diff --git a/paddle/fluid/operators/collective/recv_v2_op.cu.cc b/paddle/fluid/operators/collective/recv_v2_op.cu.cc
index a10257b45b300112dca22ffe951193526a9a7eb5..bfa12f911946d4b3eb17c99ce75caba3ba436c64 100644
--- a/paddle/fluid/operators/collective/recv_v2_op.cu.cc
+++ b/paddle/fluid/operators/collective/recv_v2_op.cu.cc
@@ -40,24 +40,24 @@ framework::DDim recv_shape_info(const platform::Place &place,
                           "to send the shape info."));
   }
 
-  phi::DataType shape_dytpe = phi::DataType::INT32;
+  phi::DataType shape_dtype = phi::DataType::INT32;
   ncclDataType_t nccl_dtype =
-      platform::ToNCCLDataType(framework::TransToProtoVarType(shape_dytpe));
+      platform::ToNCCLDataType(framework::TransToProtoVarType(shape_dtype));
 
   // step1: recv the shape size
-  phi::DenseTensor gpu_shape_size_tensor(shape_dytpe);
+  phi::DenseTensor gpu_shape_size_tensor(shape_dtype);
   if (!group) {
     gpu_shape_size_tensor.Resize({1});
-    gpu_shape_size_tensor.mutable_data(place, shape_dytpe);
+    gpu_shape_size_tensor.mutable_data(place, shape_dtype);
     auto *gpu_data = gpu_shape_size_tensor.data<int>();
     PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclRecv(
         gpu_data, 1, nccl_dtype, peer, comm->comm(), stream));
   }
 
   // copy the shape size tensor to cpu
-  phi::DenseTensor *cpu_shape_size_tensor = new phi::DenseTensor(shape_dytpe);
+  phi::DenseTensor *cpu_shape_size_tensor = new phi::DenseTensor(shape_dtype);
   cpu_shape_size_tensor->Resize({1});
-  cpu_shape_size_tensor->mutable_data(platform::CPUPlace(), shape_dytpe);
+  cpu_shape_size_tensor->mutable_data(platform::CPUPlace(), shape_dtype);
   if (group) {
     std::vector<phi::DenseTensor> shape_size_tensor;
     shape_size_tensor.emplace_back(*cpu_shape_size_tensor);
@@ -71,19 +71,19 @@ framework::DDim recv_shape_info(const platform::Place &place,
   VLOG(3) << "recv the shape size: " << shape_size << " from peer";
 
   // step2: recv the shape
-  phi::DenseTensor gpu_shape_tensor(shape_dytpe);
+  phi::DenseTensor gpu_shape_tensor(shape_dtype);
   if (!group) {
     gpu_shape_tensor.Resize({shape_size});
-    gpu_shape_tensor.mutable_data(place, shape_dytpe);
+    gpu_shape_tensor.mutable_data(place, shape_dtype);
     auto *gpu_shape_data = gpu_shape_tensor.data<int>();
     PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::ncclRecv(
         gpu_shape_data, shape_size, nccl_dtype, peer, comm->comm(), stream));
   }
 
   // copy the shape tensor to cpu
-  phi::DenseTensor *cpu_shape_tensor = new phi::DenseTensor(shape_dytpe);
+  phi::DenseTensor *cpu_shape_tensor = new phi::DenseTensor(shape_dtype);
   cpu_shape_tensor->Resize({shape_size});
-  cpu_shape_tensor->mutable_data(platform::CPUPlace(), shape_dytpe);
+  cpu_shape_tensor->mutable_data(platform::CPUPlace(), shape_dtype);
   if (group) {
     std::vector<phi::DenseTensor> shape_tensor;
     shape_tensor.emplace_back(*cpu_shape_tensor);
diff --git a/paddle/fluid/operators/collective/send_v2_op.cu.cc b/paddle/fluid/operators/collective/send_v2_op.cu.cc
index 7c1ab8ace3404d68c9e419ba45b30633d072fcf7..adea7db0b8088e61583f88c65a3b4f386177b5cd 100644
--- a/paddle/fluid/operators/collective/send_v2_op.cu.cc
+++ b/paddle/fluid/operators/collective/send_v2_op.cu.cc
@@ -39,16 +39,16 @@ void send_shape_info(const phi::DenseTensor& x,
                           "NCCLComm and Stream should be provided if use NCCL "
                           "to send the shape info."));
   }
-  phi::DataType shape_dytpe = phi::DataType::INT32;
+  phi::DataType shape_dtype = phi::DataType::INT32;
   ncclDataType_t nccl_dtype =
-      platform::ToNCCLDataType(framework::TransToProtoVarType(shape_dytpe));
+      platform::ToNCCLDataType(framework::TransToProtoVarType(shape_dtype));
   auto dims = x.dims();
   int shape_size = dims.size();
 
   // step1: send the shape size
-  phi::DenseTensor cpu_shape_size_tensor(shape_dytpe);
+  phi::DenseTensor cpu_shape_size_tensor(shape_dtype);
   cpu_shape_size_tensor.Resize({1});
-  cpu_shape_size_tensor.mutable_data(platform::CPUPlace(), shape_dytpe);
+  cpu_shape_size_tensor.mutable_data(platform::CPUPlace(), shape_dtype);
   auto* cpu_data = cpu_shape_size_tensor.data<int>();
   cpu_data[0] = shape_size;
 
@@ -58,9 +58,9 @@ void send_shape_info(const phi::DenseTensor& x,
     auto shape_size_task = group->Send(shape_size_tensor, peer);
   } else {
     // copy the shape size tensor to gpu and send
-    phi::DenseTensor* gpu_shape_size_tensor = new phi::DenseTensor(shape_dytpe);
+    phi::DenseTensor* gpu_shape_size_tensor = new phi::DenseTensor(shape_dtype);
     gpu_shape_size_tensor->Resize({1});
-    gpu_shape_size_tensor->mutable_data(place, shape_dytpe);
+    gpu_shape_size_tensor->mutable_data(place, shape_dtype);
     framework::TensorCopySync(
         cpu_shape_size_tensor, place, gpu_shape_size_tensor);
     PADDLE_ENFORCE_GPU_SUCCESS(
@@ -74,9 +74,9 @@ void send_shape_info(const phi::DenseTensor& x,
   VLOG(3) << "send the shape size: " << shape_size << " to peer";
 
   // step2: send the shape
-  phi::DenseTensor cpu_shape_tensor(shape_dytpe);
+  phi::DenseTensor cpu_shape_tensor(shape_dtype);
   cpu_shape_tensor.Resize({shape_size});
-  cpu_shape_tensor.mutable_data(platform::CPUPlace(), shape_dytpe);
+  cpu_shape_tensor.mutable_data(platform::CPUPlace(), shape_dtype);
   auto* cpu_shape_data = cpu_shape_tensor.data<int>();
   for (int i = 0; i < shape_size; ++i) {
     cpu_shape_data[i] = dims[i];
@@ -88,9 +88,9 @@ void send_shape_info(const phi::DenseTensor& x,
     auto shape_task = group->Send(shape_tensor, peer);
   } else {
     // copy the shape tensor to gpu and send
-    phi::DenseTensor* gpu_shape_tensor = new phi::DenseTensor(shape_dytpe);
+    phi::DenseTensor* gpu_shape_tensor = new phi::DenseTensor(shape_dtype);
     gpu_shape_tensor->Resize({shape_size});
-    gpu_shape_tensor->mutable_data(place, shape_dytpe);
+    gpu_shape_tensor->mutable_data(place, shape_dtype);
     framework::TensorCopySync(cpu_shape_tensor, place, gpu_shape_tensor);
     PADDLE_ENFORCE_GPU_SUCCESS(
         platform::dynload::ncclSend(gpu_shape_tensor->data<int>(),