code: def _handle_reduction(chunk):
      ax = chunk.op.axis
      data = chunk.inputs[0]
      op_str = NE_REDUCTION_TO_STRING[type(chunk.op)]
      # TODO(hks): delete it if numexpr.sum fixed
      if len(ax) == data.ndim:
          return f"{op_str}({_wrap_bool(data)})"
      elif len(ax) == 1:
          return f"{op_str}({_wrap_bool(data)},axis={ax[0]})"
      else:
          raise ValueError("numexpr cannot encode axis")
  
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 6 for calling a global function with example usage: _handle_reduction(chunk) and returns: op_str, str, _wrap_bool, str, op_str, str, _wrap_bool, str, ax, str