Bump datasets from 3.2.0 to 3.3.2

[dependabot]

Bumps datasets from 3.2.0 to 3.3.2.

Release notes

Sourced from datasets's releases.

3.3.2

Bug fixes

• Attempt to fix multiprocessing hang by closing and joining the pool before termination by @​dakinggg in huggingface/datasets#7411
• Gracefully cancel async tasks by @​lhoestq in huggingface/datasets#7414

Other general improvements

• Update use_with_pandas.mdx: to_pandas() correction in last section by @​ibarrien in huggingface/datasets#7407
• Fix a typo in arrow_dataset.py by @​jingedawang in huggingface/datasets#7402

New Contributors

• @​dakinggg made their first contribution in huggingface/datasets#7411
• @​ibarrien made their first contribution in huggingface/datasets#7407
• @​jingedawang made their first contribution in huggingface/datasets#7402

Full Changelog: huggingface/datasets@3.3.1...3.3.2

3.3.1

Bug fixes

• Fix filter speed regression by @​lhoestq in huggingface/datasets#7408

Full Changelog: huggingface/datasets@3.3.0...3.3.1

3.3.0

Dataset Features

• Support async functions in map() by @​lhoestq in huggingface/datasets#7384

  • Especially useful to download content like images or call inference APIs

  prompt = "Answer the following question: {question}. You should think step by step."
  async def ask_llm(example):
      return await query_model(prompt.format(question=example["question"]))
  ds = ds.map(ask_llm)

• Add repeat method to datasets by @​alex-hh in huggingface/datasets#7198

  ds = ds.repeat(10)

• Support faster processing using pandas or polars functions in IterableDataset.map() by @​lhoestq in huggingface/datasets#7370

  • Add support for "pandas" and "polars" formats in IterableDatasets
  • This enables optimized data processing using pandas or polars functions with zero-copy, e.g.

  ds = load_dataset("ServiceNow-AI/R1-Distill-SFT", "v0", split="train", streaming=True)
  ds = ds.with_format("polars")
  expr = pl.col("solution").str.extract("boxed\\{(.*)\\}").alias("value_solution")
  ds = ds.map(lambda df: df.with_columns(expr), batched=True)

• Apply formatting after iter_arrow to speed up format -> map, filter for iterable datasets by @​alex-hh in huggingface/datasets#7207

... (truncated)

Commits

• b37230c Release: 3.3.2 (#7416)
• c33c8bc Fix a typo in arrow_dataset.py (#7402)
• b2887eb Update use_with_pandas.mdx: to_pandas() correction in last section (#7407)
• cd67cf3 Gracefully cancel async tasks (#7414)
• b7fb17e Attempt to fix multiprocessing hang by closing and joining the pool before te...
• a2e17c4 Set dev version (#7410)
• 4ead6ec Release: 3.3.1 (#7409)
• 704704d Fix filter speed regression (#7408)
• de062f0 set dev version (#7401)
• e9dae36 Release: 3.3.0 (#7398)
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