Tensorflow implementation of AngularGrad: A New Optimization Technique for Angular Convergence of Convolutional Neural Networks.
The official implementation of AngularGrad is mhaut/AngularGrad.
You can import the optimizer as follows:
from angular_grad import AngularGrad
...
model = YourModel()
...
model.compile(optimizer=AngularGrad("cos"), ...)
...
Or you can omit a value "cos".
...
model.compile(optimizer=AngularGrad(), ...)
...
from angular_grad import AngularGrad
...
model = YourModel()
...
model.compile(optimizer=AngularGrad("tan"), ...)
...
AngularGrad(
method_angle: str = "cos",
learning_rate=1e-3,
beta_1=0.9,
beta_2=0.999,
eps=1e-7,
name: str = "AngularGrad",
**kwargs
)
- Python 3.6.9
- Tensorflow 2.5.0
Developed by Eunchan Lee([email protected]), 2021 Linewalks.
If there is any problem in this repository, please feel free to contact us at the above email address.