def set_simulated_global_batchsize(self, simulated_global_batchsize: Optional[int]):
    'Sets a simulated batch size by gradient accumulation.\n\n        Gradient accumulation adds up gradients from multiple minibatches and\n        steps the optimizer every N train_steps, where N is optimizer_period.\n        When enabled, the very last train_steps might end up not updating the\n        model, depending on the number of total steps. None means gradient\n        accumulation is disabled. Defaults to None.'
    self.simulated_global_batchsize = simulated_global_batchsize
    return self
Sets a simulated batch size by gradient accumulation.

Gradient accumulation adds up gradients from multiple minibatches and
steps the optimizer every N train_steps, where N is optimizer_period.
When enabled, the very last train_steps might end up not updating the
model, depending on the number of total steps. None means gradient
accumulation is disabled. Defaults to None.
def set_simulated_global_batchsize(self, simulated_global_batchsize: Optional[int]):
    'Sets a simulated batch size by gradient accumulation.\n\n        Gradient accumulation adds up gradients from multiple minibatches and\n        steps the optimizer every N train_steps, where N is optimizer_period.\n        When enabled, the very last train_steps might end up not updating the\n        model, depending on the number of total steps. None means gradient\n        accumulation is disabled. Defaults to None.'
    self.simulated_global_batchsize = simulated_global_batchsize
    return self