Split a dataset created by Tensorflow dataset API in to Train and Test?

Question

Does anyone know how to split a dataset created by the dataset API (tf.data.Dataset) in Tensorflow into Test and Train?

Answer 1

@ted's answer will cause some overlap. Try this.

train_ds_size = int(0.64 * full_ds_size)
valid_ds_size = int(0.16 * full_ds_size)

train_ds = full_ds.take(train_ds_size)
remaining = full_ds.skip(train_ds_size)  
valid_ds = remaining.take(valid_ds_size)
test_ds = remaining.skip(valid_ds_size)

use code below to test.

tf.enable_eager_execution()

dataset = tf.data.Dataset.range(100)

train_size = 20
valid_size = 30
test_size = 50

train = dataset.take(train_size)
remaining = dataset.skip(train_size)
valid = remaining.take(valid_size)
test = remaining.skip(valid_size)

for i in train:
    print(i)

for i in valid:
    print(i)

for i in test:
    print(i)