All DatasetBuilders expose various data subsets defined as tfds.Splits (typically tfds.Split.TRAIN and tfds.Split.TEST). A given dataset's splits are defined in tfds.DatasetBuilder.info.splits and are accessible through tfds.load and tfds.DatasetBuilder.as_dataset, both of which take split= as a keyword argument.

tfds enables you to further manipulate splits by combining them or subsplitting them up. The resulting splits can be passed to tfds.load or tfds.DatasetBuilder.as_dataset.

Add splits together

combined_split = tfds.Split.TRAIN + tfds.Split.TEST

ds = tfds.load("mnist", split=combined_split)

Note that a special tfds.Split.ALL keyword exists to merge all splits together:

# Ds will iterate over test, train and validation merged together
ds = tfds.load("mnist", split=tfds.Split.ALL)


You have 3 options for how to get a thinner slice of the data than the base splits, all based on tfds.Split.subsplit.

Specify number of subsplits

train_half_1, train_half_2 = tfds.Split.TRAIN.subsplit(2)

dataset = tfds.load("mnist", split=train_half_1)

Specify a percentage slice

first_10_percent = tfds.Split.TRAIN.subsplit(tfds.percent[:10])
last_2_percent = tfds.Split.TRAIN.subsplit(tfds.percent[-2:])
middle_50_percent = tfds.Split.TRAIN.subsplit(tfds.percent[25:75])

dataset = tfds.load("mnist", split=middle_50_percent)

Specify a weighting

half, quarter1, quarter2 = tfds.Split.TRAIN.subsplit([2, 1, 1])

dataset = tfds.load("mnist", split=half)

Composing split adding and subsplitting

It's possible to compose the above operations:

# Half of the TRAIN split plus the TEST split
split = tfds.Split.TRAIN.subsplit(tfds.percent[:50]) + tfds.Split.TEST

# Split the combined TRAIN and TEST splits into 2
first_half, second_half = (tfds.Split.TRAIN + tfds.Split.TEST).subsplit(2)

Note that a split cannot be added twice, and subsplitting can only happen once. For example, these are invalid:

# INVALID! TRAIN included twice
split = tfds.Split.TRAIN.subsplit(tfds.percent[:25]) + tfds.Split.TRAIN

# INVALID! Subsplit of subsplit
split = tfds.Split.TRAIN.subsplit(tfds.percent[0:25]).subsplit(2)

# INVALID! Subsplit of subsplit
split = (tfds.Split.TRAIN.subsplit(tfds.percent[:25]) +

Dataset using non conventional named split

For dataset using splits not in tfds.Split.{TRAIN,VALIDATION,TEST}, you can still use the subsplit API by defining the custom named split with tfds.Split('custom_split'). For instance:

split = tfds.Split('test2015') + tfds.Split.TEST
ds = tfds.load('coco2014', split= split)