code: def test_platforms_and_poly(self):
      x = np.arange(6, dtype=np.float32)
      #  returns x + 2. on CPU, x + 3. on GPU (CUDA or ROCM) and x + 4. on TPU
  
      module, version = serialize(
          """
  module @jit_f_jax attributes {jax.uses_shape_polymorphism = true} {
    func.func public @main(%arg_platform_idx: tensor<i32> {jax.global_constant = "_platform_index"}, %arg0: tensor<?xf32>) -> (tensor<?xf32>) {
      %0 = stablehlo.get_dimension_size %arg0, dim = 0 : (tensor<?xf32>) -> tensor<i32>
      %5 = call @_wrapped_jax_export_main(%arg_platform_idx, %0, %arg0) : (tensor<i32>, tensor<i32>, tensor<?xf32>) -> tensor<?xf32>
      return %5 : tensor<?xf32>
    }
  
    func.func private @_wrapped_jax_export_main(%arg_platform_idx: tensor<i32> {jax.global_constant = "_platform_index"}, %arg0: tensor<i32> {jax.global_constant = "b"}, %arg1: tensor<?xf32>) -> (tensor<?xf32>) {
      %to_add = "stablehlo.case"(%arg_platform_idx) ({
        %cpu_val = stablehlo.constant dense<2.> : tensor<f32>
        stablehlo.return %cpu_val : tensor<f32>
      }, {
        %gpu_val = stablehlo.constant dense<3.> : tensor<f32>
        stablehlo.return %gpu_val : tensor<f32>
      }, {
        %tpu_val = stablehlo.constant dense<4.> : tensor<f32>
        stablehlo.return %tpu_val : tensor<f32>
      }) : (tensor<i32>) -> tensor<f32>
      %1 = stablehlo.reshape %arg0 : (tensor<i32>) -> tensor<1xi32>
      %3 = stablehlo.dynamic_broadcast_in_dim %to_add, %1, dims = [] : (tensor<f32>, tensor<1xi32>) -> tensor<?xf32>
      %4 = stablehlo.add %3, %arg1 : tensor<?xf32>
      return %4 : tensor<?xf32>
    }
  }
  """
      )
      platforms = ["CPU", "CUDA", "ROCM", "TPU"]
  
      def f(x):
          return xla.call_module(
              [x],
              version=version,
              module=module,
              Tout=[np.float32],
              Sout=[()],
              platforms=platforms,
          )
  
      expected_value = (
          x
          + dict(CPU=2.0, CUDA=3.0, ROCM=4.0, TPU=4.0)[
              self.testing_platform()
          ]
      )
      self._assertOpOutputMatchesExpected(f, (x,), (expected_value,))
  
imports: import os
  import re
  from typing import Optional, Sequence
  import unittest
  from absl.testing import parameterized
  import numpy
  from tensorflow.compiler.mlir.stablehlo import stablehlo
  from tensorflow.compiler.tests import xla_test
  from tensorflow.compiler.tf2xla.ops import gen_xla_ops
  from tensorflow.compiler.tf2xla.python import xla
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import function
  from tensorflow.python.framework import ops
  from tensorflow.python.platform import googletest
  from tensorflow.python.platform import test
label_desc: Use image node_id 14 for calling the XlaCallModuleOpTest obj's underlying member method code with example usage: obj.test_platforms_and_poly() and returns: xla