tf.nn.max_pool1d
Stay organized with collections
Save and categorize content based on your preferences.
Performs the max pooling on the input.
tf.nn.max_pool1d(
input, ksize, strides, padding, data_format='NWC', name=None
)
Note internally this op reshapes and uses the underlying 2d operation.
Args |
|---|
input
|
A 3-D Tensor of the format specified by data_format.
|
ksize
|
An int or list of ints that has length 1 or 3. The size of the
window for each dimension of the input tensor.
|
strides
|
An int or list of ints that has length 1 or 3. The stride of
the sliding window for each dimension of the input tensor.
|
padding
|
Either the string "SAME" or "VALID" indicating the type of
padding algorithm to use, or a list indicating the explicit paddings at
the start and end of each dimension. See
here
for more information. When explicit padding is used and data_format is
"NWC", this should be in the form [[0, 0], [pad_left, pad_right], [0,
0]]. When explicit padding used and data_format is "NCW", this should
be in the form [[0, 0], [0, 0], [pad_left, pad_right]]. When using
explicit padding, the size of the paddings cannot be greater than the
sliding window size.
|
data_format
|
An optional string from: "NWC", "NCW". Defaults to "NWC".
|
name
|
A name for the operation (optional).
|
Returns |
|---|
A Tensor of format specified by data_format.
The max pooled output tensor.
|
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 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf.nn.max_pool1d\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/nn_ops.py#L4911-L4966) |\n\nPerforms the max pooling on the input.\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.nn.max_pool1d`](https://www.tensorflow.org/api_docs/python/tf/nn/max_pool1d)\n\n\u003cbr /\u003e\n\n tf.nn.max_pool1d(\n input, ksize, strides, padding, data_format='NWC', name=None\n )\n\nNote internally this op reshapes and uses the underlying 2d operation.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `input` | A 3-D `Tensor` of the format specified by `data_format`. |\n| `ksize` | An int or list of `ints` that has length `1` or `3`. The size of the window for each dimension of the input tensor. |\n| `strides` | An int or list of `ints` that has length `1` or `3`. The stride of the sliding window for each dimension of the input tensor. |\n| `padding` | Either the `string` `\"SAME\"` or `\"VALID\"` indicating the type of padding algorithm to use, or a list indicating the explicit paddings at the start and end of each dimension. See [here](https://www.tensorflow.org/api_docs/python/tf/nn#notes_on_padding_2) for more information. When explicit padding is used and data_format is `\"NWC\"`, this should be in the form `[[0, 0], [pad_left, pad_right], [0, 0]]`. When explicit padding used and data_format is `\"NCW\"`, this should be in the form `[[0, 0], [0, 0], [pad_left, pad_right]]`. When using explicit padding, the size of the paddings cannot be greater than the sliding window size. |\n| `data_format` | An optional string from: \"NWC\", \"NCW\". Defaults to \"NWC\". |\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 format specified by `data_format`. The max pooled output tensor. ||\n\n\u003cbr /\u003e"]]
View source on GitHub