tf.raw_ops.SkipDataset
Stay organized with collections
Save and categorize content based on your preferences.
Creates a dataset that skips count elements from the input_dataset.
tf.raw_ops.SkipDataset(
input_dataset,
count,
output_types,
output_shapes,
metadata='',
name=None
)
Args |
|---|
input_dataset
|
A Tensor of type variant.
|
count
|
A Tensor of type int64.
A scalar representing the number of elements from the input_dataset
that should be skipped. If count is -1, skips everything.
|
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.
|
metadata
|
An optional string. Defaults to "".
|
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 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tf.raw_ops.SkipDataset\n\n\u003cbr /\u003e\n\nCreates a dataset that skips `count` elements from the `input_dataset`.\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.SkipDataset`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/SkipDataset)\n\n\u003cbr /\u003e\n\n tf.raw_ops.SkipDataset(\n input_dataset,\n count,\n output_types,\n output_shapes,\n metadata='',\n name=None\n )\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-----------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `input_dataset` | A `Tensor` of type `variant`. |\n| `count` | A `Tensor` of type `int64`. A scalar representing the number of elements from the `input_dataset` that should be skipped. If count is -1, skips everything. |\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| `metadata` | An optional `string`. Defaults to `\"\"`. |\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"]]
