[PHI decoupling] migrate transpose_op.cu.h and gpu_utils.h to phi (#48286)

* migrate transpose_op.cu.h and gpu_utils.h

* format code style

* fix some problems

* format code

* reset tranpose_op.cc

* test commit

* recover transpose_op.h

* delete transpose_op.h

* adjust header files order in transpose_op.cc

paddle/fluid/operators/fused/fmha_ref.h

@@ -16,12 +16,12 @@ limitations under the License. */
 
 #include "paddle/fluid/operators/dropout_impl.cu.h"
 #include "paddle/fluid/operators/fused/fused_softmax_mask.cu.h"
-#include "paddle/fluid/operators/transpose_op.cu.h"
 #include "paddle/phi/kernels/funcs/broadcast_function.h"
 #include "paddle/phi/kernels/funcs/concat_and_split_functor.h"
 #include "paddle/phi/kernels/funcs/elementwise_base.h"
 #include "paddle/phi/kernels/funcs/elementwise_functor.h"
 #include "paddle/phi/kernels/funcs/functors.h"
+#include "paddle/phi/kernels/funcs/transpose_functor.cu.h"
 #include "paddle/phi/kernels/gpudnn/softmax_gpudnn.h"
 
 namespace paddle {
@@ -98,7 +98,7 @@ class FMHARef {
     // transpose with perm [2, 0, 3, 1, 4],
     // output_shape: [3, bs, num_head, seq_len, head_dim]
     std::vector<int> perm_1 = {2, 0, 3, 1, 4};
-    TransposeGPUKernelDriver<T>(
+    phi::funcs::TransposeGPUKernelDriver<T>(
         dev_ctx_, qkv_input_tensor, perm_1, transpose_2_out_tensor);
     T* qkv_data = transpose_2_out_tensor->data<T>();
     T* qk_out_data = qk_out_tensor->data<T>();
@@ -254,7 +254,7 @@ class FMHARef {
     // transpose: [0, 2, 1, 3]
     // output shape: [batch_size, seq_len, num_heads, head_dim]
     std::vector<int> perm_3 = {0, 2, 1, 3};
-    TransposeGPUKernelDriver<T>(
+    phi::funcs::TransposeGPUKernelDriver<T>(
         dev_ctx_, *qktv_out_tensor, perm_3, fmha_out_tensor);
   }
 
@@ -428,7 +428,7 @@ class FMHARef {
     // transpose: [0, 2, 1, 3]
     // output shape: [batch_size, seq_len, num_heads, head_dim]
     std::vector<int> perm_3 = {0, 2, 1, 3};
-    TransposeGPUKernelDriver<T>(
+    phi::funcs::TransposeGPUKernelDriver<T>(
         dev_ctx_, *qktv_out_tensor, perm_3, fmha_out_tensor);
   }
 
@@ -470,7 +470,7 @@ class FMHARef {
 
     // transpose bw
     std::vector<int> perm_3 = {0, 2, 1, 3};
-    TransposeGPUKernelDriver<T>(
+    phi::funcs::TransposeGPUKernelDriver<T>(
         dev_ctx_, fmha_out_grad_tensor, perm_3, qktv_out_grad_tensor);
 
     // recall batchedgemm(nn) fw: softmax_out_data(x) * v_ptr(y) =
@@ -648,7 +648,7 @@ class FMHARef {
 
     // transpose bw
     std::vector<int> perm_1 = {1, 3, 0, 2, 4};
-    TransposeGPUKernelDriver<T>(
+    phi::funcs::TransposeGPUKernelDriver<T>(
         dev_ctx_, *transpose_2_out_grad_tensor, perm_1, qkv_input_grad_tensor);
   }
 

paddle/fluid/operators/fused/fused_gate_attention.h

@@ -14,11 +14,11 @@ limitations under the License. */
 
 #pragma once
 
-#include "paddle/fluid/operators/transpose_op.cu.h"
 #include "paddle/phi/kernels/funcs/broadcast_function.h"
 #include "paddle/phi/kernels/funcs/elementwise_base.h"
 #include "paddle/phi/kernels/funcs/elementwise_functor.h"
 #include "paddle/phi/kernels/funcs/reduce_function.h"
+#include "paddle/phi/kernels/funcs/transpose_functor.cu.h"
 #include "paddle/phi/kernels/gpudnn/softmax_gpudnn.h"
 
 namespace paddle {
@@ -626,9 +626,12 @@ class FMHAGateRef {
                                   phi::DenseTensor* k_transpose_out,
                                   phi::DenseTensor* v_transpose_out) {
     std::vector<int> perm = {0, 1, 3, 2, 4};
-    TransposeGPUKernelDriver<T>(dev_ctx_, q_out, perm, q_transpose_out);
-    TransposeGPUKernelDriver<T>(dev_ctx_, k_out, perm, k_transpose_out);
-    TransposeGPUKernelDriver<T>(dev_ctx_, v_out, perm, v_transpose_out);
+    phi::funcs::TransposeGPUKernelDriver<T>(
+        dev_ctx_, q_out, perm, q_transpose_out);
+    phi::funcs::TransposeGPUKernelDriver<T>(
+        dev_ctx_, k_out, perm, k_transpose_out);
+    phi::funcs::TransposeGPUKernelDriver<T>(
+        dev_ctx_, v_out, perm, v_transpose_out);
   }
 
   void ComputeQKVTransposeBackward(const phi::DenseTensor& q_transpose_out_grad,
@@ -638,11 +641,11 @@ class FMHAGateRef {
                                    phi::DenseTensor* k_out_grad,
                                    phi::DenseTensor* v_out_grad) {
     std::vector<int> perm = {0, 1, 3, 2, 4};
-    TransposeGPUKernelDriver<T>(
+    phi::funcs::TransposeGPUKernelDriver<T>(
         dev_ctx_, q_transpose_out_grad, perm, q_out_grad);
-    TransposeGPUKernelDriver<T>(
+    phi::funcs::TransposeGPUKernelDriver<T>(
         dev_ctx_, k_transpose_out_grad, perm, k_out_grad);
-    TransposeGPUKernelDriver<T>(
+    phi::funcs::TransposeGPUKernelDriver<T>(
         dev_ctx_, v_transpose_out_grad, perm, v_out_grad);
   }
 
@@ -651,14 +654,15 @@ class FMHAGateRef {
   void ComputeQKVTransposeForward(const phi::DenseTensor& qkv_out,
                                   phi::DenseTensor* qkv_transpose_out) {
     std::vector<int> perm = {3, 0, 1, 4, 2, 5};
-    TransposeGPUKernelDriver<T>(dev_ctx_, qkv_out, perm, qkv_transpose_out);
+    phi::funcs::TransposeGPUKernelDriver<T>(
+        dev_ctx_, qkv_out, perm, qkv_transpose_out);
   }
 
   void ComputeQKVTransposeBackward(
       const phi::DenseTensor& qkv_transpose_out_grad,
       phi::DenseTensor* qkv_out_grad) {
     std::vector<int> perm = {1, 2, 4, 0, 3, 5};
-    TransposeGPUKernelDriver<T>(
+    phi::funcs::TransposeGPUKernelDriver<T>(
         dev_ctx_, qkv_transpose_out_grad, perm, qkv_out_grad);
   }
 
@@ -667,13 +671,14 @@ class FMHAGateRef {
   void ComputeQKTVTransposeForward(const phi::DenseTensor& qktv_out,
                                    phi::DenseTensor* fmha_out) {
     std::vector<int> perm = {0, 1, 3, 2, 4};
-    TransposeGPUKernelDriver<T>(dev_ctx_, qktv_out, perm, fmha_out);
+    phi::funcs::TransposeGPUKernelDriver<T>(dev_ctx_, qktv_out, perm, fmha_out);
   }
 
   void ComputeQKTVTransposeBackward(const phi::DenseTensor& fmha_out_grad,
                                     phi::DenseTensor* qktv_out_grad) {
     std::vector<int> perm = {0, 1, 3, 2, 4};
-    TransposeGPUKernelDriver<T>(dev_ctx_, fmha_out_grad, perm, qktv_out_grad);
+    phi::funcs::TransposeGPUKernelDriver<T>(
+        dev_ctx_, fmha_out_grad, perm, qktv_out_grad);
   }
 
   // qk_out = qk_out + nonbatched_bias + src_mask

paddle/fluid/operators/mkldnn/transpose_mkldnn_op.cc

@@ -15,8 +15,8 @@
 #include "paddle/fluid/framework/data_layout_transform.h"
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/memory/malloc.h"
-#include "paddle/fluid/operators/transpose_op.h"
 #include "paddle/fluid/platform/mkldnn_reuse.h"
+#include "paddle/phi/kernels/funcs/transpose_functor.h"
 
 namespace paddle {
 namespace operators {

paddle/fluid/operators/transpose_op.cc

@@ -12,8 +12,6 @@ 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 "paddle/fluid/operators/transpose_op.h"
-
 #include <memory>
 #include <string>
 #include <vector>
@@ -21,6 +19,8 @@ limitations under the License. */
 #ifdef PADDLE_WITH_MKLDNN
 #include "paddle/fluid/platform/mkldnn_helper.h"
 #endif
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/phi/kernels/funcs/transpose_functor.h"
 
 namespace paddle {
 namespace operators {

paddle/fluid/operators/transpose_op_mlu.cc

@@ -13,7 +13,7 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #include "paddle/fluid/operators/mlu/mlu_baseop.h"
-#include "paddle/fluid/operators/transpose_op.h"
+#include "paddle/phi/kernels/funcs/transpose_functor.h"
 
 namespace paddle {
 namespace operators {

paddle/fluid/operators/unique_op.h

@@ -23,8 +23,8 @@ limitations under the License. */
 
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/operators/math/concat_and_split.h"
-#include "paddle/fluid/operators/transpose_op.h"
 #include "paddle/phi/kernels/funcs/math_function.h"
+#include "paddle/phi/kernels/funcs/transpose_functor.h"
 
 namespace paddle {
 namespace operators {
@@ -251,7 +251,7 @@ static void UniqueDim(const framework::ExecutionContext& context,
   in_trans.Resize(in_trans_dims);
   in_trans.mutable_data<InT>(context.GetPlace());
   auto& dev_ctx = context.template device_context<DeviceContext>();
-  TransCompute<DeviceContext, InT>(
+  phi::funcs::TransCompute<DeviceContext, InT>(
       in.dims().size(), dev_ctx, in, &in_trans, permute);
   // reshape tensor: eg. [dim1, dim0, dim2] -> [dim1, dim0*dim2]
   framework::DDim in_trans_flat_dims = phi::flatten_to_2d(in_trans_dims, 1);
@@ -315,7 +315,7 @@ static void UniqueDim(const framework::ExecutionContext& context,
   out->Resize(phi::make_ddim(out_trans_dims_vec));
   out->mutable_data<InT>(context.GetPlace());
   concat_functor(dev_ctx, input_unbind, 0, &out_trans);
-  TransCompute<DeviceContext, InT>(
+  phi::funcs::TransCompute<DeviceContext, InT>(
       out_trans.dims().size(), dev_ctx, out_trans, out, permute);
 
   if (return_inverse) {

paddle/fluid/framework/gpu_utils.h → paddle/phi/backends/gpu/gpu_utils.h

@@ -18,11 +18,11 @@
 
 #include <array>
 
-#include "paddle/fluid/platform/enforce.h"
+#include "paddle/phi/core/enforce.h"
 #include "unsupported/Eigen/CXX11/Tensor"
 
-namespace paddle {
-namespace framework {
+namespace phi {
+namespace funcs {
 
 template <typename T, int Size, T DefaultValue>
 struct DeviceArray {
@@ -110,14 +110,14 @@ IntType CeilOrFloor(IntType x, IntType deviser) {
   PADDLE_ENFORCE_GT(
       deviser,
       0,
-      platform::errors::InvalidArgument("deviser should be greater than 0, "
+      phi::errors::InvalidArgument("deviser should be greater than 0, "
                                    "but received is:%d",
                                    deviser));
 
   PADDLE_ENFORCE_GT(
       x,
       0,
-      platform::errors::InvalidArgument("input should be greater than 0, "
+      phi::errors::InvalidArgument("input should be greater than 0, "
                                    "but received is:%d",
                                    x));
 
@@ -140,5 +140,5 @@ IntType CeilOrFloor(IntType x, IntType deviser) {
   }
 }
 
-}  // namespace framework
-}  // namespace paddle
+}  // namespace funcs
+}  // namespace phi

paddle/fluid/operators/transpose_op.cu.h → paddle/phi/kernels/funcs/transpose_functor.cu.h

@@ -14,20 +14,18 @@ limitations under the License. */
 
 #pragma once
 
-#include "paddle/fluid/framework/gpu_utils.h"
-#include "paddle/fluid/operators/transpose_op.h"
-#include "paddle/fluid/platform/fast_divmod.h"
 #include "paddle/phi/backends/gpu/gpu_launch_config.h"
 #include "paddle/phi/backends/gpu/gpu_primitives.h"
+#include "paddle/phi/backends/gpu/gpu_utils.h"
 #include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/kernels/autotune/auto_tune_base.h"
+#include "paddle/phi/kernels/funcs/transpose_functor.h"
+#include "paddle/phi/kernels/primitive/datamover_primitives.h"
 
-namespace paddle {
-namespace operators {
+namespace phi {
+namespace funcs {
 
 using Tensor = phi::DenseTensor;
-using Dim3 = framework::Dim3;
-using Index3 = framework::Index3;
 
 struct EqualTo {
   constexpr bool operator()(int a, int b) const { return a == b; }
@@ -118,8 +116,8 @@ __global__ void TilingSwapDim1And2(const T* __restrict__ input,
   };
 
   // Converts block idx to tile index, each block process a tile
-  Index3 input_block_tile_index = framework::ConvertTensorIndex<IndexType>(
-      blockIdx.x, tile_aligned_input_dim);
+  Index3 input_block_tile_index =
+      ConvertTensorIndex<IndexType>(blockIdx.x, tile_aligned_input_dim);
 
   // Compute real index align to tile:0, 32, 64...
   Index3 block_tile_index_in_input = {
@@ -130,8 +128,7 @@ __global__ void TilingSwapDim1And2(const T* __restrict__ input,
 
   // Compute block flat index against input dims.
   IndexType input_origin_block_flat_index =
-      framework::FlatTensorIndex<IndexType>(block_tile_index_in_input,
-                                            input_dims);
+      FlatTensorIndex<IndexType>(block_tile_index_in_input, input_dims);
 
   bool full_tile = true;
   IndexType tile_width = TileY;
@@ -193,8 +190,7 @@ __global__ void TilingSwapDim1And2(const T* __restrict__ input,
   };
 
   IndexType output_origin_block_flat_index =
-      framework::FlatTensorIndex<IndexType>(block_tile_index_in_output,
-                                            output_dims);
+      FlatTensorIndex<IndexType>(block_tile_index_in_output, output_dims);
 
   constexpr IndexType out_effective_thread_num = NumThreads / TileX * TileX;
 
@@ -230,13 +226,13 @@ bool SelectProperTileSize(std::vector<std::pair<int, int>>* tiles) {
   PADDLE_ENFORCE_LE(
       TSIZE,
       16,
-      platform::errors::InvalidArgument(
+      phi::errors::InvalidArgument(
           "The tile size should smaller than 16, but received is:%d.", TSIZE));
 
   PADDLE_ENFORCE_EQ(
       (TSIZE & (TSIZE - 1)),
       0,
-      platform::errors::InvalidArgument(
+      phi::errors::InvalidArgument(
           "Data types should be powers of 2, but reived size is:%d.", TSIZE));
 
   const int kMaxLongSideLen = 1024;
@@ -316,7 +312,7 @@ struct NarrowDims2TransposeDispatch {
     PADDLE_ENFORCE_EQ(
         (tile_long & (tile_long - 1)),
         0,
-        platform::errors::InvalidArgument(
+        phi::errors::InvalidArgument(
             "The length of the longer side of the tile should be power of 2."
             " But received value is:%d.",
             tile_long));
@@ -381,7 +377,7 @@ struct NarrowDims2TransposeDispatch<
     PADDLE_ENFORCE_EQ(
         (tile_long & (tile_long - 1)),
         0,
-        platform::errors::InvalidArgument(
+        phi::errors::InvalidArgument(
             "The length of the longer side of the tile should be power of 2."
             " But received value is:%d.",
             tile_long));
@@ -431,7 +427,7 @@ struct NarrowDims2TransposeDispatch<
     PADDLE_ENFORCE_EQ(
         (tile_long & (tile_long - 1)),
         0,
-        platform::errors::InvalidArgument(
+        phi::errors::InvalidArgument(
             "The length of the longer side of the tile should be power of 2,"
             " but received is:%d.",
             tile_long));
@@ -459,7 +455,7 @@ void SwapDim1And2InNarrow(const phi::GPUContext& d,
   PADDLE_ENFORCE_EQ(
       ret,
       true,
-      platform::errors::InvalidArgument(
+      phi::errors::InvalidArgument(
           "SelectProperTileSize should return true, but return value is:%d.",
           ret));
 
@@ -475,12 +471,12 @@ void SwapDim1And2InNarrow(const phi::GPUContext& d,
     // to find least wasted threads, which means we need to find tile
     // can split input properly, in another words: num_wasted_threads=0.
     int num_wasted_threads =
-        input_long_edge - framework::CeilOrFloor<int, false>(
-                              input_long_edge, proposed_tile_long_edge) *
+        input_long_edge -
+        CeilOrFloor<int, false>(input_long_edge, proposed_tile_long_edge) *
             proposed_tile_long_edge;
 
-    int num_full_tiles = framework::CeilOrFloor<int, false>(
-        input_long_edge, proposed_tile_long_edge);
+    int num_full_tiles = 
+        CeilOrFloor<int, false>(input_long_edge, proposed_tile_long_edge);
 
     float cost = num_wasted_threads;
 
@@ -514,8 +510,8 @@ void SwapDim1And2InNarrow(const phi::GPUContext& d,
   // Here finally get proper long X short tile size.
   Dim3 input_dims_aligned = {
       input_dims[0],
-      framework::CeilOrFloor<int, true>(input_dims[1], select_tile_size_i),
-      framework::CeilOrFloor<int, true>(input_dims[2], select_tile_size_j),
+      CeilOrFloor<int, true>(input_dims[1], select_tile_size_i),
+      CeilOrFloor<int, true>(input_dims[2], select_tile_size_j),
   };
 
   IndexType total_tiles_count = input_dims_aligned[0];
@@ -549,7 +545,7 @@ __global__ void TransposeSimpleKernel(IndexType nthreads,
 
   CUDA_KERNEL_LOOP_TYPE(output_index, nthreads, IndexType) {
     Index3 output_tensor_index =
-        framework::ConvertTensorIndex<IndexType>(output_index, output_dims);
+        ConvertTensorIndex<IndexType>(output_index, output_dims);
 
     Index3 input_tensor_index;
     input_tensor_index[0] = output_tensor_index[pos0];
@@ -557,7 +553,7 @@ __global__ void TransposeSimpleKernel(IndexType nthreads,
     input_tensor_index[2] = output_tensor_index[pos2];
 
     IndexType input_index =
-        framework::FlatTensorIndex<IndexType>(input_tensor_index, input_dims);
+        FlatTensorIndex<IndexType>(input_tensor_index, input_dims);
 
     output[output_index] = input[input_index];
   }
@@ -585,8 +581,8 @@ void SendSwapDim1And2InTranspose(const phi::GPUContext& d,
 
     Dim3 input_dims_aligned = {
         input_dims[0],
-        framework::CeilOrFloor<int, true>(input_dims[1], kTileSize),
-        framework::CeilOrFloor<int, true>(input_dims[2], kTileSize),
+        CeilOrFloor<int, true>(input_dims[1], kTileSize),
+        CeilOrFloor<int, true>(input_dims[2], kTileSize),
     };
 
     IndexType total_tiles_count = input_dims_aligned[0];
@@ -653,13 +649,13 @@ struct SwapDim0And2InTranspose {
 
 // This function is to combine dimension. fox example:
 // (0, 1, 3, 2) --> (0, 2, 1)
-inline void CombineTransposeDim3(const framework::DDim& shape,
+inline void CombineTransposeDim3(const DDim& shape,
                                  const std::vector<int>& perm,
                                  std::vector<int>* new_perm,
-                                 framework::DDim* new_dims) {
+                                 DDim* new_dims) {
   PADDLE_ENFORCE_EQ(shape.size(),
                     perm.size(),
-                    platform::errors::InvalidArgument(
+                    phi::errors::InvalidArgument(
                         " shape should have the save dim with perm, but"
                         " received shape size is:%d, perm size is:%d.",
                         shape.size(),
@@ -717,7 +713,7 @@ struct TransposeSimple {
                   phi::DenseTensor* out) {
     // First reduce the dimensions of the input tensor if possible.
     std::vector<int> new_perm;
-    framework::DDim new_dims;
+    DDim new_dims;
     CombineTransposeDim3(in.dims(), perm, &new_perm, &new_dims);
 
     // Only use tile copy GPU kernel when dimension is 2 or 3.
@@ -796,7 +792,7 @@ class IdxHelper<N, uint32_t> {
   explicit IdxHelper(const uint32_t* dims) {
     for (int i = N - 1; i >= 0; --i) {
       uint32_t value = i < (N - 1) ? dims[i + 1] * stride_[i + 1] : 1;
-      divmoder_[i] = paddle::platform::FastDivMod(value);
+      divmoder_[i] = phi::kps::details::FastDivMod(value);
       stride_[i] = value;
     }
   }
@@ -817,7 +813,7 @@ class IdxHelper<N, uint32_t> {
 
  private:
   uint32_t stride_[N];
-  paddle::platform::FastDivMod divmoder_[N];
+  phi::kps::details::FastDivMod divmoder_[N];
 };
 
 // Transform index between memory offset and shape coodinate.
@@ -1188,8 +1184,8 @@ void TransposeGPUKernelDriver(const phi::GPUContext& ctx,
     ret = TransposeSimple<T>::run(ctx, in, perm, out);
   }
   if (!ret) {
-    auto* tuner =
-        phi::autotune::MakeTransposeTuner<T>(TransCompute<phi::GPUContext, T>);
+    auto* tuner = phi::autotune::MakeTransposeTuner<T>(
+        funcs::TransCompute<phi::GPUContext, T>);
     tuner->AddCallBack(PermuteAndTranspose<phi::GPUContext, T>);
 
     size_t key = phi::autotune::TransposeKey(
@@ -1208,5 +1204,5 @@ void TransposeGPUKernelDriver(const phi::GPUContext& ctx,
   }
 }
 
-}  // namespace operators
-}  // namespace paddle
+}  // namespace funcs
+}  // namespace phi

paddle/fluid/operators/transpose_op.h → paddle/phi/kernels/funcs/transpose_functor.h

-/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
+/* Copyright (c) 2022 PaddlePaddle Authors. 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.
@@ -16,57 +16,15 @@ limitations under the License. */
 
 #include <vector>
 
-#include "paddle/fluid/framework/op_registry.h"
 #include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/kernels/funcs/aligned_vector.h"
 #include "paddle/phi/kernels/funcs/math_function.h"
 
-namespace paddle {
-namespace operators {
+namespace phi {
+namespace funcs {
 
 enum { kTransposeMKLDNNFP32 = 1, kTransposeMKLDNNINT8 = 2 };
 
-template <typename DeviceContext, typename T>
-inline void TransCompute(const int dim,
-                         const DeviceContext& dev_ctx,
-                         const phi::DenseTensor& in,
-                         phi::DenseTensor* out,
-                         const std::vector<int>& axis) {
-  switch (dim) {
-    case 0:
-      phi::Copy<DeviceContext>(dev_ctx, in, dev_ctx.GetPlace(), false, out);
-      break;
-    case 1:
-      phi::funcs::Transpose<DeviceContext, T, 1> trans1;
-      trans1(dev_ctx, in, out, axis);
-      break;
-    case 2:
-      phi::funcs::Transpose<DeviceContext, T, 2> trans2;
-      trans2(dev_ctx, in, out, axis);
-      break;
-    case 3:
-      phi::funcs::Transpose<DeviceContext, T, 3> trans3;
-      trans3(dev_ctx, in, out, axis);
-      break;
-    case 4:
-      phi::funcs::Transpose<DeviceContext, T, 4> trans4;
-      trans4(dev_ctx, in, out, axis);
-      break;
-    case 5:
-      phi::funcs::Transpose<DeviceContext, T, 5> trans5;
-      trans5(dev_ctx, in, out, axis);
-      break;
-    case 6:
-      phi::funcs::Transpose<DeviceContext, T, 6> trans6;
-      trans6(dev_ctx, in, out, axis);
-      break;
-    default:
-      // for dim >= 7 situation
-      phi::funcs::TransposeNormal<DeviceContext, T> trans_normal;
-      trans_normal(dev_ctx, in, out, axis);
-  }
-}
-
 enum PermuteType {
   kCopy = 1,
   kTranspose = 2,
@@ -227,5 +185,5 @@ class TranposeTypeClassifier {
   }
 };
 
-}  // namespace operators
-}  // namespace paddle
+}  // namespace funcs
+}  // namespace phi

paddle/phi/kernels/gpu/transpose_kernel.cu

@@ -16,12 +16,12 @@
 
 #include <vector>
 
-#include "paddle/fluid/operators/transpose_op.cu.h"
 #include "paddle/phi/backends/gpu/gpu_context.h"
 #include "paddle/phi/backends/gpu/gpu_launch_config.h"
 #include "paddle/phi/backends/gpu/gpu_primitives.h"
 #include "paddle/phi/common/bfloat16.h"
 #include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/transpose_functor.cu.h"
 #include "paddle/phi/kernels/impl/transpose_grad_kernel_impl.h"
 
 namespace phi {
@@ -38,7 +38,7 @@ void TransposeKernel(const Context& ctx,
     phi::Copy<Context>(ctx, x, ctx.GetPlace(), false, out);
     return;
   }
-  paddle::operators::TransposeGPUKernelDriver<T>(ctx, x, axis, out);
+  phi::funcs::TransposeGPUKernelDriver<T>(ctx, x, axis, out);
 }
 
 }  // namespace phi