Fix keyward to keyword

classification/models/intern_image.py

@@ -691,7 +691,7 @@ class InternImage(nn.Module):
             m._reset_parameters()
 
     @torch.jit.ignore
-    def lr_decay_keywards(self, decay_ratio=0.87):
+    def lr_decay_keywords(self, decay_ratio=0.87):
         lr_ratios = {}
 
         # blocks
@@ -701,7 +701,7 @@ class InternImage(nn.Module):
             for j in range(self.depths[layer_num]):
                 block_num = self.depths[layer_num] - j - 1
                 tag = 'levels.{}.blocks.{}.'.format(layer_num, block_num)
-                decay = 1.0 * (decay_ratio**idx)
+                decay = 1.0 * (decay_ratio ** idx)
                 lr_ratios[tag] = decay
                 idx += 1
         # patch_embed (before stage-1)

classification/optimizer.py

@@ -129,11 +129,11 @@ def set_weight_decay_and_lr(
 
         if lr_layer_decay:
             print('layer-wise lr decay is used !')
-            assert hasattr(model, 'lr_decay_keywards')
-            lr_ratio_keywards = model.lr_decay_keywards(lr_layer_decay_ratio)
+            assert hasattr(model, 'lr_decay_keywords')
+            lr_ratio_keywords = model.lr_decay_keywords(lr_layer_decay_ratio)
 
             # 2. check lr
-            ratio = check_keywords_in_dict(name, lr_ratio_keywards)
+            ratio = check_keywords_in_dict(name, lr_ratio_keywords)
             if ratio is not None:
                 lr = ratio * base_lr
             else: