I was trying to download the ‘pass’ image dataset pass | TensorFlow Datasets but I soon realized that it was way to big, so I tried to download only a part of it.
I found on Splits and slicing | TensorFlow Datasets that I could simply use
- Slices: Slices have the same semantic as python slice notation. Slices can be:
- Absolute (
'train[123:450]'
,train[:4000]
): (see note below for caveat about read order) - Percent (
'train[:75%]'
,'train[25%:75%]'
): Divide the full data into 100 even slices. If the data is not divisible by 100, some percent might contain additional examples. - Shard (
train[:4shard]
,train[4shard]
): Select all examples in the requested shard. (seeinfo.splits['train'].num_shards
to get the number of shards of the split)
- Absolute (
so I tried
- ds = tfds.load(‘pass’, split=[‘train[:1%]’])
- ds = tfds.load(‘pass’, split=[‘train[:10]’])
but it seems to completely ignore the commands and try to downoad a huge part of the dataset anyway
Does anybody know how to solve this?
Thanks in advance