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Use np.ndarray for var_types, basis_status

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Alinson S. Xavier
2021-08-08 07:36:57 -05:00
parent 7d55d6f34c
commit 45667ac2e4
6 changed files with 31 additions and 23 deletions
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4
miplearn/features/extractor.py
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@@ -36,7 +36,7 @@ class FeaturesExtractor:
sample.put_array("static_var_lower_bounds", variables.lower_bounds)
sample.put_array("static_var_names", variables.names)
sample.put_array("static_var_obj_coeffs", variables.obj_coeffs)
sample.put_vector("static_var_types", variables.types)
sample.put_array("static_var_types", variables.types)
sample.put_array("static_var_upper_bounds", variables.upper_bounds)
sample.put_vector("static_constr_names", constraints.names)
# sample.put("static_constr_lhs", constraints.lhs)
@@ -69,7 +69,7 @@ class FeaturesExtractor:
) -> None:
variables = solver.get_variables(with_static=False, with_sa=self.with_sa)
constraints = solver.get_constraints(with_static=False, with_sa=self.with_sa)
sample.put_vector("lp_var_basis_status", variables.basis_status)
sample.put_array("lp_var_basis_status", variables.basis_status)
sample.put_array("lp_var_reduced_costs", variables.reduced_costs)
sample.put_array("lp_var_sa_lb_down", variables.sa_lb_down)
sample.put_array("lp_var_sa_lb_up", variables.sa_lb_up)