ValueError: you tried to log -1 which is currently not supported. Try a dict or a scalar/tensor.

[kkckk1110]

What happened + What you expected to happen

I came across a bug when running the getting_started.ipynb in the following codes:
the bug is:

ValueError:
you tried to log -1 which is currently not supported. Try a dict or a scalar/tensor.

Also, I have a problem with the implementation of exogenous features. If I want to use Auto version of models, how can I add exogenous features to it? When I attempted to add futr_exog_list to AutoLSTM(h=h, config=config_lstm, loss=MQLoss(), num_samples=2), it raises an error that futr_exog_list argument cannot be found.

Versions / Dependencies

I have neuralforecast==1.6.4

Reproduction script

%%capture
horizon = 12

models = [LSTM(h=horizon, # Forecast horizon
max_steps=500, # Number of steps to train
scaler_type='standard', # Type of scaler to normalize data
encoder_hidden_size=64, # Defines the size of the hidden state of the LSTM
decoder_hidden_size=64,), # Defines the number of hidden units of each layer of the MLP decoder
NHITS(h=horizon, # Forecast horizon
input_size=2 * horizon, # Length of input sequence
max_steps=100, # Number of steps to train
n_freq_downsample=[2, 1, 1]) # Downsampling factors for each stack output
]
nf = NeuralForecast(models=models, freq='M')
nf.fit(df=Y_df)

Issue Severity

None

[jmoralez]

Hey @kkckk1110, thanks for using neuralforecast. Can you provide the full stacktrace for the error you're getting? For the auto models you have to provide the exogenous features in the config.

[kkckk1110]

Thank you very much for your attention!

Stacktrace

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
File ~/miniforge3/lib/python3.9/site-packages/lightning_fabric/loggers/tensorboard.py:202, in TensorBoardLogger.log_metrics(self, metrics, step)
    201 try:
--> 202     self.experiment.add_scalar(k, v, step)
    203 # TODO(fabric): specify the possible exception

File ~/miniforge3/lib/python3.9/site-packages/lightning_fabric/loggers/logger.py:117, in rank_zero_experiment.<locals>.experiment(self)
    115     return fn(self)
--> 117 return get_experiment() or _DummyExperiment()

File ~/miniforge3/lib/python3.9/site-packages/lightning_utilities/core/rank_zero.py:32, in rank_zero_only.<locals>.wrapped_fn(*args, **kwargs)
     31 if rank == 0:
---> 32     return fn(*args, **kwargs)
     33 return None

File ~/miniforge3/lib/python3.9/site-packages/lightning_fabric/loggers/logger.py:115, in rank_zero_experiment.<locals>.experiment.<locals>.get_experiment()
    113 @rank_zero_only
    114 def get_experiment() -> Callable:
--> 115     return fn(self)

File ~/miniforge3/lib/python3.9/site-packages/lightning_fabric/loggers/tensorboard.py:181, in TensorBoardLogger.experiment(self)
    180 if _TENSORBOARD_AVAILABLE:
--> 181     from torch.utils.tensorboard import SummaryWriter
    182 else:

File ~/miniforge3/lib/python3.9/site-packages/torch/utils/tensorboard/__init__.py:12, in <module>
     10 del tensorboard
---> 12 from .writer import FileWriter, SummaryWriter  # noqa: F401
     13 from tensorboard.summary.writer.record_writer import RecordWriter

File ~/miniforge3/lib/python3.9/site-packages/torch/utils/tensorboard/writer.py:10, in <module>
      9 from tensorboard.compat import tf
---> 10 from tensorboard.compat.proto import event_pb2
     11 from tensorboard.compat.proto.event_pb2 import Event, SessionLog

File ~/miniforge3/lib/python3.9/site-packages/tensorboard/compat/proto/event_pb2.py:6, in <module>
      5 from google.protobuf.internal import enum_type_wrapper
----> 6 from google.protobuf import descriptor as _descriptor
      7 from google.protobuf import descriptor_pool as _descriptor_pool

File ~/miniforge3/lib/python3.9/site-packages/google/protobuf/descriptor.py:47, in <module>
     46 import os
---> 47 from google.protobuf.pyext import _message
     48 _USE_C_DESCRIPTORS = True

TypeError: bases must be types

The above exception was the direct cause of the following exception:

ValueError                                Traceback (most recent call last)
Input In [16], in <cell line: 1>()
----> 1 model.fit(train)

File ~/miniforge3/lib/python3.9/site-packages/neuralforecast/core.py:274, in NeuralForecast.fit(self, df, static_df, val_size, sort_df, use_init_models, verbose)
    271         print("WARNING: Deleting previously fitted models.")
    273 for model in self.models:
--> 274     model.fit(self.dataset, val_size=val_size)
    276 self._fitted = True

File ~/miniforge3/lib/python3.9/site-packages/neuralforecast/common/_base_recurrent.py:633, in BaseRecurrent.fit(self, dataset, val_size, test_size, random_seed)
    630 self.trainer_kwargs["check_val_every_n_epoch"] = None
    632 trainer = pl.Trainer(**self.trainer_kwargs)
--> 633 trainer.fit(self, datamodule=datamodule)

File ~/miniforge3/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py:520, in Trainer.fit(self, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path)
    518 model = _maybe_unwrap_optimized(model)
    519 self.strategy._lightning_module = model
--> 520 call._call_and_handle_interrupt(
    521     self, self._fit_impl, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path
    522 )

File ~/miniforge3/lib/python3.9/site-packages/pytorch_lightning/trainer/call.py:44, in _call_and_handle_interrupt(trainer, trainer_fn, *args, **kwargs)
     42         return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)
     43     else:
---> 44         return trainer_fn(*args, **kwargs)
     46 except _TunerExitException:
     47     _call_teardown_hook(trainer)

File ~/miniforge3/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py:559, in Trainer._fit_impl(self, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path)
    549 self._data_connector.attach_data(
    550     model, train_dataloaders=train_dataloaders, val_dataloaders=val_dataloaders, datamodule=datamodule
    551 )
    553 ckpt_path = self._checkpoint_connector._select_ckpt_path(
    554     self.state.fn,
    555     ckpt_path,
    556     model_provided=True,
    557     model_connected=self.lightning_module is not None,
    558 )
--> 559 self._run(model, ckpt_path=ckpt_path)
    561 assert self.state.stopped
    562 self.training = False

File ~/miniforge3/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py:918, in Trainer._run(self, model, ckpt_path)
    915     call._call_callback_hooks(self, "on_fit_start")
    916     call._call_lightning_module_hook(self, "on_fit_start")
--> 918 _log_hyperparams(self)
    920 if self.strategy.restore_checkpoint_after_setup:
    921     log.debug(f"{self.__class__.__name__}: restoring module and callbacks from checkpoint path: {ckpt_path}")

File ~/miniforge3/lib/python3.9/site-packages/pytorch_lightning/loggers/utilities.py:94, in _log_hyperparams(trainer)
     92 for logger in trainer.loggers:
     93     if hparams_initial is not None:
---> 94         logger.log_hyperparams(hparams_initial)
     95     logger.log_graph(pl_module)
     96     logger.save()

File ~/miniforge3/lib/python3.9/site-packages/lightning_utilities/core/rank_zero.py:32, in rank_zero_only.<locals>.wrapped_fn(*args, **kwargs)
     30     raise RuntimeError("The `rank_zero_only.rank` needs to be set before use")
     31 if rank == 0:
---> 32     return fn(*args, **kwargs)
     33 return None

File ~/miniforge3/lib/python3.9/site-packages/pytorch_lightning/loggers/tensorboard.py:181, in TensorBoardLogger.log_hyperparams(self, params, metrics)
    178 else:
    179     self.hparams.update(params)
--> 181 return super().log_hyperparams(params=params, metrics=metrics)

File ~/miniforge3/lib/python3.9/site-packages/lightning_utilities/core/rank_zero.py:32, in rank_zero_only.<locals>.wrapped_fn(*args, **kwargs)
     30     raise RuntimeError("The `rank_zero_only.rank` needs to be set before use")
     31 if rank == 0:
---> 32     return fn(*args, **kwargs)
     33 return None

File ~/miniforge3/lib/python3.9/site-packages/lightning_fabric/loggers/tensorboard.py:233, in TensorBoardLogger.log_hyperparams(self, params, metrics)
    230     metrics = {"hp_metric": metrics}
    232 if metrics:
--> 233     self.log_metrics(metrics, 0)
    235     if _TENSORBOARD_AVAILABLE:
    236         from torch.utils.tensorboard.summary import hparams

File ~/miniforge3/lib/python3.9/site-packages/lightning_utilities/core/rank_zero.py:32, in rank_zero_only.<locals>.wrapped_fn(*args, **kwargs)
     30     raise RuntimeError("The `rank_zero_only.rank` needs to be set before use")
     31 if rank == 0:
---> 32     return fn(*args, **kwargs)
     33 return None

File ~/miniforge3/lib/python3.9/site-packages/lightning_fabric/loggers/tensorboard.py:206, in TensorBoardLogger.log_metrics(self, metrics, step)
    204 except Exception as ex:
    205     m = f"\n you tried to log {v} which is currently not supported. Try a dict or a scalar/tensor."
--> 206     raise ValueError(m) from ex

ValueError: 
 you tried to log -1 which is currently not supported. Try a dict or a scalar/tensor.

[jmoralez]

Thanks. That seems to be a protobuf error, can you try the fix suggested here?

[kkckk1110]

That's really helpful! Thank you very much!