对齐格式

Author: hd9568

docs/guides/model_convert/convert_from_pytorch/api_difference/torch_more_args/torch.nn.BCELoss.md

@@ -25,68 +25,64 @@ PyTorch 相比 Paddle 支持更多其他参数，具体如下：
 | reduction  | reduction            | 表示应用于输出结果的计算方式。  |
 
 ### 转写示例
+
 #### size_average
 size_average 为 True
 ```python
 # PyTorch 写法
-torch.nn.BCELoss(weight=w, size_average=True)
+torch.nn.BCELoss(size_average=True)
 
 # Paddle 写法
-paddle.nn.BCELoss(weight=w, reduction='mean')
+paddle.nn.BCELoss(reduction='mean')
 ```
 
 size_average 为 False
 ```python
 # PyTorch 写法
-torch.nn.BCELoss(weight=w, size_average=False)
+torch.nn.BCELoss(size_average=False)
 
 # Paddle 写法
-paddle.nn.BCELoss(weight=w, reduction='sum')
+paddle.nn.BCELoss(reduction='sum')
 ```
-
 #### reduce
 reduce 为 True
 ```python
 # PyTorch 写法
-torch.nn.BCELoss(weight=w, reduce=True)
+torch.nn.BCELoss(size_average=False)
 
 # Paddle 写法
-paddle.nn.BCELoss(weight=w, reduction='mean')
+paddle.nn.BCELoss(reduction='sum')
 ```
-
 reduce 为 False
 ```python
 # PyTorch 写法
-torch.nn.BCELoss(weight=w, reduce=False)
+torch.nn.BCELoss(reduce=False)
 
 # Paddle 写法
-paddle.nn.BCELoss(weight=w, reduction='none')
+paddle.nn.BCELoss(reduction='none')
 ```
-
 #### reduction
 reduction 为'none'
 ```python
 # PyTorch 写法
-torch.nn.BCELoss(weight=w, reduction='none')
+torch.nn.BCELoss(reduction='none')
 
 # Paddle 写法
-paddle.nn.BCELoss(weight=w, reduction='none')
+paddle.nn.BCELoss(reduction='none')
 ```
-
 reduction 为'mean'
 ```python
 # PyTorch 写法
-torch.nn.BCELoss(weight=w, reduction='mean')
+torch.nn.BCELoss(reduction='mean')
 
 # Paddle 写法
-paddle.nn.BCELoss(weight=w, reduction='mean')
+paddle.nn.BCELoss(reduction='mean')
 ```
-
 reduction 为'sum'
 ```python
 # PyTorch 写法
-torch.nn.BCELoss(weight=w, reduction='sum')
+torch.nn.BCELoss(reduction='sum')
 
 # Paddle 写法
-paddle.nn.BCELoss(weight=w, reduction='sum')
+paddle.nn.BCELoss(reduction='sum')
 ```

docs/guides/model_convert/convert_from_pytorch/api_difference/torch_more_args/torch.nn.BCEWithLogitsLoss.md

@@ -28,65 +28,64 @@ PyTorch 相比 Paddle 支持更多其他参数，具体如下：
 | pos_weight  | pos_weight            | 表示正类的权重。  |
 
 ### 转写示例
-#### size_averagesize_average 为 True
+
+#### size_average
+size_average 为 True
 ```python
 # PyTorch 写法
-torch.nn.BCEWithLogitsLoss(weight=w, size_average=True)
+torch.nn.BCEWithLogitsLoss(size_average=True)
 
 # Paddle 写法
-paddle.nn.BCEWithLogitsLoss(weight=w, reduction='mean')
+paddle.nn.BCEWithLogitsLoss(reduction='mean')
 ```
 
 size_average 为 False
 ```python
 # PyTorch 写法
-torch.nn.BCEWithLogitsLoss(weight=w, size_average=False)
+torch.nn.BCEWithLogitsLoss(size_average=False)
 
 # Paddle 写法
-paddle.nn.BCEWithLogitsLoss(weight=w, reduction='sum')
+paddle.nn.BCEWithLogitsLoss(reduction='sum')
 ```
-
-#### reducereduce 为 True
+#### reduce
+reduce 为 True
 ```python
 # PyTorch 写法
-torch.nn.BCEWithLogitsLoss(weight=w, reduce=True)
+torch.nn.BCEWithLogitsLoss(size_average=False)
 
 # Paddle 写法
-paddle.nn.BCEWithLogitsLoss(weight=w, reduction='mean')
+paddle.nn.BCEWithLogitsLoss(reduction='sum')
 ```
-
 reduce 为 False
 ```python
 # PyTorch 写法
-torch.nn.BCEWithLogitsLoss(weight=w, reduce=False)
+torch.nn.BCEWithLogitsLoss(reduce=False)
 
 # Paddle 写法
-paddle.nn.BCEWithLogitsLoss(weight=w, reduction='none')
+paddle.nn.BCEWithLogitsLoss(reduction='none')
 ```
-
-#### reductionreduction 为'none'
+#### reduction
+reduction 为'none'
 ```python
 # PyTorch 写法
-torch.nn.BCEWithLogitsLoss(weight=w, reduction='none')
+torch.nn.BCEWithLogitsLoss(reduction='none')
 
 # Paddle 写法
-paddle.nn.BCEWithLogitsLoss(weight=w, reduction='none')
+paddle.nn.BCEWithLogitsLoss(reduction='none')
 ```
-
 reduction 为'mean'
 ```python
 # PyTorch 写法
-torch.nn.BCEWithLogitsLoss(weight=w, reduction='mean')
+torch.nn.BCEWithLogitsLoss(reduction='mean')
 
 # Paddle 写法
-paddle.nn.BCEWithLogitsLoss(weight=w, reduction='mean')
+paddle.nn.BCEWithLogitsLoss(reduction='mean')
 ```
-
 reduction 为'sum'
 ```python
 # PyTorch 写法
-torch.nn.BCEWithLogitsLoss(weight=w, reduction='sum')
+torch.nn.BCEWithLogitsLoss(reduction='sum')
 
 # Paddle 写法
-paddle.nn.BCEWithLogitsLoss(weight=w, reduction='sum')
+paddle.nn.BCEWithLogitsLoss(reduction='sum')
 ```

docs/guides/model_convert/convert_from_pytorch/api_difference/torch_more_args/torch.nn.CosineEmbeddingLoss.md

@@ -21,17 +21,64 @@ PyTorch 相比 Paddle 支持更多其他参数，具体如下：
 | reduction    | reduction    | 指定应用于输出结果的计算方式。                 |
 
 ### 转写示例
-#### size_average 和 reduce 参数转 reduction 参数
-```python
-if size_average is None:
-    size_average = True
-if reduce is None:
-    reduce = True
-
-if size_average and reduce:
-    reduction = 'mean'
-elif reduce:
-    reduction = 'sum'
-else:
-    reduction = 'none'
+
+#### size_average
+size_average 为 True
+```python
+# PyTorch 写法
+torch.nn.CosineEmbeddingLoss(size_average=True)
+
+# Paddle 写法
+paddle.nn.CosineEmbeddingLoss(reduction='mean')
+```
+
+size_average 为 False
+```python
+# PyTorch 写法
+torch.nn.CosineEmbeddingLoss(size_average=False)
+
+# Paddle 写法
+paddle.nn.CosineEmbeddingLoss(reduction='sum')
+```
+#### reduce
+reduce 为 True
+```python
+# PyTorch 写法
+torch.nn.CosineEmbeddingLoss(size_average=False)
+
+# Paddle 写法
+paddle.nn.CosineEmbeddingLoss(reduction='sum')
+```
+reduce 为 False
+```python
+# PyTorch 写法
+torch.nn.CosineEmbeddingLoss(reduce=False)
+
+# Paddle 写法
+paddle.nn.CosineEmbeddingLoss(reduction='none')
+```
+#### reduction
+reduction 为'none'
+```python
+# PyTorch 写法
+torch.nn.CosineEmbeddingLoss(reduction='none')
+
+# Paddle 写法
+paddle.nn.CosineEmbeddingLoss(reduction='none')
+```
+reduction 为'mean'
+```python
+# PyTorch 写法
+torch.nn.CosineEmbeddingLoss(reduction='mean')
+
+# Paddle 写法
+paddle.nn.CosineEmbeddingLoss(reduction='mean')
+```
+reduction 为'sum'
+```python
+# PyTorch 写法
+torch.nn.CosineEmbeddingLoss(reduction='sum')
+
+# Paddle 写法
+paddle.nn.CosineEmbeddingLoss(reduction='sum')
 ```

docs/guides/model_convert/convert_from_pytorch/api_difference/torch_more_args/torch.nn.CrossEntropyLoss.md

@@ -36,65 +36,64 @@ PyTorch 相比 Paddle 支持更多其他参数，具体如下：
 | -             | axis       | 进行 softmax 计算的维度索引，PyTorch 无此参数，Paddle 保持默认即可。   |
 
 ### 转写示例
-#### size_average 为 True
+
+#### size_average
+size_average 为 True
 ```python
 # PyTorch 写法
-torch.nn.CrossEntropyLoss(weight=w, size_average=True)
+torch.nn.CrossEntropyLoss(size_average=True)
 
 # Paddle 写法
-paddle.nn.CrossEntropyLoss(weight=w, reduction='mean')
+paddle.nn.CrossEntropyLoss(reduction='mean')
 ```
 
 size_average 为 False
 ```python
 # PyTorch 写法
-torch.nn.CrossEntropyLoss(weight=w, size_average=False)
+torch.nn.CrossEntropyLoss(size_average=False)
 
 # Paddle 写法
-paddle.nn.CrossEntropyLoss(weight=w, reduction='sum')
+paddle.nn.CrossEntropyLoss(reduction='sum')
 ```
-
-#### reduce 为 True
+#### reduce
+reduce 为 True
 ```python
 # PyTorch 写法
-torch.nn.CrossEntropyLoss(weight=w, reduce=True)
+torch.nn.CrossEntropyLoss(size_average=False)
 
 # Paddle 写法
-paddle.nn.CrossEntropyLoss(weight=w, reduction='mean')
+paddle.nn.CrossEntropyLoss(reduction='sum')
 ```
-
 reduce 为 False
 ```python
 # PyTorch 写法
-torch.nn.CrossEntropyLoss(weight=w, reduce=False)
+torch.nn.CrossEntropyLoss(reduce=False)
 
 # Paddle 写法
-paddle.nn.CrossEntropyLoss(weight=w, reduction='none')
+paddle.nn.CrossEntropyLoss(reduction='none')
 ```
-
-#### reduction 为'none'
+#### reduction
+reduction 为'none'
 ```python
 # PyTorch 写法
-torch.nn.CrossEntropyLoss(weight=w, reduction='none')
+torch.nn.CrossEntropyLoss(reduction='none')
 
 # Paddle 写法
-paddle.nn.CrossEntropyLoss(weight=w, reduction='none')
+paddle.nn.CrossEntropyLoss(reduction='none')
 ```
-
 reduction 为'mean'
 ```python
 # PyTorch 写法
-torch.nn.CrossEntropyLoss(weight=w, reduction='mean')
+torch.nn.CrossEntropyLoss(reduction='mean')
 
 # Paddle 写法
-paddle.nn.CrossEntropyLoss(weight=w, reduction='mean')
+paddle.nn.CrossEntropyLoss(reduction='mean')
 ```
-
 reduction 为'sum'
 ```python
 # PyTorch 写法
-torch.nn.CrossEntropyLoss(weight=w, reduction='sum')
+torch.nn.CrossEntropyLoss(reduction='sum')
 
 # Paddle 写法
-paddle.nn.CrossEntropyLoss(weight=w, reduction='sum')
+paddle.nn.CrossEntropyLoss(reduction='sum')
 ```