code: def execute(cls, ctx, op):
      if vineyard is None:
          raise RuntimeError("vineyard is not available")
      socket, needs_put = resolve_vineyard_socket(ctx, op)
      client = vineyard.connect(socket)
  
      # some op might be fused and executed twice on different workers
      if not needs_put:
          # might be fused
          try:  # pragma: no cover
              meta = ctx.get_chunks_meta([op.inputs[0].key])[0]
              tensor_id = vineyard.ObjectID(meta["object_ref"])
              if not client.exists(tensor_id):
                  needs_put = True
          except KeyError:
              needs_put = True
      if needs_put:
          tensor_id = client.put(
              np.asarray(ctx[op.inputs[0].key]),
              partition_index=op.inputs[0].index,
          )
      else:  # pragma: no cover
          meta = client.get_meta(tensor_id)
          new_meta = vineyard.ObjectMeta()
          for k, v in meta.items():
              if k not in ["id", "signature", "instance_id"]:
                  if isinstance(v, vineyard.ObjectMeta):
                      new_meta.add_member(k, v)
                  else:
                      new_meta[k] = v
          new_meta["partition_index_"] = vy_data_utils.to_json(
              op.inputs[0].index
          )
          tensor_id = client.create_metadata(new_meta).id
  
      client.persist(tensor_id)
      holder = np.empty((1,), dtype=object)
      holder[0] = tensor_id
      ctx[op.outputs[0].key] = holder
  
imports: from typing import Tuple
  import numpy
  from ...None import opcodes
  from ...core.operand.base import SchedulingHint
  from ...serialization.serializables import FieldTypes, KeyField, StringField, TupleField
  from ...storage.base import StorageLevel
  from ...utils import lazy_import
  from ..datasource import tensor
  from .core import TensorDataStore
label_desc: Use image node_id 4 for calling the TensorVineyardDataStoreChunk obj's underlying member method code with example usage: obj.execute(cls, ctx, op) without return types