Simultaneous Trainer

Source: /trainers/simultaneous_trainer.py​
d_grads,g_grads = self.calculate_gradients(D, G)
self.train_d(d_grads)
self.train_g(g_grads)
examples
Configurations: /trainers/simultaneous_trainer/​
{
  "class": "function:hypergan.trainers.simultaneous_trainer.SimultaneousTrainer",
  "optimizer": {
    "class": "function:torch.optim.Adam",
    "lr": 1e-4,
    "betas":[0.0,0.999]
  },
  "hooks": [
    {
      "class": "function:hypergan.train_hooks.adversarial_norm_train_hook.AdversarialNormTrainHook",
      "gamma": 100,
      "loss": ["d"]
    },
    {
      "class": "function:hypergan.train_hooks.negative_momentum_train_hook.NegativeMomentumTrainHook",
      "gamma": 0.33
    }
  ]
}
options
attribute
description
type
optimizer
Optimizer configuration
Config (required)
hooks
Train Hooks
Array of configs (optional)

Alternating Trainer

Balanced Trainer

Last modified 2yr ago

attribute	description	type
optimizer	Optimizer configuration	Config (required)
hooks	Train Hooks	Array of configs (optional)