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https://github.com/ANL-CEEESA/MIPLearn.git
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Fix failing tests
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@@ -1,6 +1,7 @@
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# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# 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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# 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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# Released under the modified BSD license. See COPYING.md for more details.
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from typing import Hashable, Dict
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from unittest.mock import Mock
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from unittest.mock import Mock
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import pytest
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import pytest
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@@ -103,11 +104,11 @@ def test_sample_xy_without_ub(
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def test_fit_xy() -> None:
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def test_fit_xy() -> None:
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x = {
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x: Dict[Hashable, np.ndarray] = {
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"Lower bound": np.array([[0.0, 0.0], [1.0, 2.0]]),
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"Lower bound": np.array([[0.0, 0.0], [1.0, 2.0]]),
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"Upper bound": np.array([[0.0, 0.0], [1.0, 2.0]]),
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"Upper bound": np.array([[0.0, 0.0], [1.0, 2.0]]),
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}
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}
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y = {
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y: Dict[Hashable, np.ndarray] = {
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"Lower bound": np.array([[100.0]]),
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"Lower bound": np.array([[100.0]]),
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"Upper bound": np.array([[200.0]]),
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"Upper bound": np.array([[200.0]]),
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}
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}
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@@ -141,11 +142,11 @@ def test_fit_xy() -> None:
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def test_fit_xy_without_ub() -> None:
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def test_fit_xy_without_ub() -> None:
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x = {
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x: Dict[Hashable, np.ndarray] = {
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"Lower bound": np.array([[0.0, 0.0], [1.0, 2.0]]),
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"Lower bound": np.array([[0.0, 0.0], [1.0, 2.0]]),
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"Upper bound": np.array([[0.0, 0.0], [1.0, 2.0]]),
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"Upper bound": np.array([[0.0, 0.0], [1.0, 2.0]]),
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}
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}
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y = {
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y: Dict[Hashable, np.ndarray] = {
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"Lower bound": np.array([[100.0]]),
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"Lower bound": np.array([[100.0]]),
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}
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}
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reg = Mock(spec=Regressor)
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reg = Mock(spec=Regressor)
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