too many indices for array: array is 1-dimensional, but 2 were indexed

[binaryiii]

Dear Author,Is there a time step limit for this model? When I run TimeGrad related code on my own dataset, if the number of time steps exceeds tens of thousands, the following error will be reported
`---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
in
1 dataset_train = train_grouper(dataset.train)
----> 2 dataset_test = test_grouper(dataset.test)

E:\anoconda\envs\pytorch\lib\site-packages\gluonts\dataset\multivariate_grouper.py in call(self, dataset)
89 def call(self, dataset: Dataset) -> Dataset:
90 self._preprocess(dataset)
---> 91 return self._group_all(dataset)
92
93 def _preprocess(self, dataset: Dataset) -> None:

E:\anoconda\envs\pytorch\lib\site-packages\gluonts\dataset\multivariate_grouper.py in _group_all(self, dataset)
116 grouped_dataset = self._prepare_train_data(dataset)
117 else:
--> 118 grouped_dataset = self._prepare_test_data(dataset)
119 return grouped_dataset
120

E:\anoconda\envs\pytorch\lib\site-packages\gluonts\dataset\multivariate_grouper.py in _prepare_test_data(self, dataset)
149 list(dataset_at_test_date), dtype=object
150 )
--> 151 grouped_data = self._restrict_max_dimensionality(grouped_data)
152 grouped_data[FieldName.START] = self.first_timestamp
153 grouped_data[FieldName.FEAT_STATIC_CAT] = [0]

E:\anoconda\envs\pytorch\lib\site-packages\gluonts\dataset\multivariate_grouper.py in _restrict_max_dimensionality(self, data)
204 # restrict maximum dimensionality (for faster testing)
205 data[FieldName.TARGET] = data[FieldName.TARGET][
--> 206 -self.max_target_dimension :, :
207 ]
208 return data

IndexError: too many indices for array: array is 1-dimensional, but 2 were indexed
`