def get_params_lr(self): """Helper function to adjust learning rate for each sub modules. """ # Specify learning rate for each sub modules. ret = [] ret.append({ 'params': [ n for n in model_utils.get_params( self, ['semantic_classifier'], ['weight']) ], 'lr': 10 }) ret.append({ 'params': [ n for n in model_utils.get_params( self, ['semantic_classifier'], ['bias']) ], 'lr': 20, 'weight_decay': 0 }) return ret
def get_params_lr(self): """Helper function to adjust learning rate for each sub modules. """ # Specify learning rate for each sub modules. ret = [] resnet_params_name = [ 'resnet_backbone.res3', 'resnet_backbone.res4', 'resnet_backbone.res5' ] ret.append({ 'params': [ n for n in model_utils.get_params(self, resnet_params_name, ['weight']) ], 'lr': 1 }) ret.append({ 'params': [ n for n in model_utils.get_params(self, resnet_params_name, ['bias']) ], 'lr': 2, 'weight_decay': 0 }) ret.append({ 'params': [n for n in model_utils.get_params(self, ['aspp'], ['weight'])], 'lr': 10 }) ret.append({ 'params': [n for n in model_utils.get_params(self, ['aspp'], ['bias'])], 'lr': 20, 'weight_decay': 0 }) return ret