torch.optim.Optimizer.zero_grad¶
- Optimizer.zero_grad(set_to_none=True)[source]¶
- Resets the gradients of all optimized - torch.Tensors.- Parameters
- set_to_none (bool) – instead of setting to zero, set the grads to None. This will in general have lower memory footprint, and can modestly improve performance. However, it changes certain behaviors. For example: 1. When the user tries to access a gradient and perform manual ops on it, a None attribute or a Tensor full of 0s will behave differently. 2. If the user requests - zero_grad(set_to_none=True)followed by a backward pass,- .grads are guaranteed to be None for params that did not receive a gradient. 3.- torch.optimoptimizers have a different behavior if the gradient is 0 or None (in one case it does the step with a gradient of 0 and in the other it skips the step altogether).