docstr:         INPUT
           |
           v
          [t_0] --.
           |      |
           v      v
          [t_1]  RELU_1
           |
           v
          RELU_2
  Even though t_0, t_1 can be merged, but there is a branch from t_0,
  so we shouldn't remove anything here.
docstr_tok: ["INPUT","|","v","[","t_0","]","--",".","|","|","v","v","[","t_1","]","RELU_1","|","v","RELU_2","Even","though","t_0",",","t_1","can","be","merged",",","but","there","is","a","branch","from","t_0",",","so","we","should","n't","remove","anything","here","."]
code: def test_branch_case_2(self):
      """
              INPUT
               |
               v
              [t_0] --.
               |      |
               v      v
              [t_1]  RELU_1
               |
               v
              RELU_2
      Even though t_0, t_1 can be merged, but there is a branch from t_0,
      so we shouldn't remove anything here.
  
      """
      input_shape = (1, 10, 5)
      input_features = [("data", datatypes.Array(*input_shape))]
      output_features = [("out", None)]
      builder = neural_network.NeuralNetworkBuilder(
          input_features,
          output_features,
          disable_rank5_shape_mapping=True,
      )
      transpose = [[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",
          non_linearity="RELU",
          input_name="transpose_0_out",
          output_name="dumpy",
      )
      self._test_builder(builder, input_shape, 4)
  
imports: import copy
  import unittest
  from sys import platform
  import numpy
  import coremltools.models.datatypes
  from coremltools import ComputeUnit
  from coremltools._deps import _IS_MACOS
  from coremltools.converters.mil.backend.nn.passes.mlmodel_passes import remove_disconnected_layers, remove_redundant_transposes, transform_conv_crop
  from coremltools.models import MLModel
  from coremltools.models import neural_network
  from coremltools.models.neural_network.printer import print_network_spec
  from coremltools.models.utils import _macos_version
label_desc: Use image node_id 11 for calling the Redundant_Transposees_Test obj's underlying member method code with example usage: obj.test_branch_case_2() without return types