Turn off optimization in find_faulty_files
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@ -85,6 +85,6 @@ if __name__ == "__main__":
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for i, data in enumerate(tqdm(dataloader)):
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current_batch = data
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model.feed_data(data, i)
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model.optimize_parameters(i)
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model.optimize_parameters(i, optimize=False)
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@ -183,7 +183,7 @@ class ExtensibleTrainer(BaseModel):
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if isinstance(v, torch.Tensor):
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self.dstate[k] = [t.to(self.device) for t in torch.chunk(v, chunks=batch_factor, dim=0)]
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def optimize_parameters(self, step):
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def optimize_parameters(self, step, optimize=True):
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# Some models need to make parametric adjustments per-step. Do that here.
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for net in self.networks.values():
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if hasattr(net.module, "update_for_step"):
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@ -255,7 +255,7 @@ class ExtensibleTrainer(BaseModel):
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raise OverwrittenStateError(k, list(state.keys()))
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state[k] = v
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if train_step:
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if train_step and optimize:
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# And finally perform optimization.
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[e.before_optimize(state) for e in self.experiments]
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s.do_step(step)
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