diff --git a/paddle/fluid/framework/custom_operator.cc b/paddle/fluid/framework/custom_operator.cc
index a76b164467149305224bbcedf502ae9f63ab4e19..1ca2f4e56dd7176ee466da295d0f3b04a4baf51b 100644
--- a/paddle/fluid/framework/custom_operator.cc
+++ b/paddle/fluid/framework/custom_operator.cc
@@ -513,8 +513,8 @@ Custom Operator.
 
 According to the phi::DenseTensor operation function implemented by the user
 independently of the framework, it is encapsulated into a framework
-operator to adapt to various execution scenarios such as dynamic graph,
-mode static graph mode, and inference mode.
+operator to adapt to various execution scenarios such as dynamic graph
+mode, static graph mode, and inference mode.
 
 )DOC");
   }
@@ -979,11 +979,9 @@ void RegisterOperatorWithMetaInfo(const std::vector<OpMetaInfo>& op_meta_infos,
                       "Custom grad operator infershape error. "
                       "If a custom grad operator contains only one input and "
                       "only one output, the input shape will be directly set "
-                      "to "
-                      "the output shape. Otherwise, Please set the forward "
-                      "input "
-                      "as the grad operator's input or  set the InferShapeFn "
-                      "of custom grad operator by "
+                      "to the output shape. Otherwise, Please set the forward "
+                      "input as the grad operator's input or  set the "
+                      "InferShapeFn of custom grad operator by "
                       ".SetInferShapeFn(PD_INFER_SHAPE(...))"));
               ctx->ShareDim(grad_op_inputs[0], out_name);
             }
diff --git a/paddle/fluid/framework/grad_op_desc_maker.h b/paddle/fluid/framework/grad_op_desc_maker.h
index bb36742d475ad6b72edd11fa1deccbdd3da517d8..dd795e190bdd20bf0ce84338abeb330377bf17bb 100644
--- a/paddle/fluid/framework/grad_op_desc_maker.h
+++ b/paddle/fluid/framework/grad_op_desc_maker.h
@@ -56,7 +56,7 @@ using GradOpPtr = typename details::GradOpPtrTrait<T>::Type;
   operator fwd_op. After it is called (through operator()), the pairs of
   (gradient variable, corresponding input variable of fwd_op) will be added to
   grad_to_var. If an input variable of fwd_op is contained in no_grad_set, its
-  gradient varialbe will be ignored or kEmptyVarName depending on the template
+  gradient variable will be ignored or kEmptyVarName depending on the template
   argument DropEmptyIG in the derived classes.
  */
 class GradOpDescMakerBase {
diff --git a/paddle/fluid/framework/op_desc.h b/paddle/fluid/framework/op_desc.h
index 6c6f13d7c929b4346bd323aa85d4229e3679c0cf..33460d08f729b0a7a3d80bdedbc2e6bd43e36cce 100644
--- a/paddle/fluid/framework/op_desc.h
+++ b/paddle/fluid/framework/op_desc.h
@@ -217,7 +217,7 @@ class OpDesc {
     return ret_val;
   }
 
-  // it it really needed? or just mantain a ptr from block?
+  // it it really needed? or just maintain a ptr from block?
   proto::OpDesc desc_;
   BlockDesc *block_{nullptr};  // not_own
   // input arg name => input variable names
diff --git a/paddle/fluid/framework/op_proto_maker.cc b/paddle/fluid/framework/op_proto_maker.cc
index 5f75991b50671bd5293a89ff0020c103830f35a8..fbad45e889156347dcaf454331c8850ddea55e99 100644
--- a/paddle/fluid/framework/op_proto_maker.cc
+++ b/paddle/fluid/framework/op_proto_maker.cc
@@ -98,12 +98,12 @@ void OpProtoAndCheckerMaker::operator()(proto::OpProto* proto,
       .SetDefault({})
       .AsExtra();
 
-  AddAttr<std::string>(OpNamescopeAttrName(), "Operator name with namesope.")
+  AddAttr<std::string>(OpNamescopeAttrName(), "Operator name with namescope.")
       .SetDefault("")
       .AsExtra();
 
   AddAttr<std::vector<std::string>>(OpCreationCallstackAttrName(),
-                                    "Callstack for Op Creatation.")
+                                    "Callstack for Op Creation.")
       .SetDefault({})
       .AsExtra();
   AddAttr<std::string>(OpDeviceAttrName(), "Device type of this operator.")
diff --git a/paddle/fluid/operators/ops_extra_info.h b/paddle/fluid/operators/ops_extra_info.h
index 33f8c8ddb9c8ef89f57e6487659272a5bf9f0961..b16e4ed58f3fe24057325b1520cf6c342c52f180 100644
--- a/paddle/fluid/operators/ops_extra_info.h
+++ b/paddle/fluid/operators/ops_extra_info.h
@@ -37,7 +37,7 @@ enum class ExtraAttrProperty : uint8_t {
   SCHEDULE,
   // The attributes for ONEDNN only, can be saved in OneDNNContext
   ONEDNN,
-  // The attributes for ONEDNN only, can be saved in GPUContext
+  // The attributes for GPUDNN only, can be saved in GPUContext
   GPUDNN,
   // Add necessary properties as needed
 };
diff --git a/paddle/phi/api/ext/op_meta_info.h b/paddle/phi/api/ext/op_meta_info.h
index 546b0accf8ba7e41b71f672807257ffa783de0c2..7d2be9c90d79ed5b950d3d23866833e8511a98fc 100644
--- a/paddle/phi/api/ext/op_meta_info.h
+++ b/paddle/phi/api/ext/op_meta_info.h
@@ -271,7 +271,7 @@ struct KernelFuncImpl<Return (*)(Args...), impl_fn> {
     static void Compute(CustomOpKernelContext* ctx, const Args&... args) {
       static_assert(out_idx == 0,
                     "If return std::vector<Tensor> in Custom OpKernel, "
-                    "you cannot pass output by kernel funciton argument.");
+                    "you cannot pass output by kernel function argument.");
       auto outs = impl_fn(args...);
       auto* orig_outs = ctx->AllMutableOutput();
       PD_CHECK(orig_outs->size() == outs.size(),
@@ -626,8 +626,7 @@ class PADDLE_API OpMetaInfoBuilder {
 void RegisterAllCustomOperator();
 
 // Using this api to load compiled custom operator's dynamic library and
-// register Custom
-// Operator into it
+// register Custom Operator into it
 void LoadCustomOperatorLib(const std::string& dso_name);
 
 /////////////////////// Op register Macro /////////////////////////