def test_custom_root_errors(self):
with self.assertRaisesRegex(TypeError, re.escape("f() output pytree")):
lax.custom_root(lambda x: (x, x), 0.0, lambda f, x: x, lambda f, x: x)
with self.assertRaisesRegex(TypeError, re.escape("solve() output pytree")):
lax.custom_root(lambda x: x, 0.0, lambda f, x: (x, x), lambda f, x: x)
def dummy_root_usage(x):
f = lambda y: x - y
return lax.custom_root(f, 0.0, lambda f, x: x, lambda f, x: (x, x))
with self.assertRaisesRegex(
TypeError, re.escape("tangent_solve() output pytree")):
api.jvp(dummy_root_usage, (0.0,), (0.0,))
def linear_solve(a, b):
f = lambda x: np.dot(a, x) - b
factors = jsp.linalg.cho_factor(a)
cho_solve = lambda f, b: jsp.linalg.cho_solve(factors, b)
def pos_def_solve(g, b):
return lax.custom_linear_solve(g, b, cho_solve, symmetric=True)
return lax.custom_root(f, b, cho_solve, pos_def_solve)
def root_aux(a, b):
f = lambda x: high_precision_dot(a, x) - b
factors = jsp.linalg.cho_factor(a)
cho_solve = lambda f, b: (jsp.linalg.cho_solve(factors, b),
orig_aux)
def pos_def_solve(g, b):
# prune aux to allow use as tangent_solve
cho_solve_noaux = lambda f, b: cho_solve(f, b)[0]
return lax.custom_linear_solve(g,
b,
cho_solve_noaux,
symmetric=True)
return lax.custom_root(f,
b,
cho_solve,
pos_def_solve,
has_aux=True)
def dummy_root_usage(x): f = lambda y: x - y return lax.custom_root(f, 0.0, lambda f, x: x, lambda f, x: (x, x))
def linear_solve(a, b): f = lambda y: high_precision_dot(a, y) - b x0 = np.zeros_like(b) solution = np.linalg.solve(a, b) oracle = lambda func, x0: solution return lax.custom_root(f, x0, oracle, vector_solve)
def sqrt_cubed(x, tangent_solve=scalar_solve): f = lambda y: y ** 2. - np.array(x) ** 3. return lax.custom_root(f, 0.0, binary_search, tangent_solve)
def f3():
return lax.custom_root(err, 0., solve, solve)
def f2():
return lax.custom_root(g, 0., solve, err)
def f1():
return lax.custom_root(g, 0., err, solve)
def sqrt_cubed(x, tangent_solve=scalar_solve):
f = lambda y: y**2 - x**3
return lax.custom_root(f, 0.0, binary_search, tangent_solve)
def sqrt_cubed(x, tangent_solve=scalar_solve):
f = lambda y: y**2 - x**3
# Note: Nonzero derivative at x0 required for newton_raphson
return lax.custom_root(f, 1.0, solve_method, tangent_solve)
def nonlinear_solve(y):
f = lambda x: nonlinear_func(x, y)
x0 = -jnp.ones_like(y)
return lax.custom_root(f, x0, newton_raphson, tangent_solve)
