torchtext-pickle-error

$ python news_classifier.py --max_epochs 1 --num_samples 100
2022-07-19 09:39:20.830460: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2022-07-19 09:39:20.830488: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
Some weights of the model checkpoint at bert-base-uncased were not used when initializing BertModel: ['cls.predictions.transform.dense.weight', 'cls.predictions.decoder.weight', 'cls.predictions.bias', 'cls.seq_relationship.bias', 'cls.seq_relationship.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.transform.LayerNorm.weight']
- This IS expected if you are initializing BertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing BertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
/home/ubuntu/anaconda3/lib/python3.8/site-packages/transformers/tokenization_utils_base.py:1656: FutureWarning: Calling BertTokenizer.from_pretrained() with the path to a single file or url is deprecated and won't be possible anymore in v5. Use a model identifier or the path to a directory instead.
  warnings.warn(
Number of samples used for training: 80
Number of samples used for validation: 10
Number of samples used for test: 10
/home/ubuntu/anaconda3/lib/python3.8/site-packages/transformers/optimization.py:306: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning
  warnings.warn(
Epoch 1/1
6it [00:15,  2.58s/it]
Train loss 2.7903212507565818 accuracy 0.19791666666666666
Val   loss 5.48581059773763 accuracy 0.0625
TRAINING COMPLETED!!!
0.041666666666666664



 SAVING MODEL
Traceback (most recent call last):
  File "/home/ubuntu/anaconda3/lib/python3.8/site-packages/torch/utils/data/datapipes/datapipe.py", line 317, in __getstate__
    value = pickle.dumps(self._datapipe)
AttributeError: Can't pickle local object 'to_map_style_dataset.<locals>._MapStyleDataset'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "news_classifier.py", line 396, in <module>
    mlflow.pytorch.save_model(
  File "/home/ubuntu/anaconda3/lib/python3.8/site-packages/mlflow/pytorch/__init__.py", line 512, in save_model
    torch.save(pytorch_model, model_path, pickle_module=pickle_module, **kwargs)
  File "/home/ubuntu/anaconda3/lib/python3.8/site-packages/torch/serialization.py", line 379, in save
    _save(obj, opened_zipfile, pickle_module, pickle_protocol)
  File "/home/ubuntu/anaconda3/lib/python3.8/site-packages/torch/serialization.py", line 589, in _save
    pickler.dump(obj)
  File "/home/ubuntu/anaconda3/lib/python3.8/site-packages/cloudpickle/cloudpickle_fast.py", line 602, in dump
    return Pickler.dump(self, obj)
  File "/home/ubuntu/anaconda3/lib/python3.8/site-packages/torch/utils/data/datapipes/datapipe.py", line 162, in __reduce_ex__
    return super().__reduce_ex__(*args, **kwargs)
  File "/home/ubuntu/anaconda3/lib/python3.8/site-packages/torch/utils/data/datapipes/datapipe.py", line 320, in __getstate__
    value = dill.dumps(self._datapipe)
  File "/home/ubuntu/anaconda3/lib/python3.8/site-packages/dill/_dill.py", line 304, in dumps
    dump(obj, file, protocol, byref, fmode, recurse, **kwds)#, strictio)
  File "/home/ubuntu/anaconda3/lib/python3.8/site-packages/dill/_dill.py", line 276, in dump
    Pickler(file, protocol, **_kwds).dump(obj)
  File "/home/ubuntu/anaconda3/lib/python3.8/site-packages/dill/_dill.py", line 498, in dump
    StockPickler.dump(self, obj)
  File "/home/ubuntu/anaconda3/lib/python3.8/pickle.py", line 485, in dump
    self.save(obj)
  File "/home/ubuntu/anaconda3/lib/python3.8/pickle.py", line 601, in save
    self.save_reduce(obj=obj, *rv)
  File "/home/ubuntu/anaconda3/lib/python3.8/pickle.py", line 685, in save_reduce
    save(cls)
  File "/home/ubuntu/anaconda3/lib/python3.8/pickle.py", line 558, in save
    f(self, obj)  # Call unbound method with explicit self
  File "/home/ubuntu/anaconda3/lib/python3.8/site-packages/dill/_dill.py", line 1422, in save_type
    pickler.save_reduce(_create_type, (type(obj), obj.__name__,
  File "/home/ubuntu/anaconda3/lib/python3.8/pickle.py", line 690, in save_reduce
    save(args)
  File "/home/ubuntu/anaconda3/lib/python3.8/pickle.py", line 558, in save
    f(self, obj)  # Call unbound method with explicit self
  File "/home/ubuntu/anaconda3/lib/python3.8/pickle.py", line 899, in save_tuple
    save(element)
  File "/home/ubuntu/anaconda3/lib/python3.8/pickle.py", line 558, in save
    f(self, obj)  # Call unbound method with explicit self
  File "/home/ubuntu/anaconda3/lib/python3.8/site-packages/dill/_dill.py", line 990, in save_module_dict
    StockPickler.save_dict(pickler, obj)
  File "/home/ubuntu/anaconda3/lib/python3.8/pickle.py", line 969, in save_dict
    self._batch_setitems(obj.items())
  File "/home/ubuntu/anaconda3/lib/python3.8/pickle.py", line 995, in _batch_setitems
    save(v)
  File "/home/ubuntu/anaconda3/lib/python3.8/pickle.py", line 576, in save
    rv = reduce(self.proto)
TypeError: cannot pickle '_abc_data' object