code: def test_partial_fusion_4(self):
      @mb.program(input_specs=[mb.TensorSpec(shape=(10, 2, 3, 5))])
      def prog(x):
          x = mb.relu(x=x)
          out2 = mb.transpose(x=x, perm=[0, 2, 1, 3])
          out1 = mb.transpose(x=out2, perm=[0, 2, 1, 3])
          return out1, out2
  
      prev_prog, prev_block, block = apply_pass_and_basic_check(
          prog, "common::reduce_transposes"
      )
      self.assertEqual(
          get_op_types_in_program(prev_prog),
          ["relu", "transpose", "transpose"],
      )
      self.assertEqual(
          get_op_types_in_program(prog),
          ["relu", "transpose", "transpose"],
      )
  
      assert (
          block.outputs[1]
          == block.find_ops(op_type="transpose")[0].outputs[0]
      )
      assert_model_is_valid(
          prog,
          {"x": (10, 2, 3, 5)},
          expected_output_shapes={
              block.outputs[0].name: (10, 2, 3, 5),
              block.outputs[1].name: (10, 3, 2, 5),
          },
      )
  
imports: from coremltools.converters.mil.mil import Builder
  from coremltools.converters.mil.testing_utils import assert_op_count_match, assert_model_is_valid, get_op_types_in_program, apply_pass_and_basic_check
  import unittest
  import pytest
  import numpy
label_desc: Use image node_id 11 for calling the TransposeOptimizationPass obj's underlying member method code with example usage: obj.test_partial_fusion_4() and returns: out1,  out2