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.

Warning: TFDS does not currently guarantee the order of the data on disk when data is generated, so if you regenerate the data, the subsplits may no longer be the same.

Warning: If the total_number_examples % 100 != 0, then remainder examples may not be evenly distributed among subsplits.

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)

Specifying weights

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)