code: def execute(cls, ctx, op):
      if op.stage == OperandStage.map:
          cls._execute_map(ctx, op)
      elif op.stage == OperandStage.reduce:
          cls._execute_reduce(ctx, op)
      else:
          from scipy.spatial.distance import squareform
  
          (x,), device_id, xp = as_same_device(
              [ctx[inp.key] for inp in op.inputs],
              device=op.device,
              ret_extra=True,
          )
  
          if xp is cp:  # pragma: no cover
              raise NotImplementedError(
                  "`squareform` does not support running on GPU yet"
              )
  
          with device(device_id):
              ctx[op.outputs[0].key] = squareform(x, checks=op.checks)
  
imports: import itertools
  import numpy
  from ....None import opcodes
  from ....core import recursive_tile
  from ....core.operand import OperandStage
  from ....serialization.serializables import FieldTypes, KeyField, BoolField, TupleField
  from ....config import options
  from ....utils import has_unknown_shape, require_module
  from ...core import TensorOrder
  from ...operands import TensorMapReduceOperand, TensorOperandMixin, TensorShuffleProxy
  from ...datasource import ascontiguousarray, array, zeros
  from ...arithmetic import equal
  from ...utils import decide_chunk_sizes
  from ...array_utils import as_same_device, device, cp
label_desc: Use image node_id 18 for calling the TensorSquareform obj's underlying member method code with example usage: obj.execute(cls, ctx, op) without return types