can't pickle SwigPyObject objects when calling dataset.get_nearest_examples from FAISS index

So, I have the following instances in my dataset

```
{'question': 'An astronomer observes that a planet rotates faster after a meteorite impact. Which is the most likely effect of 
this increase in rotation?', 
'answer': 'C', 
'example_id': 'ARCCH_Mercury_7175875', 
'options':[{'option_context': 'One effect of increased amperage in the planetary world (..)', 'option_id': 'A', 'option_text': 'Planetary density will decrease.'},
 (...)]}
```

The `options` value is always an list with 4 options, each one is a dict with `option_context`; `option_id` and `option_text`.

I would like to overwrite the `option_context` of each instance of my dataset for a dpr result that I am developing. Then, I trained a model already and save it in a FAISS index
```
dpr_dataset = load_dataset(
            "text",
            data_files=ARC_CORPUS_TEXT,
            cache_dir=CACHE_DIR,
            split="train[:100%]",
        )
dpr_dataset.load_faiss_index("embeddings", f"{ARC_CORPUS_FAISS}")
torch.set_grad_enabled(False)
```

Then, as a processor of my dataset, I created a map function that calls the `dpr_dataset` for each _option_

```
def generate_context(example):
    question_text = example['question']
    for option in example['options']:
        question_with_option = question_text + " " + option['option_text']
        tokenize_text =  question_tokenizer(question_with_option, return_tensors="pt").to(device)
        question_embed = (
            question_encoder(**tokenize_text)
        )[0][0].cpu().numpy()
        _, retrieved_examples = dpr_dataset.get_nearest_examples(
            "embeddings", question_embed, k=10
        )
    #    option["option_context"] = retrieved_examples["text"]
    #    option["option_context"] = " ".join(option["option_context"]).strip()
    #result_dict = {
    #    'example_id': example['example_id'],
    #    'answer': example['answer'],
    #    'question': question_text,
        #options': example['options']
    # }
    return example
```

I intentionally commented on this portion of the code.

But when I call the `map` method, `ds_with_context = dataset.map(generate_context,load_from_cache_file=False)`

It calls the following error:

```
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-55-75a458ce205c> in <module>
----> 1 ds_with_context = dataset.map(generate_context,load_from_cache_file=False)

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/datasets/dataset_dict.py in map(self, function, with_indices, input_columns, batched, batch_size, remove_columns, keep_in_memory, load_from_cache_file, cache_file_names, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc)
    301                     num_proc=num_proc,
    302                 )
--> 303                 for k, dataset in self.items()
    304             }
    305         )

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/datasets/dataset_dict.py in <dictcomp>(.0)
    301                     num_proc=num_proc,
    302                 )
--> 303                 for k, dataset in self.items()
    304             }
    305         )

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/datasets/arrow_dataset.py in map(self, function, with_indices, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint)
   1257                 fn_kwargs=fn_kwargs,
   1258                 new_fingerprint=new_fingerprint,
-> 1259                 update_data=update_data,
   1260             )
   1261         else:

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-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

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/datasets/fingerprint.py in wrapper(*args, **kwargs)
    156                         kwargs_for_fingerprint["fingerprint_name"] = fingerprint_name
    157                         kwargs[fingerprint_name] = update_fingerprint(
--> 158                             self._fingerprint, transform, kwargs_for_fingerprint
    159                         )
    160 

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-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 

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-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):

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-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):

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-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

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-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 

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-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 

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/dill/_dill.py in dump(self, obj)
    452             raise PicklingError(msg)
    453         else:
--> 454             StockPickler.dump(self, obj)
    455         stack.clear()  # clear record of 'recursion-sensitive' pickled objects
    456         return

/usr/lib/python3.7/pickle.py in dump(self, obj)
    435         if self.proto >= 4:
    436             self.framer.start_framing()
--> 437         self.save(obj)
    438         self.write(STOP)
    439         self.framer.end_framing()

/usr/lib/python3.7/pickle.py in save(self, obj, save_persistent_id)
    502         f = self.dispatch.get(t)
    503         if f is not None:
--> 504             f(self, obj) # Call unbound method with explicit self
    505             return
    506 

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/datasets/utils/py_utils.py in save_function(pickler, obj)
    554                 dill._dill._create_function,
    555                 (obj.__code__, globs, obj.__name__, obj.__defaults__, obj.__closure__, obj.__dict__, fkwdefaults),
--> 556                 obj=obj,
    557             )
    558         else:

/usr/lib/python3.7/pickle.py in save_reduce(self, func, args, state, listitems, dictitems, obj)
    636         else:
    637             save(func)
--> 638             save(args)
    639             write(REDUCE)
    640 

/usr/lib/python3.7/pickle.py in save(self, obj, save_persistent_id)
    502         f = self.dispatch.get(t)
    503         if f is not None:
--> 504             f(self, obj) # Call unbound method with explicit self
    505             return
    506 

/usr/lib/python3.7/pickle.py in save_tuple(self, obj)
    784         write(MARK)
    785         for element in obj:
--> 786             save(element)
    787 
    788         if id(obj) in memo:

/usr/lib/python3.7/pickle.py in save(self, obj, save_persistent_id)
    502         f = self.dispatch.get(t)
    503         if f is not None:
--> 504             f(self, obj) # Call unbound method with explicit self
    505             return
    506 

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/dill/_dill.py in save_module_dict(pickler, obj)
    939             # we only care about session the first pass thru
    940             pickler._session = False
--> 941         StockPickler.save_dict(pickler, obj)
    942         log.info("# D2")
    943     return

/usr/lib/python3.7/pickle.py in save_dict(self, obj)
    854 
    855         self.memoize(obj)
--> 856         self._batch_setitems(obj.items())
    857 
    858     dispatch[dict] = save_dict

/usr/lib/python3.7/pickle.py in _batch_setitems(self, items)
    880                 for k, v in tmp:
    881                     save(k)
--> 882                     save(v)
    883                 write(SETITEMS)
    884             elif n:

/usr/lib/python3.7/pickle.py in save(self, obj, save_persistent_id)
    547 
    548         # Save the reduce() output and finally memoize the object
--> 549         self.save_reduce(obj=obj, *rv)
    550 
    551     def persistent_id(self, obj):

/usr/lib/python3.7/pickle.py in save_reduce(self, func, args, state, listitems, dictitems, obj)
    660 
    661         if state is not None:
--> 662             save(state)
    663             write(BUILD)
    664 

/usr/lib/python3.7/pickle.py in save(self, obj, save_persistent_id)
    502         f = self.dispatch.get(t)
    503         if f is not None:
--> 504             f(self, obj) # Call unbound method with explicit self
    505             return
    506 

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/dill/_dill.py in save_module_dict(pickler, obj)
    939             # we only care about session the first pass thru
    940             pickler._session = False
--> 941         StockPickler.save_dict(pickler, obj)
    942         log.info("# D2")
    943     return

/usr/lib/python3.7/pickle.py in save_dict(self, obj)
    854 
    855         self.memoize(obj)
--> 856         self._batch_setitems(obj.items())
    857 
    858     dispatch[dict] = save_dict

/usr/lib/python3.7/pickle.py in _batch_setitems(self, items)
    880                 for k, v in tmp:
    881                     save(k)
--> 882                     save(v)
    883                 write(SETITEMS)
    884             elif n:

/usr/lib/python3.7/pickle.py in save(self, obj, save_persistent_id)
    502         f = self.dispatch.get(t)
    503         if f is not None:
--> 504             f(self, obj) # Call unbound method with explicit self
    505             return
    506 

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/dill/_dill.py in save_module_dict(pickler, obj)
    939             # we only care about session the first pass thru
    940             pickler._session = False
--> 941         StockPickler.save_dict(pickler, obj)
    942         log.info("# D2")
    943     return

/usr/lib/python3.7/pickle.py in save_dict(self, obj)
    854 
    855         self.memoize(obj)
--> 856         self._batch_setitems(obj.items())
    857 
    858     dispatch[dict] = save_dict

/usr/lib/python3.7/pickle.py in _batch_setitems(self, items)
    885                 k, v = tmp[0]
    886                 save(k)
--> 887                 save(v)
    888                 write(SETITEM)
    889             # else tmp is empty, and we're done

/usr/lib/python3.7/pickle.py in save(self, obj, save_persistent_id)
    547 
    548         # Save the reduce() output and finally memoize the object
--> 549         self.save_reduce(obj=obj, *rv)
    550 
    551     def persistent_id(self, obj):

/usr/lib/python3.7/pickle.py in save_reduce(self, func, args, state, listitems, dictitems, obj)
    660 
    661         if state is not None:
--> 662             save(state)
    663             write(BUILD)
    664 

/usr/lib/python3.7/pickle.py in save(self, obj, save_persistent_id)
    502         f = self.dispatch.get(t)
    503         if f is not None:
--> 504             f(self, obj) # Call unbound method with explicit self
    505             return
    506 

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/dill/_dill.py in save_module_dict(pickler, obj)
    939             # we only care about session the first pass thru
    940             pickler._session = False
--> 941         StockPickler.save_dict(pickler, obj)
    942         log.info("# D2")
    943     return

/usr/lib/python3.7/pickle.py in save_dict(self, obj)
    854 
    855         self.memoize(obj)
--> 856         self._batch_setitems(obj.items())
    857 
    858     dispatch[dict] = save_dict

/usr/lib/python3.7/pickle.py in _batch_setitems(self, items)
    880                 for k, v in tmp:
    881                     save(k)
--> 882                     save(v)
    883                 write(SETITEMS)
    884             elif n:

/usr/lib/python3.7/pickle.py in save(self, obj, save_persistent_id)
    547 
    548         # Save the reduce() output and finally memoize the object
--> 549         self.save_reduce(obj=obj, *rv)
    550 
    551     def persistent_id(self, obj):

/usr/lib/python3.7/pickle.py in save_reduce(self, func, args, state, listitems, dictitems, obj)
    660 
    661         if state is not None:
--> 662             save(state)
    663             write(BUILD)
    664 

/usr/lib/python3.7/pickle.py in save(self, obj, save_persistent_id)
    502         f = self.dispatch.get(t)
    503         if f is not None:
--> 504             f(self, obj) # Call unbound method with explicit self
    505             return
    506 

~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/dill/_dill.py in save_module_dict(pickler, obj)
    939             # we only care about session the first pass thru
    940             pickler._session = False
--> 941         StockPickler.save_dict(pickler, obj)
    942         log.info("# D2")
    943     return

/usr/lib/python3.7/pickle.py in save_dict(self, obj)
    854 
    855         self.memoize(obj)
--> 856         self._batch_setitems(obj.items())
    857 
    858     dispatch[dict] = save_dict

/usr/lib/python3.7/pickle.py in _batch_setitems(self, items)
    885                 k, v = tmp[0]
    886                 save(k)
--> 887                 save(v)
    888                 write(SETITEM)
    889             # else tmp is empty, and we're done

/usr/lib/python3.7/pickle.py in save(self, obj, save_persistent_id)
    522             reduce = getattr(obj, "__reduce_ex__", None)
    523             if reduce is not None:
--> 524                 rv = reduce(self.proto)
    525             else:
    526                 reduce = getattr(obj, "__reduce__", None)

TypeError: can't pickle SwigPyObject objects
```

Which I have no idea how to solve/deal with it




Hi ! Indeed we used to require mapping functions to be picklable with `pickle` or `dill` in order to cache the resulting datasets. And FAISS indexes are not picklable unfortunately.

But since #1703 this is no longer required (the caching will simply be disabled). This change will be available in the next release of `datasets`, or you can also install `datasets` from source.

I totally forgot to answer this issue, I'm so sorry. 

I was able to get it working by installing `datasets` from source. Huge thanks!