tf.data.experimental.Counter

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
)

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 to `tf.int64`.

Returns
A `Dataset` of scalar `dtype` elements.

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Last updated 2023-10-06 UTC.

tf.data.experimental.Counter

Args

Returns