code: def execute(cls, ctx, op: "TensorUnique"):
      if op.stage == OperandStage.map:
          cls._execute_map(ctx, op)
      elif op.stage == OperandStage.reduce:
          if op.reducer_phase == "agg":
              cls._execute_agg_reduce(ctx, op)
          else:
              assert op.reducer_phase == "inverse"
              cls._execute_inverse_reduce(ctx, op)
      else:
          (ar,), device_id, xp = as_same_device(
              [ctx[c.key] for c in op.inputs],
              device=op.device,
              ret_extra=True,
          )
  
          with device(device_id):
              kw = dict(
                  return_index=op.return_index,
                  return_inverse=op.return_inverse,
                  return_counts=op.return_counts,
              )
              if ar.dtype != object and sum(ar.shape) > 0:
                  # axis cannot pass when dtype is object or array size is 0
                  kw["axis"] = op.axis
              results = xp.unique(ar, **kw)
              outs = op.outputs
              if len(outs) == 1:
                  ctx[outs[0].key] = results
                  return
  
              assert len(outs) == len(results)
              for out, result in zip(outs, results):
                  ctx[out.key] = result
  
imports: import itertools
  import numpy
  from ...None import opcodes
  from ...config import options
  from ...core import recursive_tile
  from ...core.operand import OperandStage
  from ...lib import sparse
  from ...lib.sparse.core import get_array_module
  from ...serialization.serializables import BoolField, Int32Field, Int64Field
  from ...utils import has_unknown_shape
  from ..operands import TensorMapReduceOperand, TensorOperandMixin, TensorShuffleProxy
  from ..array_utils import as_same_device, device
  from ..core import TensorOrder
  from ..utils import validate_axis, hash_on_axis
label_desc: Use image node_id 17 for calling the TensorUnique obj's underlying member method code with example usage: obj.execute(cls, ctx, op) without return types