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"""Module for testing grouped optimizer.""" |
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from unittest import TestCase |
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from unittest.mock import Mock |
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from grortir.main.model.core.abstract_process import AbstractProcess |
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from grortir.main.model.core.abstract_stage import AbstractStage |
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from grortir.main.optimizers.grouped_optimizer import GroupedOptimizer |
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10
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class TestGroupedOptimizer(TestCase): |
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"""Class for testing Optimizer.""" |
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def setUp(self): |
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"""Set up environment.""" |
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self.some_process = AbstractProcess() |
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self.first_stage = AbstractStage() |
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self.second_stage = AbstractStage() |
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self.third_stage_a = Mock() |
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self.third_stage_b = Mock() |
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self.some_process.add_path([self.first_stage, self.second_stage, |
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self.third_stage_a]) |
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self.some_process.add_edge(self.second_stage, self.third_stage_b) |
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def test___init__(self): |
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"""Testing creating object.""" |
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optimizer = GroupedOptimizer(self.some_process, Mock()) |
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self.assertIsNotNone(optimizer) |
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self.assertEqual(optimizer.process, self.some_process) |
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def test_calling_functions(self): |
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"""Test correct order of calling function.""" |
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optimizer = GroupedOptimizer(self.some_process, Mock()) |
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optimizer.optimize_process() |
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class DeterministicStage(AbstractStage): |
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def __init__(self, max_get_output_of_stage_count=10, |
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max_is_enough_quality_count=10, |
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max_could_be_optimized_count=10, max_get_quality_count=10, |
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max_get_cost_count=10): |
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super().__init__((0, 0, 0, 0)) |
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self.get_cost_count = 0 |
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self.get_quality_count = 0 |
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self.could_be_optimized_count = 0 |
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self.is_enough_quality_count = 0 |
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self.get_output_of_stage_count = 0 |
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self.max_get_cost_count = max_get_cost_count |
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self.max_get_quality_count = max_get_quality_count |
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self.max_could_be_optimized_count = max_could_be_optimized_count |
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self.max_is_enough_quality_count = max_is_enough_quality_count |
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self.max_get_output_of_stage_count = max_get_output_of_stage_count |
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def get_cost(self): |
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self.get_cost_count += 1 |
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def get_quality(self, control_params=None): |
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self.get_quality_count += 1 |
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return |
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def could_be_optimized(self): |
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self.could_be_optimized_count += 1 |
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return True |
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def is_enough_quality(self, value): |
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self.is_enough_quality_count += 1 |
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return self.is_enough_quality_count == value |
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def get_output_of_stage(self): |
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self.get_output_of_stage_count += 1 |
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return [self.get_output_of_stage_count] * len(self.input_vector) |
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qbahn /
grortir
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