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46 lines
1.3 KiB
46 lines
1.3 KiB
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
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# Released under the modified BSD license. See COPYING.md for more details.
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import logging
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from abc import ABC, abstractmethod
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import numpy as np
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logger = logging.getLogger(__name__)
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class Extractor(ABC):
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@abstractmethod
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def extract(self, instances):
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pass
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@staticmethod
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def split_variables(instance):
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result = {}
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lp_solution = instance.training_data[0].lp_solution
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for var_name in lp_solution:
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for index in lp_solution[var_name]:
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category = instance.get_variable_category(var_name, index)
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if category is None:
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continue
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if category not in result:
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result[category] = []
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result[category] += [(var_name, index)]
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return result
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class InstanceFeaturesExtractor(Extractor):
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def extract(self, instances):
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return np.vstack(
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[
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np.hstack(
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[
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instance.get_instance_features(),
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instance.training_data[0].lp_value,
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]
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)
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for instance in instances
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]
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)
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