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