Storing Datasets in Tar Archives
The format used for WebDataset is standard POSIX tar archives, the same archives used for backup and data distribution. In order to use the format to store training samples for deep learning, we adopt some simple naming conventions:
* datasets are POSIX tar archives
* each training sample consists of adjacent files with the same basename
* shards are numbered consecutively
For example, ImageNet is stored in 1282 separate 100 Mbyte shards with names pythonimagenet-train-000000.tar to imagenet-train-001281.tar, the contents of the first shard are:
```python
-r--r--r-- bigdata/bigdata      3 2020-05-08 21:23 n03991062_24866.cls
-r--r--r-- bigdata/bigdata 108611 2020-05-08 21:23 n03991062_24866.jpg
-r--r--r-- bigdata/bigdata      3 2020-05-08 21:23 n07749582_9506.cls
-r--r--r-- bigdata/bigdata 129044 2020-05-08 21:23 n07749582_9506.jpg
-r--r--r-- bigdata/bigdata      3 2020-05-08 21:23 n03425413_23604.cls