Datasets:

Salesforce

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GiftEval

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I'm getting an error when I try to load the dataset - stack trace below. There's a similar error in the huggingface data preview; see attached image.

from datasets import load_dataset
load_dataset('Salesforce/GiftEval')

Downloading data: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 58/58 [02:14<00:00, 2.32s/files]
Generating train split: 323 examples [00:00, 1688.01 examples/s]Failed to read file '/Users/geoff/.cache/huggingface/hub/datasets--Salesforce--GiftEval/snapshots/930b5513aed532a99dc260c38893223738858044/M_DENSE/D/data-00000-of-00001.arrow' with error <class 'datasets.table.CastError'>: Couldn't cast
item_id: string
start: timestamp[s]
freq: string
target: list<item: float>
child 0, item: float
past_feat_dynamic_real: fixed_size_list<item: list<item: float>>[7]
child 0, item: list<item: float>
child 0, item: float
-- schema metadata --
huggingface: '{"info": {"features": {"item_id": {"dtype": "string", "_typ' + 347
to
{'item_id': Value(dtype='string', id=None), 'start': Value(dtype='timestamp[s]', id=None), 'freq': Value(dtype='string', id=None), 'target': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None)}
because column names don't match
Generating train split: 969 examples [00:00, 4605.30 examples/s]

CastError Traceback (most recent call last)
File /opt/anaconda3/envs/gifteval/lib/python3.12/site-packages/datasets/builder.py:1854, in ArrowBasedBuilder._prepare_split_single(self, gen_kwargs, fpath, file_format, max_shard_size, job_id)
1853 _time = time.time()
-> 1854 for _, table in generator:
1855 if max_shard_size is not None and writer._num_bytes > max_shard_size:

File /opt/anaconda3/envs/gifteval/lib/python3.12/site-packages/datasets/packaged_modules/arrow/arrow.py:76, in Arrow.generate_tables(self, files)
73 # Uncomment for debugging (will print the Arrow table size and elements)
74 # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
75 # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
---> 76 yield f"{file_idx}{batch_idx}", self._cast_table(pa_table)
77 except ValueError as e:

File /opt/anaconda3/envs/gifteval/lib/python3.12/site-packages/datasets/packaged_modules/arrow/arrow.py:59, in Arrow._cast_table(self, pa_table)
56 if self.info.features is not None:
57 # more expensive cast to support nested features with keys in a different order
58 # allows str <-> int/float or str to Audio for example
---> 59 pa_table = table_cast(pa_table, self.info.features.arrow_schema)
60 return pa_table

File /opt/anaconda3/envs/gifteval/lib/python3.12/site-packages/datasets/table.py:2292, in table_cast(table, schema)
2291 if table.schema != schema:
-> 2292 return cast_table_to_schema(table, schema)
2293 elif table.schema.metadata != schema.metadata:

File /opt/anaconda3/envs/gifteval/lib/python3.12/site-packages/datasets/table.py:2240, in cast_table_to_schema(table, schema)
2239 if not table_column_names <= set(schema.names):
-> 2240 raise CastError(
2241 f"Couldn't cast\n{_short_str(table.schema)}\nto\n{_short_str(features)}\nbecause column names don't match",
2242 table_column_names=table.column_names,
2243 requested_column_names=list(features),
2244 )
2245 arrays = [
2246 cast_array_to_feature(
2247 table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
(...)
2250 for name, feature in features.items()
2251 ]

CastError: Couldn't cast
item_id: string
start: timestamp[s]
freq: string
target: list<item: float>
child 0, item: float
past_feat_dynamic_real: fixed_size_list<item: list<item: float>>[7]
child 0, item: list<item: float>
child 0, item: float
-- schema metadata --
huggingface: '{"info": {"features": {"item_id": {"dtype": "string", "_typ' + 347
to
{'item_id': Value(dtype='string', id=None), 'start': Value(dtype='timestamp[s]', id=None), 'freq': Value(dtype='string', id=None), 'target': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None)}
because column names don't match

The above exception was the direct cause of the following exception:

DatasetGenerationError Traceback (most recent call last)
Cell In[6], line 1
----> 1 load_dataset('Salesforce/GiftEval')

File /opt/anaconda3/envs/gifteval/lib/python3.12/site-packages/datasets/load.py:2154, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, keep_in_memory, save_infos, revision, token, streaming, num_proc, storage_options, trust_remote_code, **config_kwargs)
2151 return builder_instance.as_streaming_dataset(split=split)
2153 # Download and prepare data
-> 2154 builder_instance.download_and_prepare(
2155 download_config=download_config,
2156 download_mode=download_mode,
2157 verification_mode=verification_mode,
2158 num_proc=num_proc,
2159 storage_options=storage_options,
2160 )
2162 # Build dataset for splits
2163 keep_in_memory = (
2164 keep_in_memory if keep_in_memory is not None else is_small_dataset(builder_instance.info.dataset_size)
2165 )

File /opt/anaconda3/envs/gifteval/lib/python3.12/site-packages/datasets/builder.py:924, in DatasetBuilder.download_and_prepare(self, output_dir, download_config, download_mode, verification_mode, dl_manager, base_path, file_format, max_shard_size, num_proc, storage_options, **download_and_prepare_kwargs)
922 if num_proc is not None:
923 prepare_split_kwargs["num_proc"] = num_proc
--> 924 self._download_and_prepare(
925 dl_manager=dl_manager,
926 verification_mode=verification_mode,
927 **prepare_split_kwargs,
928 **download_and_prepare_kwargs,
929 )
930 # Sync info
931 self.info.dataset_size = sum(split.num_bytes for split in self.info.splits.values())

File /opt/anaconda3/envs/gifteval/lib/python3.12/site-packages/datasets/builder.py:1000, in DatasetBuilder._download_and_prepare(self, dl_manager, verification_mode, **prepare_split_kwargs)
996 split_dict.add(split_generator.split_info)
998 try:
999 # Prepare split will record examples associated to the split
-> 1000 self._prepare_split(split_generator, **prepare_split_kwargs)
1001 except OSError as e:
1002 raise OSError(
1003 "Cannot find data file. "
1004 + (self.manual_download_instructions or "")
1005 + "\nOriginal error:\n"
1006 + str(e)
1007 ) from None

File /opt/anaconda3/envs/gifteval/lib/python3.12/site-packages/datasets/builder.py:1741, in ArrowBasedBuilder._prepare_split(self, split_generator, file_format, num_proc, max_shard_size)
1739 job_id = 0
1740 with pbar:
-> 1741 for job_id, done, content in self._prepare_split_single(
1742 gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
1743 ):
1744 if done:
1745 result = content

File /opt/anaconda3/envs/gifteval/lib/python3.12/site-packages/datasets/builder.py:1897, in ArrowBasedBuilder._prepare_split_single(self, gen_kwargs, fpath, file_format, max_shard_size, job_id)
1895 if isinstance(e, DatasetGenerationError):
1896 raise
-> 1897 raise DatasetGenerationError("An error occurred while generating the dataset") from e
1899 yield job_id, True, (total_num_examples, total_num_bytes, writer._features, num_shards, shard_lengths)

DatasetGenerationError: An error occurred while generating the dataset