another classic commit so i can copy it to another machine to gut out things and use the trainer bits for a side project that I should really get around to working on sooner than later
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@ -66,7 +66,6 @@ class Engine(DeepSpeedEngine):
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def set_lr(self, lr):
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def set_lr(self, lr):
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try:
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try:
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if hasattr(self.optimizer, 'param_groups'):
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if hasattr(self.optimizer, 'param_groups'):
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print(self.optimizer.param_groups)
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for param_group in self.optimizer.param_groups:
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for param_group in self.optimizer.param_groups:
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param_group['lr'] = lr
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param_group['lr'] = lr
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else:
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else:
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@ -100,9 +100,9 @@ def run_eval(engines, eval_name, dl):
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if AR is not None and NAR is not None:
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if AR is not None and NAR is not None:
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name = "+".join(names)
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name = "+".join(names)
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resps_list = AR(text_list=batch["text"], proms_list=batch["proms"], max_steps=cfg.evaluation.steps, sampling_temperature=cfg.evaluation.temperature)
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resps_list = AR(text_list=batch["text"], proms_list=batch["proms"], max_steps=cfg.evaluation.steps, sampling_temperature=cfg.evaluation.ar_temperature)
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resps_list = [ r.unsqueeze(-1) for r in resps_list ]
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resps_list = [ r.unsqueeze(-1) for r in resps_list ]
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resps_list = NAR(text_list=batch["text"], proms_list=batch["proms"], resps_list=resps_list, sampling_temperature=cfg.evaluation.temperature)
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resps_list = NAR(text_list=batch["text"], proms_list=batch["proms"], resps_list=resps_list, sampling_temperature=cfg.evaluation.nar_temperature)
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process( name, batch, resps_list )
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process( name, batch, resps_list )
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else:
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else:
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