How to split a tensorflow dataset into train, test and validation in a Python script?

问题

On a jupyter notebook with Tensorflow-2.0.0, a train-validation-test split of 80-10-10 was performed in this way:

import tensorflow_datasets as tfds
from os import getcwd
splits = tfds.Split.ALL.subsplit(weighted=(80, 10, 10))

filePath = f"{getcwd()}/../tmp2/"
splits, info = tfds.load('fashion_mnist', with_info=True, as_supervised=True, split=splits, data_dir=filePath)

However, when trying to run the same code locally I get the error

AttributeError: type object 'Split' has no attribute 'ALL'

I have seen I can create two sets in this way:

splits, info = tfds.load('fashion_mnist', with_info=True, as_supervised=True, split=['train[:80]','test[80:90]'], data_dir=filePath)

but I do not know how I can add a third set.

回答1:

tfds.Split.ALL.subsplit or tfds.Split.TRAIN.subsplit apparently are deprecated and no longer supported.

Some of the datasets are already split between train and test. In this case I found the following solution (using for example the fashion MNIST dataset):

splits, info = tfds.load('fashion_mnist', with_info=True, as_supervised=True,
split=['train+test[:80]','train+test[80:90]', 'train+test[90:]'],
data_dir=filePath)
(train_examples, validation_examples, test_examples) = splits

来源：https://stackoverflow.com/questions/64451516/how-to-split-a-tensorflow-dataset-into-train-test-and-validation-in-a-python-sc