code: def __call__(self, a, p, chunk_size=None):
      inputs = []
      if isinstance(a, TENSOR_TYPE):
          inputs.append(a)
      if isinstance(p, TENSOR_TYPE):
          inputs.append(p)
      return self.new_tensor(
          inputs,
          shape=self.size,
          raw_chunk_size=chunk_size,
          order=TensorOrder.C_ORDER,
      )
  
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 2 for calling the TensorChoice obj's underlying member method code with example usage: obj.__call__(a, p, chunk_size) and returns: self