docstr:           INPUT
             |
             v
            [t_0]
             |
             v
            [t_1]--.
             |     |
             |     v
             |    RELU_1
             |
             v
            [t_2]--.
             |     |
             |     v
             |    RELU_2
            [t_3]
             |
             v
            [t_4]--.
             |     |
             |     v
             |    RELU_3
             v
            RELU_4
  
    Even though t_0, t_1 can be merged, t_2 is identity, t_3, t_4 can be merge,
    The final output should be
               INPUT
                 |
    .------------.----------.
    |        |       |      |
    v        v       v      v
  RELU_1   RELU_2  RELU_3  RELU_4
  
    
docstr_tok: ["INPUT","|","v","[","t_0","]","|","v","[","t_1","]","--",".","|","|","|","v","|","RELU_1","|","v","[","t_2","]","--",".","|","|","|","v","|","RELU_2","[","t_3","]","|","v","[","t_4","]","--",".","|","|","|","v","|","RELU_3","v","RELU_4","Even","though","t_0",",","t_1","can","be","merged",",","t_2","is","identity",",","t_3",",","t_4","can","be","merge",",","The","final","output","should","be","INPUT","|",".","--","--","--","--","--","--",".","--","--","--","--","--",".","|","|","|","|","v","v","v","v","RELU_1","RELU_2","RELU_3","RELU_4"]
code: def test_fork_structure_case_3(self):
      """
                INPUT
                 |
                 v
                [t_0]
                 |
                 v
                [t_1]--.
                 |     |
                 |     v
                 |    RELU_1
                 |
                 v
                [t_2]--.
                 |     |
                 |     v
                 |    RELU_2
                [t_3]
                 |
                 v
                [t_4]--.
                 |     |
                 |     v
                 |    RELU_3
                 v
                RELU_4
  
        Even though t_0, t_1 can be merged, t_2 is identity, t_3, t_4 can be merge,
        The final output should be
                   INPUT
                     |
        .------------.----------.
        |        |       |      |
        v        v       v      v
      RELU_1   RELU_2  RELU_3  RELU_4
  
      """
      input_shape = (1, 10, 5)
      input_features = [("data", datatypes.Array(1, 10, 5))]
      output_features = [("out", None)]
      builder = neural_network.NeuralNetworkBuilder(
          input_features,
          output_features,
          disable_rank5_shape_mapping=True,
      )
      transpose = [
          [2, 1, 0],
          [2, 1, 0],
          [0, 1, 2],
          [2, 1, 0],
          [2, 1, 0],
      ]
      input_name = "data"
      for i, axes in enumerate(transpose):
          name = "transpose_" + str(i)
          output_name = name + "_out"
          builder.add_transpose(
              name=name,
              axes=axes,
              input_name=input_name,
              output_name=output_name,
          )
          input_name = output_name
  
      builder.add_activation(
          name="relu",
          non_linearity="RELU",
          input_name=input_name,
          output_name="out",
      )
      builder.add_activation(
          name="dumpy_1",
          non_linearity="RELU",
          input_name="transpose_1_out",
          output_name="dumpy_1",
      )
      builder.add_activation(
          name="dumpy_2",
          non_linearity="RELU",
          input_name="transpose_2_out",
          output_name="dumpy_2",
      )
      builder.add_activation(
          name="dumpy_4",
          non_linearity="RELU",
          input_name="transpose_4_out",
          output_name="dumpy_4",
      )
  
      self._test_builder(builder, input_shape, 4)
  
imports: import copy
  import pytest
  import numpy
  import unittest
  from sys import platform
  from coremltools._deps import _IS_MACOS
  import coremltools.models.datatypes
  from coremltools.models.utils import _macos_version
  from coremltools.models import neural_network
  from coremltools.models import MLModel
  from coremltools.models.neural_network.printer import print_network_spec
  from coremltools.converters.mil.backend.nn.passes.mlmodel_passes import remove_disconnected_layers, transform_conv_crop, remove_redundant_transposes
label_desc: Use image node_id 12 for calling the Redundant_Transposees_Test obj's underlying member method code with example usage: obj.test_fork_structure_case_3() without return types