code: def execute_map(cls, ctx, op):
      (in_chunk,), device_id, xp = as_same_device(
          [ctx[c.key] for c in op.inputs],
          device=op.device,
          ret_extra=True,
      )
  
      axis = cls.get_axis(op.axis)
  
      with device(device_id):
          chunk_count = nannumel(
              in_chunk,
              axis=axis,
              dtype=np.int64,
              keepdims=bool(op.keepdims),
          )
          chunk_sum = xp.nansum(
              in_chunk,
              axis=axis,
              dtype=op.dtype,
              keepdims=bool(op.keepdims),
          )
          ctx[op.outputs[0].key] = (chunk_sum, chunk_count)
  
file_path: mars/mars/tensor/reduction/nanmean.py
imports: import numpy
  from ...None import opcodes
  from ..datasource import tensor
  from ..array_utils import as_same_device, device
  from .core import TensorReduction, TensorReductionMixin, nannumel
  from .mean import TensorMean
label_desc: Use image node_id 2 for calling the TensorNanMean obj's underlying member method code with example usage: obj.execute_map(cls, ctx, op) without return types