[geometric]Add paddle.geometric.send_uv API

paddle/phi/api/yaml/api.yaml

@@ -135,6 +135,16 @@
     func : fft_r2c
   backward : fft_r2c_grad
 
+- api : graph_send_uv
+  args : (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, str message_op = "ADD")
+  output : Tensor(out)
+  infer_meta :
+    func : GraphSendUVInferMeta
+  kernel :
+    func : graph_send_uv
+    data_type : x
+  backward : graph_send_uv_grad
+
 - api : lgamma
   args : (Tensor x)
   output : Tensor(out)

paddle/phi/api/yaml/backward.yaml

@@ -147,6 +147,17 @@
     data_type: out_grad
   no_need_buffer: x
 
+- backward_api : graph_send_uv_grad
+  forward : graph_send_uv (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, str message_op = "ADD") -> Tensor(out)
+  args: (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, Tensor out_grad, str message_op = "ADD")
+  output : Tensor(x_grad), Tensor(y_grad)
+  infer_meta :
+    func : GeneralBinaryGradInferMeta
+    param : [x, y]
+  kernel :
+    func : graph_send_uv_grad
+    data_type : x
+
 - backward_api : lgamma_grad
   forward : lgamma(Tensor x) -> Tensor(out)
   args : (Tensor x, Tensor out_grad)

paddle/phi/infermeta/multiary.cc

@@ -2687,6 +2687,76 @@ void GraphSendUERecvInferMeta(const MetaTensor& x,
   out->set_dims(phi::make_ddim(out_dims_array));
 }
 
+void GraphSendUVInferMeta(const MetaTensor& x,
+                          const MetaTensor& y,
+                          const MetaTensor& src_index,
+                          const MetaTensor& dst_index,
+                          const std::string& message_op,
+                          MetaTensor* out) {
+  auto src_index_dims = src_index.dims();
+  if (src_index_dims.size() == 2) {
+    PADDLE_ENFORCE_EQ(src_index_dims[1],
+                      1,
+                      phi::errors::InvalidArgument(
+                          "The last dim of Src_index should be 1 when it "
+                          "is 2D, but we get %d",
+                          src_index_dims[1]));
+  } else {
+    PADDLE_ENFORCE_EQ(
+        src_index_dims.size(),
+        1,
+        phi::errors::InvalidArgument(
+            "The Src_index should be 1D, when it is not 2D, but we get %d",
+            src_index_dims.size()));
+  }
+
+  auto dst_index_dims = dst_index.dims();
+  if (dst_index_dims.size() == 2) {
+    PADDLE_ENFORCE_EQ(dst_index_dims[1],
+                      1,
+                      phi::errors::InvalidArgument(
+                          "The last dim of Dst_index should be 1 when it "
+                          "is 2D, but we get %d",
+                          dst_index_dims[1]));
+  } else {
+    PADDLE_ENFORCE_EQ(
+        dst_index_dims.size(),
+        1,
+        phi::errors::InvalidArgument("The Dst_index should be 1D, "
+                                     "when it is not 2D, but we get %d",
+                                     dst_index_dims.size()));
+  }
+
+  PADDLE_ENFORCE_EQ(src_index_dims[0],
+                    dst_index_dims[0],
+                    phi::errors::InvalidArgument(
+                        "Src_index and Dst_index should have the same shape."));
+
+  // Infer out's shape according to x and y(need broadcasting condition)
+  out->set_dtype(x.dtype());
+  auto x_dims = x.dims();
+  auto y_dims = y.dims();
+  auto x_dims1 = phi::vectorize<int>(x_dims);
+  auto y_dims1 = phi::vectorize<int>(y_dims);
+  std::vector<int> x_dims2(x_dims1.begin() + 1, x_dims1.end());
+  std::vector<int> y_dims2(y_dims1.begin() + 1, y_dims1.end());
+  int max_dim = std::max(x_dims2.size(), y_dims2.size());
+  int axis = std::abs(static_cast<int>(x_dims2.size() - y_dims2.size()));
+  std::vector<int> x_dims_array(max_dim);
+  std::vector<int> y_dims_array(max_dim);
+  std::vector<int> out_dims_array(max_dim);
+  // Only need to broadcast dimensions other than the 0th dimension.
+  phi::funcs::GetBroadcastDimsArrays(phi::make_ddim(x_dims2),
+                                     phi::make_ddim(y_dims2),
+                                     x_dims_array.data(),
+                                     y_dims_array.data(),
+                                     out_dims_array.data(),
+                                     max_dim,
+                                     axis);
+  out_dims_array.insert(out_dims_array.begin(), src_index_dims[0]);
+  out->set_dims(phi::make_ddim(out_dims_array));
+}
+
 }  // namespace phi
 
 PD_REGISTER_INFER_META_FN(batch_norm, phi::BatchNormInferMeta);

paddle/phi/infermeta/multiary.h

@@ -476,4 +476,11 @@ void GraphSendUERecvInferMeta(const MetaTensor& x,
                               MetaTensor* out,
                               MetaTensor* dst_count);
 
+void GraphSendUVInferMeta(const MetaTensor& x,
+                          const MetaTensor& y,
+                          const MetaTensor& src_index,
+                          const MetaTensor& dst_index,
+                          const std::string& message_op,
+                          MetaTensor* out);
+
 }  // namespace phi

paddle/phi/kernels/cpu/graph_send_ue_recv_grad_kernel.cc

@@ -24,7 +24,7 @@
 #include "paddle/phi/kernels/cpu/graph_send_ue_recv_funcs.h"
 #include "paddle/phi/kernels/empty_kernel.h"
 #include "paddle/phi/kernels/funcs/math_function.h"
-#include "paddle/phi/kernels/impl/graph_messaage_passing_impl.h"
+#include "paddle/phi/kernels/impl/graph_message_passing_impl.h"
 #include "paddle/phi/kernels/reduce_sum_kernel.h"
 
 namespace phi {

paddle/phi/kernels/cpu/graph_send_ue_recv_kernel.cc

@@ -22,7 +22,7 @@
 #include "paddle/phi/core/hostdevice.h"
 #include "paddle/phi/core/kernel_registry.h"
 #include "paddle/phi/kernels/cpu/graph_send_ue_recv_funcs.h"
-#include "paddle/phi/kernels/impl/graph_messaage_passing_impl.h"
+#include "paddle/phi/kernels/impl/graph_message_passing_impl.h"
 
 namespace phi {