decay is deprecated in the new Keras optimizer,
时间: 2024-05-15 22:12:10 浏览: 9
Yes, that's correct. In the latest versions of Keras, the "decay" parameter has been deprecated in favor of the "learning_rate_decay" parameter. The new parameter provides a more flexible way to adjust the learning rate during training. You can specify a function that takes the current epoch as input and returns the new learning rate. This allows you to implement more sophisticated learning rate schedules, such as cosine annealing or step decay. Here's an example:
```python
from keras.optimizers import Adam
def lr_schedule(epoch):
if epoch < 10:
return 0.001
elif epoch < 20:
return 0.0005
else:
return 0.0001
optimizer = Adam(learning_rate=0.001, learning_rate_decay=lr_schedule)
```
In this example, we define a learning rate schedule that decreases the learning rate by a factor of 2 every 10 epochs. The "learning_rate_decay" parameter is set to a function that implements this schedule.