code: def _execute_reduce(cls, ctx, op: "TensorSquareform"):
      raw_inputs = list(op.iter_mapper_data(ctx))
      raw_indices = [inp[0] for inp in raw_inputs]
      raw_dists = [inp[1] for inp in raw_inputs]
      inputs, device_id, xp = as_same_device(
          raw_indices + raw_dists, op.device, ret_extra=True
      )
      raw_indices = inputs[: len(raw_indices)]
      raw_dists = inputs[len(raw_indices) :]
      output = op.outputs[0]
  
      with device(device_id):
          out_dists = xp.zeros(output.shape, dtype=output.dtype)
          indices = xp.concatenate(raw_indices)
          dists = xp.concatenate(raw_dists)
          out_dists.flat[indices] = dists
          ctx[output.key] = out_dists
  
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 17 for calling the TensorSquareform obj's underlying member method code with example usage: obj._execute_reduce(cls, ctx, op) without return types