def test_adagrad_tf(self):
"""Test creating an AdaGrad optimizer."""
opt = optimizers.AdaGrad(learning_rate=0.01)
global_step = tf.Variable(0)
tfopt = opt._create_tf_optimizer(global_step)
assert isinstance(tfopt, tf.keras.optimizers.Adagrad)
def test_adagrad_pytorch(self):
"""Test creating an AdaGrad optimizer."""
opt = optimizers.AdaGrad(learning_rate=0.01)
params = [torch.nn.Parameter(torch.Tensor([1.0]))]
torchopt = opt._create_pytorch_optimizer(params)
assert isinstance(torchopt, torch.optim.Adagrad)
def test_adagrad_jax(self):
"""Test creating an AdaGrad optimizer."""
import optax
opt = optimizers.AdaGrad(learning_rate=0.01)
jaxopt = opt._create_jax_optimizer()
assert isinstance(jaxopt, optax.GradientTransformation)