diff --git a/tf_adapter/kernels/non_zero_with_value_ops.cc b/tf_adapter/kernels/non_zero_with_value_ops.cc
new file mode 100644
index 0000000000000000000000000000000000000000..b19df065120e18c35664d0199f94f44a8c35fb1f
--- /dev/null
+++ b/tf_adapter/kernels/non_zero_with_value_ops.cc
@@ -0,0 +1,40 @@
+/*
+ * Copyright (c) Huawei Technologies Co., Ltd. 2019-2020. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "tensorflow/core/framework/op_kernel.h"
+#include "tensorflow/core/framework/register_types.h"
+
+namespace tensorflow {
+template<typename T>
+class NonZeroWithValueOP : public OpKernel {
+ public:
+  explicit NonZeroWithValueOP(OpKernelConstruction*ctx) : OpKernel(ctx) {
+    LOG(INFO) << "new NonZeroWithValueOP";
+  }
+  ~NonZeroWithValueOP() {
+    LOG(INFO) << "del NonZeroWithValueOP";
+  }
+  void Compute(OpKernelContext*ctx) override {
+    LOG(INFO) << "compute in NonZeroWithValueOP";
+  }
+  bool IsExpensive() override { 
+    LOG(INFO) << "in NonZeroWithValue IsExpensive";
+    return false;
+  }
+};
+
+REGISTER_KERNEL_BUILDER(Name("NonZeroWithValue").Device(DEVICE_CPU), NonZeroWithValueOP<float>);
+}  //namespace tensorflow
\ No newline at end of file
diff --git a/tf_adapter/ops/npu_aicore_ops.cc b/tf_adapter/ops/npu_aicore_ops.cc
index c29f84c4052691f9bde100ca4b8bd2be42764bf5..e8899082f7bfd59f7d0336a54e8e1da9def9cc40 100644
--- a/tf_adapter/ops/npu_aicore_ops.cc
+++ b/tf_adapter/ops/npu_aicore_ops.cc
@@ -341,5 +341,28 @@ REGISTER_OP("NonZero")
         c->set_output(0, c->MakeShape({rank, -1}));
         return Status::OK();
     });
+
+REGISTER_OP("NonZeroWithValue")
+    .Input("x:T")
+    .Output("value:T")
+    .Output("index:output_type")
+    .Output("count:output_type")
+    .Attr("transpose:bool = false")
+    .Attr("T:numbertype")
+    .Attr("output_type:{int32, int64} = DT_INT64")
+    .SetIsStateful()
+    .SetShapeFn([](InferenceContext* c) {
+        auto input_shape = c->input(0);
+        int64_t dim1 = c->Value(c->Dim(input_shape, 0));
+        int64_t dim2 = c->Value(c->Dim(input_shape, 1));
+        int64_t value_num = dim1 * dim2;
+        int64_t index_dim = 2 * dim1 * dim2;
+        int64_t count_dim = 1;
+
+        c->set_output(0, c->MakeShape({c->MakeDim(value_num)}));
+        c->set_output(1, c->MakeShape({c->MakeDim(index_dim)}));
+        c->set_output(2, c->MakeShape({c->MakeDim(count_dim)}));
+        return Status::OK();
+    });
 }  // namespace
 } // namespace tensorflow
\ No newline at end of file
diff --git a/tf_adapter/python/npu_bridge/estimator/npu_aicore_ops.py b/tf_adapter/python/npu_bridge/estimator/npu_aicore_ops.py
index 2e03f817f09819c0781963dac2bce0bb7876e930..acaf4485536f7c043b909699a0cf631541153aab 100644
--- a/tf_adapter/python/npu_bridge/estimator/npu_aicore_ops.py
+++ b/tf_adapter/python/npu_bridge/estimator/npu_aicore_ops.py
@@ -162,4 +162,16 @@ def nonzero(x, transpose=False, output_type=dtypes.int64, name=None):
     x = ops.convert_to_tensor(x, name="x")
     result = npu_aicore_ops.non_zero(x, transpose, output_type, name=name)
     return result
+
+def nonzerowithvalue(x, transpose=False, output_type=dtypes.int64, name=None):
+    """
+    nonezero op
+    Return the indices of the elementes that are non-zero.
+    Return a tuple of arrays,one for each dimension of a ,containing the indices of the non-zero elementes in that dimension.
+    The values in a are always tested and returned in row-major ,C-style order.
+
+    """
+    x = ops.convert_to_tensor(x, name="x")
+    result = npu_aicore_ops.non_zero_with_value(x, transpose, output_type, name=name)
+    return result
 # go/tf-wildcard-import