enable import of _status_message for scipy > 1.7.1

torchmin/bfgs.py

@@ -2,11 +2,14 @@
 import torch
 from torch import Tensor
 from scipy.optimize import OptimizeResult
-from scipy.optimize.optimize import _status_message
 
 from .function import ScalarFunction
 from .line_search import strong_wolfe
 
+try:
+    from scipy.optimize.optimize import _status_message
+except ImportError:
+    from scipy.optimize._optimize import _status_message
 
 class HessianUpdateStrategy(ABC):
     def __init__(self):
@@ -378,4 +381,4 @@ def _minimize_lbfgs(
     return _minimize_bfgs_core(
         fun, x0, lr, low_mem=True, history_size=history_size,
         max_iter=max_iter, line_search=line_search, gtol=gtol, xtol=xtol,
-        normp=normp, callback=callback, disp=disp, return_all=return_all)
+        normp=normp, callback=callback, disp=disp, return_all=return_all)

torchmin/cg.py

@@ -1,10 +1,13 @@
 import torch
 from scipy.optimize import OptimizeResult
-from scipy.optimize.optimize import _status_message
 
 from .function import ScalarFunction
 from .line_search import strong_wolfe
 
+try:
+    from scipy.optimize.optimize import _status_message
+except ImportError:
+    from scipy.optimize._optimize import _status_message
 
 dot = lambda u,v: torch.dot(u.view(-1), v.view(-1))
 
@@ -140,4 +143,4 @@ def descent_condition(t, f_next, g_next):
                             message=msg, nit=niter, nfev=sf.nfev)
     if return_all:
         result['allvecs'] = allvecs
-    return result
+    return result

torchmin/newton.py

@@ -1,12 +1,16 @@
 from scipy.optimize import OptimizeResult
-from scipy.optimize.optimize import _status_message
 from scipy.sparse.linalg import eigsh
 from torch import Tensor
 import torch
 
 from .function import ScalarFunction
 from .line_search import strong_wolfe
 
+try:
+    from scipy.optimize.optimize import _status_message
+except ImportError:
+    from scipy.optimize._optimize import _status_message
+
 _status_message['cg_warn'] = "Warning: CG iterations didn't converge. The " \
                              "Hessian is not positive definite."
 

torchmin/trustregion/base.py

@@ -9,11 +9,16 @@
 from abc import ABC, abstractmethod
 import torch
 from torch.linalg import norm
-from scipy.optimize.optimize import OptimizeResult, _status_message
+from scipy.optimize import OptimizeResult
 
 from ..function import ScalarFunction
 from ..optim.minimizer import Minimizer
 
+try:
+    from scipy.optimize.optimize import _status_message
+except ImportError:
+    from scipy.optimize._optimize import _status_message
+
 status_messages = (
     _status_message['success'],
     _status_message['maxiter'],
@@ -262,4 +267,4 @@ def _minimize_trust_region(fun, x0, subproblem=None, initial_trust_radius=1.,
     if return_all:
         result['allvecs'] = allvecs
 
-    return result
+    return result