code: def _UnaryFunctionLayerParams(op, inexpr, etab):
      op_type = op.type
      if op_type == op.SQRT:
          return _op.sqrt(inexpr)
      elif op_type == op.RSQRT:
          epsilon = _expr.const(op.epsilon)
          return _op.rsqrt(inexpr + epsilon)
      elif op_type == op.INVERSE:
          epsilon = _expr.const(op.epsilon)
          return _expr.const(1.0) / (inexpr + epsilon)
      elif op_type == op.POWER:
          alpha = _expr.const(op.alpha)
          return _op.power(inexpr, alpha)
      elif op_type == op.EXP:
          return _op.exp(inexpr)
      elif op_type == op.LOG:
          return _op.log(inexpr)
      elif op_type == op.ABS:
          return _op.abs(inexpr)
      elif op_type == op.THRESHOLD:
          alpha = _expr.const(op.alpha)
          return _op.maximum(inexpr, alpha)
      else:
          msg = f"Unary Op type value {op_type} is not supported in frontend CoreML."
          raise tvm.error.OpAttributeUnImplemented(msg)
  
imports: import math
  import numpy
  import tvm
  from tvm.ir import IRModule
  from ..None import analysis
  from ..None import expr
  from ..None import function
  from ..None import op
  from ...None import nd
  from ..._ffi import base
  from .common import ExprTable
  from .common import infer_shape
label_desc: Use image node_id 22 for calling a global function with example usage: _UnaryFunctionLayerParams(op, inexpr, etab) and returns: _op, _op, unknown, _op, _op, _op, _op, _op