code: def test_value_expression(
      arg_type: Union[BaseType, OptionalType, Type],
      index: int,
      op_name: str,
  ) -> str:
      tensor_size_ex = test_tensor_shape(op_name)
      if tensor_size_ex == "":
          num_tensors = 16 if index == 0 else 64
          num_dim = test_tensor_dim(op_name)
          size_per_dim = math.ceil(num_tensors / float(num_dim))
          size_per_dim += size_per_dim % 2
          tensor_size_ex = "{%s}" % (
              ",".join([f"{size_per_dim}"] * num_dim)
          )
      if should_use_int_tensor(op_name):
          tensor_expression = (
              f"at::randint(1, 100, {tensor_size_ex}, at::kInt)"
          )
      elif should_use_complex_tensor(op_name):
          tensor_expression = (
              f"at::randn({tensor_size_ex}, at::kComplexFloat)"
          )
      else:
          tensor_expression = f"at::rand({tensor_size_ex})"
  
      value_expressions = {
          BaseTy.Tensor: tensor_expression,
          BaseTy.int: "1",
          BaseTy.bool: "false",
          BaseTy.Scalar: "2",
          BaseTy.ScalarType: "at::ScalarType::Float",
          BaseTy.str: '"floor"',
      }
  
      base_ty_object = None
      if isinstance(arg_type, BaseType):
          base_ty_object = arg_type.name
      else:
          assert isinstance(arg_type, OptionalType) and isinstance(
              arg_type.elem, BaseType
          )
          base_ty_object = arg_type.elem.name
      assert base_ty_object in value_expressions, "not expected type"
      value_expression = value_expressions[base_ty_object]
      return value_expression
  
imports: import json
  import logging
  import math
  from typing import Dict, List, Optional, Sequence, Tuple, Union
  import torchgen.api.cpp
  from torchgen.context import native_function_manager
  from torchgen.model import Argument, BackendIndex, BaseTy, BaseType, FunctionSchema, NativeFunctionsGroup, NativeFunctionsViewGroup, OptionalType, SelfArgument, TensorOptionsArguments, Type
  from torchgen.static_runtime import config
label_desc: Use image node_id 8 for calling a global function with example usage: test_value_expression(arg_type, index, op_name) and returns: value_expression