Wie restauriere ich einen Orbax -Checkpoint mit Jax/Flachs? ⇐ Python

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Ich habe einen Orbax -Checkpoint mit dem folgenden Code gespeichert: < /p>

Code: Select all

check_options = ocp.CheckpointManagerOptions(max_to_keep=5, create=True)
check_path = Path(os.getcwd(), out_dir, 'checkpoint')
checkpoint_manager = ocp.CheckpointManager(check_path, options=check_options, item_names=('state', 'metadata'))
checkpoint_manager.save(
step=iter_num,
args=ocp.args.Composite(
state=ocp.args.StandardSave(state),
metadata=ocp.args.JsonSave((model_args, iter_num, best_val_loss, losses['val'].item(), config))))

Wenn ich versuche, von den gespeicherten Checkpoints wieder aufzunehmen, habe ich den folgenden Code verwendet, um den Status Variable zu erhalten:

Code: Select all

state, lr_schedule = init_train_state(model, params['params'], learning_rate, weight_decay, beta1, beta2, decay_lr, warmup_iters,
lr_decay_iters, min_lr)  # Here state is the initialied state variable with type Train_state.
state = checkpoint_manager.restore(checkpoint_manager.latest_step(), items={'state': state})
< /code>
Aber wenn ich versuche, den wiederhergestellten Status in der Trainingsschleife zu verwenden, habe ich diesen Fehler erhalten: < /p>
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
File /opt/conda/envs/py_3.10/lib/python3.10/site-packages/jax/_src/api_util.py:584, in shaped_abstractify(x)
583 try:
--> 584   return _shaped_abstractify_handlers[type(x)](x)
585 except KeyError:

KeyError: 

During handling of the above exception, another exception occurred:

TypeError                                 Traceback (most recent call last)
Cell In[40], line 37
34 if iter_num == 0 and eval_only:
35     break
---> 37 state, loss = train_step(state, get_batch('train'))
39 # timing and logging
40 t1 = time.time()

[... skipping hidden 6 frame]

File /opt/conda/envs/py_3.10/lib/python3.10/site-packages/jax/_src/api_util.py:575, in _shaped_abstractify_slow(x)
573   dtype = dtypes.canonicalize_dtype(x.dtype, allow_extended_dtype=True)
574 else:
--> 575   raise TypeError(
576       f"Cannot interpret value of type {type(x)} as an abstract array; it "
577       "does not have a dtype attribute")
578 return core.ShapedArray(np.shape(x), dtype, weak_type=weak_type,
579                         named_shape=named_shape)

TypeError: Cannot interpret value of type  as an abstract array; it does not have a dtype attribute

Wie soll ich den Status Checkpoint korrekt wiederherstellen und in der Trainingsschleife verwenden?
Danke!