cherry pick: reduce log for type promotion. (#62116)

Author: zxcd

paddle/fluid/eager/api/manual/eager_manual/forwards/multiply_fwd_func.cc

@@ -61,8 +61,9 @@ paddle::Tensor multiply_ad_func(const paddle::Tensor& x,
   // Type promotion Logic
   if (phi::NeedTypePromotion(x.dtype(), y.dtype())) {
     VLOG(5) << "got different data type, run type protmotion automatically.";
-    LOG(WARNING) << "got different data type, run type protmotion "
-                    "automatically, this may cause data type been changed.";
+    LOG_FIRST_N(WARNING, 1)
+        << "got different data type, run type protmotion "
+           "automatically, this may cause data type been changed.";
     auto op_name = phi::TransToFluidOpName("multiply");
     auto promotion_type = phi::GetPromoteDtype(op_name, x.dtype(), y.dtype());
 
@@ -407,8 +408,9 @@ paddle::Tensor multiply_ad_func(const paddle::Tensor& x,
   // Type promotion Logic
   if (phi::NeedTypePromotion(x.dtype(), y.dtype())) {
     VLOG(5) << "got different data type, run type protmotion automatically.";
-    LOG(WARNING) << "got different data type, run type protmotion "
-                    "automatically, this may cause data type been changed.";
+    LOG_FIRST_N(WARNING, 1)
+        << "got different data type, run type protmotion "
+           "automatically, this may cause data type been changed.";
     auto op_name = phi::TransToFluidOpName("multiply");
     auto promotion_type = phi::GetPromoteDtype(op_name, x.dtype(), y.dtype());
 

paddle/fluid/eager/auto_code_generator/generator/eager_gen.py

@@ -528,7 +528,7 @@ class {} : public egr::GradNodeBase {{
 
 TYPE_PROMOTION_LOGIC_TEMPLATE = """   if (phi::NeedTypePromotion({x}.dtype(), {y}.dtype())) {{
     VLOG(5) << "got different data type, run type protmotion automatically.";
-    LOG(WARNING) << "got different data type, run type protmotion automatically, this may cause data type been changed.";
+    LOG_FIRST_N(WARNING, 1) << "got different data type, run type protmotion automatically, this may cause data type been changed.";
     {op_name}
     auto promotion_type = phi::GetPromoteDtype(op_name, {x}.dtype(), {y}.dtype());
 

python/paddle/base/layers/math_op_patch.py

@@ -538,8 +538,10 @@ def __impl__(self, other_var):
                             op_type, lhs_dtype, rhs_dtype
                         )
                         warnings.warn(
-                            f"The input dtypes of OP {op_type} are {lhs_dtype} and {rhs_dtype}, "
-                            "the output will be auto-promoted to {common_dtype}"
+                            f"The input dtypes of OP {op_type} are {lhs_dtype} and {rhs_dtype}, the output will be auto-promoted to {common_dtype}"
+                        )
+                        warnings.filterwarnings(
+                            "ignore", message="The input dtypes of OP"
                         )
                         if rhs_dtype != common_dtype:
                             other_var = astype(other_var, common_dtype)