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Method state_dict

internlm/data/batch_sampler.py:316–330  ·  view source on GitHub ↗
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314 self.get_indices() # get a new round
315
316 def state_dict(self):
317 states = {
318 "batch_size": self.batch_size,
319 "raw_rampup_batch_size": self.raw_rampup_batch_size,
320 "rng_state": self.rng_state,
321 "epoch": self.epoch,
322 "seed": self.seed,
323 "data_world_size": self.data_world_size,
324 "num_consumed_samples_in_epoch": self.num_consumed_samples_in_epoch,
325 "batch_count": self.batch_count, # The batch_count here is due to the existence of multiple processes,
326 # the batch may be oversent, and it needs to be overwritten by the external batch_count
327 "indices": self.indices, # The sequence used to breakpoint retraining is the same as before
328 }
329
330 return states
331
332 def load_state_dict(self, states):
333 for name in ("data_world_size", "raw_rampup_batch_size", "seed"): # 'batch_size'

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