PaddlePaddle · luotao1 · Aug 5, 2025 · Aug 3, 2025
diff --git a/paddle/fluid/eager/accumulation/accumulation_node.cc b/paddle/fluid/eager/accumulation/accumulation_node.cc
@@ -161,12 +161,12 @@ GradNodeAccumulation::operator()(
   VLOG(3) << "Running AD API Grad: GradNodeAccumulation";
   PADDLE_ENFORCE(grads.size() == 1,
                  common::errors::Fatal(
-                     "GradNodeAccumulation should take exactly 1 grad tensor"
+                     "GradNodeAccumulation should take exactly 1 grad tensor. "
                      "However received: %d slot.",
                      grads.size()));
   PADDLE_ENFORCE(grads[0].size() == 1,
                  common::errors::Fatal(
-                     "GradNodeAccumulation should take exactly 1 grad tensor"
+                     "GradNodeAccumulation should take exactly 1 grad tensor. "
                      "However received: %d in slot %d .",
                      grads[0].size(),
                      0));

diff --git a/paddle/fluid/eager/api/manual/eager_manual/nodes/multiply_node.cc b/paddle/fluid/eager/api/manual/eager_manual/nodes/multiply_node.cc
@@ -484,8 +484,8 @@ MultiplyDoubleGradNode::operator()(
   if (need_skip) {
     if (trace_backward) {
       PADDLE_THROW(common::errors::Unavailable(
-          "The Op multiply_double_grad doesn't have any grad"
-          "op. If you don't intend calculating higher order"
+          "The Op multiply_double_grad doesn't have any grad "
+          "op. If you don't intend calculating higher order "
           "derivatives, please set `create_graph`to False."));
     }
   }
@@ -669,8 +669,8 @@ MultiplyGradNode::operator()(
   // Create Grad Node
   if (trace_backward) {
     PADDLE_THROW(common::errors::Unavailable(
-        "The Op multiply_grad doesn't have any grad"
-        "op. If you don't intend calculating higher order"
+        "The Op multiply_grad doesn't have any grad "
+        "op. If you don't intend calculating higher order "
         "derivatives, please set `create_graph`to False."));
   }
   VLOG(4) << "Finish AD API GRAD: multiply_grad";

diff --git a/paddle/fluid/eager/api/manual/eager_manual/nodes/sync_batch_norm_node.cc b/paddle/fluid/eager/api/manual/eager_manual/nodes/sync_batch_norm_node.cc
@@ -201,8 +201,8 @@ SyncBatchNormGradNode::operator()(
   // Create Grad Node
   if (trace_backward) {
     PADDLE_THROW(common::errors::Unavailable(
-        "The Op sync_batch_norm_grad doesn't have any grad"
-        "op. If you don't intend calculating higher order"
+        "The Op sync_batch_norm_grad doesn't have any grad "
+        "op. If you don't intend calculating higher order "
         "derivatives, please set `create_graph`to False."));
   }
   VLOG(4) << "Finish AD API GRAD: sync_batch_norm_grad";
@@ -442,8 +442,8 @@ SyncBatchNormGradNode::operator()(
   // Create Grad Node
   if (trace_backward) {
     PADDLE_THROW(common::errors::Unavailable(
-        "The Op sync_batch_norm_grad doesn't have any grad"
-        "op. If you don't intend calculating higher order"
+        "The Op sync_batch_norm_grad doesn't have any grad "
+        "op. If you don't intend calculating higher order "
         "derivatives, please set `create_graph`to False."));
   }
   VLOG(4) << "Finish AD API GRAD: sync_batch_norm_grad";

diff --git a/paddle/fluid/eager/general_grad.h b/paddle/fluid/eager/general_grad.h
@@ -304,7 +304,7 @@ class GeneralGrad {
 
         PADDLE_ENFORCE_NOT_NULL(
             target_node,
-            common::errors::Fatal("There is no grad op for inputs:[%d] or it's"
+            common::errors::Fatal("There is no grad op for inputs:[%d] or it's "
                                   "stop_gradient=True.",
                                   i));
 

diff --git a/paddle/fluid/eager/to_static/run_program_impl.cc b/paddle/fluid/eager/to_static/run_program_impl.cc
@@ -1070,7 +1070,7 @@ void LegacyRunProgramGradImpl(
   if (!cache.Has(cache_key)) {
     phi::RecordEvent record_event(
         "create_new_interpretercore", phi::TracerEventType::UserDefined, 1);
-    VLOG(2) << "No interpretercore cache, so create a new interpretercore"
+    VLOG(2) << "No interpretercore cache, so create a new interpretercore "
                "for program: "
             << program_id;
     details::ShareTensorsIntoScope(out_grad, global_inner_scope);

diff --git a/paddle/fluid/framework/ir/elementwiseadd_transpose_pass.cc b/paddle/fluid/framework/ir/elementwiseadd_transpose_pass.cc
@@ -153,7 +153,7 @@ int ElementwiseAddTransposeFusePass::ApplyEleTransPattern(
           << "found that shape_attr[3](channel size) mod 8 !=0 for reshape op "
              "in elementwise_add_transpose, "
              "currently, the elementwiseadd transpose pass only support "
-             "channel size mod 8 == 0 for khwc8 trt format"
+             "channel size mod 8 == 0 for khwc8 trt format. "
              "Therefore, the fusion will be stopped.";
       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
@@ -113,9 +113,9 @@ void PrelnSkipLayerNormFusePass::ApplyImpl(ir::Graph *graph) const {
         graph->Has(framework::ir::kMultiheadMatmulPass) && !pos_id.empty() &&
         !mask_id.empty() && with_dynamic_shape)) {
     VLOG(3) << "preln_skip_layernorm_fuse_pass need: use_trt, enable_int8, "
-               "with_interleaved"
+               "with_interleaved, "
                "use_varseqlen, preln_embedding_eltwise_layernorm_fuse_pass, "
-               "trt_multihead_matmul_fuse_pass"
+               "trt_multihead_matmul_fuse_pass, "
                "set pos_id, set mask_id, with_dynamic_shape. Stop this pass, "
                "please "
                "reconfig.";

diff --git a/paddle/fluid/framework/ir/transfer_layout_elim_pass.cc b/paddle/fluid/framework/ir/transfer_layout_elim_pass.cc
@@ -92,8 +92,8 @@ void TransferLayoutElimPass::PutTransferlayoutAfterOp(
   PADDLE_ENFORCE_EQ(
       var2_shape.size() >= 4L,
       true,
-      common::errors::InvalidArgument("var2_shape.size is too small"
-                                      "expected no small than 4L"
+      common::errors::InvalidArgument("var2_shape.size is too small, "
+                                      "expected no small than 4L, "
                                       "received %d",
                                       var2_shape.size()));
   auto new_var2_shape = var2_shape;

diff --git a/paddle/fluid/framework/new_executor/interpreter/interpreter_util.cc b/paddle/fluid/framework/new_executor/interpreter/interpreter_util.cc
@@ -632,7 +632,7 @@ void BuildOpFuncList(const phi::Place& place,
         "conditional_block",
         "conditional_block_grad",
         "pylayer",
-        "pylayer_grad"
+        "pylayer_grad",
         "recurrent_grad",
         "while",
         "while_grad"};

diff --git a/paddle/fluid/framework/op_registry.cc b/paddle/fluid/framework/op_registry.cc
@@ -109,7 +109,7 @@ static VariableNameMap ConvertOpDescVarsToVarNameMap(
 
 std::unique_ptr<OperatorBase> OpRegistry::CreateOp(
     const proto::OpDesc& op_desc) {
-  VLOG(1) << "CreateOp directly from OpDesc is deprecated. It should only be"
+  VLOG(1) << "CreateOp directly from OpDesc is deprecated. It should only be "
              "used in unit tests. Use CreateOp(const OpDesc& op_desc) "
              "instead.";
   VariableNameMap inputs = ConvertOpDescVarsToVarNameMap(op_desc.inputs());

diff --git a/paddle/fluid/imperative/reducer.cc b/paddle/fluid/imperative/reducer.cc
@@ -652,13 +652,13 @@ void Reducer::PrepareForBackward(
 // concat + allreduce + split is emitted in turn according to next_group_.
 // 3, FinalizeBackward: after the end, synchronize each stream.
 void Reducer::AddDistHook(size_t var_index) {
-  PADDLE_ENFORCE_LT(
-      var_index,
-      variable_locators_.size(),
-      common::errors::OutOfRange("Out of bounds variable index. it must be less"
-                                 "than %d, but it is %d",
-                                 variable_locators_.size(),
-                                 var_index));
+  PADDLE_ENFORCE_LT(var_index,
+                    variable_locators_.size(),
+                    common::errors::OutOfRange(
+                        "Out of bounds variable index. it must be less "
+                        "than %d, but it is %d",
+                        variable_locators_.size(),
+                        var_index));
 
   // gradient synchronization is not required when grad_need_hooks_ is false.
   if (!grad_need_hooks_) {

diff --git a/paddle/fluid/inference/api/details/zero_copy_tensor.cc b/paddle/fluid/inference/api/details/zero_copy_tensor.cc
@@ -372,7 +372,7 @@ void Tensor::CopyStringsFromCpu(const paddle_infer::Strings *data) {
                     0,
                     common::errors::PreconditionNotMet(
                         "You should call Tensor::Reshape(const "
-                        "std::size_t &shape)function before copying"
+                        "std::size_t &shape) function before copying "
                         "the string data from cpu."));
   *tensor = *data;
 }

diff --git a/paddle/fluid/inference/tensorrt/op_teller.cc b/paddle/fluid/inference/tensorrt/op_teller.cc
@@ -1430,7 +1430,7 @@ struct SimpleOpTypeSetTeller : public Teller {
             input_type != framework::proto::VarType::FP32 &&
             input_type != framework::proto::VarType::FP64) {
           VLOG(3) << "the fill_any_like only supports "
-                     "int32/int64/float32/float64 by"
+                     "int32/int64/float32/float64 by "
                      "trt8.4 below";
           return false;
         }

diff --git a/paddle/fluid/operators/hierarchical_sigmoid_op.cc b/paddle/fluid/operators/hierarchical_sigmoid_op.cc
@@ -88,18 +88,18 @@ class HierarchicalSigmoidOpMaker : public framework::OpProtoAndCheckerMaker {
              "(phi::DenseTensor, required), The parameters of hierarchical "
              "sigmoid operator, each of them is a 2-D tensor, the shape is"
              "[K, D]. Which K is the num of non-leaf node in Path Tree");
-    AddInput("Label",
-             "(phi::DenseTensor, required), The labels of training data. It's a"
-             "tensor with shape [N, 1].");
     AddInput(
-        "PathTable",
-        "(phi::DenseTensor, optional), The Path Table from root to current word"
-        "it should have shape like [N, L], L is the length of the Path")
+        "Label",
+        "(phi::DenseTensor, required), The labels of training data. It's a "
+        "tensor with shape [N, 1].");
+    AddInput("PathTable",
+             "(phi::DenseTensor, optional), The Path Table from root to "
+             "current word, it should have shape like [N, L], L is the length "
+             "of the Path")
         .AsDispensable();
     AddInput("PathCode",
              "(phi::DenseTensor, optional), The Code on each Node of the Path "
-             "from root "
-             "to current word"
+             "from root to current word, "
              "it should have shape like [N, L], L is the length of the Path")
         .AsDispensable();
     AddInput("Bias",
@@ -118,8 +118,7 @@ class HierarchicalSigmoidOpMaker : public framework::OpProtoAndCheckerMaker {
         .AsIntermediate();
     AddOutput("W_Out",
               "(phi::DenseTensor, optional) using input 'W' as Output to make "
-              "it mutable"
-              "When we are using prefetch")
+              "it mutable when we are using prefetch")
         .AsIntermediate();
     AddAttr<AttrType>("num_classes", "(int, optional), The number of classes")
         .SetDefault(2);

diff --git a/paddle/fluid/operators/lookup_table_op.cc b/paddle/fluid/operators/lookup_table_op.cc
@@ -109,7 +109,7 @@ class LookupTableOpMaker : public framework::OpProtoAndCheckerMaker {
     AddAttr<std::string>("entry_config",
                          "embedding sparse feature entry config, "
                          " probability entry / counting "
-                         " this can only be used in distributed training"
+                         " this can only be used in distributed training "
                          "entry")
         .SetDefault("");