task update

official/vision/beta/projects/yolo/optimization/sgd_torch.py

@@ -44,12 +44,8 @@ class SGDTorch(tf.keras.optimizers.Optimizer):
   opt = SGDTorch(learning_rate, weight_decay = 0.0001)
   l2_regularization = None
 
-  # Models must implement a method to iterate all model.trainable_variables
-  # and split the variables by key into the weights, biases, and others.
-  # Weight decay wil be applied to all variables in the weights group. Bias 
-  # and others are included as a way to proved alternate LR scedules to various 
-  # paramter groups. An example of this variable search can be found in 
-  # official/vision/beta/projects/yolo/modeling/yolo_model.py.
+  # iterate all model.trainable_variables and split the variables by key 
+  # into the weights, biases, and others.
   optimizer.search_and_set_variable_groups(model.trainable_variables)
 
   # if the learning rate schedule on the biases are different. if lr is not set