code: def execute(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 isinstance(op.a, TENSOR_CHUNK_TYPE):
          a = inputs[0]
      else:
          a = op.a
      if isinstance(op.p, TENSOR_CHUNK_TYPE):
          p = inputs[-1]
      else:
          p = op.p
  
      with device(device_id):
          rs = xp.random.RandomState(op.seed)
          ctx[op.outputs[0].key] = rs.choice(
              a, size=op.size, replace=op.replace, p=p
          )
  
imports: from numbers import Integral
  import numpy
  from ...None import opcodes
  from ...config import options
  from ...core import recursive_tile
  from ...serialization.serializables import FieldTypes, AnyField, KeyField, BoolField, TupleField
  from ...utils import has_unknown_shape, ceildiv
  from ..operands import TensorOperandMixin
  from ..core import TENSOR_TYPE, TENSOR_CHUNK_TYPE, TensorOrder
  from ..datasource import arange, array
  from ..utils import decide_chunk_sizes, normalize_chunk_sizes, gen_random_seeds
  from ..array_utils import as_same_device, device
  from .core import TensorRandomOperand, RandomState
label_desc: Use image node_id 7 for calling the TensorChoice obj's underlying member method code with example usage: obj.execute(cls, ctx, op) without return types