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[bugfix] fix streaming #6104

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merged 1 commit into from
Oct 13, 2025
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[bugfix] fix streaming #6104

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18 changes: 8 additions & 10 deletions swift/llm/dataset/preprocessor/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -314,7 +314,6 @@ def __call__(
dataset = sample_dataset(dataset, self.dataset_sample, True, self.random_state)

map_kwargs = {'batched': True, 'batch_size': batch_size}
cache_file_name = None
if isinstance(dataset, HfDataset):
if not load_from_cache_file and is_dist() and not is_master():
load_from_cache_file = True
Expand All @@ -326,29 +325,28 @@ def __call__(
dataset = RowPreprocessor.get_features_dataset(dataset)
if 'solution' in dataset.features:
with safe_ddp_context(None, True):
if not dataset.cache_files:
cache_file_name = os.path.join(get_cache_dir(), 'datasets', 'map_cache',
f'{dataset._fingerprint}.arrow')
dataset = dataset.map(
lambda x: {'__#solution': x['solution']}, **map_kwargs, cache_file_name=cache_file_name)
if isinstance(dataset, HfDataset) and not dataset.cache_files:
map_kwargs['cache_file_name'] = os.path.join(get_cache_dir(), 'datasets', 'map_cache',
f'{dataset._fingerprint}.arrow')
Comment on lines +328 to +330
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medium

This logic for setting cache_file_name is duplicated on lines 340-342. To improve code clarity and maintainability, you could extract this repeated logic into a helper function. This would centralize the caching logic, making it easier to manage and modify in the future.

For example, you could introduce a helper function:

def _set_cache_file_name_in_kwargs(dataset, kwargs):
    if isinstance(dataset, HfDataset) and not dataset.cache_files:
        kwargs['cache_file_name'] = os.path.join(
            get_cache_dir(), 'datasets', 'map_cache', f'{dataset._fingerprint}.arrow')

And then call it in both places:

_set_cache_file_name_in_kwargs(dataset, map_kwargs)

dataset = dataset.map(lambda x: {'__#solution': x['solution']}, **map_kwargs)
map_kwargs.pop('cache_file_name', None)
dataset = self._rename_columns(dataset)
dataset = self.prepare_dataset(dataset)
dataset = self._cast_pil_image(dataset)

ignore_max_length_error = True if isinstance(dataset, HfDataset) and num_proc > 1 else False
with self._patch_arrow_writer(), safe_ddp_context(None, True):
try:
if not dataset.cache_files:
cache_file_name = os.path.join(get_cache_dir(), 'datasets', 'map_cache',
f'{dataset._fingerprint}.arrow')
if isinstance(dataset, HfDataset) and not dataset.cache_files:
map_kwargs['cache_file_name'] = os.path.join(get_cache_dir(), 'datasets', 'map_cache',
f'{dataset._fingerprint}.arrow')
dataset_mapped = dataset.map(
self.batched_preprocess,
fn_kwargs={
'strict': strict,
'ignore_max_length_error': ignore_max_length_error
},
remove_columns=list(dataset.features.keys()),
cache_file_name=cache_file_name,
**map_kwargs)
except NotImplementedError:
pass
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