The only variable as input should be the target which is part of time_varying_unknown_reals

[Mohan16071996]

My data set has : time_idx, Date, Ticker, Open, high, low, close, Stock split and Dividends.
My Time series data set is:
training = TimeSeriesDataSet(
combined_data[lambda x: x.time_idx <= training_cutoff],
time_idx="time_idx",
target="Close",
group_ids=["Ticker"],
max_encoder_length=60,
max_prediction_length=7,
static_categoricals=["Ticker"],
time_varying_known_reals=["time_idx", "Open", "High", "Low", "Volume", "Stock Splits", "Dividends"],
time_varying_unknown_reals=["Close"],
allow_missing_timesteps=True,
target_normalizer=GroupNormalizer(
groups=["Ticker"], transformation="softplus"
),
add_relative_time_idx=False,
add_target_scales=True,
add_encoder_length=True,
)

I get this error, when I run this :

Define the model with the suggested hyperparameters

model = NBeats.from_dataset(
    training,
    learning_rate=learning_rate,
    hidden_size=hidden_size,
    widths=widths,
    backcast_loss_ratio=backcast_loss_ratio,
    dropout=dropout
)

I see the data set has reals like encoder_length, Close_min, close_scaled and all time varying known reals I gave in the data set.
I tried removing all the reals, still I get the error as number of reals are encoder, and Close related variables. I cannot not give encoder length. Issue arise from this piece of code:

assert (
len(dataset.flat_categoricals) == 0
and len(dataset.reals) == 1
and len(dataset.time_varying_unknown_reals) == 1
and dataset.time_varying_unknown_reals[0] == dataset.target
), "The only variable as input should be the target which is part of time_varying_unknown_reals"

[Mohan16071996]

Can someone please update on this issue as soon as possible?