code: def execute(cls, ctx, op):
      if vineyard is None:
          raise RuntimeError("vineyard is not available")
  
      socket = resolve_vineyard_socket(ctx, op)
      client = vineyard.connect(socket)
  
      meta = client.get_meta(vineyard.ObjectID(op.object_id))
      chunks = []
      for idx in range(meta["partitions_-size"]):
          chunk_meta = meta["partitions_-%d" % idx]
          if not chunk_meta.islocal:
              continue
          dtype = vy_data_utils.normalize_dtype(
              chunk_meta["value_type_"],
              chunk_meta.get("value_type_meta_", None),
          )
          shape = tuple(json.loads(chunk_meta["shape_"]))
          chunk_index = tuple(
              json.loads(chunk_meta.get("partition_index_", "[]"))
          )
          # chunk: (chunk_id, worker_address, dtype, shape, index)
          chunks.append(
              (
                  repr(chunk_meta.id),
                  ctx.worker_address,
                  dtype,
                  shape,
                  chunk_index,
              )
          )
  
      holder = np.empty((1,), dtype=object)
      holder[0] = chunks
      ctx[op.outputs[0].key] = np.asarray(holder)
  
imports: import json
  import numpy
  from ...None import opcodes
  from ...serialization.serializables import Int32Field, StringField
  from ...storage.base import StorageLevel
  from ...utils import calc_nsplits, has_unknown_shape, lazy_import
  from ...core.context import get_context
  from ..operands import TensorOperand, TensorOperandMixin
  from .core import TensorNoInput
label_desc: Use image node_id 3 for calling the TensorFromVineyard obj's underlying member method code with example usage: obj.execute(cls, ctx, op) without return types