Datasets:

bertin-project

/

mc4-sampling

like 10

Stacktrace provided below:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[2], line 1
----> 1 mc4random = load_dataset(
      2     "bertin-project/mc4-sampling", "es",
      3     split="train",
      4     streaming=True,
      5     sampling_method="random",
      6     factor=0.5,
      7 )

File ~/.conda/envs/sample_env/lib/python3.9/site-packages/datasets/load.py:1735, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, num_proc, **config_kwargs)
   1732 ignore_verifications = ignore_verifications or save_infos
   1734 # Create a dataset builder
-> 1735 builder_instance = load_dataset_builder(
   1736     path=path,
   1737     name=name,
   1738     data_dir=data_dir,
   1739     data_files=data_files,
   1740     cache_dir=cache_dir,
   1741     features=features,
   1742     download_config=download_config,
   1743     download_mode=download_mode,
   1744     revision=revision,
   1745     use_auth_token=use_auth_token,
   1746     **config_kwargs,
   1747 )
   1749 # Return iterable dataset in case of streaming
   1750 if streaming:

File ~/.conda/envs/sample_env/lib/python3.9/site-packages/datasets/load.py:1519, in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, use_auth_token, **config_kwargs)
   1516     raise ValueError(error_msg)
   1518 # Instantiate the dataset builder
-> 1519 builder_instance: DatasetBuilder = builder_cls(
   1520     cache_dir=cache_dir,
   1521     config_name=config_name,
   1522     data_dir=data_dir,
   1523     data_files=data_files,
   1524     hash=hash,
   1525     features=features,
   1526     use_auth_token=use_auth_token,
   1527     **builder_kwargs,
   1528     **config_kwargs,
   1529 )
   1531 return builder_instance

File ~/.cache/huggingface/modules/datasets_modules/datasets/bertin-project--mc4-sampling/ae7065df866e6fa45f5bdf929ecc5400934c9d2d9dd5db39393d47a8459048b5/mc4-sampling.py:316, in Mc4Sampling.__init__(self, writer_batch_size, *args, **kwargs)
    311             self.should_keep_doc = self._should_keep_doc_step
    312 init_kwargs = {
    313     prop: kwargs.get(prop)
    314     for prop in ("name", "version", "data_dir", "data_files", "description")
    315 }
--> 316 super().__init__(*args, writer_batch_size=writer_batch_size, **init_kwargs)

File ~/.conda/envs/sample_env/lib/python3.9/site-packages/datasets/builder.py:1357, in GeneratorBasedBuilder.__init__(self, writer_batch_size, *args, **kwargs)
   1356 def __init__(self, *args, writer_batch_size=None, **kwargs):
-> 1357     super().__init__(*args, **kwargs)
   1358     # Batch size used by the ArrowWriter
   1359     # It defines the number of samples that are kept in memory before writing them
   1360     # and also the length of the arrow chunks
   1361     # None means that the ArrowWriter will use its default value
   1362     self._writer_batch_size = writer_batch_size or self.DEFAULT_WRITER_BATCH_SIZE

File ~/.conda/envs/sample_env/lib/python3.9/site-packages/datasets/builder.py:322, in DatasetBuilder.__init__(self, cache_dir, config_name, hash, base_path, info, features, use_auth_token, repo_id, data_files, data_dir, name, **config_kwargs)
    320 if data_dir is not None:
    321     config_kwargs["data_dir"] = data_dir
--> 322 self.config, self.config_id = self._create_builder_config(
    323     config_name=config_name,
    324     custom_features=features,
    325     **config_kwargs,
    326 )
    328 # prepare info: DatasetInfo are a standardized dataclass across all datasets
    329 # Prefill datasetinfo
    330 if info is None:

File ~/.conda/envs/sample_env/lib/python3.9/site-packages/datasets/builder.py:475, in DatasetBuilder._create_builder_config(self, config_name, custom_features, **config_kwargs)
    473     if "version" not in config_kwargs and hasattr(self, "VERSION") and self.VERSION:
    474         config_kwargs["version"] = self.VERSION
--> 475     builder_config = self.BUILDER_CONFIG_CLASS(**config_kwargs)
    477 # otherwise use the config_kwargs to overwrite the attributes
    478 else:
    479     builder_config = copy.deepcopy(builder_config)

TypeError: __init__() missing 1 required keyword-only argument: 'languages'

Note: Including "languages" in the init_kwargs at https://huggingface.co/datasets/bertin-project/mc4-sampling/blob/main/mc4-sampling.py#L314 seems to solve the problem (kinda), as long as "languages" kwarg is passed in the load_dataset call with a single entry:

    311             self.should_keep_doc = self._should_keep_doc_step
    312 init_kwargs = {
    313     prop: kwargs.get(prop)
    314     for prop in ("name", "version", "data_dir", "data_files", "description", "languages")
    315 }
    316 super().__init__(*args, writer_batch_size=writer_batch_size, **init_kwargs)

Modified call:

mc4random = load_dataset(
    "bertin-project/mc4-sampling", languages=["es"],
    split="train",
    streaming=True,
    sampling_method="random",
    factor=0.5,
)