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157 lines
4.8 KiB
157 lines
4.8 KiB
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020-2021, 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 tempfile import NamedTemporaryFile
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from typing import Any
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import numpy as np
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from miplearn.features.sample import MemorySample, Sample, Hdf5Sample, _pad, _crop
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from miplearn.solvers.tests import assert_equals
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def test_memory_sample() -> None:
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_test_sample(MemorySample())
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def test_hdf5_sample() -> None:
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file = NamedTemporaryFile()
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_test_sample(Hdf5Sample(file.name))
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def _test_sample(sample: Sample) -> None:
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# Scalar
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_assert_roundtrip_scalar(sample, "A")
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_assert_roundtrip_scalar(sample, True)
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_assert_roundtrip_scalar(sample, 1)
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_assert_roundtrip_scalar(sample, 1.0)
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# Vector
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_assert_roundtrip_vector(sample, ["A", "BB", "CCC", "こんにちは", None])
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_assert_roundtrip_vector(sample, [True, True, False])
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_assert_roundtrip_vector(sample, [1, 2, 3])
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_assert_roundtrip_vector(sample, [1.0, 2.0, 3.0])
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_assert_roundtrip_vector(sample, np.array([1.0, 2.0, 3.0]), check_type=False)
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# VectorList
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_assert_roundtrip_vector_list(sample, [["A"], ["BB", "CCC"], None])
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_assert_roundtrip_vector_list(sample, [[True], [False, False], None])
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_assert_roundtrip_vector_list(sample, [[1], None, [2, 2], [3, 3, 3]])
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_assert_roundtrip_vector_list(sample, [[1.0], None, [2.0, 2.0], [3.0, 3.0, 3.0]])
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_assert_roundtrip_vector_list(sample, [None, None])
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# Bytes
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_assert_roundtrip_bytes(sample, b"\x00\x01\x02\x03\x04\x05")
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# Querying unknown keys should return None
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assert sample.get_scalar("unknown-key") is None
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assert sample.get_vector("unknown-key") is None
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assert sample.get_vector_list("unknown-key") is None
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assert sample.get_bytes("unknown-key") is None
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# Putting None should not modify HDF5 file
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sample.put_scalar("key", None)
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sample.put_vector("key", None)
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def _assert_roundtrip_bytes(sample: Sample, expected: Any) -> None:
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sample.put_bytes("key", expected)
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actual = sample.get_bytes("key")
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assert actual == expected
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assert actual is not None
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_assert_same_type(actual, expected)
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def _assert_roundtrip_scalar(sample: Sample, expected: Any) -> None:
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sample.put_scalar("key", expected)
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actual = sample.get_scalar("key")
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assert actual == expected
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assert actual is not None
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_assert_same_type(actual, expected)
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def _assert_roundtrip_vector(
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sample: Sample, expected: Any, check_type: bool = True
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) -> None:
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sample.put_vector("key", expected)
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actual = sample.get_vector("key")
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assert_equals(actual, expected)
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assert actual is not None
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if check_type:
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_assert_same_type(actual[0], expected[0])
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def _assert_roundtrip_vector_list(sample: Sample, expected: Any) -> None:
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sample.put_vector_list("key", expected)
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actual = sample.get_vector_list("key")
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assert actual == expected
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assert actual is not None
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if actual[0] is not None:
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_assert_same_type(actual[0][0], expected[0][0])
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def _assert_same_type(actual: Any, expected: Any) -> None:
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assert isinstance(
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actual, expected.__class__
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), f"Expected {expected.__class__}, found {actual.__class__} instead"
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def test_pad_int() -> None:
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_assert_roundtrip_pad(
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original=[[1], [2, 2, 2], [], [3, 3], [4, 4, 4, 4], None],
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expected_padded=[
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[1, 0, 0, 0],
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[2, 2, 2, 0],
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[0, 0, 0, 0],
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[3, 3, 0, 0],
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[4, 4, 4, 4],
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[0, 0, 0, 0],
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],
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expected_lens=[1, 3, 0, 2, 4, -1],
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dtype=int,
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)
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def test_pad_float() -> None:
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_assert_roundtrip_pad(
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original=[[1.0], [2.0, 2.0, 2.0], [3.0, 3.0], [4.0, 4.0, 4.0, 4.0], None],
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expected_padded=[
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[1.0, 0.0, 0.0, 0.0],
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[2.0, 2.0, 2.0, 0.0],
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[3.0, 3.0, 0.0, 0.0],
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[4.0, 4.0, 4.0, 4.0],
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[0.0, 0.0, 0.0, 0.0],
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],
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expected_lens=[1, 3, 2, 4, -1],
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dtype=float,
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)
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def test_pad_str() -> None:
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_assert_roundtrip_pad(
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original=[["A"], ["B", "B", "B"], ["C", "C"]],
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expected_padded=[["A", "", ""], ["B", "B", "B"], ["C", "C", ""]],
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expected_lens=[1, 3, 2],
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dtype=str,
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)
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def _assert_roundtrip_pad(
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original: Any,
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expected_padded: Any,
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expected_lens: Any,
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dtype: Any,
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) -> None:
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actual_padded, actual_lens = _pad(original)
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assert actual_padded == expected_padded
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assert actual_lens == expected_lens
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for v in actual_padded:
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for vi in v: # type: ignore
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assert isinstance(vi, dtype)
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cropped = _crop(actual_padded, actual_lens)
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assert cropped == original
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for v in cropped:
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if v is None:
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continue
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for vi in v: # type: ignore
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assert isinstance(vi, dtype)
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