modify d2d copy to xpu::copy in xpu kernel, test=kunlun

paddle/fluid/operators/reader/buffered_reader.cc

@@ -417,8 +417,13 @@ void BufferedReader::ReadAsync(size_t i) {
         // TODO(zhanghuan) for now hardware not support xpu_memcpy_async, maybe
         // KL3
         if ((platform::is_xpu_place(cpu_place))) {
-          memory::Copy(place_, xpu_ptr, cpu_place, cpu_ptr, size);
           platform::XPUStreamSync(stream_.get());
+          char *tmp = new char[size];
+          PADDLE_ENFORCE_XPU_SUCCESS(xpu_memcpy(
+              tmp, cpu_ptr, size, XPUMemcpyKind::XPU_DEVICE_TO_HOST));
+          PADDLE_ENFORCE_XPU_SUCCESS(xpu_memcpy(
+              xpu_ptr, tmp, size, XPUMemcpyKind::XPU_HOST_TO_DEVICE));
+          delete[] tmp;
         } else {
           memory::Copy(place_, xpu_ptr, cpu_place, cpu_ptr, size);
         }

paddle/phi/backends/xpu/xpu_info.cc

@@ -169,19 +169,12 @@ void MemcpySyncD2D(void* dst,
                    const phi::XPUContext& dev_ctx) {
   int dev_id = GetXPUCurrentDeviceId();
   if (dst_place.device == dev_id && src_place.device == dev_id) {
-    dev_ctx.Wait();
-    char* tmp = new char[count];
-    PADDLE_ENFORCE_XPU_SUCCESS(
-        xpu_memcpy(tmp, src, count, XPUMemcpyKind::XPU_DEVICE_TO_HOST));
-    PADDLE_ENFORCE_XPU_SUCCESS(
-        xpu_memcpy(dst, tmp, count, XPUMemcpyKind::XPU_HOST_TO_DEVICE));
-    delete[] tmp;
-    // PADDLE_ENFORCE_XDNN_SUCCESS(
-    //    baidu::xpu::api::copy(dev_ctx.x_context(),
-    //                          static_cast<const int8_t*>(src),
-    //                          static_cast<int8_t*>(dst),
-    //                          count),
-    //    "copy ");
+    PADDLE_ENFORCE_XDNN_SUCCESS(
+        baidu::xpu::api::copy(dev_ctx.x_context(),
+                              static_cast<const int8_t*>(src),
+                              static_cast<int8_t*>(dst),
+                              count),
+        "copy ");
   } else {
     PADDLE_ENFORCE_XPU_SUCCESS(
         xpu_memcpy_peer(dst_place.device, dst, src_place.device, src, count));

paddle/phi/kernels/reshape_grad_kernel.cc

@@ -17,6 +17,9 @@
 #include "paddle/phi/backends/all_context.h"
 #include "paddle/phi/core/kernel_registry.h"
 #include "paddle/phi/core/tensor_utils.h"
+#ifdef PADDLE_WITH_XPU
+#include "paddle/phi/backends/xpu/enforce_xpu.h"
+#endif
 
 namespace phi {
 
@@ -29,6 +32,25 @@ void ReshapeGradKernel(const Context& dev_ctx,
   x_grad->Resize(x_dims);
 }
 
+#ifdef PADDLE_WITH_XPU
+template <>
+void ReshapeGradKernel<phi::XPUContext>(const XPUContext& dev_ctx,
+                                        const DenseTensor& out_grad,
+                                        DenseTensor* x_grad) {
+  auto x_dims = x_grad->dims();
+  dev_ctx.Alloc(x_grad, out_grad.dtype());
+  auto* src_ptr = out_grad.data();
+  auto* dst_ptr = x_grad->data();
+  auto size = out_grad.numel() * paddle::experimental::SizeOf(out_grad.dtype());
+  int ret = xpu::copy(dev_ctx.x_context(),
+                      reinterpret_cast<const int8_t*>(src_ptr),
+                      reinterpret_cast<int8_t*>(dst_ptr),
+                      size);
+  PADDLE_ENFORCE_XDNN_SUCCESS(ret, "copy");
+  x_grad->Resize(x_dims);
+}
+#endif
+
 template <typename Context>
 void ReshapeDoubleGradKernel(const Context& dev_ctx,
                              const DenseTensor& out_grad,

paddle/phi/kernels/reshape_kernel.cc

@@ -19,6 +19,9 @@
 #include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/infermeta/unary.h"
 #include "paddle/phi/kernels/funcs/common_shape.h"
+#ifdef PADDLE_WITH_XPU
+#include "paddle/phi/backends/xpu/enforce_xpu.h"
+#endif
 
 namespace phi {
 
@@ -42,6 +45,33 @@ void ReshapeKernel(const Context& dev_ctx,
   out->ResetLoD(x.lod());
 }
 
+#ifdef PADDLE_WITH_XPU
+template <>
+void ReshapeKernel<phi::XPUContext>(const XPUContext& dev_ctx,
+                                    const DenseTensor& x,
+                                    const IntArray& shape,
+                                    DenseTensor* out) {
+  MetaTensor meta_out(out);
+  InferMetaFromVecValue(x, shape.GetData(), &meta_out);
+  if (x.initialized() && x.Holder() == out->Holder()) {
+    dev_ctx.Alloc(out, x.dtype());
+    return;
+  }
+  dev_ctx.Alloc(out, x.dtype());
+  auto dims = out->dims();
+  auto* src_ptr = x.data();
+  auto* dst_ptr = out->data();
+  auto size = x.numel() * paddle::experimental::SizeOf(x.dtype());
+  int ret = xpu::copy(dev_ctx.x_context(),
+                      reinterpret_cast<const int8_t*>(src_ptr),
+                      reinterpret_cast<int8_t*>(dst_ptr),
+                      size);
+  PADDLE_ENFORCE_XDNN_SUCCESS(ret, "copy");
+  out->Resize(dims);
+  out->ResetLoD(x.lod());
+}
+#endif
+
 template <typename Context>
 void ReshapeWithXShape(const Context& dev_ctx,
                        const DenseTensor& x,

paddle/phi/kernels/xpu/gather_nd_kernel.cc

@@ -30,7 +30,10 @@ void GatherNdKernel(const Context &ctx,
   if (x.numel() == 0) return;
 
   if (index.numel() == 0) {
-    phi::Copy(ctx, x, phi::XPUPlace(), true, out);
+    out->Resize(x.dims());
+    ctx.template Alloc<T>(out);
+    int r = xpu::copy(ctx.x_context(), x.data<T>(), out->data<T>(), x.numel());
+    PADDLE_ENFORCE_XDNN_SUCCESS(r, "copy");
     return;
   }
 
@@ -69,12 +72,7 @@ void GatherNdKernel(const Context &ctx,
                                      x_vec,
                                      index_shape);
   }
-  PADDLE_ENFORCE_EQ(
-      ret,
-      XPU_SUCCESS,
-      phi::errors::External("XPU gather_nd kernel return wrong value[%d %s]",
-                            ret,
-                            XPUAPIErrorMsg[ret]));
+  PADDLE_ENFORCE_XDNN_SUCCESS(ret, "gather_nd");
 }
 
 }  // namespace phi

paddle/phi/kernels/xpu/generate_proposals_kernel.cc

@@ -372,16 +372,16 @@ void GenerateProposalsKernel(const Context& dev_ctx,
     DenseTensor& proposals = tensor_pair.first;
     DenseTensor& nscores = tensor_pair.second;
 
-    paddle::memory::Copy(place,
-                         rpn_rois->data<T>() + num_proposals * 4,
-                         place,
-                         proposals.data<T>(),
-                         sizeof(T) * proposals.numel());
-    paddle::memory::Copy(place,
-                         rpn_roi_probs->data<T>() + num_proposals,
-                         place,
-                         nscores.data<T>(),
-                         sizeof(T) * scores.numel());
+    r = xpu::copy(dev_ctx.x_context(),
+                  proposals.data<T>(),
+                  rpn_rois->data<T>() + num_proposals * 4,
+                  proposals.numel());
+    PADDLE_ENFORCE_XDNN_SUCCESS(r, "copy");
+    r = xpu::copy(dev_ctx.x_context(),
+                  nscores.data<T>(),
+                  rpn_roi_probs->data<T>() + num_proposals,
+                  nscores.numel());
+    PADDLE_ENFORCE_XDNN_SUCCESS(r, "copy");
 
     if (dev_ctx.x_context()->xpu_stream) {
       dev_ctx.Wait();

paddle/phi/kernels/xpu/scatter_kernel.cc

@@ -27,7 +27,10 @@ void ScatterKernel(const Context &ctx,
                    const DenseTensor &updates,
                    bool overwrite,
                    DenseTensor *out) {
-  phi::Copy(ctx, x, ctx.GetPlace(), false, out);
+  out->Resize(x.dims());
+  ctx.template Alloc<T>(out);
+  int ret = xpu::copy(ctx.x_context(), x.data<T>(), out->data<T>(), x.numel());
+  PADDLE_ENFORCE_XDNN_SUCCESS(ret, "copy");
   // Apply ScatterUpdate: Out[index] = Updates[:]
   const auto &index_type = index.dtype();
   bool index_type_match =

paddle/phi/kernels/xpu/tile_kernel.cc

@@ -102,7 +102,11 @@ void TileKernel(const Context& dev_ctx,
 
   std::vector<int64_t> temp(repeat_times.size(), 1);
   if (repeat_times == temp) {
-    phi::Copy(dev_ctx, x, dev_ctx.GetPlace(), false, out);
+    out->Resize(x.dims());
+    dev_ctx.template Alloc<T>(out);
+    int r =
+        xpu::copy(dev_ctx.x_context(), x.data<T>(), out->data<T>(), x.numel());
+    PADDLE_ENFORCE_XDNN_SUCCESS(r, "copy");
     return;
   }
 

python/paddle/fluid/tests/unittests/xpu/get_test_cover_info.py

@@ -94,6 +94,8 @@
     "c_embedding_float32",  # unittests of collective ops do not using xpu testing framework
     "c_sync_comm_stream_float32",
     "c_sync_calc_stream_float32",
+    "reshape2_bool",
+    "reshape2_grad_bool",
 ]
 xpu_test_device_op_white_list = []
 xpu_test_device_op_type_white_list = []

python/paddle/fluid/tests/unittests/xpu/test_reshape2_op_xpu.py

@@ -41,6 +41,7 @@ class TestReshapeOp(XPUOpTest):
         def setUp(self):
             self.init_data()
             self.op_type = "reshape2"
+            self.dtype = self.in_type
             self.init_test_input()
             self.init_test_output()
             self.init_attrs()