text: # Copyright (C) 2018-2021 Intel Corporation
  # SPDX-License-Identifier: Apache-2.0
  
  import unittest
  
  import numpy as np
  
  from extensions.middle.FakeSplitOutputs import AddFakeOutputsToSplit, AddFakeOutputsToVariadicSplit
  from mo.front.common.partial_infer.elemental import copy_shape_infer
  from mo.graph.graph import Node
  from mo.middle.passes.eliminate import graph_clean_up
  from mo.utils.unittest.graph import build_graph
  
  nodes_attributes = {
      'placeholder_1': {'type': 'Parameter', 'kind': 'op', 'op': 'Parameter', 'shape': np.array([1, 227, 227, 3])},
      # VariadicSplit operation
      'variadic_split': {'type': 'VariadicSplit', 'kind': 'op', 'op': 'VariadicSplit'},
      'split': {'type': 'Split', 'kind': 'op', 'op': 'Split', 'num_splits': 3, 'axis': 3},
      # Test operation
      'last': {'type': None, 'value': None, 'kind': 'op', 'op': None, 'infer': copy_shape_infer},
      'res': {'type': 'Result', 'kind': 'op', 'op': 'Result'},
      # Data nodes
      'placeholder_data': {'kind': 'data', 'value': None, 'shape': np.array([1, 227, 227, 3])},
      'variadic_split_data_1': {'kind': 'data', 'value': None, 'shape': np.array([1, 2, 227, 3])},
      'split_data_1': {'kind': 'data', 'value': None, 'shape': np.array([1, 227, 227, 1])},
      'last_data': {'kind': 'data', 'value': None, 'shape': np.array([1, 227, 227, 3])},
  
      'axis_const': {'kind': 'op', 'op': 'Const'},
      'axis_const_data': {'value': np.int64(1), 'shape': None, 'kind': 'data'},
      'split_dim_const': {'kind': 'op', 'op': 'Const'},
      'split_dim_const_data': {'value': np.array([1, 2, 3]), 'shape': None, 'kind': 'data'},
  
  }
  
  
  class SplitSaveEmptyBranchesTest(unittest.TestCase):
      def test_variadic_split_non_zero(self):
          graph = build_graph(nodes_attributes,
                              [('placeholder_1', 'placeholder_data'), ('placeholder_data', 'variadic_split'),
                               ('variadic_split', 'variadic_split_data_1'), ('variadic_split_data_1', 'last'),
                               ('last', 'last_data'), ('last_data', 'res'),
  
                               ('axis_const', 'axis_const_data'),
                               ('split_dim_const', 'split_dim_const_data'),
                               ('axis_const_data', 'variadic_split', {'in': 1}),
                               ('split_dim_const_data', 'variadic_split', {'in': 2}),
                               ], nodes_with_edges_only=True)
          node = Node(graph, 'variadic_split')
  
          # extractor should do it
          node['out_ports_count'] = 3
          for p in range(len(node.out_edges()), node.out_ports_count):
              node.add_output_port(p)
  
          replacer = AddFakeOutputsToVariadicSplit()
          replacer.find_and_replace_pattern(graph)
  
          for n in graph.get_op_nodes():
              n['need_shape_inference'] = False
          graph_clean_up(graph)
  
          self.assertTrue(len(node.out_edges()) == 3)
  
      def test_split(self):
          graph = build_graph(nodes_attributes,
                              [('placeholder_1', 'placeholder_data'), ('placeholder_data', 'split'),
                               ('split', 'split_data_1'), ('split_data_1', 'last'),
                               ('last', 'last_data'), ('last_data', 'res'),
                               ], nodes_with_edges_only=True)
          node = Node(graph, 'split')
  
          # extractor should do it
          node['out_ports_count'] = node.num_splits
          for p in range(len(node.out_edges()), node.out_ports_count):
              node.add_output_port(p)
  
          replacer = AddFakeOutputsToSplit()
          replacer.find_and_replace_pattern(graph)
  
          for n in graph.get_op_nodes():
              n['need_shape_inference'] = False
          graph_clean_up(graph)
  
          self.assertTrue(len(node.out_edges()) == node.num_splits)
  