tf.data.experimental.Counter
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Creates a Dataset that counts from start in steps of size step.
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 2021-08-16 UTC.
[null,null,["Last updated 2021-08-16 UTC."],[],[],null,["# tf.data.experimental.Counter\n\n\u003cbr /\u003e\n\n|--------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 1 version](/versions/r1.15/api_docs/python/tf/data/experimental/Counter) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.6.0/tensorflow/python/data/experimental/ops/counter.py#L28-L66) |\n\nCreates a `Dataset` that counts from `start` in steps of size `step`. \n\n tf.data.experimental.Counter(\n start=0, step=1, dtype=tf.dtypes.int64\n )\n\nUnlike [`tf.data.Dataset.range`](../../../tf/data/Dataset#range) which will stop at some ending number,\n`Counter` will produce elements indefinitely. \n\n dataset = tf.data.experimental.Counter().take(5)\n list(dataset.as_numpy_iterator())\n [0, 1, 2, 3, 4]\n dataset.element_spec\n TensorSpec(shape=(), dtype=tf.int64, name=None)\n dataset = tf.data.experimental.Counter(dtype=tf.int32)\n dataset.element_spec\n TensorSpec(shape=(), dtype=tf.int32, name=None)\n dataset = tf.data.experimental.Counter(start=2).take(5)\n list(dataset.as_numpy_iterator())\n [2, 3, 4, 5, 6]\n dataset = tf.data.experimental.Counter(start=2, step=5).take(5)\n list(dataset.as_numpy_iterator())\n [2, 7, 12, 17, 22]\n dataset = tf.data.experimental.Counter(start=10, step=-1).take(5)\n list(dataset.as_numpy_iterator())\n [10, 9, 8, 7, 6]\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------|----------------------------------------------------------------------------------------------|\n| `start` | (Optional.) The starting value for the counter. Defaults to 0. |\n| `step` | (Optional.) The step size for the counter. Defaults to 1. |\n| `dtype` | (Optional.) The data type for counter elements. Defaults to [`tf.int64`](../../../tf#int64). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Dataset` of scalar `dtype` elements. ||\n\n\u003cbr /\u003e"]]
TensorFlow 1 version
View source on GitHub