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70 lines
2.4 KiB
70 lines
2.4 KiB
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020-2022, 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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from typing import Optional, List
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import numpy as np
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from miplearn.extractors.abstract import FeaturesExtractor
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from miplearn.h5 import H5File
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class H5FieldsExtractor(FeaturesExtractor):
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def __init__(
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self,
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instance_fields: Optional[List[str]] = None,
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var_fields: Optional[List[str]] = None,
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constr_fields: Optional[List[str]] = None,
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):
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self.instance_fields = instance_fields
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self.var_fields = var_fields
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self.constr_fields = constr_fields
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def get_instance_features(self, h5: H5File) -> np.ndarray:
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if self.instance_fields is None:
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raise Exception("No instance fields provided")
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x = []
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for field in self.instance_fields:
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try:
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data = h5.get_array(field)
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except ValueError:
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data = h5.get_scalar(field)
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assert data is not None
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x.append(data)
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x = np.hstack(x)
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assert len(x.shape) == 1
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return x
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def get_var_features(self, h5: H5File) -> np.ndarray:
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var_types = h5.get_array("static_var_types")
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assert var_types is not None
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n_vars = len(var_types)
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if self.var_fields is None:
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raise Exception("No var fields provided")
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return self._extract(h5, self.var_fields, n_vars)
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def get_constr_features(self, h5: H5File) -> np.ndarray:
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constr_sense = h5.get_array("static_constr_sense")
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assert constr_sense is not None
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n_constr = len(constr_sense)
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if self.constr_fields is None:
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raise Exception("No constr fields provided")
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return self._extract(h5, self.constr_fields, n_constr)
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def _extract(self, h5, fields, n_expected):
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x = []
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for field in fields:
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try:
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data = h5.get_array(field)
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except ValueError:
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v = h5.get_scalar(field)
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data = np.repeat(v, n_expected)
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assert data is not None
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assert len(data.shape) == 1
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assert data.shape[0] == n_expected
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x.append(data)
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features = np.vstack(x).T
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assert len(features.shape) == 2
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assert features.shape[0] == n_expected
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return features
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