Change 'mod_step' to 'every'
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@ -177,8 +177,8 @@ class ExtensibleTrainer(BaseModel):
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# Iterate through the steps, performing them one at a time.
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state = self.dstate
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for step_num, s in enumerate(self.steps):
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# Skip steps if mod_step doesn't line up.
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if 'mod_step' in s.step_opt.keys() and step % s.step_opt['mod_step'] != 0:
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# 'every' is used to denote steps that should only occur at a certain integer factor rate. e.g. '2' occurs every 2 steps.
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if 'every' in s.step_opt.keys() and step % s.step_opt['every'] != 0:
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continue
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# Steps can opt out of early (or late) training, make sure that happens here.
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if 'after' in s.step_opt.keys() and step < s.step_opt['after'] or 'before' in s.step_opt.keys() and step > s.step_opt['before']:
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