fix code

Author: zty-king

python/paddle/nn/layer/loss.py

@@ -21,8 +21,8 @@
 from paddle.base.framework import in_dynamic_or_pir_mode
 from paddle.utils.decorator_utils import (
     ParamAliasDecorator,
-    legacy_reduction_guard,
-    legacy_reduction_special_guard,
+    legacy_reduction_decorator,
+    legacy_reduction_special_decorator,
 )
 
 from .. import functional as F
@@ -125,7 +125,7 @@ class BCEWithLogitsLoss(Layer):
     pos_weight: Tensor | None
     name: str | None
 
-    @legacy_reduction_guard
+    @legacy_reduction_decorator
     def __init__(
         self,
         weight: Tensor | None = None,
@@ -423,7 +423,7 @@ class CrossEntropyLoss(Layer):
     label_smoothing: float
     name: str | None
 
-    @legacy_reduction_special_guard
+    @legacy_reduction_special_decorator
     def __init__(
         self,
         weight: Tensor | None = None,
@@ -662,7 +662,7 @@ class MSELoss(Layer):
 
     reduction: _ReduceMode
 
-    @legacy_reduction_guard
+    @legacy_reduction_decorator
     def __init__(self, reduction: _ReduceMode = 'mean'):
         super().__init__()
         if reduction not in ['sum', 'mean', 'none']:
@@ -766,7 +766,7 @@ class L1Loss(Layer):
     reduction: _ReduceMode
     name: str | None
 
-    @legacy_reduction_guard
+    @legacy_reduction_decorator
     def __init__(
         self, reduction: _ReduceMode = 'mean', name: str | None = None
     ) -> None:
@@ -857,7 +857,7 @@ class BCELoss(Layer):
     reduction: _ReduceMode
     name: str | None
 
-    @legacy_reduction_guard
+    @legacy_reduction_decorator
     def __init__(
         self,
         weight: Tensor | None = None,
@@ -970,7 +970,7 @@ class NLLLoss(Layer):
 
     """
 
-    @legacy_reduction_guard
+    @legacy_reduction_decorator
     def __init__(
         self,
         weight: Tensor | None = None,
@@ -1059,7 +1059,7 @@ class PoissonNLLLoss(Layer):
 
     """
 
-    @legacy_reduction_guard
+    @legacy_reduction_decorator
     def __init__(
         self,
         log_input: bool = True,
@@ -1191,7 +1191,7 @@ class KLDivLoss(Layer):
     reduction: _ReduceMode
     log_target: bool
 
-    @legacy_reduction_special_guard
+    @legacy_reduction_special_decorator
     def __init__(
         self, reduction: _ReduceMode = 'mean', log_target: bool = False
     ) -> None:
@@ -1264,7 +1264,7 @@ class MarginRankingLoss(Layer):
     reduction: _ReduceMode
     name: str | None
 
-    @legacy_reduction_guard
+    @legacy_reduction_decorator
     def __init__(
         self,
         margin: float = 0.0,
@@ -1538,7 +1538,7 @@ class SmoothL1Loss(Layer):
     delta: float
     name: str | None
 
-    @legacy_reduction_guard
+    @legacy_reduction_decorator
     def __init__(
         self,
         reduction: _ReduceMode = 'mean',
@@ -1628,7 +1628,7 @@ class MultiLabelSoftMarginLoss(Layer):
     reduction: _ReduceMode
     name: str | None
 
-    @legacy_reduction_guard
+    @legacy_reduction_decorator
     def __init__(
         self,
         weight: Tensor | None = None,
@@ -1741,7 +1741,7 @@ class HingeEmbeddingLoss(Layer):
     reduction: _ReduceMode
     name: str | None
 
-    @legacy_reduction_guard
+    @legacy_reduction_decorator
     def __init__(
         self,
         margin: float = 1.0,
@@ -1840,7 +1840,7 @@ class CosineEmbeddingLoss(Layer):
     reduction: _ReduceMode
     name: str | None
 
-    @legacy_reduction_guard
+    @legacy_reduction_decorator
     def __init__(
         self,
         margin: float = 0,
@@ -2078,7 +2078,7 @@ class TripletMarginLoss(Layer):
     reduction: _ReduceMode
     name: str | None
 
-    @legacy_reduction_guard
+    @legacy_reduction_decorator
     def __init__(
         self,
         margin: float = 1.0,
@@ -2195,7 +2195,7 @@ class MultiMarginLoss(Layer):
     reduction: _ReduceMode
     name: str | None
 
-    @legacy_reduction_guard
+    @legacy_reduction_decorator
     def __init__(
         self,
         p: int = 1,
@@ -2291,7 +2291,7 @@ class MultiLabelMarginLoss(Layer):
     reduction: _ReduceMode
     name: str | None
 
-    @legacy_reduction_guard
+    @legacy_reduction_decorator
     def __init__(
         self,
         reduction: _ReduceMode = 'mean',
@@ -2380,7 +2380,7 @@ class SoftMarginLoss(Layer):
     reduction: _ReduceMode
     name: str | None
 
-    @legacy_reduction_guard
+    @legacy_reduction_decorator
     def __init__(
         self, reduction: _ReduceMode = 'mean', name: str | None = None
     ) -> None:

python/paddle/utils/decorator_utils.py

@@ -778,8 +778,6 @@ def wrapper(*args: _InputT.args, **kwargs: _InputT.kwargs) -> _RetT:
 
 
 def compute_legacy_reduction(reduce_val, size_average_val):
-    reduce_val = reduce_val if reduce_val != '' else None
-    size_average_val = size_average_val if size_average_val != '' else None
     if reduce_val is False:
         return 'none'
     if reduce_val is True:
@@ -810,14 +808,16 @@ def get_legacy_reduce_and_size_average(cls_name, args, kwargs):
 
 def raise_deprecated_error(cls_name, reduce_val, size_avg_val):
     suggested = compute_legacy_reduction(reduce_val, size_avg_val)
+    reduce_val = None if reduce_val == '' else reduce_val
+    size_avg_val = None if size_avg_val == '' else size_avg_val
     raise ValueError(
         f"[Deprecated] '{cls_name}' no longer supports 'reduce' or 'size_average'."
         f"\nDetected: reduce={reduce_val}, size_average={size_avg_val}"
         f"\nPlease use: reduction='{suggested}' instead."
     )
 
 
-def legacy_reduction_guard(init_func):
+def legacy_reduction_decorator(init_func):
     """
     Function decorator for __init__: intercept deprecated 'reduce' and 'size_average'.
     """
@@ -836,7 +836,7 @@ def wrapper(self, *args, **kwargs):
     return wrapper
 
 
-def legacy_reduction_special_guard(init_func):
+def legacy_reduction_special_decorator(init_func):
     """
     Specialized decorator: add CrossEntropyLoss / KLDivLoss special case judgment based on general logic.
     """