""" Copyright (C) 2018-2020 Intel Corporation Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import unittest import numpy as np from extensions.front.binary_quantize_normalization import BinaryFakeQuantizeNormalization from mo.utils.ir_engine.compare_graphs import compare_graphs from mo.utils.unittest.graph import build_graph graph_nodes = { '0': {'name': 'input', 'kind': 'op', 'op': 'Parameter'}, '1': {'name': 'mi_i', 'kind': 'op', 'op': 'Const'}, '2': {'name': 'ma_i', 'kind': 'op', 'op': 'Const'}, '3': {'name': 'mi_o', 'kind': 'op', 'op': 'Const'}, '4': {'name': 'mi_o', 'kind': 'op', 'op': 'Const'}, 'add': {'kind': 'op', 'op': 'Add'}, 'const': {'kind': 'op', 'op': 'Const', 'value': np.array(0.5)}, 'mul': {'kind': 'op', 'op': 'Mul'}, 'quantize': {'name': 'quantize', 'levels': 2, 'kind': 'op', 'op': 'FakeQuantize'}, 'output': {'name': 'output1', 'kind': 'op', 'op': 'Result', 'type': 'Result'}, } graph_edges = [ ('0', 'quantize', {'in': 0}), ('1', 'quantize', {'in': 1}), ('2', 'quantize', {'in': 2}), ('3', 'quantize', {'in': 3}), ('4', 'quantize', {'in': 4}), ('quantize', 'output'), ] graph_ref_edges = [ ('0', 'quantize', {'in': 0}), ('1', 'add'), ('2', 'add'), ('add', 'mul'), ('const', 'mul'), ('mul', 'quantize', {'in': 1, 'out': 0}), ('mul', 'quantize', {'in': 2, 'out': 0}), ('3', 'quantize', {'in': 3}), ('4', 'quantize', {'in': 4}), ('quantize', 'output'), ] class TestBinaryQuantizeNormalization(unittest.TestCase): def test_binary_quantize_normalizer(self): graph = build_graph(graph_nodes, graph_edges, nodes_with_edges_only=True) graph.stage = 'front' BinaryFakeQuantizeNormalization().find_and_replace_pattern(graph) graph.clean_up() graph_ref = build_graph(graph_nodes, graph_ref_edges) graph_ref.clean_up() (flag, resp) = compare_graphs(graph, graph_ref, 'output') self.assertTrue(flag, resp)