          gamma=None,
          beta=None,
          epsilon=1e-5,
      )
  
imports: import numpy
  from coremltools.converters.mil.mil import DefaultInputs, InputSpec, Operation, TensorInputType, precondition, types
  from coremltools.converters.mil.mil.operation import VALUE
  from coremltools.converters.mil.mil.ops.defs._op_reqs import register_op
  from coremltools.converters.mil.mil.types.symbolic import any_symbolic
label_desc: Use image node_id 1 for calling the instance_norm obj's underlying member method code with example usage: obj.default_inputs() and returns: DefaultInputs