DMSTGCN 运行 PEMSD4、PEMSD8 数据集报错

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/home/xiezhicong/anaconda3/envs/libcity_py38/lib/python3.8/site-packages/gensim/similarities/init.py:15: UserWarning: The gensim.similarities.levenshtein submodule is disabled, because the optional Levenshtein package https://pypi.org/project/python-Levenshtein/ is unavailable. Install Levenhstein (e.g. pip install python-Levenshtein) to suppress this warning. warnings.warn(msg) /home/xiezhicong/Code/ospp/Bigscity-LibCity/libcity/data/dataset/traffic_state_datatset.py:909: RuntimeWarning: Mean of empty slice. scaler = StandardScaler(mean=x_train.mean(), std=x_train.std()) /home/xiezhicong/anaconda3/envs/libcity_py38/lib/python3.8/site-packages/numpy/core/_methods.py:170: RuntimeWarning: invalid value encountered in double_scalars ret = ret.dtype.type(ret / rcount) /home/xiezhicong/anaconda3/envs/libcity_py38/lib/python3.8/site-packages/numpy/core/_methods.py:233: RuntimeWarning: Degrees of freedom <= 0 for slice ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, /home/xiezhicong/anaconda3/envs/libcity_py38/lib/python3.8/site-packages/numpy/core/_methods.py:194: RuntimeWarning: invalid value encountered in true_divide arrmean = um.true_divide( /home/xiezhicong/anaconda3/envs/libcity_py38/lib/python3.8/site-packages/numpy/core/_methods.py:226: RuntimeWarning: invalid value encountered in double_scalars ret = ret.dtype.type(ret / rcount) /home/xiezhicong/anaconda3/envs/libcity_py38/lib/python3.8/site-packages/numpy/core/_asarray.py:83: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray return array(a, dtype, copy=False, order=order)

<__array_function__ internals>:5: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray Using backend: pytorch Traceback (most recent call last): File "run_model.py", line 36, in run_model(task=args.task, model_name=args.model, dataset_name=args.dataset, File "/home/xiezhicong/Code/ospp/Bigscity-LibCity/libcity/pipeline/pipeline.py", line 63, in run_model executor.evaluate(test_data) File "/home/xiezhicong/Code/ospp/Bigscity-LibCity/libcity/executor/traffic_state_executor.py", line 274, in evaluate self.evaluator.collect({'y_true': torch.tensor(y_truths), 'y_pred': torch.tensor(y_preds)}) File "/home/xiezhicong/Code/ospp/Bigscity-LibCity/libcity/evaluator/traffic_state_evaluator.py", line 47, in collect raise ValueError("batch['y_true'].shape is not equal to batch['y_pred'].shape") ValueError: batch['y_true'].shape is not equal to batch['y_pred'].shape