def _initial_state(self, num_constraints):
# For an AdditiveSwapRegretOptimizer, the internal state is a tensor of
# shape (m+1,m+1), where m is the number of constraints, representing a
# left-stochastic matrix.
dimension = num_constraints + 1
# Initialize by putting all weight on the objective, and none on the
# constraints.
return standard_ops.concat((standard_ops.ones(
(1, dimension)), standard_ops.zeros((dimension - 1, dimension))),
axis=0)
def _initial_state(self, num_constraints):
# For an AdditiveSwapRegretOptimizer, the internal state is a tensor of
# shape (m+1,m+1), where m is the number of constraints, representing a
# left-stochastic matrix.
dimension = num_constraints + 1
# Initialize by putting all weight on the objective, and none on the
# constraints.
return standard_ops.concat((standard_ops.ones(
(1, dimension)), standard_ops.zeros((dimension - 1, dimension))),
axis=0)