def DynT_Constraints(N: dyn_typing.DepSize) -> dyn_typing.DepType:
nConstraint = dyn_typing.SizeVar()
return dyn_typing.Tuple((
dyn_typing.NDArray(numpy.float64, (nConstraint, N)),
dyn_typing.NDArray(numpy.float64, (nConstraint, )),
dyn_typing.NDArray(numpy.float64, (N, )),
dyn_typing.NDArray(numpy.float64, (N, )),
))
def test_NDArray(self) -> None:
T = dyn_typing.NDArray(numpy.float64, (SizeConst(2), SizeConst(4)))
assert T.isinstance(numpy.zeros((2, 4)))
assert not T.isinstance(numpy.zeros((2, 5)))
assert not T.isinstance(numpy.zeros((2, 4), dtype=numpy.int64))
assert not T.isinstance(numpy.zeros((2, 4, 5)))
assert not T.isinstance(1)
assert T.isinstance(numpy.zeros((2, 4), order="F"))
n = SizeVar()
T = dyn_typing.NDArray(numpy.float64, (n, n))
assert T.isinstance(numpy.zeros((1, 1)))
assert T.isinstance(numpy.zeros((2, 2)))
assert T.isinstance(numpy.zeros((3, 3)))
assert not T.isinstance(numpy.zeros((1, 2)))
assert not T.isinstance(numpy.zeros((2, 1)))
assert not T.isinstance(numpy.zeros((3, 2)))
assert not T.isinstance(numpy.zeros((3, 4)))
def _pcg_output_check(output: Status) -> None:
pass
N = dyn_typing.SizeVar()
assertNoInfNaN_proj = cast(Callable[[typing.proj_t], None], assertNoInfNaN)
@dyn_typing.dyn_check_4(
input=(
dyn_typing.Class(QuadEvaluator),
typing.DynT_Constraints(N),
dyn_typing.Float(),
dyn_typing.NDArray(numpy.float64, (N, N)),
),
output=dyn_typing.Class(Status),
)
@bind_checker.bind_checker_4(
input=bind_checker.make_checker_4(
no_check_QPeval,
constraint_check,
assertNoInfNaN_float,
assertNoInfNaN_proj,
),
output=_pcg_output_check,
)
def quad_prog(
qpval: QuadEvaluator,
constraints: typing.constraints_t,
def f9(a: Any, b: Any, c: Any, d: Any, e: Any, f: Any, g: Any, h: Any,
ii: Any) -> None:
return None
fff = (f0, f1, f2, f3, f4, f5, f6, f7, f8, f9)
MM = SizeVar()
NN = SizeVar()
KK = SizeVar()
@tuplize.tuplize_2
@dyn_typing.dyn_check_2(
input=(
dyn_typing.NDArray(numpy.float64, (MM, KK)),
dyn_typing.NDArray(numpy.float64, (KK, NN)),
),
output=dyn_typing.NDArray(numpy.float64, (MM, NN)),
)
def matmul(a: Any, b: Any) -> Any:
return a @ b
@tuplize.tuplize_2
@dyn_typing.dyn_check_2(
input=(
dyn_typing.NDArray(numpy.float64, (MM, KK)),
dyn_typing.NDArray(numpy.float64, (KK, NN)),
),
output=dyn_typing.NDArray(numpy.float64, (MM, NN)),
def _input_checker(
parameters: Tuple[ndarray, Tuple[ndarray, ndarray, ndarray,
ndarray]]) -> None:
theta, constraints = parameters
constraint_check(constraints, theta=theta)
n = dyn_typing.SizeVar()
nConstraint = dyn_typing.SizeVar()
@dyn_typing.dyn_check_2(
input=(
dyn_typing.NDArray(numpy.float64, (n, )),
dyn_typing.Tuple((
dyn_typing.NDArray(numpy.float64, (nConstraint, n)),
dyn_typing.NDArray(numpy.float64, (nConstraint, )),
dyn_typing.NDArray(numpy.float64, (n, )),
dyn_typing.NDArray(numpy.float64, (n, )),
)),
),
output=dyn_typing.Bool(),
)
@bind_checker.bind_checker_2(input=_input_checker, output=noCheck)
def check(theta: ndarray, constraints: Tuple[ndarray, ndarray, ndarray,
ndarray]) -> bool:
A, b, lb, ub = constraints
"""检查参数theta是否满足约束[A @ theta <= b]，空约束返回True"""
result = bool(
import numpy
from optimizer._internals.common import findiff
from overloads import bind_checker, difference, dyn_typing
from overloads.shortcuts import assertNoInfNaN
from overloads.typedefs import ndarray
H = numpy.array([[2, 1], [1, 1]])
A = numpy.array([[1, 1]], dtype=numpy.float64)
b = numpy.array([1], dtype=numpy.float64)
lb = numpy.zeros((2, ))
ub = numpy.full((2, ), numpy.inf)
@dyn_typing.dyn_check_1(
input=(dyn_typing.NDArray(numpy.float64, (dyn_typing.SizeConst(2), )), ),
output=dyn_typing.NDArray(numpy.float64, (dyn_typing.SizeConst(2), )),
)
@bind_checker.bind_checker_1( # force line wrap
input=bind_checker.make_checker_1(assertNoInfNaN), # force line wrap
output=assertNoInfNaN, # force line wrap
)
def grad(x: ndarray) -> ndarray:
x1, x2 = x
assert x1 + x2 <= 1
assert x1 >= 0
assert x2 >= 0
g = (H @ x) * 2.0
return g # type: ignore
hessian_GT: ndarray = 2.0 * H