From b0e7226e6a307b9ed99e6a5cedef34f5fcffb2ed Mon Sep 17 00:00:00 2001
From: wanghuancoder <wanghuan29@baidu.com>
Date: Tue, 13 Dec 2022 20:28:32 +0800
Subject: [PATCH] fix rmsprop_ yaml bug (#49026)

* fix rmsprop_ yaml bug
---
 paddle/phi/api/yaml/legacy_ops.yaml |  2 +-
 python/paddle/optimizer/rmsprop.py  | 69 ++++++++++++++++++-----------
 2 files changed, 45 insertions(+), 26 deletions(-)

diff --git a/paddle/phi/api/yaml/legacy_ops.yaml b/paddle/phi/api/yaml/legacy_ops.yaml
index f228a70857..ba446289f7 100755
--- a/paddle/phi/api/yaml/legacy_ops.yaml
+++ b/paddle/phi/api/yaml/legacy_ops.yaml
@@ -1646,7 +1646,7 @@
   kernel :
     func : rmsprop {dense, dense, dense, dense, dense, dense -> dense, dense, dense, dense}
            rmsprop_dense_param_sparse_grad {dense, dense, selected_rows, dense, dense, dense -> dense, dense, dense, dense}
-    optional : mean_grad
+  optional : mean_grad
   inplace : (param -> param_out), (moment -> moment_out), (mean_square -> mean_square_out), (mean_grad -> mean_grad_out)
 
 - op : rnn
diff --git a/python/paddle/optimizer/rmsprop.py b/python/paddle/optimizer/rmsprop.py
index c6e78f538b..460c5e00ed 100644
--- a/python/paddle/optimizer/rmsprop.py
+++ b/python/paddle/optimizer/rmsprop.py
@@ -12,7 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from paddle import _C_ops
+
 from ..fluid import framework
+from ..fluid.framework import in_dygraph_mode
 from .optimizer import Optimizer
 
 __all__ = []
@@ -216,32 +219,48 @@ class RMSProp(Optimizer):
         mean_grad_acc = self._get_accumulator(
             self._mean_grad_acc_str, param_and_grad[0]
         )
-        rmsprop_op = block.append_op(
-            type=self.type,
-            inputs={
-                "Param": param_and_grad[0],
-                "Grad": param_and_grad[1],
-                "Moment": momentum_acc,
-                "MeanSquare": mean_square_acc,
-                "MeanGrad": mean_grad_acc,
-                "LearningRate": self._create_param_lr(param_and_grad),
-            },
-            outputs={
-                "ParamOut": param_and_grad[0],
-                "MomentOut": momentum_acc,
-                "MeanSquareOut": mean_square_acc,
-                "MeanGradOut": mean_grad_acc,
-            },
-            attrs={
-                "epsilon": self._epsilon,
-                "decay": self._rho,
-                "momentum": self._momentum,
-                "centered": self._centered,
-            },
-            stop_gradient=True,
-        )
 
-        return rmsprop_op
+        if in_dygraph_mode():
+            _C_ops.rmsprop_(
+                param_and_grad[0],
+                mean_square_acc,
+                param_and_grad[1],
+                momentum_acc,
+                self._create_param_lr(param_and_grad),
+                mean_grad_acc,
+                self._epsilon,
+                self._rho,
+                self._momentum,
+                self._centered,
+            )
+            return None
+        else:
+            rmsprop_op = block.append_op(
+                type=self.type,
+                inputs={
+                    "Param": param_and_grad[0],
+                    "Grad": param_and_grad[1],
+                    "Moment": momentum_acc,
+                    "MeanSquare": mean_square_acc,
+                    "MeanGrad": mean_grad_acc,
+                    "LearningRate": self._create_param_lr(param_and_grad),
+                },
+                outputs={
+                    "ParamOut": param_and_grad[0],
+                    "MomentOut": momentum_acc,
+                    "MeanSquareOut": mean_square_acc,
+                    "MeanGradOut": mean_grad_acc,
+                },
+                attrs={
+                    "epsilon": self._epsilon,
+                    "decay": self._rho,
+                    "momentum": self._momentum,
+                    "centered": self._centered,
+                },
+                stop_gradient=True,
+            )
+
+            return rmsprop_op
 
     def _update_param_group(self, parameters):
         self._epsilon = parameters.get('epsilon', self._default_dict['epsilon'])
-- 
GitLab