[Question] How to load wikipedia ? Beam runner ?
I have seen that somebody is hard working on easierly loadable wikipedia. #129 
Maybe I should wait a few days for that version ?
When `nlp.load_dataset('wikipedia')`, I got
* `WARNING:nlp.builder:Trying to generate a dataset using Apache Beam, yet no Beam Runner or PipelineOptions() has been provided. Please pass a nlp.DownloadConfig(beam_runner=...) object to the builder.download_and_prepare(download_config=...) method. Default values will be used.`
* `AttributeError: 'NoneType' object has no attribute 'size'`

Could somebody tell me what should I do ? 

# Env
On Colab,
```
git clone https://github.com/huggingface/nlp
cd nlp
pip install -q .
```
```
%pip install -q apache_beam mwparserfromhell
-> ERROR: pydrive 1.3.1 has requirement oauth2client>=4.0.0, but you'll have oauth2client 3.0.0 which is incompatible.
ERROR: google-api-python-client 1.7.12 has requirement httplib2<1dev,>=0.17.0, but you'll have httplib2 0.12.0 which is incompatible.
ERROR: chainer 6.5.0 has requirement typing-extensions<=3.6.6, but you'll have typing-extensions 3.7.4.2 which is incompatible.
```
```
pip install -q apache-beam[interactive]
ERROR: google-colab 1.0.0 has requirement ipython~=5.5.0, but you'll have ipython 5.10.0 which is incompatible.
```

# The whole message
```
WARNING:nlp.builder:Trying to generate a dataset using Apache Beam, yet no Beam Runner or PipelineOptions() has been provided. Please pass a nlp.DownloadConfig(beam_runner=...) object to the builder.download_and_prepare(download_config=...) method. Default values will be used.

Downloading and preparing dataset wikipedia/20200501.aa (download: Unknown size, generated: Unknown size, total: Unknown size) to /root/.cache/huggingface/datasets/wikipedia/20200501.aa/1.0.0...

---------------------------------------------------------------------------

AttributeError                            Traceback (most recent call last)

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.DoFnRunner.process()

44 frames

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.PerWindowInvoker.invoke_process()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window()

/usr/local/lib/python3.6/dist-packages/apache_beam/io/iobase.py in process(self, element, init_result)
   1081       writer.write(e)
-> 1082     return [window.TimestampedValue(writer.close(), timestamp.MAX_TIMESTAMP)]
   1083 

/usr/local/lib/python3.6/dist-packages/apache_beam/io/filebasedsink.py in close(self)
    422   def close(self):
--> 423     self.sink.close(self.temp_handle)
    424     return self.temp_shard_path

/usr/local/lib/python3.6/dist-packages/apache_beam/io/parquetio.py in close(self, writer)
    537     if len(self._buffer[0]) > 0:
--> 538       self._flush_buffer()
    539     if self._record_batches_byte_size > 0:

/usr/local/lib/python3.6/dist-packages/apache_beam/io/parquetio.py in _flush_buffer(self)
    569       for b in x.buffers():
--> 570         size = size + b.size
    571     self._record_batches_byte_size = self._record_batches_byte_size + size

AttributeError: 'NoneType' object has no attribute 'size'

During handling of the above exception, another exception occurred:

AttributeError                            Traceback (most recent call last)

<ipython-input-9-340aabccefff> in <module>()
----> 1 dset = nlp.load_dataset('wikipedia')

/usr/local/lib/python3.6/dist-packages/nlp/load.py in load_dataset(path, name, version, data_dir, data_files, split, cache_dir, download_config, download_mode, ignore_verifications, save_infos, **config_kwargs)
    518         download_mode=download_mode,
    519         ignore_verifications=ignore_verifications,
--> 520         save_infos=save_infos,
    521     )
    522 

/usr/local/lib/python3.6/dist-packages/nlp/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, save_infos, dl_manager, **download_and_prepare_kwargs)
    370                 verify_infos = not save_infos and not ignore_verifications
    371                 self._download_and_prepare(
--> 372                     dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
    373                 )
    374                 # Sync info

/usr/local/lib/python3.6/dist-packages/nlp/builder.py in _download_and_prepare(self, dl_manager, verify_infos)
    770         with beam.Pipeline(runner=beam_runner, options=beam_options,) as pipeline:
    771             super(BeamBasedBuilder, self)._download_and_prepare(
--> 772                 dl_manager, pipeline=pipeline, verify_infos=False
    773             )  # TODO{beam} verify infos
    774 

/usr/local/lib/python3.6/dist-packages/apache_beam/pipeline.py in __exit__(self, exc_type, exc_val, exc_tb)
    501   def __exit__(self, exc_type, exc_val, exc_tb):
    502     if not exc_type:
--> 503       self.run().wait_until_finish()
    504 
    505   def visit(self, visitor):

/usr/local/lib/python3.6/dist-packages/apache_beam/pipeline.py in run(self, test_runner_api)
    481       return Pipeline.from_runner_api(
    482           self.to_runner_api(use_fake_coders=True), self.runner,
--> 483           self._options).run(False)
    484 
    485     if self._options.view_as(TypeOptions).runtime_type_check:

/usr/local/lib/python3.6/dist-packages/apache_beam/pipeline.py in run(self, test_runner_api)
    494       finally:
    495         shutil.rmtree(tmpdir)
--> 496     return self.runner.run_pipeline(self, self._options)
    497 
    498   def __enter__(self):

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/direct/direct_runner.py in run_pipeline(self, pipeline, options)
    128       runner = BundleBasedDirectRunner()
    129 
--> 130     return runner.run_pipeline(pipeline, options)
    131 
    132 

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in run_pipeline(self, pipeline, options)
    553 
    554     self._latest_run_result = self.run_via_runner_api(
--> 555         pipeline.to_runner_api(default_environment=self._default_environment))
    556     return self._latest_run_result
    557 

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in run_via_runner_api(self, pipeline_proto)
    563     # TODO(pabloem, BEAM-7514): Create a watermark manager (that has access to
    564     #   the teststream (if any), and all the stages).
--> 565     return self.run_stages(stage_context, stages)
    566 
    567   @contextlib.contextmanager

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in run_stages(self, stage_context, stages)
    704               stage,
    705               pcoll_buffers,
--> 706               stage_context.safe_coders)
    707           metrics_by_stage[stage.name] = stage_results.process_bundle.metrics
    708           monitoring_infos_by_stage[stage.name] = (

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in _run_stage(self, worker_handler_factory, pipeline_components, stage, pcoll_buffers, safe_coders)
   1071         cache_token_generator=cache_token_generator)
   1072 
-> 1073     result, splits = bundle_manager.process_bundle(data_input, data_output)
   1074 
   1075     def input_for(transform_id, input_id):

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in process_bundle(self, inputs, expected_outputs)
   2332 
   2333     with UnboundedThreadPoolExecutor() as executor:
-> 2334       for result, split_result in executor.map(execute, part_inputs):
   2335 
   2336         split_result_list += split_result

/usr/lib/python3.6/concurrent/futures/_base.py in result_iterator()
    584                     # Careful not to keep a reference to the popped future
    585                     if timeout is None:
--> 586                         yield fs.pop().result()
    587                     else:
    588                         yield fs.pop().result(end_time - time.monotonic())

/usr/lib/python3.6/concurrent/futures/_base.py in result(self, timeout)
    430                 raise CancelledError()
    431             elif self._state == FINISHED:
--> 432                 return self.__get_result()
    433             else:
    434                 raise TimeoutError()

/usr/lib/python3.6/concurrent/futures/_base.py in __get_result(self)
    382     def __get_result(self):
    383         if self._exception:
--> 384             raise self._exception
    385         else:
    386             return self._result

/usr/local/lib/python3.6/dist-packages/apache_beam/utils/thread_pool_executor.py in run(self)
     42       # If the future wasn't cancelled, then attempt to execute it.
     43       try:
---> 44         self._future.set_result(self._fn(*self._fn_args, **self._fn_kwargs))
     45       except BaseException as exc:
     46         # Even though Python 2 futures library has #set_exection(),

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in execute(part_map)
   2329           self._registered,
   2330           cache_token_generator=self._cache_token_generator)
-> 2331       return bundle_manager.process_bundle(part_map, expected_outputs)
   2332 
   2333     with UnboundedThreadPoolExecutor() as executor:

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in process_bundle(self, inputs, expected_outputs)
   2243             process_bundle_descriptor_id=self._bundle_descriptor.id,
   2244             cache_tokens=[next(self._cache_token_generator)]))
-> 2245     result_future = self._worker_handler.control_conn.push(process_bundle_req)
   2246 
   2247     split_results = []  # type: List[beam_fn_api_pb2.ProcessBundleSplitResponse]

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in push(self, request)
   1557       self._uid_counter += 1
   1558       request.instruction_id = 'control_%s' % self._uid_counter
-> 1559     response = self.worker.do_instruction(request)
   1560     return ControlFuture(request.instruction_id, response)
   1561 

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/sdk_worker.py in do_instruction(self, request)
    413       # E.g. if register is set, this will call self.register(request.register))
    414       return getattr(self, request_type)(
--> 415           getattr(request, request_type), request.instruction_id)
    416     else:
    417       raise NotImplementedError

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/sdk_worker.py in process_bundle(self, request, instruction_id)
    448         with self.maybe_profile(instruction_id):
    449           delayed_applications, requests_finalization = (
--> 450               bundle_processor.process_bundle(instruction_id))
    451           monitoring_infos = bundle_processor.monitoring_infos()
    452           monitoring_infos.extend(self.state_cache_metrics_fn())

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/bundle_processor.py in process_bundle(self, instruction_id)
    837         for data in data_channel.input_elements(instruction_id,
    838                                                 expected_transforms):
--> 839           input_op_by_transform_id[data.transform_id].process_encoded(data.data)
    840 
    841       # Finish all operations.

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/bundle_processor.py in process_encoded(self, encoded_windowed_values)
    214       decoded_value = self.windowed_coder_impl.decode_from_stream(
    215           input_stream, True)
--> 216       self.output(decoded_value)
    217 
    218   def try_split(self, fraction_of_remainder, total_buffer_size):

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.Operation.output()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.Operation.output()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.SingletonConsumerSet.receive()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.DoOperation.process()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.DoOperation.process()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.DoFnRunner.process()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.DoFnRunner._reraise_augmented()

/usr/local/lib/python3.6/dist-packages/future/utils/__init__.py in raise_with_traceback(exc, traceback)
    417         if traceback == Ellipsis:
    418             _, _, traceback = sys.exc_info()
--> 419         raise exc.with_traceback(traceback)
    420 
    421 else:

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.DoFnRunner.process()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.PerWindowInvoker.invoke_process()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window()

/usr/local/lib/python3.6/dist-packages/apache_beam/io/iobase.py in process(self, element, init_result)
   1080     for e in bundle[1]:  # values
   1081       writer.write(e)
-> 1082     return [window.TimestampedValue(writer.close(), timestamp.MAX_TIMESTAMP)]
   1083 
   1084 

/usr/local/lib/python3.6/dist-packages/apache_beam/io/filebasedsink.py in close(self)
    421 
    422   def close(self):
--> 423     self.sink.close(self.temp_handle)
    424     return self.temp_shard_path

/usr/local/lib/python3.6/dist-packages/apache_beam/io/parquetio.py in close(self, writer)
    536   def close(self, writer):
    537     if len(self._buffer[0]) > 0:
--> 538       self._flush_buffer()
    539     if self._record_batches_byte_size > 0:
    540       self._write_batches(writer)

/usr/local/lib/python3.6/dist-packages/apache_beam/io/parquetio.py in _flush_buffer(self)
    568     for x in arrays:
    569       for b in x.buffers():
--> 570         size = size + b.size
    571     self._record_batches_byte_size = self._record_batches_byte_size + size

AttributeError: 'NoneType' object has no attribute 'size' [while running 'train/Save to parquet/Write/WriteImpl/WriteBundles']
```
[Question] How to load wikipedia ? Beam runner ? 
 When `nlp.load_dataset('wikipedia')`, I got
* `WARNING:nlp.builder:Trying to generate a dataset using Apache Beam, yet no Beam Runner or PipelineOptions() has been provided. Please pass a nlp.DownloadConfig(beam_runner=...) object to the builder.download_and_prepare(download_config=...) method. Default values will be used.`
* `AttributeError: 'NoneType' object has no attribute 'size'`

Could somebody tell me what should I do ? 

# Env
On Colab,
```
git clone https://github.com/huggingface/nlp
cd nlp
pip install -q .
```
```
%pip install -q apache_beam mwparserfromhell
-> ERROR: pydrive 1.3.1 has requirement oauth2client>=4.0.0, but you'll have oauth2client 3.0.0 which is incompatible.
ERROR: google-api-python-client 1.7.12 has requirement httplib2<1dev,>=0.17.0, but you'll have httplib2 0.12.0 which is incompatible.
ERROR: chainer 6.5.0 has requirement typing-extensions<=3.6.6, but you'll have typing-extensions 3.7.4.2 which is incompatible.
```
```
pip install -q apache-beam[interactive]
ERROR: google-colab 1.0.0 has requirement ipython~=5.5.0, but you'll have ipython 5.10.0 which is incompatible.
```

# The whole message
```
WARNING:nlp.builder:Trying to generate a dataset using Apache Beam, yet no Beam Runner or PipelineOptions() has been provided. Please pass a nlp.DownloadConfig(beam_runner=...) object to the builder.download_and_prepare(download_config=...) method. Default values will be used.

Downloading and preparing dataset wikipedia/20200501.aa (download: Unknown size, generated: Unknown size, total: Unknown size) to /root/.cache/huggingface/datasets/wikipedia/20200501.aa/1.0.0...

---------------------------------------------------------------------------

AttributeError                            Traceback (most recent call last)

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.DoFnRunner.process()

44 frames

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.PerWindowInvoker.invoke_process()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window()

/usr/local/lib/python3.6/dist-packages/apache_beam/io/iobase.py in process(self, element, init_result)
   1081       writer.write(e)
-> 1082     return [window.TimestampedValue(writer.close(), timestamp.MAX_TIMESTAMP)]
   1083 

/usr/local/lib/python3.6/dist-packages/apache_beam/io/filebasedsink.py in close(self)
    422   def close(self):
--> 423     self.sink.close(self.temp_handle)
    424     return self.temp_shard_path

/usr/local/lib/python3.6/dist-packages/apache_beam/io/parquetio.py in close(self, writer)
    537     if len(self._buffer[0]) > 0:
--> 538       self._flush_buffer()
    539     if self._record_batches_byte_size > 0:

/usr/local/lib/python3.6/dist-packages/apache_beam/io/parquetio.py in _flush_buffer(self)
    569       for b in x.buffers():
--> 570         size = size + b.size
    571     self._record_batches_byte_size = self._record_batches_byte_size + size

AttributeError: 'NoneType' object has no attribute 'size'

During handling of the above exception, another exception occurred:

AttributeError                            Traceback (most recent call last)

<ipython-input-9-340aabccefff> in <module>()
----> 1 dset = nlp.load_dataset('wikipedia')

/usr/local/lib/python3.6/dist-packages/nlp/load.py in load_dataset(path, name, version, data_dir, data_files, split, cache_dir, download_config, download_mode, ignore_verifications, save_infos, **config_kwargs)
    518         download_mode=download_mode,
    519         ignore_verifications=ignore_verifications,
--> 520         save_infos=save_infos,
    521     )
    522 

/usr/local/lib/python3.6/dist-packages/nlp/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, save_infos, dl_manager, **download_and_prepare_kwargs)
    370                 verify_infos = not save_infos and not ignore_verifications
    371                 self._download_and_prepare(
--> 372                     dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
    373                 )
    374                 # Sync info

/usr/local/lib/python3.6/dist-packages/nlp/builder.py in _download_and_prepare(self, dl_manager, verify_infos)
    770         with beam.Pipeline(runner=beam_runner, options=beam_options,) as pipeline:
    771             super(BeamBasedBuilder, self)._download_and_prepare(
--> 772                 dl_manager, pipeline=pipeline, verify_infos=False
    773             )  # TODO{beam} verify infos
    774 

/usr/local/lib/python3.6/dist-packages/apache_beam/pipeline.py in __exit__(self, exc_type, exc_val, exc_tb)
    501   def __exit__(self, exc_type, exc_val, exc_tb):
    502     if not exc_type:
--> 503       self.run().wait_until_finish()
    504 
    505   def visit(self, visitor):

/usr/local/lib/python3.6/dist-packages/apache_beam/pipeline.py in run(self, test_runner_api)
    481       return Pipeline.from_runner_api(
    482           self.to_runner_api(use_fake_coders=True), self.runner,
--> 483           self._options).run(False)
    484 
    485     if self._options.view_as(TypeOptions).runtime_type_check:

/usr/local/lib/python3.6/dist-packages/apache_beam/pipeline.py in run(self, test_runner_api)
    494       finally:
    495         shutil.rmtree(tmpdir)
--> 496     return self.runner.run_pipeline(self, self._options)
    497 
    498   def __enter__(self):

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/direct/direct_runner.py in run_pipeline(self, pipeline, options)
    128       runner = BundleBasedDirectRunner()
    129 
--> 130     return runner.run_pipeline(pipeline, options)
    131 
    132 

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in run_pipeline(self, pipeline, options)
    553 
    554     self._latest_run_result = self.run_via_runner_api(
--> 555         pipeline.to_runner_api(default_environment=self._default_environment))
    556     return self._latest_run_result
    557 

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in run_via_runner_api(self, pipeline_proto)
    563     # TODO(pabloem, BEAM-7514): Create a watermark manager (that has access to
    564     #   the teststream (if any), and all the stages).
--> 565     return self.run_stages(stage_context, stages)
    566 
    567   @contextlib.contextmanager

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in run_stages(self, stage_context, stages)
    704               stage,
    705               pcoll_buffers,
--> 706               stage_context.safe_coders)
    707           metrics_by_stage[stage.name] = stage_results.process_bundle.metrics
    708           monitoring_infos_by_stage[stage.name] = (

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in _run_stage(self, worker_handler_factory, pipeline_components, stage, pcoll_buffers, safe_coders)
   1071         cache_token_generator=cache_token_generator)
   1072 
-> 1073     result, splits = bundle_manager.process_bundle(data_input, data_output)
   1074 
   1075     def input_for(transform_id, input_id):

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in process_bundle(self, inputs, expected_outputs)
   2332 
   2333     with UnboundedThreadPoolExecutor() as executor:
-> 2334       for result, split_result in executor.map(execute, part_inputs):
   2335 
   2336         split_result_list += split_result

/usr/lib/python3.6/concurrent/futures/_base.py in result_iterator()
    584                     # Careful not to keep a reference to the popped future
    585                     if timeout is None:
--> 586                         yield fs.pop().result()
    587                     else:
    588                         yield fs.pop().result(end_time - time.monotonic())

/usr/lib/python3.6/concurrent/futures/_base.py in result(self, timeout)
    430                 raise CancelledError()
    431             elif self._state == FINISHED:
--> 432                 return self.__get_result()
    433             else:
    434                 raise TimeoutError()

/usr/lib/python3.6/concurrent/futures/_base.py in __get_result(self)
    382     def __get_result(self):
    383         if self._exception:
--> 384             raise self._exception
    385         else:
    386             return self._result

/usr/local/lib/python3.6/dist-packages/apache_beam/utils/thread_pool_executor.py in run(self)
     42       # If the future wasn't cancelled, then attempt to execute it.
     43       try:
---> 44         self._future.set_result(self._fn(*self._fn_args, **self._fn_kwargs))
     45       except BaseException as exc:
     46         # Even though Python 2 futures library has #set_exection(),

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in execute(part_map)
   2329           self._registered,
   2330           cache_token_generator=self._cache_token_generator)
-> 2331       return bundle_manager.process_bundle(part_map, expected_outputs)
   2332 
   2333     with UnboundedThreadPoolExecutor() as executor:

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in process_bundle(self, inputs, expected_outputs)
   2243             process_bundle_descriptor_id=self._bundle_descriptor.id,
   2244             cache_tokens=[next(self._cache_token_generator)]))
-> 2245     result_future = self._worker_handler.control_conn.push(process_bundle_req)
   2246 
   2247     split_results = []  # type: List[beam_fn_api_pb2.ProcessBundleSplitResponse]

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/portability/fn_api_runner.py in push(self, request)
   1557       self._uid_counter += 1
   1558       request.instruction_id = 'control_%s' % self._uid_counter
-> 1559     response = self.worker.do_instruction(request)
   1560     return ControlFuture(request.instruction_id, response)
   1561 

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/sdk_worker.py in do_instruction(self, request)
    413       # E.g. if register is set, this will call self.register(request.register))
    414       return getattr(self, request_type)(
--> 415           getattr(request, request_type), request.instruction_id)
    416     else:
    417       raise NotImplementedError

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/sdk_worker.py in process_bundle(self, request, instruction_id)
    448         with self.maybe_profile(instruction_id):
    449           delayed_applications, requests_finalization = (
--> 450               bundle_processor.process_bundle(instruction_id))
    451           monitoring_infos = bundle_processor.monitoring_infos()
    452           monitoring_infos.extend(self.state_cache_metrics_fn())

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/bundle_processor.py in process_bundle(self, instruction_id)
    837         for data in data_channel.input_elements(instruction_id,
    838                                                 expected_transforms):
--> 839           input_op_by_transform_id[data.transform_id].process_encoded(data.data)
    840 
    841       # Finish all operations.

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/bundle_processor.py in process_encoded(self, encoded_windowed_values)
    214       decoded_value = self.windowed_coder_impl.decode_from_stream(
    215           input_stream, True)
--> 216       self.output(decoded_value)
    217 
    218   def try_split(self, fraction_of_remainder, total_buffer_size):

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.Operation.output()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.Operation.output()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.SingletonConsumerSet.receive()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.DoOperation.process()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/worker/operations.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.worker.operations.DoOperation.process()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.DoFnRunner.process()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.DoFnRunner._reraise_augmented()

/usr/local/lib/python3.6/dist-packages/future/utils/__init__.py in raise_with_traceback(exc, traceback)
    417         if traceback == Ellipsis:
    418             _, _, traceback = sys.exc_info()
--> 419         raise exc.with_traceback(traceback)
    420 
    421 else:

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.DoFnRunner.process()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.PerWindowInvoker.invoke_process()

/usr/local/lib/python3.6/dist-packages/apache_beam/runners/common.cpython-36m-x86_64-linux-gnu.so in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window()

/usr/local/lib/python3.6/dist-packages/apache_beam/io/iobase.py in process(self, element, init_result)
   1080     for e in bundle[1]:  # values
   1081       writer.write(e)
-> 1082     return [window.TimestampedValue(writer.close(), timestamp.MAX_TIMESTAMP)]
   1083 
   1084 

/usr/local/lib/python3.6/dist-packages/apache_beam/io/filebasedsink.py in close(self)
    421 
    422   def close(self):
--> 423     self.sink.close(self.temp_handle)
    424     return self.temp_shard_path

/usr/local/lib/python3.6/dist-packages/apache_beam/io/parquetio.py in close(self, writer)
    536   def close(self, writer):
    537     if len(self._buffer[0]) > 0:
--> 538       self._flush_buffer()
    539     if self._record_batches_byte_size > 0:
    540       self._write_batches(writer)

/usr/local/lib/python3.6/dist-packages/apache_beam/io/parquetio.py in _flush_buffer(self)
    568     for x in arrays:
    569       for b in x.buffers():
--> 570         size = size + b.size
    571     self._record_batches_byte_size = self._record_batches_byte_size + size

AttributeError: 'NoneType' object has no attribute 'size' [while running 'train/Save to parquet/Write/WriteImpl/WriteBundles']
``` 
 I have seen that somebody is hard working on easierly loadable wikipedia. #129 
Maybe I should wait a few days for that version ?