code: def _execute_map(cls, ctx, op):
      inputs, device_id, xp = as_same_device(
          [ctx[inp.key] for inp in op.inputs],
          device=op.device,
          ret_extra=True,
      )
  
      if len(inputs) == 2 and not inputs[1]:
          # check fail
          raise ValueError("Distance matrix X must be symmetric.")
  
      if xp is cp:  # pragma: no cover
          raise NotImplementedError(
              "`squareform` does not support running on GPU yet"
          )
  
      with device(device_id):
          x = inputs[0]
          if x.ndim == 1:
              cls._to_matrix(ctx, xp, x, op)
          else:
              cls._to_vector(ctx, xp, x, op)
  
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 16 for calling the TensorSquareform obj's underlying member method code with example usage: obj._execute_map(cls, ctx, op) without return types