【Hackathon No.68】Remove utils in phi (#50833)

* remove utils

* remove utils

* remove utils

* remove utils

* Update get_data_from_tensor.h

* Update rnn_functor.h

* Update rnn_grad_kernel.cu.cc

* Update rnn_kernel.cu.cc

* Update rnn_kernel.cc

* Update rnn_grad_kernel.cu.cc

* Update rnn_functor.h

* Update rnn_kernel.cu.cc

* Update rnn_kernel.cc

* remove utils

* Update rnn_functor.h

* remove utils

* remove utils

* remove utils

* remove utils

* remove utils

* Update rnn_functor.h

* Update unsqueeze_op.h

* Update utils.h

* roll back

* Update tensor_utils.h

* Update tensor_utils.h

* Update tensor_utils.h

* Update tensor_utils.h

* Update tensor_utils.h

* use TensorToVector

* use TensorToVector

* use TensorToVector

* use TensorToVector

* use TensorToVector

* Update rnn_kernel.cc

* Update rnn_grad_kernel.cc

* Update rnn_functor.h

* Update rnn_grad_kernel.cu.cc

* Update rnn_kernel.cu.cc

* Update rnn_functor.h

* Update rnn_grad_kernel.cu.cc

* Update rnn_kernel.cu.cc

* Update rnn_functor.h

* Update rnn_grad_kernel.cu.cc

* Update rnn_kernel.cu.cc

* add TensorToVector

* roll back

* Update tensor_utils.h

* Update rnn_functor.h

* Update rnn_grad_kernel.cu.cc

* Update tensor_utils.h

* Update rnn_kernel.cu.cc

* Update rnn_grad_kernel.cc

* Update rnn_kernel.cc

* Update rnn_grad_kernel.cu.cc

* Update rnn_kernel.cu.cc

* Update rnn_grad_kernel.cc

* Update rnn_kernel.cc

* TensorCopySync to phi::Copy

* fix codestyle

* rnn_kernel.cc: add ;

* replace all GetDataFromTensor with phi::GetVectorFromTensor

* delete include of util.h

paddle/fluid/operators/concat_op_mlu.cc

@@ -14,6 +14,7 @@ limitations under the License. */
 
 #include "paddle/fluid/operators/concat_op.h"
 #include "paddle/fluid/operators/mlu/mlu_baseop.h"
+#include "paddle/phi/core/tensor_utils.h"
 
 namespace paddle {
 namespace operators {
@@ -32,7 +33,7 @@ class ConcatMLUKernel : public framework::OpKernel<T> {
     bool need_resize_out_dims = false;
     if (ctx.HasInput("AxisTensor")) {
       auto* axis_tensor = ctx.Input<phi::DenseTensor>("AxisTensor");
-      axis = GetDataFromTensor<int>(axis_tensor)[0];
+      axis = phi::GetVectorFromTensor<int>(axis_tensor)[0];
       need_resize_out_dims = true;
     }
     axis = ComputeAxis(static_cast<int64_t>(axis),
@@ -97,7 +98,7 @@ class ConcatGradMLUKernel : public framework::OpKernel<T> {
 
     if (ctx.HasInput("AxisTensor")) {
       auto* axis_tensor = ctx.Input<phi::DenseTensor>("AxisTensor");
-      axis = GetDataFromTensor<int>(axis_tensor)[0];
+      axis = phi::GetVectorFromTensor<int>(axis_tensor)[0];
     }
 
     axis = ComputeAxis(static_cast<int64_t>(axis),

paddle/fluid/operators/cudnn_lstm_op.cu.cc

@@ -13,8 +13,8 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #include "paddle/fluid/framework/op_registry.h"
-#include "paddle/fluid/operators/utils.h"
 #include "paddle/phi/core/generator.h"
+#include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/kernels/funcs/math_function.h"
 #ifdef PADDLE_WITH_CUDA
 #include "paddle/fluid/operators/cudnn_lstm_cache.h"
@@ -242,7 +242,7 @@ class CudnnLSTMGPUKernel : public framework::OpKernel<T> {
     std::vector<int> SequenceLength;
     if (has_seq_length) {
       auto *sequence_length = ctx.Input<phi::DenseTensor>("SequenceLength");
-      SequenceLength = operators::GetDataFromTensor<int>(sequence_length);
+      SequenceLength = phi::GetVectorFromTensor<int>(sequence_length);
     }
 
     auto &dev_ctx = ctx.template device_context<phi::GPUContext>();
@@ -532,7 +532,7 @@ class CudnnLSTMGPUGradKernel : public framework::OpKernel<T> {
     std::vector<int> SequenceLength;
     if (has_seq_length) {
       auto *sequence_length = ctx.Input<phi::DenseTensor>("SequenceLength");
-      SequenceLength = operators::GetDataFromTensor<int>(sequence_length);
+      SequenceLength = phi::GetVectorFromTensor<int>(sequence_length);
     }
 
     int seq_length = input_dims[0];

paddle/fluid/operators/interpolate_v2_op_mlu.cc

@@ -15,7 +15,7 @@ limitations under the License. */
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/operators/interpolate_op.h"
 #include "paddle/fluid/operators/mlu/mlu_baseop.h"
-#include "paddle/fluid/operators/utils.h"
+#include "paddle/phi/core/tensor_utils.h"
 
 namespace paddle {
 namespace operators {
@@ -96,7 +96,7 @@ class InterpolateV2MLUKernel : public framework::OpKernel<T> {
       auto scale = ctx.Attr<std::vector<float>>("scale");
       if (scale_tensor != nullptr) {
         std::vector<float> scale_data;
-        scale_data = GetDataFromTensor<float>(scale_tensor);
+        scale_data = phi::GetVectorFromTensor<float>(scale_tensor);
 
         if (scale_data.size() > 1 && scale_data.size() <= 2) {
           scale_h = scale_data[0];
@@ -147,7 +147,7 @@ class InterpolateV2MLUKernel : public framework::OpKernel<T> {
       auto out_size = ctx.Input<phi::DenseTensor>("OutSize");
       if (out_size != nullptr) {
         std::vector<int32_t> out_size_data;
-        out_size_data = GetDataFromTensor<int>(out_size);
+        out_size_data = phi::GetVectorFromTensor<int>(out_size);
         if (out_size_data.size() <= 2) {
           out_h = out_size_data[0];
           out_w = out_size_data[1];
@@ -398,7 +398,7 @@ class InterpolateV2GradMLUKernel : public framework::OpKernel<T> {
       auto scale = ctx.Attr<std::vector<float>>("scale");
       if (scale_tensor != nullptr) {
         std::vector<float> scale_data;
-        scale_data = GetDataFromTensor<float>(scale_tensor);
+        scale_data = phi::GetVectorFromTensor<float>(scale_tensor);
         if (scale_data.size() > 1) {
           scale_h = scale_data[0];
           scale_w = scale_data[1];
@@ -430,7 +430,7 @@ class InterpolateV2GradMLUKernel : public framework::OpKernel<T> {
       auto out_size = ctx.Input<phi::DenseTensor>("OutSize");
       if (out_size != nullptr) {
         std::vector<int32_t> out_size_data;
-        out_size_data = GetDataFromTensor<int>(out_size);
+        out_size_data = phi::GetVectorFromTensor<int>(out_size);
         out_h = out_size_data[0];
         out_w = out_size_data[1];
       }

paddle/fluid/operators/one_hot_v2_op_mlu.cc

@@ -15,7 +15,7 @@ limitations under the License. */
 
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/operators/mlu/mlu_baseop.h"
-#include "paddle/fluid/operators/utils.h"
+#include "paddle/phi/core/tensor_utils.h"
 
 namespace paddle {
 namespace operators {
@@ -31,8 +31,8 @@ class OneHotV2MLUKernel : public framework::OpKernel<T> {
     int depth = ctx.Attr<int>("depth");
     if (ctx.HasInput("depth_tensor")) {
       std::vector<int32_t> depth_data;
-      depth_data =
-          GetDataFromTensor<int>(ctx.Input<phi::DenseTensor>("depth_tensor"));
+      depth_data = phi::GetVectorFromTensor<int>(
+          ctx.Input<phi::DenseTensor>("depth_tensor"));
       depth = depth_data[0];
 
       auto out_dims = out->dims();

paddle/fluid/operators/reshape_op_mlu.cc

@@ -13,7 +13,7 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #include "paddle/fluid/framework/op_registry.h"
-#include "paddle/fluid/operators/utils.h"
+#include "paddle/phi/core/tensor_utils.h"
 
 namespace paddle {
 namespace operators {
@@ -38,14 +38,15 @@ class Reshape2MLUKernel : public framework::OpKernel<T> {
                 "shape is [%d]",
                 shape_tensor->dims().size()));
 
-        target_shape_vector.push_back(GetDataFromTensor<int>(shape_tensor)[0]);
+        target_shape_vector.push_back(
+            phi::GetVectorFromTensor<int>(shape_tensor)[0]);
       }
     } else {
       auto* shape_tensor = ctx.HasInput("Shape")
                                ? ctx.Input<phi::DenseTensor>("Shape")
                                : nullptr;
       if (shape_tensor) {
-        target_shape_vector = GetDataFromTensor<int>(shape_tensor);
+        target_shape_vector = phi::GetVectorFromTensor<int>(shape_tensor);
       } else {
         target_shape_vector = ctx.Attr<std::vector<int>>("shape");
         PADDLE_ENFORCE_GT(

paddle/fluid/operators/reshape_op_npu.cc

@@ -16,8 +16,8 @@ limitations under the License. */
 #include <string>
 
 #include "paddle/fluid/framework/op_registry.h"
-#include "paddle/fluid/operators/utils.h"
 #include "paddle/fluid/platform/device/npu/npu_op_runner.h"
+#include "paddle/phi/core/tensor_utils.h"
 
 namespace paddle {
 namespace operators {
@@ -46,14 +46,15 @@ class Reshape2NPUKernel : public framework::OpKernel<T> {
                 "shape is [%d]",
                 shape_tensor->dims().size()));
 
-        target_shape_vector.push_back(GetDataFromTensor<int>(shape_tensor)[0]);
+        target_shape_vector.push_back(
+            phi::GetVectorFromTensor<int>(shape_tensor)[0]);
       }
     } else {
       auto* shape_tensor = ctx.HasInput("Shape")
                                ? ctx.Input<phi::DenseTensor>("Shape")
                                : nullptr;
       if (shape_tensor) {
-        target_shape_vector = GetDataFromTensor<int>(shape_tensor);
+        target_shape_vector = phi::GetVectorFromTensor<int>(shape_tensor);
       } else {
         target_shape_vector = ctx.Attr<std::vector<int>>("shape");
         PADDLE_ENFORCE_GT(

paddle/fluid/operators/rnn_op_mlu.cc

@@ -11,10 +11,10 @@ limitations under the License. */
 
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/operators/mlu/mlu_baseop.h"
-#include "paddle/fluid/operators/utils.h"
 #include "paddle/fluid/platform/device/device_wrapper.h"
 #include "paddle/fluid/platform/device/xpu/xpu_header.h"
 #include "paddle/fluid/platform/device_context.h"
+#include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/kernels/funcs/math_function.h"
 
 namespace paddle {
@@ -97,7 +97,7 @@ class RNNMLUKernel : public framework::OpKernel<T> {
     std::vector<int> seq_len_vec(batch_size, seq_len);
     if (has_seq_length) {  // set seq_len if no padding, otherwise seq_len for
                            // each element.
-      seq_len_vec = operators::GetDataFromTensor(sequence_length);
+      seq_len_vec = phi::GetVectorFromTensor(sequence_length);
     }
     cnnlDirectionMode_t direction =
         is_bidirec ? CNNL_RNN_BIDIRECTIONAL : CNNL_RNN_UNIDIRECTIONAL;
@@ -480,7 +480,7 @@ class RNNMLUGradKernel : public framework::OpKernel<T> {
 
     std::vector<int> seq_len_vec(batch_size, seq_len);
     if (has_seq_length) {
-      seq_len_vec = operators::GetDataFromTensor(sequence_length);
+      seq_len_vec = phi::GetVectorFromTensor(sequence_length);
     }
     cnnlDirectionMode_t direction =
         is_bidirec ? CNNL_RNN_BIDIRECTIONAL : CNNL_RNN_UNIDIRECTIONAL;

paddle/fluid/operators/slice_op_mlu.cc

@@ -15,6 +15,7 @@ limitations under the License. */
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/operators/mlu/mlu_baseop.h"
 #include "paddle/fluid/operators/utils.h"
+#include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/kernels/funcs/slice_utils.h"
 
 namespace paddle {
@@ -38,15 +39,16 @@ class SliceMLUKernel : public framework::OpKernel<T> {
     auto starts_tensor_list =
         ctx.MultiInput<phi::DenseTensor>("StartsTensorList");
     if (ctx.HasInput("StartsTensor")) {
-      starts =
-          GetDataFromTensor<int>(ctx.Input<phi::DenseTensor>("StartsTensor"));
+      starts = phi::GetVectorFromTensor<int>(
+          ctx.Input<phi::DenseTensor>("StartsTensor"));
     } else if (starts_tensor_list.size() > 0) {
       starts = GetDataFromTensorList<int>(starts_tensor_list);
     }
 
     auto ends_tensor_list = ctx.MultiInput<phi::DenseTensor>("EndsTensorList");
     if (ctx.HasInput("EndsTensor")) {
-      ends = GetDataFromTensor<int>(ctx.Input<phi::DenseTensor>("EndsTensor"));
+      ends = phi::GetVectorFromTensor<int>(
+          ctx.Input<phi::DenseTensor>("EndsTensor"));
     } else if (ends_tensor_list.size() > 0) {
       ends = GetDataFromTensorList<int>(ends_tensor_list);
     }
@@ -141,15 +143,16 @@ class SliceGradMLUKernel : public framework::OpKernel<T> {
     auto starts_tensor_list =
         ctx.MultiInput<phi::DenseTensor>("StartsTensorList");
     if (ctx.HasInput("StartsTensor")) {
-      starts =
-          GetDataFromTensor<int>(ctx.Input<phi::DenseTensor>("StartsTensor"));
+      starts = phi::GetVectorFromTensor<int>(
+          ctx.Input<phi::DenseTensor>("StartsTensor"));
     } else if (starts_tensor_list.size() > 0) {
       starts = GetDataFromTensorList<int>(starts_tensor_list);
     }
 
     auto ends_tensor_list = ctx.MultiInput<phi::DenseTensor>("EndsTensorList");
     if (ctx.HasInput("EndsTensor")) {
-      ends = GetDataFromTensor<int>(ctx.Input<phi::DenseTensor>("EndsTensor"));
+      ends = phi::GetVectorFromTensor<int>(
+          ctx.Input<phi::DenseTensor>("EndsTensor"));
     } else if (ends_tensor_list.size() > 0) {
       ends = GetDataFromTensorList<int>(ends_tensor_list);
     }

paddle/fluid/operators/slice_op_npu.cc

@@ -15,6 +15,7 @@ limitations under the License. */
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/operators/utils.h"
 #include "paddle/fluid/platform/device/npu/npu_op_runner.h"
+#include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/kernels/funcs/slice_utils.h"
 
 namespace paddle {
@@ -77,15 +78,16 @@ class SliceNPUKernel : public framework::OpKernel<T> {
     auto starts_tensor_list =
         ctx.MultiInput<phi::DenseTensor>("StartsTensorList");
     if (ctx.HasInput("StartsTensor")) {
-      starts =
-          GetDataFromTensor<int>(ctx.Input<phi::DenseTensor>("StartsTensor"));
+      starts = phi::GetVectorFromTensor<int>(
+          ctx.Input<phi::DenseTensor>("StartsTensor"));
     } else if (starts_tensor_list.size() > 0) {
       starts = GetDataFromTensorList<int>(starts_tensor_list);
     }
 
     auto ends_tensor_list = ctx.MultiInput<phi::DenseTensor>("EndsTensorList");
     if (ctx.HasInput("EndsTensor")) {
-      ends = GetDataFromTensor<int>(ctx.Input<phi::DenseTensor>("EndsTensor"));
+      ends = phi::GetVectorFromTensor<int>(
+          ctx.Input<phi::DenseTensor>("EndsTensor"));
     } else if (ends_tensor_list.size() > 0) {
       ends = GetDataFromTensorList<int>(ends_tensor_list);
     }
@@ -172,15 +174,16 @@ class SliceGradNPUKernel : public framework::OpKernel<T> {
     auto starts_tensor_list =
         ctx.MultiInput<phi::DenseTensor>("StartsTensorList");
     if (ctx.HasInput("StartsTensor")) {
-      starts =
-          GetDataFromTensor<int>(ctx.Input<phi::DenseTensor>("StartsTensor"));
+      starts = phi::GetVectorFromTensor<int>(
+          ctx.Input<phi::DenseTensor>("StartsTensor"));
     } else if (starts_tensor_list.size() > 0) {
       starts = GetDataFromTensorList<int>(starts_tensor_list);
     }
 
     auto ends_tensor_list = ctx.MultiInput<phi::DenseTensor>("EndsTensorList");
     if (ctx.HasInput("EndsTensor")) {
-      ends = GetDataFromTensor<int>(ctx.Input<phi::DenseTensor>("EndsTensor"));
+      ends = phi::GetVectorFromTensor<int>(
+          ctx.Input<phi::DenseTensor>("EndsTensor"));
     } else if (ends_tensor_list.size() > 0) {
       ends = GetDataFromTensorList<int>(ends_tensor_list);
     }

paddle/fluid/operators/split_op_mlu.cc

@@ -14,6 +14,7 @@ limitations under the License. */
 
 #include "paddle/fluid/operators/mlu/mlu_baseop.h"
 #include "paddle/fluid/operators/split_op.h"
+#include "paddle/phi/core/tensor_utils.h"
 
 namespace paddle {
 namespace operators {
@@ -35,7 +36,7 @@ class SplitMLUKernel : public framework::OpKernel<T> {
     bool need_resize_outs_dims = false;
     if (ctx.HasInput("AxisTensor")) {
       auto* axis_tensor = ctx.Input<phi::DenseTensor>("AxisTensor");
-      axis = GetDataFromTensor(axis_tensor)[0];
+      axis = phi::GetVectorFromTensor(axis_tensor)[0];
       need_resize_outs_dims = true;
     }
     auto sections_tensor_list =

paddle/fluid/operators/strided_slice_op_mlu.cc

@@ -15,6 +15,7 @@ limitations under the License. */
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/operators/mlu/mlu_baseop.h"
 #include "paddle/fluid/operators/utils.h"
+#include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/kernels/funcs/strided_slice.h"
 
 namespace paddle {
@@ -168,21 +169,21 @@ class StridedSliceMLUKernel : public framework::OpKernel<T> {
       starts = GetDataFromTensorList<int64_t>(list_new_starts_tensor);
     } else if (ctx.HasInput("StartsTensor")) {
       auto* starts_tensor = ctx.Input<phi::DenseTensor>("StartsTensor");
-      starts = GetDataFromTensor<int64_t>(starts_tensor);
+      starts = phi::GetVectorFromTensor<int64_t>(starts_tensor);
     }
 
     if (list_new_ends_tensor.size() > 0) {
       ends = GetDataFromTensorList<int64_t>(list_new_ends_tensor);
     } else if (ctx.HasInput("EndsTensor")) {
       auto* ends_tensor = ctx.Input<phi::DenseTensor>("EndsTensor");
-      ends = GetDataFromTensor<int64_t>(ends_tensor);
+      ends = phi::GetVectorFromTensor<int64_t>(ends_tensor);
     }
 
     if (list_new_strides_tensor.size() > 0) {
       strides = GetDataFromTensorList<int64_t>(list_new_strides_tensor);
     } else if (ctx.HasInput("StridesTensor")) {
       auto* strides_tensor = ctx.Input<phi::DenseTensor>("StridesTensor");
-      strides = GetDataFromTensor<int64_t>(strides_tensor);
+      strides = phi::GetVectorFromTensor<int64_t>(strides_tensor);
     }
 
     // out dims calculation
@@ -336,21 +337,21 @@ class StridedSliceGradMLUKernel : public framework::OpKernel<T> {
       starts = GetDataFromTensorList<int64_t>(list_new_starts_tensor);
     } else if (ctx.HasInput("StartsTensor")) {
       auto* starts_tensor = ctx.Input<phi::DenseTensor>("StartsTensor");
-      starts = GetDataFromTensor<int64_t>(starts_tensor);
+      starts = phi::GetVectorFromTensor<int64_t>(starts_tensor);
     }
 
     if (list_new_ends_tensor.size() > 0) {
       ends = GetDataFromTensorList<int64_t>(list_new_ends_tensor);
     } else if (ctx.HasInput("EndsTensor")) {
       auto* ends_tensor = ctx.Input<phi::DenseTensor>("EndsTensor");
-      ends = GetDataFromTensor<int64_t>(ends_tensor);
+      ends = phi::GetVectorFromTensor<int64_t>(ends_tensor);
     }
 
     if (list_new_strides_tensor.size() > 0) {
       strides = GetDataFromTensorList<int64_t>(list_new_strides_tensor);
     } else if (ctx.HasInput("StridesTensor")) {
       auto* strides_tensor = ctx.Input<phi::DenseTensor>("StridesTensor");
-      strides = GetDataFromTensor<int64_t>(strides_tensor);
+      strides = phi::GetVectorFromTensor<int64_t>(strides_tensor);
     }
 
     std::vector<int64_t> out_dims_vector(input_dims.size(), -1);

paddle/fluid/operators/strided_slice_op_npu.cc

@@ -15,6 +15,7 @@ limitations under the License. */
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/operators/utils.h"
 #include "paddle/fluid/platform/device/npu/npu_op_runner.h"
+#include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/kernels/funcs/strided_slice.h"
 
 namespace paddle {
@@ -99,21 +100,21 @@ class StridedSliceNPUKernel : public framework::OpKernel<T> {
       starts = GetDataFromTensorList<int64_t>(list_new_starts_tensor);
     } else if (ctx.HasInput("StartsTensor")) {
       auto* starts_tensor = ctx.Input<phi::DenseTensor>("StartsTensor");
-      starts = GetDataFromTensor<int64_t>(starts_tensor);
+      starts = phi::GetVectorFromTensor<int64_t>(starts_tensor);
     }
 
     if (list_new_ends_tensor.size() > 0) {
       ends = GetDataFromTensorList<int64_t>(list_new_ends_tensor);
     } else if (ctx.HasInput("EndsTensor")) {
       auto* ends_tensor = ctx.Input<phi::DenseTensor>("EndsTensor");
-      ends = GetDataFromTensor<int64_t>(ends_tensor);
+      ends = phi::GetVectorFromTensor<int64_t>(ends_tensor);
     }
 
     if (list_new_strides_tensor.size() > 0) {
       strides = GetDataFromTensorList<int64_t>(list_new_strides_tensor);
     } else if (ctx.HasInput("StridesTensor")) {
       auto* strides_tensor = ctx.Input<phi::DenseTensor>("StridesTensor");
-      strides = GetDataFromTensor<int64_t>(strides_tensor);
+      strides = phi::GetVectorFromTensor<int64_t>(strides_tensor);
     }
 
     // out dims calculation
@@ -325,21 +326,21 @@ class StridedSliceGradNPUKernel : public framework::OpKernel<T> {
       starts = GetDataFromTensorList<int64_t>(list_new_starts_tensor);
     } else if (ctx.HasInput("StartsTensor")) {
       auto* starts_tensor = ctx.Input<phi::DenseTensor>("StartsTensor");
-      starts = GetDataFromTensor<int64_t>(starts_tensor);
+      starts = phi::GetVectorFromTensor<int64_t>(starts_tensor);
     }
 
     if (list_new_ends_tensor.size() > 0) {
       ends = GetDataFromTensorList<int64_t>(list_new_ends_tensor);
     } else if (ctx.HasInput("EndsTensor")) {
       auto* ends_tensor = ctx.Input<phi::DenseTensor>("EndsTensor");
-      ends = GetDataFromTensor<int64_t>(ends_tensor);
+      ends = phi::GetVectorFromTensor<int64_t>(ends_tensor);
     }
 
     if (list_new_strides_tensor.size() > 0) {
       strides = GetDataFromTensorList<int64_t>(list_new_strides_tensor);
     } else if (ctx.HasInput("StridesTensor")) {
       auto* strides_tensor = ctx.Input<phi::DenseTensor>("StridesTensor");
-      strides = GetDataFromTensor<int64_t>(strides_tensor);
+      strides = phi::GetVectorFromTensor<int64_t>(strides_tensor);
     }
 
     std::vector<int64_t> out_dims_vector(input_dims.size(), -1);

paddle/fluid/operators/unsqueeze_op.h

@@ -19,6 +19,7 @@ limitations under the License. */
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/operators/utils.h"
 #include "paddle/fluid/platform/device_context.h"
+#include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/kernels/funcs/blas/blas.h"
 #include "paddle/phi/kernels/funcs/math_function.h"
 
@@ -42,7 +43,7 @@ class UnsqueezeKernel : public framework::OpKernel<T> {
         axes = GetDataFromTensorList<int>(axes_tensor_list);
       } else if (context.HasInput("AxesTensor")) {
         auto *axes_tensor = context.Input<phi::DenseTensor>("AxesTensor");
-        axes = GetDataFromTensor<int>(axes_tensor);
+        axes = phi::GetVectorFromTensor<int>(axes_tensor);
       }
       need_resize_out_dims = true;
     }

paddle/fluid/operators/utils.h

@@ -18,41 +18,11 @@ limitations under the License. */
 #include <string>
 #include <vector>
 
+#include "paddle/phi/core/tensor_utils.h"
+
 namespace paddle {
 namespace operators {
 
-template <typename T = int32_t>
-inline std::vector<T> GetDataFromTensor(const phi::DenseTensor* x) {
-  std::vector<T> vec_new_data;
-  if (framework::TransToProtoVarType(x->dtype()) ==
-      framework::proto::VarType::INT32) {
-    auto* data = x->data<int>();
-    phi::DenseTensor cpu_attr_tensor;
-    if (!platform::is_cpu_place(x->place())) {
-      paddle::framework::TensorCopySync(
-          *x, platform::CPUPlace(), &cpu_attr_tensor);
-      data = cpu_attr_tensor.data<int>();
-    }
-    vec_new_data = std::vector<T>(data, data + x->numel());
-  } else if (framework::TransToProtoVarType(x->dtype()) ==
-             framework::proto::VarType::INT64) {
-    auto* data = x->data<int64_t>();
-    phi::DenseTensor cpu_attr_tensor;
-    if (!platform::is_cpu_place(x->place())) {
-      paddle::framework::TensorCopySync(
-          *x, platform::CPUPlace(), &cpu_attr_tensor);
-      data = cpu_attr_tensor.data<int64_t>();
-    }
-    // NOTE: Converting int64 to int32 may cause data overflow.
-    vec_new_data = std::vector<T>(data, data + x->numel());
-  } else {
-    PADDLE_THROW(platform::errors::InvalidArgument(
-        "The dtype of Tensor must be int32 or int64, but received: %s",
-        framework::TransToProtoVarType(x->dtype())));
-  }
-  return vec_new_data;
-}
-
 template <typename T = int32_t>
 inline std::vector<T> GetDataFromTensorList(
     const std::vector<const phi::DenseTensor*>& list_tensor) {
@@ -100,7 +70,7 @@ inline framework::DDim GetShape(const framework::ExecutionContext& ctx) {
   // 1. shape is a Tensor
   if (ctx.HasInput("ShapeTensor")) {
     auto* shape_tensor = ctx.Input<phi::DenseTensor>("ShapeTensor");
-    auto vec_shape = GetDataFromTensor<int>(shape_tensor);
+    auto vec_shape = phi::GetVectorFromTensor<int>(shape_tensor);
     return phi::make_ddim(vec_shape);
   }
 

paddle/phi/core/tensor_utils.h

@@ -14,12 +14,16 @@ limitations under the License. */
 
 #pragma once
 
+#include "paddle/phi/backends/all_context.h"
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/common/place.h"
 #include "paddle/phi/core/dense_tensor.h"
 #include "paddle/phi/core/device_context.h"
 #include "paddle/phi/core/selected_rows.h"
 #include "paddle/phi/core/sparse_coo_tensor.h"
 #include "paddle/phi/core/sparse_csr_tensor.h"
 #include "paddle/phi/core/tensor_meta.h"
+#include "paddle/phi/core/utils/data_type.h"
 
 namespace phi {
 
@@ -144,4 +148,36 @@ inline T GetValue(const Context& dev_ctx, const DenseTensor& x) {
   return value;
 }
 
+template <typename T = int32_t>
+inline std::vector<T> GetVectorFromTensor(const phi::DenseTensor* x) {
+  std::vector<T> vec_new_data;
+  if (phi::TransToProtoVarType(x->dtype()) == ProtoDataType::INT32) {
+    auto* data = x->data<int>();
+    phi::DenseTensor cpu_attr_tensor;
+    if (!paddle::platform::is_cpu_place(x->place())) {
+      phi::DeviceContextPool& pool = phi::DeviceContextPool::Instance();
+      auto dev_ctx = pool.Get(x->place());
+      phi::Copy(*dev_ctx, *x, CPUPlace(), true, &cpu_attr_tensor);
+      data = cpu_attr_tensor.data<int>();
+    }
+    vec_new_data = std::vector<T>(data, data + x->numel());
+  } else if (phi::TransToProtoVarType(x->dtype()) == ProtoDataType::INT64) {
+    auto* data = x->data<int64_t>();
+    phi::DenseTensor cpu_attr_tensor;
+    if (!paddle::platform::is_cpu_place(x->place())) {
+      phi::DeviceContextPool& pool = phi::DeviceContextPool::Instance();
+      auto dev_ctx = pool.Get(x->place());
+      phi::Copy(*dev_ctx, *x, CPUPlace(), true, &cpu_attr_tensor);
+      data = cpu_attr_tensor.data<int64_t>();
+    }
+    // NOTE: Converting int64 to int32 may cause data overflow.
+    vec_new_data = std::vector<T>(data, data + x->numel());
+  } else {
+    PADDLE_THROW(phi::errors::InvalidArgument(
+        "The dtype of Tensor must be int32 or int64, but received: %s",
+        phi::TransToProtoVarType(x->dtype())));
+  }
+  return vec_new_data;
+}
+
 }  // namespace phi

paddle/phi/kernels/cpu/rnn_functor.h

@@ -14,7 +14,6 @@
 
 #pragma once
 
-#include "paddle/fluid/operators/utils.h"
 #include "paddle/phi/core/dense_tensor.h"
 #include "paddle/phi/core/generator.h"
 #include "paddle/phi/core/tensor_utils.h"
@@ -47,8 +46,7 @@ void CreateMaskMatrix(const CPUContext& dev_ctx,
                       DenseTensor* mask_matrix,
                       const bool& is_reverse,
                       int* min_seq_len) {
-  const auto& seq_len_vec =
-      paddle::operators::GetDataFromTensor<int>(sequence_length);
+  const auto& seq_len_vec = phi::GetVectorFromTensor<int>(sequence_length);
   const int table_width = mask_matrix->dims()[0];
   DenseTensor temp =
       Empty<T>(dev_ctx, {mask_matrix->dims()[1], mask_matrix->dims()[0]});

paddle/phi/kernels/gpu/rnn_grad_kernel.cu.cc

@@ -14,9 +14,9 @@
 
 #include "paddle/phi/kernels/rnn_grad_kernel.h"
 
-#include "paddle/fluid/operators/utils.h"
 #include "paddle/phi/backends/gpu/gpu_context.h"
 #include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/kernels/empty_kernel.h"
 #include "paddle/phi/kernels/full_kernel.h"
 #include "paddle/phi/kernels/gpu/rnn_functor.h"
@@ -223,8 +223,7 @@ void RnnGradKernel(const Context &dev_ctx,
 #endif
   std::vector<int> SequenceLength;
   if (has_seq_length) {
-    SequenceLength =
-        paddle::operators::GetDataFromTensor<int>(sequence_length.get_ptr());
+    SequenceLength = phi::GetVectorFromTensor<int>(sequence_length.get_ptr());
   }
 
   auto input_dims = x.dims();

paddle/phi/kernels/gpu/rnn_kernel.cu.cc

@@ -14,10 +14,10 @@
 
 #include "paddle/phi/kernels/rnn_kernel.h"
 
-#include "paddle/fluid/operators/utils.h"
 #include "paddle/phi/backends/gpu/gpu_context.h"
 #include "paddle/phi/core/generator.h"
 #include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/kernels/empty_kernel.h"
 #include "paddle/phi/kernels/gpu/rnn_functor.h"
 
@@ -205,8 +205,7 @@ void RnnKernel(const Context &dev_ctx,
 #endif
   std::vector<int> SequenceLength;
   if (has_seq_length) {
-    SequenceLength =
-        paddle::operators::GetDataFromTensor<int>(sequence_length.get_ptr());
+    SequenceLength = phi::GetVectorFromTensor<int>(sequence_length.get_ptr());
   }
 
   auto handle = dev_ctx.cudnn_handle();

paddle/phi/kernels/xpu/rnn_grad_kernel.cc

@@ -13,9 +13,9 @@
 // limitations under the License.
 
 #include "paddle/phi/kernels/rnn_grad_kernel.h"
-#include "paddle/fluid/operators/utils.h"
 #include "paddle/phi/backends/xpu/enforce_xpu.h"
 #include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/kernels/funcs/math_function.h"
 #include "paddle/phi/kernels/xpu/rnn_util.h"
 
@@ -165,8 +165,7 @@ void RnnGradKernel(const Context& dev_ctx,
   bool has_seq_length = sequence_length.is_initialized();
   std::vector<int> seq_len_tensor(batch_size, seq_len);
   if (has_seq_length) {
-    seq_len_tensor =
-        paddle::operators::GetDataFromTensor<int>(sequence_length.get_ptr());
+    seq_len_tensor = phi::GetVectorFromTensor<int>(sequence_length.get_ptr());
   }
 
   for (int i = num_layers - 1; i >= 0; --i) {

paddle/phi/kernels/xpu/rnn_kernel.cc

@@ -13,9 +13,9 @@
 // limitations under the License.
 
 #include "paddle/phi/kernels/rnn_kernel.h"
-#include "paddle/fluid/operators/utils.h"
 #include "paddle/phi/backends/xpu/enforce_xpu.h"
 #include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/kernels/funcs/math_function.h"
 #include "paddle/phi/kernels/xpu/rnn_util.h"
 
@@ -119,8 +119,7 @@ void RnnKernel(const Context& dev_ctx,
   bool has_seq_length = sequence_length.is_initialized();
 
   if (has_seq_length) {
-    seq_len_tensor =
-        paddle::operators::GetDataFromTensor<int>(sequence_length.get_ptr());
+    seq_len_tensor = phi::GetVectorFromTensor<int>(sequence_length.get_ptr());
   }
 
   int state_offset = pre_state[0]->dims()[1] * pre_state[0]->dims()[2];