96 lines
4.4 KiB
Python
96 lines
4.4 KiB
Python
# Copyright (C) 2018-2021 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import unittest
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from extensions.middle.LeakyReluPattern import LeakyReLUFusion
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from mo.front.common.partial_infer.utils import float_array, int64_array
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from mo.graph.graph import Node
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from mo.ops.result import Result
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from mo.utils.ir_engine.compare_graphs import compare_graphs
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from unit_tests.utils.graph import build_graph, result, build_graph_with_edge_attrs, connect, \
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regular_op_with_shaped_data, valued_const_with_data, connect_data
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shape = int64_array([1, 3, 5, 2])
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nodes = {**regular_op_with_shaped_data('input', shape, {'type': 'Parameter', 'op': 'Parameter'}),
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**regular_op_with_shaped_data('mul', shape, {'type': 'Multiply', 'name': 'mul'}),
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**regular_op_with_shaped_data('max', shape, {'type': 'Maximum', 'name': 'final_max'}),
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**valued_const_with_data('const', float_array([0.5])),
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**result('result')
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}
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edges = [*connect('input:0', '0:mul'),
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*connect('const', '1:mul'),
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*connect_data('input', '0:max'),
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*connect('mul:0', '1:max'),
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*connect('max:0', 'result'),
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]
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ref_nodes = {**regular_op_with_shaped_data('input', shape, {'type': 'Parameter', 'op': 'Parameter'}),
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**regular_op_with_shaped_data('leaky_relu', shape, {'type': 'LeakyReLU', 'name': 'max_final',
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'negative_slope': None}),
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**result('result')
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}
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ref_edges = [*connect('input:0', 'leaky_relu'), *connect('leaky_relu', 'result')]
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class LeakyReluFusionTest(unittest.TestCase):
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def test_leaky_relu_data_port_0(self):
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graph = build_graph_with_edge_attrs(nodes, edges, {})
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graph_ref = build_graph(ref_nodes, ref_edges)
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Node(graph_ref, 'leaky_relu')['negative_slope'] = 0.5
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LeakyReLUFusion().find_and_replace_pattern(graph)
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graph.clean_up()
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(flag, resp) = compare_graphs(graph, graph_ref, 'result')
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self.assertTrue(flag, resp)
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self.assertTrue(len(graph.get_op_nodes(name='final_max')) == 1 and
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graph.get_op_nodes(name='final_max')[0].op == 'LeakyReLU')
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def test_leaky_relu_not_applicable_non_scalar_const(self):
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# const value is not a scalar or 1D tensor with 1 element so the transformation is not applicable
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graph = build_graph_with_edge_attrs(nodes, edges, {})
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Node(graph, 'const')['value'] = float_array([0.5, 0.7])
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Node(graph, 'const_d')['value'] = float_array([0.5, 0.7])
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graph_ref = graph.copy()
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LeakyReLUFusion().find_and_replace_pattern(graph)
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graph.clean_up()
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(flag, resp) = compare_graphs(graph, graph_ref, 'result')
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self.assertTrue(flag, resp)
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def test_leaky_relu_mul_multiple_consumers(self):
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# multiple consumers of Mul operation
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graph = build_graph_with_edge_attrs(nodes, edges, {})
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additional_result = Result(graph, {'name': 'result_2'}).create_node()
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Node(graph, 'mul').out_port(0).connect(additional_result.in_port(0))
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ref_nodes = {**regular_op_with_shaped_data('input', shape, {'type': 'Parameter', 'op': 'Parameter'}),
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**regular_op_with_shaped_data('mul', shape, {'type': 'Multiply', 'name': 'mul'}),
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**regular_op_with_shaped_data('max', shape, {'type': 'Maximum', 'name': 'final_max'}),
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**valued_const_with_data('const', float_array([0.5])),
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**regular_op_with_shaped_data('leaky_relu', shape, {'type': 'LeakyReLU', 'name': 'max_final',
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'negative_slope': None}),
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**result('result'),
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**result('result_2')
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}
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ref_edges = [*connect('input:0', '0:mul'),
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*connect('const', '1:mul'),
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*connect('max:0', 'result'),
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*connect('mul:0', 'result_2'),
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*connect_data('input', 'leaky_relu'),
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*connect('leaky_relu', 'result')
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]
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graph_ref = build_graph_with_edge_attrs(ref_nodes, ref_edges)
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LeakyReLUFusion().find_and_replace_pattern(graph)
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graph.clean_up()
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(flag, resp) = compare_graphs(graph, graph_ref, 'result')
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self.assertTrue(flag, resp)
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(flag, resp) = compare_graphs(graph, graph_ref, 'result_2')
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self.assertTrue(flag, resp)
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