def __init__(self, objective, constraints=None):
if constraints is None:
constraints = []
# Check that objective is Minimize or Maximize.
if not isinstance(objective, (Minimize, Maximize)):
raise error.DCPError(
"Problem objective must be Minimize or Maximize.")
# Constraints and objective are immutable.
self._objective = objective
self._constraints = [c for c in constraints]
self._value = None
self._status = None
self._solution = None
# The intermediate and solving chains to canonicalize and solve the problem
self._intermediate_chain = None
self._solving_chain = None
self._cached_chain_key = None
# List of separable (sub)problems
self._separable_problems = None
# Information about the shape of the problem and its constituent parts
self._size_metrics = None
# Benchmarks reported by the solver:
self._solver_stats = None
self.args = [self._objective, self._constraints]
# Cache for warm start.
self._solver_cache = {}
def __init__(self, objective, constraints=None):
if constraints is None:
constraints = []
# Check that objective is Minimize or Maximize.
if not isinstance(objective, (Minimize, Maximize)):
raise error.DCPError("Problem objective must be Minimize or Maximize.")
# Constraints and objective are immutable.
self._objective = objective
self._constraints = [c for c in constraints]
self._value = None
self._status = None
self._solution = None
self._cache = Cache()
self._solver_cache = {}
# Information about the shape of the problem and its constituent parts
self._size_metrics = None
# Benchmarks reported by the solver:
self._solver_stats = None
self.args = [self._objective, self._constraints]