Fix lbfgsb grad when bounds are specified

jaxopt/_src/lbfgsb.py

@@ -21,6 +21,7 @@
 # [2] J. Nocedal and S. Wright.  Numerical Optimization, second edition.
 
 import dataclasses
+import inspect
 import warnings
 from typing import Any, Callable, NamedTuple, Optional, Union
 
@@ -558,15 +559,26 @@ def _value_and_grad_fun(self, params, *args, **kwargs):
       params = params.params
     (value, _), grad = self._value_and_grad_with_aux(params, *args, **kwargs)
     return value, grad
+
+  def _grad_fun(self, params, *args, **kwargs):
+    return self._value_and_grad_fun(params, *args, **kwargs)[1]
 
   def __post_init__(self):
     _, _, self._value_and_grad_with_aux = base._make_funs_with_aux(
         fun=self.fun,
         value_and_grad=self.value_and_grad,
         has_aux=self.has_aux,
     )
+
+    # Sets up reference signature.
+    fun = getattr(self.fun, "subfun", self.fun)
+    signature = inspect.signature(fun)
+    parameters = list(signature.parameters.values())
+    new_param = inspect.Parameter(name="bounds",
+                                  kind=inspect.Parameter.POSITIONAL_OR_KEYWORD)
+    parameters.insert(1, new_param)
+    self.reference_signature = inspect.Signature(parameters)
 
-    self.reference_signature = self.fun
 
     jit, unroll = self._get_loop_options()
     linesearch_solver = _setup_linesearch(

tests/lbfgsb_test.py

@@ -248,6 +248,21 @@ def fun(x):
 
     self.assertEqual(N_CALLS, n_iter + 1)
 
+  def test_grad_with_bounds(self):
+    # Test that the gradient is correct when bounds are specified by keyword.
+    # Pertinent to issue #463.
+    def pipeline(x, init_pars, bounds, data):
+      def fit_objective(pars, data, x):
+        return -jax.scipy.stats.norm.logpdf(pars, loc=data*x, scale=1.0)
+      solver = LBFGSB(fun=fit_objective, implicit_diff=True, maxiter=500, tol=1e-6)
+      return solver.run(init_pars, bounds=bounds, data=data, x=x)[0]
+
+    grad_fn = jax.grad(pipeline)
+    data = jnp.array(1.5)
+    res = grad_fn(0.5, jnp.array(0.0), (jnp.array(0.0), jnp.array(10.0)), data)
+    self.assertEqual(res, data)
+
+
 
 if __name__ == "__main__":
   absltest.main()