[Fix] Increase docstring coverage (#2039)

improve coverage

mmagic/datasets/transforms/random_degradations.py

@@ -138,6 +138,7 @@ def _apply_random_blur(self, imgs):
         return imgs
 
     def __call__(self, results):
+        """Call this transform."""
         if np.random.uniform() > self.params.get('prob', 1):
             return results
 
@@ -147,6 +148,7 @@ def __call__(self, results):
         return results
 
     def __repr__(self):
+        """Print the basic information of the transform."""
         repr_str = self.__class__.__name__
         repr_str += (f'(params={self.params}, keys={self.keys})')
         return repr_str
@@ -208,6 +210,7 @@ def _apply_random_compression(self, imgs):
         return outputs
 
     def __call__(self, results):
+        """Call this transform."""
         if np.random.uniform() > self.params.get('prob', 1):
             return results
 
@@ -217,6 +220,7 @@ def __call__(self, results):
         return results
 
     def __repr__(self):
+        """Print the basic information of the transform."""
         repr_str = self.__class__.__name__
         repr_str += (f'(params={self.params}, keys={self.keys})')
         return repr_str
@@ -329,6 +333,7 @@ def _apply_random_noise(self, imgs):
         return imgs
 
     def __call__(self, results):
+        """Call this transform."""
         if np.random.uniform() > self.params.get('prob', 1):
             return results
 
@@ -338,6 +343,7 @@ def __call__(self, results):
         return results
 
     def __repr__(self):
+        """Print the basic information of the transform."""
         repr_str = self.__class__.__name__
         repr_str += (f'(params={self.params}, keys={self.keys})')
         return repr_str
@@ -443,6 +449,7 @@ def _random_resize(self, imgs):
         return outputs
 
     def __call__(self, results):
+        """Call this transform."""
         if np.random.uniform() > self.params.get('prob', 1):
             return results
 
@@ -452,6 +459,7 @@ def __call__(self, results):
         return results
 
     def __repr__(self):
+        """Print the basic information of the transform."""
         repr_str = self.__class__.__name__
         repr_str += (f'(params={self.params}, keys={self.keys})')
         return repr_str
@@ -519,6 +527,7 @@ def _apply_random_compression(self, imgs):
         return outputs
 
     def __call__(self, results):
+        """Call this transform."""
         if np.random.uniform() > self.params.get('prob', 1):
             return results
 
@@ -528,6 +537,7 @@ def __call__(self, results):
         return results
 
     def __repr__(self):
+        """Print the basic information of the transform."""
         repr_str = self.__class__.__name__
         repr_str += (f'(params={self.params}, keys={self.keys})')
         return repr_str
@@ -593,6 +603,7 @@ def _build_degradations(self, degradations):
         return degradations
 
     def __call__(self, results):
+        """Call this transform."""
         # shuffle degradations
         if len(self.shuffle_idx) > 0:
             shuffle_list = [self.degradations[i] for i in self.shuffle_idx]
@@ -611,6 +622,7 @@ def __call__(self, results):
         return results
 
     def __repr__(self):
+        """Print the basic information of the transform."""
         repr_str = self.__class__.__name__
         repr_str += (f'(degradations={self.degradations}, '
                      f'keys={self.keys}, '

mmagic/models/editors/deblurganv2/deblurganv2_generator.py

@@ -89,6 +89,7 @@ def __init__(self, norm_layer, num_filter=256, pretrained='imagenet'):
             param.requires_grad = False
 
     def unfreeze(self):
+        """Unfreeze params."""
         for param in self.inception.parameters():
             param.requires_grad = True
 
@@ -174,6 +175,7 @@ def __init__(self,
             num_filter // 2, output_ch, kernel_size=3, padding=1)
 
     def unfreeze(self):
+        """Unfreeze params."""
         self.fpn.unfreeze()
 
     def forward(self, x):
@@ -256,6 +258,7 @@ def __init__(self, norm_layer, num_filters=256):
             param.requires_grad = False
 
     def unfreeze(self):
+        """Unfreeze params."""
         for param in self.inception.parameters():
             param.requires_grad = True
 
@@ -338,6 +341,7 @@ def __init__(self,
             num_filter // 2, output_ch, kernel_size=3, padding=1)
 
     def unfreeze(self):
+        """unfreeze the fpn network."""
         self.fpn.unfreeze()
 
     def forward(self, x):
@@ -423,6 +427,7 @@ def __init__(self, norm_layer, num_filters=128, pretrained=None):
             param.requires_grad = False
 
     def unfreeze(self):
+        """Unfreeze params."""
         for param in self.features.parameters():
             param.requires_grad = True