tf.data.experimental.Counter | TensorFlow v2.16.1 (original) (raw)

tf.data.experimental.Counter

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Creates a Dataset that counts from start in steps of size step. (deprecated)

tf.data.experimental.Counter(
    start=0,
    step=1,
    dtype=tf.dtypes.int64
)

Used in the notebooks

Used in the guide	Used in the tutorials
tf.data: Build TensorFlow input pipelines	Data augmentation

Unlike tf.data.Dataset.range which will stop at some ending number,Counter will produce elements indefinitely.

dataset = tf.data.experimental.Counter().take(5) list(dataset.as_numpy_iterator()) [0, 1, 2, 3, 4] dataset.element_spec TensorSpec(shape=(), dtype=tf.int64, name=None) dataset = tf.data.experimental.Counter(dtype=tf.int32) dataset.element_spec TensorSpec(shape=(), dtype=tf.int32, name=None) dataset = tf.data.experimental.Counter(start=2).take(5) list(dataset.as_numpy_iterator()) [2, 3, 4, 5, 6] dataset = tf.data.experimental.Counter(start=2, step=5).take(5) list(dataset.as_numpy_iterator()) [2, 7, 12, 17, 22] dataset = tf.data.experimental.Counter(start=10, step=-1).take(5) list(dataset.as_numpy_iterator()) [10, 9, 8, 7, 6]

Args
start	(Optional.) The starting value for the counter. Defaults to 0.
step	(Optional.) The step size for the counter. Defaults to 1.
dtype	(Optional.) The data type for counter elements. Defaults totf.int64.

Returns
A Dataset of scalar dtype elements.

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Last updated 2024-04-26 UTC.