def create_default_optimizer(ops, **cfg): learn_rate = util.env_opt("learn_rate", 0.001) beta1 = util.env_opt("optimizer_B1", 0.9) beta2 = util.env_opt("optimizer_B2", 0.999) eps = util.env_opt("optimizer_eps", 1e-8) L2 = util.env_opt("L2_penalty", 1e-6) max_grad_norm = util.env_opt("grad_norm_clip", 1.0) optimizer = Adam(ops, learn_rate, L2=L2, beta1=beta1, beta2=beta2, eps=eps) optimizer.max_grad_norm = max_grad_norm optimizer.device = ops.device return optimizer
def create_default_optimizer(ops, **cfg): learn_rate = util.env_opt("learn_rate", 0.001) beta1 = util.env_opt("optimizer_B1", 0.9) beta2 = util.env_opt("optimizer_B2", 0.999) eps = util.env_opt("optimizer_eps", 1e-8) L2 = util.env_opt("L2_penalty", 1e-6) max_grad_norm = util.env_opt("grad_norm_clip", 1.0) optimizer = Adam(ops, learn_rate, L2=L2, beta1=beta1, beta2=beta2, eps=eps) optimizer.max_grad_norm = max_grad_norm optimizer.device = ops.device return optimizer
def create_default_optimizer(ops, **cfg): learn_rate = util.env_opt('learn_rate', 0.001) beta1 = util.env_opt('optimizer_B1', 0.9) beta2 = util.env_opt('optimizer_B2', 0.999) eps = util.env_opt('optimizer_eps', 1e-08) L2 = util.env_opt('L2_penalty', 1e-6) max_grad_norm = util.env_opt('grad_norm_clip', 1.) optimizer = Adam(ops, learn_rate, L2=L2, beta1=beta1, beta2=beta2, eps=eps) optimizer.max_grad_norm = max_grad_norm optimizer.device = ops.device return optimizer
def create_default_optimizer(ops, **cfg): learn_rate = util.env_opt('learn_rate', 0.001) beta1 = util.env_opt('optimizer_B1', 0.9) beta2 = util.env_opt('optimizer_B2', 0.999) eps = util.env_opt('optimizer_eps', 1e-08) L2 = util.env_opt('L2_penalty', 1e-6) max_grad_norm = util.env_opt('grad_norm_clip', 1.) optimizer = Adam(ops, learn_rate, L2=L2, beta1=beta1, beta2=beta2, eps=eps) optimizer.max_grad_norm = max_grad_norm optimizer.device = ops.device return optimizer