Fix typos (#51338)

paddle/fluid/distributed/collective/process_group_nccl.cc

@@ -129,7 +129,7 @@ ncclComm_t ProcessGroupNCCL::NCCLComm(const Place& place) const {
       iter,
       place_to_comm_ctx_.end(),
       phi::errors::NotFound(
-          "Cannot find the NCCL commmunicator in this process group."));
+          "Cannot find the NCCL communicator in this process group."));
   return iter->second->nccl_comm();
 }
 

paddle/fluid/distributed/collective/reducer.cc

@@ -803,7 +803,7 @@ void EagerReducer::MarkVarReady(const size_t var_index,
         "parameters participate in the backward calculation "
         "again at a later time (e.g. after the forward function, "
         "the loss calculation uses the unused "
-        "paramters of the forward and trigger backward), "
+        "parameters of the forward and trigger backward), "
         "its gradient will be wrong.";
 
     PADDLE_ENFORCE_EQ(has_marked_unused_vars_,
@@ -868,7 +868,7 @@ void EagerReducer::MarkVarReady(const size_t var_index,
             "parameters without generating gradients during training. "
             "For example, if is_sparese=True is used in Embedding, "
             "the current step of this parameter cannot generate gradient "
-            "because of stop_gradient/detatch, where error will occur.",
+            "because of stop_gradient/detach, where error will occur.",
             var_index,
             tensors_[var_index].name()));
 
@@ -996,7 +996,7 @@ void EagerReducer::ProcessUnusedDenseVars() {
 
       // NOTE(haohongxiang): Calling SetFakeEmpty here is to make sure that
       // gradient accumulation can continue normally after clear_gradients()
-      // especiall in cases including complex control flow.
+      // especially in cases including complex control flow.
       std::static_pointer_cast<egr::GradNodeAccumulation>(
           GetGradNodeFromTensor(&tensors_[var_index]))
           ->SetFakeEmpty(false);

paddle/fluid/distributed/fleet_executor/compute_interceptor.cc

@@ -192,7 +192,7 @@ void ComputeInterceptor::RunOps() {
                       microbatch_scopes_.size(),
                       platform::errors::InvalidArgument(
                           "Step out of range. There are %ld "
-                          "microbatch_scopes, but recevice scope index %ld",
+                          "microbatch_scopes, but receive scope index %ld",
                           microbatch_scopes_.size(),
                           cur_scope_id_));
   }

paddle/fluid/distributed/index_dataset/index_wrapper.cc

@@ -52,7 +52,7 @@ int TreeIndex::Load(const std::string filename) {
         platform::errors::InvalidArgument(
             "Read from file: %s failed. Valid Format is "
             "an integer representing the length of the following string, "
-            "and the string itself.We got an iteger[% d], "
+            "and the string itself.We got an integer[% d], "
             "but the following string's length is [%d].",
             filename,
             num,
@@ -75,7 +75,7 @@ int TreeIndex::Load(const std::string filename) {
 
       // PADDLE_ENFORCE_NE(node.id(), 0,
       //                  platform::errors::InvalidArgument(
-      //                      "Node'id should not be equel to zero."));
+      //                      "Node'id should not be equal to zero."));
       if (node.is_leaf()) {
         id_codes_map_[node.id()] = code;
       }

paddle/fluid/distributed/ps.proto

@@ -81,7 +81,7 @@ message ServerServiceParameter {
     optional string server_class      = 1 [ default = "DownpourBrpcPsServer" ];
     optional string client_class      = 2 [ default = "DownpourBrpcPsClient" ];
     optional string service_class     = 3 [ default = "DownpourPsService"];
-    optional uint32 start_server_port = 4 [ default = 0 ];  //will find a avaliable port from it
+    optional uint32 start_server_port = 4 [ default = 0 ];  //will find a available port from it
     optional uint32 server_thread_num = 5 [ default = 12 ];
 }
 

paddle/fluid/distributed/ps/service/communicator/communicator.cc

@@ -174,7 +174,7 @@ void Communicator::RpcSendDenseParam(const std::vector<std::string> &varnames,
       float *w = tensor->mutable_data<float>(place);
       paddle::distributed::Region reg(w, tensor->numel());
       regions.emplace_back(reg);
-      VLOG(1) << "rpc_send_dense_param Var " << t << " talbe_id " << table_id
+      VLOG(1) << "rpc_send_dense_param Var " << t << " table_id " << table_id
               << " Temp_data[0] " << w[0] << " Temp_data[-1] "
               << w[tensor->numel() - 1];
     }
@@ -1514,7 +1514,7 @@ void FLCommunicator::InitBrpcClient(
   if (_worker_ptr.get() == nullptr) {
     VLOG(0) << "fl-ps > FLCommunicator::InitBrpcClient get _worker_ptr";
     _worker_ptr =
-        fleet->worker_ptr_;  // FleetWrapper::InitWorker must be excuted
+        fleet->worker_ptr_;  // FleetWrapper::InitWorker must be executed
                              // before, but no need for Coordinator
   }
   if (coordinator_client_ptr_ == nullptr) {

paddle/fluid/distributed/ps/service/communicator/communicator.h

@@ -277,7 +277,7 @@ class Communicator {
   virtual void RpcRecvSparse(const std::string &varname,
                              int table_id,
                              Scope *scope);
-  // 7. send gloabl step
+  // 7. send global step
   virtual void SendGlobalStep(const CommContext &ctx,
                               int batches,
                               Scope *send_scope);
@@ -572,7 +572,7 @@ class SyncCommunicator : public HalfAsyncCommunicator {
       : HalfAsyncCommunicator(envs) {}
 
   void InitEnvs() {
-    // enfore to recv after send
+    // enforce to recv after send
     independent_recv_ = false;
     min_send_grad_num_before_recv_ = 0;
     max_merge_var_num_ = std::stoi(envs.at("communicator_max_merge_var_num"));