diff --git a/mindspore/nn/optim/momentum.py b/mindspore/nn/optim/momentum.py
index 2e74f03264..0b73d5c0c8 100755
--- a/mindspore/nn/optim/momentum.py
+++ b/mindspore/nn/optim/momentum.py
@@ -24,11 +24,11 @@ from .optimizer import Optimizer
 _momentum_opt = C.MultitypeFuncGraph("momentum_opt")
 
 
-@_momentum_opt.register("Function", "Tensor", "Tensor", "Tensor", "Tensor", "Tensor", "Bool")
-def _tensor_run_opt_ext(opt, momentum, learning_rate, gradient, weight, moment, ps_parameter):
+@_momentum_opt.register("Function", "Tensor", "Tensor", "Tensor", "Tensor", "Tensor", "Bool", "Bool")
+def _tensor_run_opt_ext(opt, momentum, learning_rate, gradient, weight, moment, ps_parameter, cache_enable):
     """Apply momentum optimizer to the weight parameter using Tensor."""
     success = True
-    if ps_parameter:
+    if ps_parameter and not cache_enable:
         op_shape = P.Shape()
         _ps_pull = P.Pull()
         _ps_push = P.Push("ApplyMomentum", [])
@@ -146,8 +146,8 @@ class Momentum(Optimizer):
         lr = self.get_lr()
         if self.is_group_lr:
             success = self.hyper_map(F.partial(_momentum_opt, self.opt, self.momentum), lr, gradients, params, moments,
-                                     self.ps_parameters)
+                                     self.ps_parameters, self.cache_enable)
         else:
             success = self.hyper_map(F.partial(_momentum_opt, self.opt, self.momentum, lr), gradients, params, moments,
-                                     self.ps_parameters)
+                                     self.ps_parameters, self.cache_enable)
         return success