[bugfix] fix streaming

[Jintao-Huang]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @Jintao-Huang, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request implements a bug fix related to streaming dataset processing by refining the management of cache file names during dataset mapping operations. The changes ensure that cache_file_name is applied conditionally and scoped correctly within map_kwargs for HfDataset instances, which helps prevent potential issues with caching behavior in streaming contexts and improves the robustness of data preprocessing.

Highlights

• Conditional Cache File Handling: The cache_file_name parameter is now conditionally added to map_kwargs only when the dataset is an HfDataset and does not already have cache files, ensuring more precise control over caching behavior.
• Scoped Cache File Usage: After each dataset.map operation where cache_file_name was added to map_kwargs, it is explicitly removed from map_kwargs to prevent it from unintentionally affecting subsequent mapping operations.
• Removal of Global Cache File Initialization: The initial global assignment of cache_file_name = None was removed, reinforcing the localized and conditional management of cache file names within the mapping logic.

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[gemini-code-assist]

Code Review

This pull request addresses a bug with streaming datasets by adding a check to ensure caching logic is only applied to HfDataset instances, which correctly avoids errors with IterableDataset. The implementation is sound, but I've identified a small area of code duplication. My feedback includes a suggestion to refactor this duplicated logic to enhance code maintainability.

[gemini-code-assist]

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)