[optim][adamw] default to foreach when CUDA + differentiable=False #92306
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[ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/92306
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janeyx99
added
module: bc-breaking
…le=False" cc ezyang gchanan [ghstack-poisoned]
…le=False" cc ezyang gchanan [ghstack-poisoned]
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Stack from ghstack (oldest at bottom):
cc @ezyang @gchanan
BC-breaking note
Algorithms
{Adadelta, Adagrad, Adam, Adamax, AdamW, ASGD, NAdam, RAdam, RMSProp, RProp, SGD}default to fasterforeachimplementation when on CUDA + differentiable=FalseWhen applicable, this changes the default behavior of
step()and anything that calls intoadadelta(...),adagrad(...),adam(...),adamax(...),adamw(...),asgd(...),nadam(...),radam(...),rmsprop(...),rprop(...),sgd(...)directly to use theforeachimplementation instead of the for-loop for better performance. Applicable meansforeach,fused, ordifferentiable),torch.jit.is_scriptingisFalse.When these conditions are satisfied, the implementation used will match the implementation used when one passes
foreach=True. The user defined flag forforeachwill NOT be overwritten in order to preserve user selections. For more details, check the documentation. There should be no significant differences between the results returned by these optimizers. To revert to the old behavior, say, foradam, pass inadam(..., foreach=False, ...)or initializeAdamwithAdam(..., foreach=False, ...).