huggingface type_error ai_generated true

TypeError: Streaming dataset does not have a known length. Use `len(dataset)` only on non-streaming datasets.

ID: huggingface/datasets-streaming-iterable-dataset-length-error

Also available as: JSON · Markdown · 中文
90%Fix Rate
87%Confidence
1Evidence
2023-02-10First Seen

Version Compatibility

VersionStatusIntroducedDeprecatedNotes
datasets>=2.5.0 active — — —

Root Cause

Calling len() on a streaming (Iterable) dataset which does not support length computation because it is lazily loaded.

generic

中文

对流式（Iterable）数据集调用 len()，该数据集由于是惰性加载而不支持长度计算。

Official Documentation

https://huggingface.co/docs/datasets/en/stream

Workarounds

  1. 95% success Check if the dataset is streaming with `isinstance(dataset, IterableDataset)` before calling len(). Example: `if not isinstance(dataset, IterableDataset): print(len(dataset)) else: print('Length unknown')` 
    Check if the dataset is streaming with `isinstance(dataset, IterableDataset)` before calling len(). Example: `if not isinstance(dataset, IterableDataset): print(len(dataset)) else: print('Length unknown')`
  2. 85% success If you need the length, load the dataset non-streaming only once to get the size, then reload with streaming=True: `length = len(load_dataset('dataset_name', split='train', streaming=False)); dataset = load_dataset('dataset_name', split='train', streaming=True)` 
    If you need the length, load the dataset non-streaming only once to get the size, then reload with streaming=True: `length = len(load_dataset('dataset_name', split='train', streaming=False)); dataset = load_dataset('dataset_name', split='train', streaming=True)`
  3. 70% success Use dataset.n_shards if available (for sharded datasets) to estimate length, or rely on the dataset's metadata if provided by the source. 
    Use dataset.n_shards if available (for sharded datasets) to estimate length, or rely on the dataset's metadata if provided by the source.

中文步骤

  1. Check if the dataset is streaming with `isinstance(dataset, IterableDataset)` before calling len(). Example: `if not isinstance(dataset, IterableDataset): print(len(dataset)) else: print('Length unknown')`
  2. If you need the length, load the dataset non-streaming only once to get the size, then reload with streaming=True: `length = len(load_dataset('dataset_name', split='train', streaming=False)); dataset = load_dataset('dataset_name', split='train', streaming=True)`
  3. Use dataset.n_shards if available (for sharded datasets) to estimate length, or rely on the dataset's metadata if provided by the source.

Dead Ends

Common approaches that don't work:

  1. 70% fail

    This defeats the purpose of streaming (memory efficiency) and may cause OOM for large datasets. Also, the dataset might be too large to fit in memory.

  2. 80% fail

    These methods also rely on known length and will raise similar errors or return None.

  3. 50% fail

    This iterates through the entire dataset, which is slow and defeats streaming benefits; also, for very large datasets it may take hours or cause memory issues.