diff --git a/mindspore/ccsrc/device/kernel_runtime.cc b/mindspore/ccsrc/device/kernel_runtime.cc
index d3fccc11fd..e77d348630 100644
--- a/mindspore/ccsrc/device/kernel_runtime.cc
+++ b/mindspore/ccsrc/device/kernel_runtime.cc
@@ -201,6 +201,7 @@ void KernelRuntime::RunOpAssignOutputMemory(const AnfNodePtr &kernel) {
   if (AnfAlgo::GetCNodeName(kernel) == "ApplyMomentum") {
     auto device_address = AnfAlgo::GetPrevNodeMutableOutputAddr(kernel, 0);
     AnfAlgo::SetOutputAddr(device_address, 0, kernel.get());
+    AnfAlgo::SetOutputAddr(device_address, 1, kernel.get());
     return;
   }
 
diff --git a/mindspore/ops/_op_impl/tbe/apply_momentum.py b/mindspore/ops/_op_impl/tbe/apply_momentum.py
index 920a48e48d..deb8f0d387 100644
--- a/mindspore/ops/_op_impl/tbe/apply_momentum.py
+++ b/mindspore/ops/_op_impl/tbe/apply_momentum.py
@@ -29,23 +29,24 @@ apply_momentum_op_info = TBERegOp("ApplyMomentum") \
     .input(2, "lr", False, "required", "all") \
     .input(3, "grad", False, "required", "all") \
     .input(4, "momentum", False, "required", "all") \
-    .output(0, "out", False, "required", "all") \
+    .output(0, "var", False, "required", "all") \
+    .output(1, "accum", False, "required", "all") \
     .dtype_format(DataType.F16_Default, DataType.F16_Default, DataType.F16_Default, DataType.F16_Default,
-                  DataType.F16_Default, DataType.F16_Default) \
+                  DataType.F16_Default, DataType.F16_Default, DataType.F16_Default) \
     .dtype_format(DataType.F16_5HD, DataType.F16_5HD, DataType.F16_Default, DataType.F16_5HD,
-                  DataType.F16_Default, DataType.F16_5HD) \
+                  DataType.F16_Default, DataType.F16_5HD, DataType.F16_5HD) \
     .dtype_format(DataType.F16_C1HWNCoC0, DataType.F16_C1HWNCoC0, DataType.F16_Default, DataType.F16_C1HWNCoC0,
-                  DataType.F16_Default, DataType.F16_C1HWNCoC0) \
+                  DataType.F16_Default, DataType.F16_C1HWNCoC0, DataType.F16_C1HWNCoC0) \
     .dtype_format(DataType.F16_FracZ, DataType.F16_FracZ, DataType.F16_Default, DataType.F16_FracZ,
-                  DataType.F16_Default, DataType.F16_FracZ) \
+                  DataType.F16_Default, DataType.F16_FracZ, DataType.F16_FracZ) \
     .dtype_format(DataType.F32_Default, DataType.F32_Default, DataType.F32_Default, DataType.F32_Default,
-                  DataType.F32_Default, DataType.F32_Default) \
+                  DataType.F32_Default, DataType.F32_Default, DataType.F32_Default) \
     .dtype_format(DataType.F32_5HD, DataType.F32_5HD, DataType.F32_Default, DataType.F32_5HD,
-                  DataType.F32_Default, DataType.F32_5HD) \
+                  DataType.F32_Default, DataType.F32_5HD, DataType.F32_5HD) \
     .dtype_format(DataType.F32_C1HWNCoC0, DataType.F32_C1HWNCoC0, DataType.F32_Default, DataType.F32_C1HWNCoC0,
-                  DataType.F32_Default, DataType.F32_C1HWNCoC0) \
+                  DataType.F32_Default, DataType.F32_C1HWNCoC0, DataType.F32_C1HWNCoC0) \
     .dtype_format(DataType.F32_FracZ, DataType.F32_FracZ, DataType.F32_Default, DataType.F32_FracZ,
-                  DataType.F32_Default, DataType.F32_FracZ) \
+                  DataType.F32_Default, DataType.F32_FracZ, DataType.F32_FracZ) \
     .get_op_info()
 
 
diff --git a/mindspore/ops/operations/nn_ops.py b/mindspore/ops/operations/nn_ops.py
index fb8e908924..2a2dbe08a8 100644
--- a/mindspore/ops/operations/nn_ops.py
+++ b/mindspore/ops/operations/nn_ops.py
@@ -1427,8 +1427,11 @@ class ApplyMomentum(PrimitiveWithInfer):
     def __init__(self, use_nesterov=False, use_locking=False, gradient_scale=1.0):
         self.init_prim_io_names(inputs=['variable', 'accumulation', 'learning_rate', 'gradient', 'momentum'],
                                 outputs=['output'])
+        self.is_tbe = context.get_context("device_target") == "Ascend"
 
     def infer_shape(self, v_shape, a_shape, l_shape, g_shape, m_shape):
+        if self.is_tbe:
+            return v_shape, v_shape
         return v_shape
 
     def infer_dtype(self, v_dtype, a_dtype, l_dtype, g_dtype, m_dtype):
@@ -1439,6 +1442,8 @@ class ApplyMomentum(PrimitiveWithInfer):
         validator.check_scalar_or_tensor_type_same({"l_dtype": l_dtype}, valid_types, self.name)
         validator.check_scalar_or_tensor_type_same({"g_dtype": g_dtype}, valid_types, self.name)
         validator.check_scalar_or_tensor_type_same({"m_dtype": m_dtype}, valid_types, self.name)
+        if self.is_tbe:
+            return g_dtype, g_dtype
         return g_dtype