Mu-L · pull · Nov 12, 2025 · Nov 12, 2025 · Nov 12, 2025 · Nov 12, 2025
diff --git a/paddle/ap/include/axpr/builtin_class_instance_method_class.h b/paddle/ap/include/axpr/builtin_class_instance_method_class.h
@@ -88,14 +88,14 @@ struct MethodClassImpl<ValueT, BuiltinClassInstance<ValueT>> {
     if (opt_val.has_value()) {
       return opt_val.value();
     }
-    const auto& opt_gettattr = GetClassAttr(self, "__getattr__");
+    const auto& opt_getattr = GetClassAttr(self, "__getattr__");
     const auto& class_attrs = self.type.class_attrs();
-    ADT_CHECK(opt_gettattr.has_value())
+    ADT_CHECK(opt_getattr.has_value())
         << adt::errors::AttributeError{std::string() + class_attrs->class_name +
                                        " class has no attribute '__getattr__'"};
     std::vector<ValueT> args{attr_name_val};
     ADT_LET_CONST_REF(ret,
-                      interpreter->InterpretCall(opt_gettattr.value(), args));
+                      interpreter->InterpretCall(opt_getattr.value(), args));
     return ret;
   }
 

diff --git a/paddle/cinn/backends/codegen_c.cc b/paddle/cinn/backends/codegen_c.cc
@@ -870,8 +870,8 @@ void CodeGenC::Visit(const ir::_LoweredFunc_ *op) {
   std::vector<Expr> new_body;
 
   std::vector<Expr> create_temp_buffers = op->PrepareCreateTempBufferExprs();
-  std::vector<Expr> alloca_temp_buffers = op->PrepareAllocTempBufferExprs();
-  std::vector<Expr> dealloca_temp_buffers = op->PrepareDeallocTempBufferExprs();
+  std::vector<Expr> alloc_temp_buffers = op->PrepareAllocTempBufferExprs();
+  std::vector<Expr> dealloc_temp_buffers = op->PrepareDeallocTempBufferExprs();
 #define APPEND_TO_NEW_BODY(field__) \
   new_body.insert(                  \
       std::end(new_body), std::begin(op->field__), std::end(op->field__));
@@ -881,13 +881,13 @@ void CodeGenC::Visit(const ir::_LoweredFunc_ *op) {
                   std::end(create_temp_buffers));
   APPEND_TO_NEW_BODY(alloc_output_buffer_exprs)
   new_body.insert(std::end(new_body),
-                  std::begin(alloca_temp_buffers),
-                  std::end(alloca_temp_buffers));
+                  std::begin(alloc_temp_buffers),
+                  std::end(alloc_temp_buffers));
   APPEND_TO_NEW_BODY(buffer_data_cast_exprs)
   new_body.push_back(op->body);
   new_body.insert(std::end(new_body),
-                  std::begin(dealloca_temp_buffers),
-                  std::end(dealloca_temp_buffers));
+                  std::begin(dealloc_temp_buffers),
+                  std::end(dealloc_temp_buffers));
   APPEND_TO_NEW_BODY(dealloc_output_buffer_exprs)
 
   Expr func_body = ir::Block::Make(new_body);

diff --git a/paddle/cinn/backends/codegen_gpu_dev.cc b/paddle/cinn/backends/codegen_gpu_dev.cc
@@ -170,7 +170,7 @@ void CodeGenGpuDev::Visit(const ir::_LoweredFunc_ *op) {
 
   auto axis_range_assumption_stmts = op->PrepareAxisRangeAssumptionStmts();
   auto alloca_temp_buffer_stmts = op->PrepareAllocTempBufferStmts();
-  auto temp_buffer_alia_stmts = GenerateBufferAliasStmts(op, op->temp_bufs);
+  auto temp_buffer_alias_stmts = GenerateBufferAliasStmts(op, op->temp_bufs);
   auto alias_var_stmts = op->CudaAliasVarStmts();
   auto dealloc_temp_buffer_stmts =
       FilterDeallocTempBuffers(op->PrepareDeallocTempBufferStmts());
@@ -180,7 +180,7 @@ void CodeGenGpuDev::Visit(const ir::_LoweredFunc_ *op) {
       std::end(new_body_stmts), std::begin(field__), std::end(field__));
   APPEND_TO_NEW_BODY_STMTS(axis_range_assumption_stmts)
   APPEND_TO_NEW_BODY_STMTS(alloca_temp_buffer_stmts)
-  APPEND_TO_NEW_BODY_STMTS(temp_buffer_alia_stmts)
+  APPEND_TO_NEW_BODY_STMTS(temp_buffer_alias_stmts)
   APPEND_TO_NEW_BODY_STMTS(alias_var_stmts)
   APPEND_TO_NEW_BODY_STMTS(op->body_block->stmts())
   APPEND_TO_NEW_BODY_STMTS(dealloc_temp_buffer_stmts);

diff --git a/paddle/cinn/backends/llvm/codegen_llvm.cc b/paddle/cinn/backends/llvm/codegen_llvm.cc
@@ -1165,16 +1165,16 @@ llvm::Value *CodeGenLLVM::Visit(const ir::_LoweredFunc_ *op) {
 
   std::vector<Expr> new_body;
   auto create_temp_buffers = op->PrepareCreateTempBufferExprs();
-  auto alloca_temp_buffers = op->PrepareAllocTempBufferExprs();
-  auto dealloca_temp_buffers = op->PrepareDeallocTempBufferExprs();
+  auto alloc_temp_buffers = op->PrepareAllocTempBufferExprs();
+  auto dealloc_temp_buffers = op->PrepareDeallocTempBufferExprs();
 
   appendBody(new_body, op->argument_prepare_exprs);
   appendBody(new_body, create_temp_buffers);
-  appendBody(new_body, alloca_temp_buffers);
+  appendBody(new_body, alloc_temp_buffers);
   appendBody(new_body, op->alloc_output_buffer_exprs);
   appendBody(new_body, op->buffer_data_cast_exprs);
   appendBody(new_body, op->body);
-  appendBody(new_body, dealloca_temp_buffers);
+  appendBody(new_body, dealloc_temp_buffers);
   appendBody(new_body, op->dealloc_output_buffer_exprs);
 
   ir::Expr function_body = ir::Block::Make(new_body);

diff --git a/paddle/cinn/backends/nvrtc/nvrtc_util.cc b/paddle/cinn/backends/nvrtc/nvrtc_util.cc
@@ -291,9 +291,6 @@ std::string Compiler::CompileWithNvcc(const std::string& cuda_c) {
   return prefix_name_ + ".cubin";
 }
 
-// std::string Compiler::GetPtx() { return ReadFile(prefix_name_ + ".ptx",
-// std::ios::in); }
-
 void Compiler::CompileToPtx() {
   auto include_dir = cinn::common::Context::Global().runtime_include_dir();
   std::string include_dir_str = "";

diff --git a/paddle/cinn/backends/sycl/codegen_sycl_dev.cc b/paddle/cinn/backends/sycl/codegen_sycl_dev.cc
@@ -156,7 +156,7 @@ void CodeGenSyclDevice::PrintFunctionBody(const ir::_LoweredFunc_ *op) {
   std::vector<ir::stmt::StmtRef> new_body_stmts;
   auto axis_range_assumption_stmts = op->PrepareAxisRangeAssumptionStmts();
   auto alloca_temp_buffer_stmts = op->PrepareAllocTempBufferStmts();
-  auto temp_buffer_alia_stmts = GenerateBufferAliasStmts(op, op->temp_bufs);
+  auto temp_buffer_alias_stmts = GenerateBufferAliasStmts(op, op->temp_bufs);
   auto alias_var_stmts = op->CudaAliasVarStmts();
   auto dealloc_temp_buffer_stmts =
       FilterDeallocTempBuffers(op->PrepareDeallocTempBufferStmts());
@@ -165,7 +165,7 @@ void CodeGenSyclDevice::PrintFunctionBody(const ir::_LoweredFunc_ *op) {
       std::end(new_body_stmts), std::begin(field__), std::end(field__));
   APPEND_TO_NEW_BODY_STMTS(axis_range_assumption_stmts)
   APPEND_TO_NEW_BODY_STMTS(alloca_temp_buffer_stmts)
-  APPEND_TO_NEW_BODY_STMTS(temp_buffer_alia_stmts)
+  APPEND_TO_NEW_BODY_STMTS(temp_buffer_alias_stmts)
   APPEND_TO_NEW_BODY_STMTS(alias_var_stmts)
   APPEND_TO_NEW_BODY_STMTS(op->body_block->stmts())
   APPEND_TO_NEW_BODY_STMTS(dealloc_temp_buffer_stmts);

diff --git a/paddle/fluid/framework/ir/embedding_eltwise_layernorm_fuse_pass.cc b/paddle/fluid/framework/ir/embedding_eltwise_layernorm_fuse_pass.cc
@@ -477,4 +477,4 @@ REGISTER_PASS_CAPABILITY(embedding_eltwise_layernorm_fuse_pass)
         paddle::framework::compatible::OpVersionComparatorCombination()
             .LE("lookup_table", 1)
             .LE("lookup_table_v2", 1)
-            .LE("elementweise_add", 1));
+            .LE("elementwise_add", 1));
diff --git a/paddle/fluid/framework/ir/fuse_bn_act_pass.cc b/paddle/fluid/framework/ir/fuse_bn_act_pass.cc
@@ -29,15 +29,13 @@ namespace paddle::framework::ir {
 
 void FuseBatchNormActPass::ApplyImpl(ir::Graph *graph) const {
 #if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
-#if defined(PADDLE_WITH_HIP) || CUDNN_VERSION_MIN(7, 4, 1)
   // forward
   std::unordered_set<std::string> act_types = {"relu"};
   graph = FuseBatchNormAct(graph, act_types);
   // backward
   std::unordered_set<std::string> act_grad_types = {"relu_grad"};
   graph = FuseBatchNormActGrad(graph, act_grad_types);  // NOLINT
 #endif
-#endif
 }
 
 // act(bn(x))

diff --git a/paddle/fluid/framework/ir/fuse_bn_add_act_pass.cc b/paddle/fluid/framework/ir/fuse_bn_add_act_pass.cc
@@ -24,15 +24,13 @@ namespace paddle::framework::ir {
 
 void FuseBatchNormAddActPass::ApplyImpl(ir::Graph *graph) const {
 #if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
-#if defined(PADDLE_WITH_HIP) || CUDNN_VERSION_MIN(7, 4, 1)
   // forward
   std::unordered_set<std::string> act_types = {"relu"};
   graph = FuseBatchNormAddAct(graph, act_types);
   // backward
   std::unordered_set<std::string> act_grad_types = {"relu_grad"};
   graph = FuseBatchNormAddActGrad(graph, act_grad_types);  // NOLINT
 #endif
-#endif
 }
 
 // act(bn(x) + z)

diff --git a/paddle/fluid/framework/ir/graph_pattern_detector.cc b/paddle/fluid/framework/ir/graph_pattern_detector.cc
@@ -5436,7 +5436,7 @@ PDNode *patterns::BNAddActConvGrad::operator()(
   return bn1_grad;
 }
 
-void patterns::SparseConvOptimPartern::operator()() {
+void patterns::SparseConvOptimPattern::operator()() {
   auto sp_conv3d_x = pattern->NewNode(sp_conv3d_x_repr())
                          ->AsInput()
                          ->assert_is_op_input("sparse_conv3d", "x");

diff --git a/paddle/fluid/framework/ir/graph_pattern_detector.h b/paddle/fluid/framework/ir/graph_pattern_detector.h
@@ -2637,9 +2637,9 @@ struct BNAddActConvGrad : public PatternBase {
   PATTERN_DECL_NODE(d_bn2_bias);
 };
 
-struct SparseConvOptimPartern : public PatternBase {
-  SparseConvOptimPartern(PDPattern* pattern, const std::string& name_scope)
-      : PatternBase(pattern, name_scope, "sparse_conv_optim_partern") {}
+struct SparseConvOptimPattern : public PatternBase {
+  SparseConvOptimPattern(PDPattern* pattern, const std::string& name_scope)
+      : PatternBase(pattern, name_scope, "sparse_conv_optim_pattern") {}
 
   void operator()();
   PATTERN_DECL_NODE(sp_conv3d_x);

diff --git a/paddle/fluid/framework/ir/layer_norm_fuse_pass.cc b/paddle/fluid/framework/ir/layer_norm_fuse_pass.cc
@@ -72,7 +72,7 @@ bool validateReduceOpAttrs(const Node* node,
     }
     for (size_t i = 1; i < dims.size(); ++i) {
       if (1 != dims[i] - dims[i - 1]) {
-        LOG(WARNING) << "The LayerNorm dim of mean must be  continuous";
+        LOG(WARNING) << "The LayerNorm dim of mean must be continuous";
         return false;
       }
     }

diff --git a/paddle/fluid/framework/ir/preln_embedding_eltwise_layernorm_fuse_pass.cc b/paddle/fluid/framework/ir/preln_embedding_eltwise_layernorm_fuse_pass.cc
@@ -458,4 +458,4 @@ REGISTER_PASS_CAPABILITY(preln_embedding_eltwise_layernorm_fuse_pass)
         paddle::framework::compatible::OpVersionComparatorCombination()
             .LE("lookup_table", 1)
             .LE("lookup_table_v2", 1)
-            .LE("elementweise_add", 1));
+            .LE("elementwise_add", 1));
diff --git a/paddle/fluid/framework/ir/preln_embedding_eltwise_layernorm_fuse_pass.h b/paddle/fluid/framework/ir/preln_embedding_eltwise_layernorm_fuse_pass.h
@@ -124,8 +124,8 @@ struct PrelnSkipLayerNorm : public PatternBase {
 // (word, weights_0)                lookup_table     ->  word_emb
 // (pos, weights_1)                 lookup_table     ->  pos_emb
 // (sent, weights_2)                lookup_table     ->  sent_emb
-// (word_emb, pos_emb)              elementweise_add -> elementwise_out_0
-// (elemtwise_out_0, sent_emb)      elementweise_add -> elementwise_out_1
+// (word_emb, pos_emb)              elementwise_add -> elementwise_out_0
+// (elemtwise_out_0, sent_emb)      elementwise_add -> elementwise_out_1
 // (elementwise_out_1, scale, bias) layer_norm       -> layer_norm_out
 //
 // and then convert the corresponding subgraph to:

diff --git a/paddle/fluid/framework/ir/preln_residual_bias_fuse_pass.cc b/paddle/fluid/framework/ir/preln_residual_bias_fuse_pass.cc
@@ -217,7 +217,7 @@ int PrelnResidualBiasFusePass::ApplyPattern(ir::Graph *graph,
     // elementwise1_out. This will lead to two or more PrelnResidualBias
     // patterns is found near elementwise1_out, and these patterns will interact
     // on each other, so we make below check to ensure only one
-    // PrelnResidualBias pattern is delalted with.
+    // PrelnResidualBias pattern is dealt with.
     for (auto op : elementwise1_out->inputs) {
       if (op->Name() == "fused_bias_dropout_residual_layer_norm") return;
     }

diff --git a/paddle/fluid/framework/ir/preln_skip_layernorm_fuse_pass.cc b/paddle/fluid/framework/ir/preln_skip_layernorm_fuse_pass.cc
@@ -117,8 +117,7 @@ void PrelnSkipLayerNormFusePass::ApplyImpl(ir::Graph *graph) const {
                "use_varseqlen, preln_embedding_eltwise_layernorm_fuse_pass, "
                "trt_multihead_matmul_fuse_pass, "
                "set pos_id, set mask_id, with_dynamic_shape. Stop this pass, "
-               "please "
-               "reconfig.";
+               "please reconfig.";
     return;
   }
   int found_subgraph_count = 0;

diff --git a/paddle/fluid/framework/ir/seq_concat_fc_fuse_pass.cc b/paddle/fluid/framework/ir/seq_concat_fc_fuse_pass.cc
@@ -37,8 +37,8 @@ PDNode* BuildSeqExpandConcatPattern(PDPattern* pattern) {
   // concat output
 
   // So the following variables will be removed:
-  // sequence-expand output
-  // sequence-expand output
+  // sequence_expand output
+  // sequence_expand output
 
   // Three operators
   auto* sequence_expand0 = pattern->NewNode(

diff --git a/paddle/fluid/framework/ir/sparse_conv_optim_pass.cc b/paddle/fluid/framework/ir/sparse_conv_optim_pass.cc
@@ -60,7 +60,7 @@ SparseConvOptimPass::SparseConvOptimPass() {
 }
 
 void SparseConvOptimPass::ApplyImpl(ir::Graph* graph) const {
-  const std::string pattern_name = "sparse_conv_optim_partern";
+  const std::string pattern_name = "sparse_conv_optim_pattern";
   FusePassBase::Init(pattern_name, graph);
 
   GraphPatternDetector gpd;
@@ -70,7 +70,7 @@ void SparseConvOptimPass::ApplyImpl(ir::Graph* graph) const {
       common::errors::InvalidArgument(
           "Scope in SparseConvOptimPass should not be null."));
   // Create pattern
-  patterns::SparseConvOptimPartern pattern(gpd.mutable_pattern(), pattern_name);
+  patterns::SparseConvOptimPattern pattern(gpd.mutable_pattern(), pattern_name);
   pattern();
   int found_count = 0;
 

diff --git a/paddle/fluid/framework/ir/trt_cross_multihead_matmul_fuse_pass.cc b/paddle/fluid/framework/ir/trt_cross_multihead_matmul_fuse_pass.cc
@@ -311,11 +311,11 @@ int TrtCrossMultiHeadMatmulFusePass::BuildCrossFusion(
     int hidden_out = wq_tensor->dims()[1];
     int head_size = hidden_out / head_number;
     if (abs(scale_attr - 1.0f / sqrt(static_cast<float>(head_size))) > 1e-5) {
-      VLOG(3) << "scale of muilthead matmul do not fit the requirement of "
+      VLOG(3) << "scale of multihead matmul do not fit the requirement of "
                  "flash attention plugin, Stop fusing.";
       return;
     }
-    VLOG(5) << "trt cross attention get wq_tensor name = " << mul0_w->Name()
+    VLOG(5) << "trt cross attention wq_tensor name = " << mul0_w->Name()
             << "trt cross attention wk_tensor name = " << mul1_w->Name()
             << "trt cross attention wv_tensor name = " << mul2_w->Name();
 

diff --git a/paddle/fluid/framework/ir/trt_embedding_eltwise_layernorm_fuse_pass.h b/paddle/fluid/framework/ir/trt_embedding_eltwise_layernorm_fuse_pass.h
@@ -124,8 +124,8 @@ struct TrtSkipLayerNorm : public PatternBase {
 // (word, weights_0)                lookup_table     ->  word_emb
 // (pos, weights_1)                 lookup_table     ->  pos_emb
 // (sent, weights_2)                lookup_table     ->  sent_emb
-// (word_emb, pos_emb)              elementweise_add -> elementwise_out_0
-// (elemtwise_out_0, sent_emb)      elementweise_add -> elementwise_out_1
+// (word_emb, pos_emb)              elementwise_add -> elementwise_out_0
+// (elemtwise_out_0, sent_emb)      elementwise_add -> elementwise_out_1
 // (elementwise_out_1, scale, bias) layer_norm       -> layer_norm_out
 //
 // and then convert the corresponding subgraph to:

diff --git a/paddle/fluid/framework/ir/trt_multihead_matmul_fuse_pass.cc b/paddle/fluid/framework/ir/trt_multihead_matmul_fuse_pass.cc
@@ -62,9 +62,6 @@ static int BuildFusion(Graph* graph, const std::string& name_scope) {
                           Node* scale,
                           Node* scale_out) {
     auto scale_attr = PADDLE_GET_CONST(float, scale->Op()->GetAttr("scale"));
-    // auto scale_bias = PADDLE_GET_CONST(float, scale->Op()->GetAttr("bias"));
-    // bool after_scale =
-    //    PADDLE_GET_CONST(bool, scale->Op()->GetAttr("bias_after_scale"));
 
     // create multihead
     OpDesc multihead_op_desc(mul0->Op()->Block());

diff --git a/paddle/fluid/framework/ir/trt_prompt_tuning_embedding_eltwise_layernorm_fuse_pass.cc b/paddle/fluid/framework/ir/trt_prompt_tuning_embedding_eltwise_layernorm_fuse_pass.cc
@@ -585,4 +585,4 @@ REGISTER_PASS_CAPABILITY(
         paddle::framework::compatible::OpVersionComparatorCombination()
             .LE("lookup_table", 1)
             .LE("lookup_table_v2", 1)
-            .LE("elementweise_add", 1));
+            .LE("elementwise_add", 1));
diff --git a/paddle/fluid/framework/ir/trt_qk_multihead_matmul_fuse_pass.cc b/paddle/fluid/framework/ir/trt_qk_multihead_matmul_fuse_pass.cc
@@ -228,7 +228,7 @@ PDNode* TrtQKMultiHeadMatmulPattern::operator()() {
       .LinksTo({matmul_qk_out_var});
   scale->LinksFrom({matmul_qk_out_var}).LinksTo({scale_out_var});
   softmax_qk->LinksFrom({scale_out_var}).LinksTo({softmax_qk_out_var});
-  // V  path
+  // V path
   mul2->LinksFrom({input1, mul2_w_var}).LinksTo({mul2_out_var});
   elementwise2->LinksFrom({mul2_out_var, elementwise2_w})
       .LinksTo({elementwise2_out});

diff --git a/paddle/fluid/inference/io.cc b/paddle/fluid/inference/io.cc
@@ -148,7 +148,7 @@ void LoadSeparatePersistables(framework::Executor* executor,
   num_threads = std::min(num_threads, persistable_vars.size() / chunk_size);
   size_t remains_size = persistable_vars.size() % num_threads;
   VLOG(4) << "Start Load with multi-thread: " << num_threads
-          << " chund size: " << chunk_size;
+          << " chunk size: " << chunk_size;
 
   auto load_handler = [&](const std::vector<framework::VarDesc*>& vars) {
     if (vars.empty()) {

diff --git a/paddle/fluid/inference/tensorrt/convert/generic_and_custom_plugin_creater.cc b/paddle/fluid/inference/tensorrt/convert/generic_and_custom_plugin_creater.cc
@@ -23,7 +23,7 @@ limitations under the License. */
 
 namespace paddle::inference::tensorrt {
 
-class CustomPluginCreater : public OpConverter {
+class CustomPluginCreator : public OpConverter {
  public:
   void operator()(const framework::proto::OpDesc &op,
                   const framework::Scope &scope,
@@ -335,7 +335,7 @@ class CustomGenericPluginCreator : public OpConverter {
 }  // namespace paddle::inference::tensorrt
 
 REGISTER_TRT_OP_CONVERTER(custom_plugin_creater,
-                          CustomPluginCreater);  // typos: disable-line
+                          CustomPluginCreator);  // typos: disable-line
 REGISTER_TRT_OP_CONVERTER(generic_plugin_creator, GenericPluginCreator);
 REGISTER_TRT_OP_CONVERTER(custom_generic_plugin_creator,
                           CustomGenericPluginCreator);
diff --git a/paddle/fluid/inference/tensorrt/convert/op_converter.h b/paddle/fluid/inference/tensorrt/convert/op_converter.h
@@ -151,7 +151,7 @@ class OpConverter {
         it = Registry<OpConverter>::Global().Lookup("generic_plugin_creator");
         break;
 
-      case OpConverterType::CustomPluginCreater:  // typos: disable-line
+      case OpConverterType::CustomPluginCreator:
         LOG(INFO) << "There is no OpConverter for type " << op_desc.Type()
                   << ", now use custom_plugin_creater!";  // typos: disable-line
         it = Registry<OpConverter>::Global().Lookup(

diff --git a/paddle/fluid/inference/tensorrt/convert/test_custom_plugin_creater.cc b/paddle/fluid/inference/tensorrt/convert/test_custom_plugin_creater.cc
@@ -36,7 +36,7 @@ PD_BUILD_OP(custom_op)
 
 namespace paddle::inference::tensorrt {
 
-TEST(CustomPluginCreater, StaticShapePlugin) {
+TEST(CustomPluginCreator, StaticShapePlugin) {
   framework::ProgramDesc prog;
   auto *block = prog.MutableBlock(0);
   auto *op = block->AppendOp();
@@ -118,14 +118,14 @@ TEST(CustomPluginCreater, StaticShapePlugin) {
           "(*custom_plugin_tell)(custom_op, false, true) is False."));
 
   OpTeller::Global().SetOpConverterType(&custom_op,
-                                        OpConverterType::CustomPluginCreater);
+                                        OpConverterType::CustomPluginCreator);
 
   OpConverter converter;
   converter.ConvertBlock(
       *block->Proto(), {}, scope, engine_.get() /*TensorRTEngine*/);
 }
 
-TEST(CustomPluginCreater, DynamicShapePlugin) {
+TEST(CustomPluginCreator, DynamicShapePlugin) {
   framework::ProgramDesc prog;
   auto *block = prog.MutableBlock(0);
   auto *op = block->AppendOp();
@@ -204,7 +204,7 @@ TEST(CustomPluginCreater, DynamicShapePlugin) {
           "(*custom_plugin_tell)(custom_op, false, true) is False."));
 
   OpTeller::Global().SetOpConverterType(&custom_op,
-                                        OpConverterType::CustomPluginCreater);
+                                        OpConverterType::CustomPluginCreator);
 
   OpConverter converter;
   converter.ConvertBlock(

diff --git a/paddle/fluid/inference/tensorrt/op_teller.cc b/paddle/fluid/inference/tensorrt/op_teller.cc
@@ -3475,9 +3475,7 @@ bool OpTeller::Tell(const framework::ir::Node* node,
                               with_dynamic_shape,
                               forbid_dynamic_op_enter_into_trt,
                               use_explicit_quantization)) {
-    SetOpConverterType(
-        node->Op(),
-        OpConverterType::CustomPluginCreater);  // typos: disable-line
+    SetOpConverterType(node->Op(), OpConverterType::CustomPluginCreator);
     return true;
   }
   auto& custom_generic_plugin_teller = GetCustomGenericPluginTeller();

diff --git a/paddle/fluid/inference/tensorrt/op_teller.h b/paddle/fluid/inference/tensorrt/op_teller.h
@@ -60,7 +60,7 @@ struct Teller {
 enum class OpConverterType {
   Default = 0,
   GenericPluginCreator,
-  CustomPluginCreater,  // typos: disable-line
+  CustomPluginCreator,
   CustomGenericPluginCreator
 };
 /*

diff --git a/paddle/fluid/inference/tensorrt/plugin_arg_mapping_context.cc b/paddle/fluid/inference/tensorrt/plugin_arg_mapping_context.cc
@@ -74,7 +74,7 @@ paddle::any PluginArgumentMappingContext::Attr(
       break;
     };
     default: {
-      LOG(ERROR) << "Can't cover op's attribute [" << attr_name
+      LOG(ERROR) << "Can't covert op's attribute [" << attr_name
                  << "] to paddle any.";
     }
   }