diff --git a/paddle/fluid/framework/tensor.h b/paddle/fluid/framework/tensor.h
index f30dcc000b71428bcd8cbed64bd143de086cbacd..5a6b24bfafbe76c2c1a1ed309ece33d64cc969a7 100644
--- a/paddle/fluid/framework/tensor.h
+++ b/paddle/fluid/framework/tensor.h
@@ -98,9 +98,6 @@ class Tensor {
   /*! The internal of two tensors share the same memory block. */
   inline Tensor& ShareDataWith(const Tensor& src);
 
-  /*! Share part of the memory of the two tensors */
-  inline Tensor& ShareDataWith(const Tensor* src, size_t offset);
-
   /**
    * @brief  Return a sub-tensor of the given tensor.
    *
diff --git a/paddle/fluid/framework/tensor_impl.h b/paddle/fluid/framework/tensor_impl.h
index a177ef74166f202a205c6d306e84915e0f8f1129..f49d1a47a325b2aac6185073203df124be18b54d 100644
--- a/paddle/fluid/framework/tensor_impl.h
+++ b/paddle/fluid/framework/tensor_impl.h
@@ -162,37 +162,6 @@ inline Tensor& Tensor::ShareDataWith(const Tensor& src) {
   return *this;
 }
 
-inline Tensor& Tensor::ShareDataWith(const Tensor* src, size_t offset) {
-  // NOTE: data size is determined by current tensor shape and data type
-  src->check_memory_size();
-  PADDLE_ENFORCE_EQ(src->type(), this->type(),
-                    "tensor data type must be the same when sharing data");
-  auto place = src->place();
-  auto type = src->type();
-  size_t size = src->numel() * SizeOfType(src->type());
-  auto* ref = src->data<uint8_t>() + offset;
-  if (platform::is_cpu_place(place)) {
-    holder_.reset(new SharedPlaceholderImpl<platform::CPUPlace>(
-        boost::get<platform::CPUPlace>(place), ref, size, type));
-  } else if (platform::is_gpu_place(place) ||
-             platform::is_cuda_pinned_place(place)) {
-#ifndef PADDLE_WITH_CUDA
-    PADDLE_THROW(
-        "CUDAPlace or CUDAPinnedPlace is not supported in CPU-only mode.");
-  }
-#else
-    if (platform::is_gpu_place(place)) {
-      holder_.reset(new SharedPlaceholderImpl<platform::CUDAPlace>(
-          boost::get<platform::CUDAPlace>(place), ref, size, type));
-    } else if (platform::is_cuda_pinned_place(place)) {
-      holder_.reset(new SharedPlaceholderImpl<platform::CUDAPinnedPlace>(
-          boost::get<platform::CUDAPinnedPlace>(place), ref, size, type));
-    }
-  }
-#endif
-  return *this;
-}
-
 inline Tensor Tensor::Slice(int begin_idx, int end_idx) const {
   check_memory_size();
   PADDLE_ENFORCE_GE(begin_idx, 0,
diff --git a/paddle/fluid/operators/split_byref_op.h b/paddle/fluid/operators/split_byref_op.h
index 7c3ab1c1b9d9550c63b56056746c6223ce1b9c77..9b54c7c74acb512b9493d603e83380b9a92ac91b 100644
--- a/paddle/fluid/operators/split_byref_op.h
+++ b/paddle/fluid/operators/split_byref_op.h
@@ -26,15 +26,14 @@ class SplitByrefOpKernel : public framework::OpKernel<T> {
   void Compute(const framework::ExecutionContext& ctx) const override {
     auto* in = ctx.Input<framework::Tensor>("X");
     auto outs = ctx.MultiOutput<framework::Tensor>("Out");
-    auto in_stride = framework::stride_numel(in->dims());
     auto place = ctx.GetPlace();
 
-    size_t input_offset = 0;
+    size_t row_offset = 0;
     for (size_t i = 0; i < outs.size(); ++i) {
       // NOTE: no need to call mutable_data here to allocate memory.
       auto* out = outs[i];
-      out->ShareDataWith(in, input_offset);
-      input_offset += out->numel() * framework::SizeOfType(out->type());
+      *out = std::move(in->Slice(row_offset, out->dims()[0]));
+      row_offset += out->dims()[0];
     }
   }
 };