Datajoint demo notebook
method_fn = "mei.methods.gradient_ascent"
method_config = dict(
initial=dict(path="mei.initial.RandomNormal"),
optimizer=dict(path="torch.optim.SGD", kwargs=dict(lr=0.1)),
stopper=dict(path="mei.stoppers.NumIterations", kwargs=dict(num_iterations=1000)),
objectives=[dict(path="mei.objectives.EvaluationObjective", kwargs=dict(interval=10))],
device="cuda",
)
MEIMethod().add_method(method_fn, method_config, comment="My MEI method", skip_duplicates=True)
MEIMethod()Uses lr=0.1, there resulting image looks like noise, which could confuse new users. The datajoint free pipe uses lr=1 which works better.
Datajoint demo notebook
Uses
lr=0.1, there resulting image looks like noise, which could confuse new users. The datajoint free pipe useslr=1which works better.