update ResNet en docs (#43523)

* add `Returns`

* refine en doc

* refine parameter `pretrained`, test=document_fix

python/paddle/vision/models/resnet.py

@@ -181,13 +181,16 @@ class ResNet(nn.Layer):
 
     Args:
         Block (BasicBlock|BottleneckBlock): block module of model.
-        depth (int, optional): layers of resnet, Default: 50.
+        depth (int, optional): layers of ResNet, Default: 50.
         width (int, optional): base width per convolution group for each convolution block, Default: 64.
         num_classes (int, optional): output dim of last fc layer. If num_classes <=0, last fc layer
                             will not be defined. Default: 1000.
         with_pool (bool, optional): use pool before the last fc layer or not. Default: True.
         groups (int, optional): number of groups for each convolution block, Default: 1.
 
+    Returns:
+        ResNet model. An instance of :ref:`api_fluid_dygraph_Layer`.
+
     Examples:
         .. code-block:: python
 
@@ -330,7 +333,11 @@ def resnet18(pretrained=False, **kwargs):
     `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_
 
     Args:
-        pretrained (bool, optional): If True, returns a model pre-trained on ImageNet. Default: False.
+        pretrained (bool, optional): Whether to load pre-trained weights. If True, returns a model pre-trained
+                            on ImageNet. Default: False.
+
+    Returns:
+        ResNet 18-layer model. An instance of :ref:`api_fluid_dygraph_Layer`.
 
     Examples:
         .. code-block:: python
@@ -358,7 +365,11 @@ def resnet34(pretrained=False, **kwargs):
     `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_
 
     Args:
-        pretrained (bool, optional): If True, returns a model pre-trained on ImageNet. Default: False.
+        pretrained (bool, optional): Whether to load pre-trained weights. If True, returns a model pre-trained
+                            on ImageNet. Default: False.
+
+    Returns:
+        ResNet 34-layer model. An instance of :ref:`api_fluid_dygraph_Layer`.
 
     Examples:
         .. code-block:: python
@@ -386,7 +397,11 @@ def resnet50(pretrained=False, **kwargs):
     `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_
 
     Args:
-        pretrained (bool, optional): If True, returns a model pre-trained on ImageNet. Default: False.
+        pretrained (bool, optional): Whether to load pre-trained weights. If True, returns a model pre-trained
+                            on ImageNet. Default: False.
+
+    Returns:
+        ResNet 50-layer model. An instance of :ref:`api_fluid_dygraph_Layer`.
 
     Examples:
         .. code-block:: python
@@ -414,7 +429,11 @@ def resnet101(pretrained=False, **kwargs):
     `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_
 
     Args:
-        pretrained (bool, optional): If True, returns a model pre-trained on ImageNet. Default: False.
+        pretrained (bool, optional): Whether to load pre-trained weights. If True, returns a model pre-trained
+                            on ImageNet. Default: False.
+
+    Returns:
+        ResNet 101-layer. An instance of :ref:`api_fluid_dygraph_Layer`.
 
     Examples:
         .. code-block:: python
@@ -442,7 +461,11 @@ def resnet152(pretrained=False, **kwargs):
     `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_
 
     Args:
-        pretrained (bool, optional): If True, returns a model pre-trained on ImageNet. Default: False.
+        pretrained (bool, optional): Whether to load pre-trained weights. If True, returns a model pre-trained
+                            on ImageNet. Default: False.
+
+    Returns:
+        ResNet 152-layer model. An instance of :ref:`api_fluid_dygraph_Layer`.
 
     Examples:
         .. code-block:: python
@@ -470,7 +493,11 @@ def resnext50_32x4d(pretrained=False, **kwargs):
     `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_
     
     Args:
-        pretrained (bool, optional): If True, returns a model pre-trained on ImageNet. Default: False.
+        pretrained (bool, optional): Whether to load pre-trained weights. If True, returns a model pre-trained
+                            on ImageNet. Default: False.
+
+    Returns:
+        ResNeXt-50 32x4d model. An instance of :ref:`api_fluid_dygraph_Layer`.
 
     Examples:
         .. code-block:: python
@@ -500,7 +527,11 @@ def resnext50_64x4d(pretrained=False, **kwargs):
     `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_
     
     Args:
-        pretrained (bool, optional): If True, returns a model pre-trained on ImageNet. Default: False.
+        pretrained (bool, optional): Whether to load pre-trained weights. If True, returns a model pre-trained
+                            on ImageNet. Default: False.
+
+    Returns:
+        ResNeXt-50 64x4d model. An instance of :ref:`api_fluid_dygraph_Layer`.
 
     Examples:
         .. code-block:: python
@@ -530,7 +561,11 @@ def resnext101_32x4d(pretrained=False, **kwargs):
     `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_
     
     Args:
-        pretrained (bool, optional): If True, returns a model pre-trained on ImageNet. Default: False.
+        pretrained (bool, optional): Whether to load pre-trained weights. If True, returns a model pre-trained
+                            on ImageNet. Default: False.
+
+    Returns:
+        ResNeXt-101 32x4d model. An instance of :ref:`api_fluid_dygraph_Layer`.
 
     Examples:
         .. code-block:: python
@@ -561,7 +596,11 @@ def resnext101_64x4d(pretrained=False, **kwargs):
     `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_
     
     Args:
-        pretrained (bool, optional): If True, returns a model pre-trained on ImageNet. Default: False.
+        pretrained (bool, optional): Whether to load pre-trained weights. If True, returns a model pre-trained
+                            on ImageNet. Default: False.
+
+    Returns:
+        ResNeXt-101 64x4d model. An instance of :ref:`api_fluid_dygraph_Layer`.
 
     Examples:
         .. code-block:: python
@@ -592,7 +631,11 @@ def resnext152_32x4d(pretrained=False, **kwargs):
     `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_
     
     Args:
-        pretrained (bool, optional): If True, returns a model pre-trained on ImageNet. Default: False.
+        pretrained (bool, optional): Whether to load pre-trained weights. If True, returns a model pre-trained
+                            on ImageNet. Default: False.
+
+    Returns:
+        ResNeXt-152 32x4d model. An instance of :ref:`api_fluid_dygraph_Layer`.
 
     Examples:
         .. code-block:: python
@@ -623,7 +666,11 @@ def resnext152_64x4d(pretrained=False, **kwargs):
     `"Aggregated Residual Transformations for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_
     
     Args:
-        pretrained (bool, optional): If True, returns a model pre-trained on ImageNet. Default: False.
+        pretrained (bool, optional): Whether to load pre-trained weights. If True, returns a model pre-trained
+                            on ImageNet. Default: False.
+
+    Returns:
+        ResNeXt-152 64x4d model. An instance of :ref:`api_fluid_dygraph_Layer`.
 
     Examples:
         .. code-block:: python
@@ -654,7 +701,11 @@ def wide_resnet50_2(pretrained=False, **kwargs):
     `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_.
 
     Args:
-        pretrained (bool, optional): If True, returns a model pre-trained on ImageNet. Default: False.
+        pretrained (bool, optional): Whether to load pre-trained weights. If True, returns a model pre-trained
+                            on ImageNet. Default: False.
+
+    Returns:
+        Wide ResNet-50-2 model. An instance of :ref:`api_fluid_dygraph_Layer`.
 
     Examples:
         .. code-block:: python
@@ -683,7 +734,11 @@ def wide_resnet101_2(pretrained=False, **kwargs):
     `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_.
 
     Args:
-        pretrained (bool, optional): If True, returns a model pre-trained on ImageNet. Default: False.
+        pretrained (bool, optional): Whether to load pre-trained weights. If True, returns a model pre-trained
+                            on ImageNet. Default: False.
+
+    Returns:
+        Wide ResNet-101-2 model. An instance of :ref:`api_fluid_dygraph_Layer`.
 
     Examples:
         .. code-block:: python