tf.keras.utils.split_dataset | TensorFlow v2.16.1 (original) (raw)
tf.keras.utils.split_dataset
Splits a dataset into a left half and a right half (e.g. train / test).
tf.keras.utils.split_dataset(
dataset, left_size=None, right_size=None, shuffle=False, seed=None
)
| Args | |
|---|---|
| dataset | A tf.data.Dataset, a torch.utils.data.Dataset object, or a list/tuple of arrays with the same length. |
| left_size | If float (in the range [0, 1]), it signifies the fraction of the data to pack in the left dataset. If integer, it signifies the number of samples to pack in the left dataset. IfNone, defaults to the complement to right_size. Defaults to None. |
| right_size | If float (in the range [0, 1]), it signifies the fraction of the data to pack in the right dataset. If integer, it signifies the number of samples to pack in the right dataset. If None, defaults to the complement to left_size. Defaults to None. |
| shuffle | Boolean, whether to shuffle the data before splitting it. |
| seed | A random seed for shuffling. |
| Returns |
|---|
| A tuple of two tf.data.Dataset objects: the left and right splits. |
Example:
data = np.random.random(size=(1000, 4))
left_ds, right_ds = keras.utils.split_dataset(data, left_size=0.8)
int(left_ds.cardinality())
800
int(right_ds.cardinality())
200
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Last updated 2024-06-07 UTC.