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 Dividir y rebanar | TensorFlow Datasets that I could simply use
Slices: Slices have the same semantic as python slice notation. Slices can be:
train[:4000]): (see note below for caveat about read order)
'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.
train[4shard]): Select all examples in the requested shard. (see
info.splits['train'].num_shardsto 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