_set_lr
set_lr
¶
Set the learning rate of a given model
generated by fe.build
.
This method can be used with TensorFlow models:
m = fe.build(fe.architecture.tensorflow.LeNet, optimizer_fn="adam") # m.optimizer.lr == 0.001
fe.backend.set_lr(m, lr=0.8) # m.optimizer.lr == 0.8
This method can be used with PyTorch models:
m = fe.build(fe.architecture.pytorch.LeNet, optimizer_fn="adam") # m.optimizer.param_groups[-1]['lr'] == 0.001
fe.backend.set_lr(m, lr=0.8) # m.optimizer.param_groups[-1]['lr'] == 0.8
Parameters:
Name | Type | Description | Default |
---|---|---|---|
model
|
Union[Model, Module]
|
A neural network instance to modify. |
required |
lr
|
float
|
The learning rate to assign to the |
required |
weight_decay
|
Optional[float]
|
The weight decay parameter. |
None
|
Raises:
Type | Description |
---|---|
ValueError
|
If |