tf.raw_ops.RangeDataset
Stay organized with collections
Save and categorize content based on your preferences.
Creates a dataset with a range of values. Corresponds to python's xrange.
tf.raw_ops.RangeDataset(
start, stop, step, output_types, output_shapes, name=None
)
Args |
|---|
start
|
A Tensor of type int64.
corresponds to start in python's xrange().
|
stop
|
A Tensor of type int64.
corresponds to stop in python's xrange().
|
step
|
A Tensor of type int64.
corresponds to step in python's xrange().
|
output_types
|
A list of tf.DTypes that has length >= 1.
|
output_shapes
|
A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.
|
name
|
A name for the operation (optional).
|
Returns |
|---|
A Tensor of type variant.
|
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2021-02-18 UTC.
[null,null,["Last updated 2021-02-18 UTC."],[],[],null,["# tf.raw_ops.RangeDataset\n\n\u003cbr /\u003e\n\nCreates a dataset with a range of values. Corresponds to python's xrange.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.raw_ops.RangeDataset`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/RangeDataset)\n\n\u003cbr /\u003e\n\n tf.raw_ops.RangeDataset(\n start, stop, step, output_types, output_shapes, name=None\n )\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-----------------|--------------------------------------------------------------------------------------------------------------|\n| `start` | A `Tensor` of type `int64`. corresponds to start in python's xrange(). |\n| `stop` | A `Tensor` of type `int64`. corresponds to stop in python's xrange(). |\n| `step` | A `Tensor` of type `int64`. corresponds to step in python's xrange(). |\n| `output_types` | A list of `tf.DTypes` that has length `\u003e= 1`. |\n| `output_shapes` | A list of shapes (each a [`tf.TensorShape`](../../tf/TensorShape) or list of `ints`) that has length `\u003e= 1`. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor` of type `variant`. ||\n\n\u003cbr /\u003e"]]
