Rolling Memory

(no paper)

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.

examples

{
    "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.

options

memory types

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