Rolling Memory
Rolling memory is a type of experience replay. Each training step, a memory is replaced with the top scoring batch item.
Each types pairing becomes a discriminator that is added to the loss.
{"class": "function:hypergan.train_hooks.experimental.rolling_memory_2_train_hook.RollingMemoryTrainHook","types": ["mx-/g(mz-)"]}
mx- is a memory of x that gets updated each training step. g(mz-) is a memory of z that gets run through a generator and updated each trainng step.
A discriminator d(mx-, g(mz-)) is created and added to the gan loss.
attribute | description | type |
types | What memories and how they are paired. See memory types below | array of strings |
top_k | How many memory items to replace per frame. Defaults to | integer |
only | Overrides all other losses when this is set. Defaults to | boolean |
memory | description |
mx- | x reverse sorted by d_real |
mx+ | x sorted by d_real |
mg- | memory of g reverse sorted by d_fake |
mg+ | memory of g sorted by d_fake |
g(mz-) | generator of memory of z reverse sorted by d_fake |
g(mz+) | generator of memory of z sorted by d_fake |
x | gan.inputs.x |
g | gan.generator.sample |
