code: def _handle_unary(chunk):
      if len(chunk.inputs) != 1:
          raise ValueError("unary operand inputs should be 1")
      data = chunk.inputs[0]
      unary_op = NE_UNARYOP_TO_STRING[type(chunk.op)]
      return f"{unary_op}({{{data.key}}})"
  
imports: from collections import defaultdict
  from itertools import count
  import numpy
  from ..operands import TensorFuse
  from ..None import arithmetic, reduction
  from ..array_utils import as_same_device
  from .core import TensorFuseChunkMixin
label_desc: Use image node_id 1 for calling a global function with example usage: _handle_unary(chunk) and returns: unary_op, str, data, str