def test_adamw_tf(self):
"""Test creating an AdamW optimizer."""
opt = optimizers.AdamW(learning_rate=0.01)
global_step = tf.Variable(0)
tfopt = opt._create_tf_optimizer(global_step)
assert isinstance(tfopt, tfa.optimizers.AdamW)
def test_adamw_pytorch(self):
"""Test creating an AdamW optimizer."""
opt = optimizers.AdamW(learning_rate=0.01)
params = [torch.nn.Parameter(torch.Tensor([1.0]))]
torchopt = opt._create_pytorch_optimizer(params)
assert isinstance(torchopt, torch.optim.AdamW)
def test_adamw_jax(self):
"""Test creating an AdamW optimizer."""
import optax
opt = optimizers.AdamW(learning_rate=0.01)
jaxopt = opt._create_jax_optimizer()
assert isinstance(jaxopt, optax.GradientTransformation)