2022-06-01_pre-commit

PaddlePaddle · Jun 1, 2022 · a6c17b0 · a6c17b0
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Showing 2 changed files with 32 additions and 27 deletions.
diff --git a/python/paddle/nn/functional/loss.py b/python/paddle/nn/functional/loss.py
@@ -2232,13 +2232,13 @@ def hinge_embedding_loss(input, label, margin=1.0, reduction='mean', name=None):
 
 
 def triplet_margin_with_distance_loss(input,
-				      positive,
-				      negative,
-				      distance_function = None,
-				      margin=1.0, 
-                        	      swap=False, 
-				      reduction='mean',
-                        	      name=None):
+                                      positive,
+                                      negative,
+                                      distance_function=None,
+                                      margin=1.0,
+                                      swap=False,
+                                      reduction='mean',
+                                      name=None):
     r"""
     Measures the triplet loss given an input
     tensors :math:`x1`, :math:`x2`, :math:`x3` and a margin with a value greater than :math:`0`.
@@ -2275,7 +2275,7 @@ def triplet_margin_with_distance_loss(input,
 
         distance_function (callable, optional): Quantifies the distance between two tensors. if not specified, 2 norm functions will be used.
 	
-	margin (float, optional):Default: :math:`1`.A nonnegative margin representing the minimum difference
+	    margin (float, optional):Default: :math:`1`.A nonnegative margin representing the minimum difference
             between the positive and negative distances required for the loss to be 0.
 	
         swap (bool, optional):The distance swap changes the negative distance to the swap distance (distance between positive samples
@@ -2313,10 +2313,9 @@ def triplet_margin_with_distance_loss(input,
 
     """
     if reduction not in ['sum', 'mean', 'none']:
-        raise ValueError(
-            "'reduction' in 'triplet_margin_with_distance_loss' "
-            "should be 'sum', 'mean' or 'none', "
-            "but received {}.".format(reduction))
+        raise ValueError("'reduction' in 'triplet_margin_with_distance_loss' "
+                         "should be 'sum', 'mean' or 'none', "
+                         "but received {}.".format(reduction))
     if margin < 0:
         raise ValueError(
             "The margin between positive samples and negative samples should be greater than 0."
@@ -2329,11 +2328,10 @@ def triplet_margin_with_distance_loss(input,
         check_variable_and_dtype(negative, 'negative', ['float32', 'float64'],
                                  'triplet_margin_with_distance_loss')
 
-    if not(input.shape==positive.shape==negative.shape):
-        raise ValueError(
-            "input's shape must equal to "
-            "positive's shape and  "
-            "negative's shape")
+    if not (input.shape == positive.shape == negative.shape):
+        raise ValueError("input's shape must equal to "
+                         "positive's shape and  "
+                         "negative's shape")
 
     distance_function = distance_function if distance_function is not None \
         else paddle.nn.PairwiseDistance(2)
@@ -2350,7 +2348,7 @@ def triplet_margin_with_distance_loss(input,
             "The positive distance or negative distance should be greater than 0, "
             "The distance functions should be checked.")
 
-    loss = paddle.clip(positive_dist-negative_dist+margin, min=0.0)
+    loss = paddle.clip(positive_dist - negative_dist + margin, min=0.0)
 
     if reduction == 'mean':
         return paddle.mean(loss, name=name)

diff --git a/python/paddle/nn/layer/loss.py b/python/paddle/nn/layer/loss.py
@@ -1361,7 +1361,7 @@ class TripletMarginWithDistanceLoss(Layer):
         negative (Tensor):Negative tensor, the data type is float32 or float64.
 	The shape of label is the same as the shape of input.
 	
-	output(Tensor): The tensor variable storing the triplet_margin_with_distance_loss of input and positive and negative.
+	    output(Tensor): The tensor variable storing the triplet_margin_with_distance_loss of input and positive and negative.
 
     Return：
         A callable object of TripletMarginWithDistanceLoss
@@ -1386,7 +1386,13 @@ class TripletMarginWithDistanceLoss(Layer):
             # Tensor([0.19165580])
 
     """
-    def __init__(self, distance_function=None, margin=1.0, swap=False, reduction: str = 'mean', name=None):
+
+    def __init__(self,
+                 distance_function=None,
+                 margin=1.0,
+                 swap=False,
+                 reduction: str='mean',
+                 name=None):
         super(TripletMarginWithDistanceLoss, self).__init__()
         if reduction not in ['sum', 'mean', 'none']:
             raise ValueError(
@@ -1400,10 +1406,11 @@ def __init__(self, distance_function=None, margin=1.0, swap=False, reduction: st
         self.name = name
 
     def forward(self, input, positive, negative):
-        return F.triplet_margin_with_distance_loss(input,
-                                                   positive,
-                                                   negative,
-                                                   margin=self.margin,
-                                                   swap=self.swap,
-                                                   reduction=self.reduction,
-                                                   name=self.name)
+        return F.triplet_margin_with_distance_loss(
+            input,
+            positive,
+            negative,
+            margin=self.margin,
+            swap=self.swap,
+            reduction=self.reduction,
+            name=self.name)