Datasets map and select(range()) is giving dill error
MEMBER
It looks like an error that we observed once in https://github.com/huggingface/datasets/pull/5166

Can you try to update `datasets` ?

```
pip install -U datasets
```

if it doesn't work, can you make sure you don't have packages installed that may modify `dill`'s behavior, such as `apache-beam` ?
2023-03-16T16:54:53Z
https://github.com/huggingface/datasets/issues/5645#issuecomment-1472348976
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2023-03-16T16:56:10Z
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@lhoestq That fixed the problem, Thanks :)
2023-03-17T04:24:51Z
https://github.com/huggingface/datasets/issues/5645#issuecomment-1473110148
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### Describe the bug

I'm using Huggingface Datasets library to load the dataset in google colab

When I do, 
 

> data = train_dataset.select(range(10))

or 

> train_datasets = train_dataset.map(
>      process_data_to_model_inputs,
>      batched=True,
>      batch_size=batch_size,
>      remove_columns=["article", "abstract"],
>  )

 I get following error: `module 'dill._dill' has no attribute 'log'`
I've tried downgrading the dill version from latest to 0.2.8, but no luck. 

Stack trace:

> ---------------------------------------------------------------------------
> ModuleNotFoundError                       Traceback (most recent call last)
> /usr/local/lib/python3.9/dist-packages/datasets/utils/py_utils.py in _no_cache_fields(obj)
>     367     try:
> --> 368         import transformers as tr
>     369 
> 
> ModuleNotFoundError: No module named 'transformers'
> 
> During handling of the above exception, another exception occurred:
> 
> AttributeError                            Traceback (most recent call last)
> 17 frames
> <ipython-input-13-dd14813880a6> in <module>
> ----> 1 test = train_dataset.select(range(10))
> 
> /usr/local/lib/python3.9/dist-packages/datasets/arrow_dataset.py in wrapper(*args, **kwargs)
>     155         }
>     156         # apply actual function
> --> 157         out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
>     158         datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out]
>     159         # re-apply format to the output
> 
> /usr/local/lib/python3.9/dist-packages/datasets/fingerprint.py in wrapper(*args, **kwargs)
>     155                     if kwargs.get(fingerprint_name) is None:
>     156                         kwargs_for_fingerprint["fingerprint_name"] = fingerprint_name
> --> 157                         kwargs[fingerprint_name] = update_fingerprint(
>     158                             self._fingerprint, transform, kwargs_for_fingerprint
>     159                         )
> 
> /usr/local/lib/python3.9/dist-packages/datasets/fingerprint.py in update_fingerprint(fingerprint, transform, transform_args)
>     103     for key in sorted(transform_args):
>     104         hasher.update(key)
> --> 105         hasher.update(transform_args[key])
>     106     return hasher.hexdigest()
>     107 
> 
> /usr/local/lib/python3.9/dist-packages/datasets/fingerprint.py in update(self, value)
>      55     def update(self, value):
>      56         self.m.update(f"=={type(value)}==".encode("utf8"))
> ---> 57         self.m.update(self.hash(value).encode("utf-8"))
>      58 
>      59     def hexdigest(self):
> 
> /usr/local/lib/python3.9/dist-packages/datasets/fingerprint.py in hash(cls, value)
>      51             return cls.dispatch[type(value)](cls, value)
>      52         else:
> ---> 53             return cls.hash_default(value)
>      54 
>      55     def update(self, value):
> 
> /usr/local/lib/python3.9/dist-packages/datasets/fingerprint.py in hash_default(cls, value)
>      44     @classmethod
>      45     def hash_default(cls, value):
> ---> 46         return cls.hash_bytes(dumps(value))
>      47 
>      48     @classmethod
> 
> /usr/local/lib/python3.9/dist-packages/datasets/utils/py_utils.py in dumps(obj)
>     387     file = StringIO()
>     388     with _no_cache_fields(obj):
> --> 389         dump(obj, file)
>     390     return file.getvalue()
>     391 
> 
> /usr/local/lib/python3.9/dist-packages/datasets/utils/py_utils.py in dump(obj, file)
>     359 def dump(obj, file):
>     360     """pickle an object to a file"""
> --> 361     Pickler(file, recurse=True).dump(obj)
>     362     return
>     363 
> 
> /usr/local/lib/python3.9/dist-packages/dill/_dill.py in dump(self, obj)
>     392     return
>     393 
> --> 394 def load_session(filename='/tmp/session.pkl', main=None):
>     395     """update the __main__ module with the state from the session file"""
>     396     if main is None: main = _main_module
> 
> /usr/lib/python3.9/pickle.py in dump(self, obj)
>     485         if self.proto >= 4:
>     486             self.framer.start_framing()
> --> 487         self.save(obj)
>     488         self.write(STOP)
>     489         self.framer.end_framing()
> 
> /usr/local/lib/python3.9/dist-packages/dill/_dill.py in save(self, obj, save_persistent_id)
>     386         pickler._byref = False   # disable pickling by name reference
>     387         pickler._recurse = False # disable pickling recursion for globals
> --> 388         pickler._session = True  # is best indicator of when pickling a session
>     389         pickler.dump(main)
>     390     finally:
> 
> /usr/lib/python3.9/pickle.py in save(self, obj, save_persistent_id)
>     558             f = self.dispatch.get(t)
>     559             if f is not None:
> --> 560                 f(self, obj)  # Call unbound method with explicit self
>     561                 return
>     562 
> 
> /usr/local/lib/python3.9/dist-packages/dill/_dill.py in save_singleton(pickler, obj)
> 
> /usr/lib/python3.9/pickle.py in save_reduce(self, func, args, state, listitems, dictitems, state_setter, obj)
>     689             write(NEWOBJ)
>     690         else:
> --> 691             save(func)
>     692             save(args)
>     693             write(REDUCE)
> 
> /usr/local/lib/python3.9/dist-packages/dill/_dill.py in save(self, obj, save_persistent_id)
>     386         pickler._byref = False   # disable pickling by name reference
>     387         pickler._recurse = False # disable pickling recursion for globals
> --> 388         pickler._session = True  # is best indicator of when pickling a session
>     389         pickler.dump(main)
>     390     finally:
> 
> /usr/lib/python3.9/pickle.py in save(self, obj, save_persistent_id)
>     558             f = self.dispatch.get(t)
>     559             if f is not None:
> --> 560                 f(self, obj)  # Call unbound method with explicit self
>     561                 return
>     562 
> 
> /usr/local/lib/python3.9/dist-packages/datasets/utils/py_utils.py in save_function(pickler, obj)
>     583         dill._dill.log.info("# F1")
>     584     else:
> --> 585         dill._dill.log.info("F2: %s" % obj)
>     586         name = getattr(obj, "__qualname__", getattr(obj, "__name__", None))
>     587         dill._dill.StockPickler.save_global(pickler, obj, name=name)
> 
> AttributeError: module 'dill._dill' has no attribute 'log'

### Steps to reproduce the bug

After loading the dataset(eg: https://huggingface.co/datasets/scientific_papers) in google colab

do either 
> data = train_dataset.select(range(10))

or 

> train_datasets = train_dataset.map(
>      process_data_to_model_inputs,
>      batched=True,
>      batch_size=batch_size,
>      remove_columns=["article", "abstract"],
>  )

### Expected behavior

The map and select function should work

### Environment info

dataset: https://huggingface.co/datasets/scientific_papers
dill = 0.3.6
python= 3.9.16
transformer = 4.2.0