wehub-resource-sync
68 lines
3.5 KiB
Markdown
68 lines
3.5 KiB
Markdown
# InstanceNormalizationPlugin
|
|
|
|
**Table Of Contents**
|
|
- [Description](#description)
|
|
* [Structure](#structure)
|
|
- [Parameters](#parameters)
|
|
- [Additional resources](#additional-resources)
|
|
- [License](#license)
|
|
- [Changelog](#changelog)
|
|
- [Known issues](#known-issues)
|
|
|
|
## Description
|
|
|
|
> NOTE: `InstanceNormalization_TRT` version 1 is deprecated since TensorRT 10.3. `InstanceNormalization_TRT` version 2 is deprecated since TensorRT 10.12. Please use `InstanceNormalization_TRT` version 3. Alternatively, the native `INormalizationLayer` can also be used as appropriate to replace their functionality.
|
|
|
|
The `InstanceNormalizePlugin` is used for the InstanceNormalization layer, which is generally used in deep learning models that perform image generation. This plugin is based off the [ONNX opset 6 definition](https://github.com/onnx/onnx/blob/master/docs/Operators.md#InstanceNormalization), and is used in any ONNX model that uses this operation.
|
|
|
|
Specifically, given an array of values `x = [x_0, x_1, ..., x_n]` , a scale factor, a bias factor, and an epsilon, the InstanceNormalization of x is `scale * (x-mean) / sqrt(variance + epsilon) + bias` where the mean and variance are computed per instance per channel.
|
|
|
|
### Structure
|
|
|
|
This plugin takes one input and generates one output. The first input is the data from the last layer that is going to be normalized. It has a shape of `[N, C, H, W]`, where `N` is the batch size, `C` is the number of channels, `H` is the height, `W` is the width.
|
|
|
|
The dimensions of the output are exactly the same as the input.
|
|
|
|
## Parameters
|
|
|
|
This plugin consists of the plugin creator class `InstanceNormalizationPluginCreator` and the plugin class `InstanceNormalizationPlugin`. To create the plugin instance, the following parameters are used:
|
|
|
|
| Type | Parameter | Description
|
|
|------------|--------------------------|--------------------------------------------------------
|
|
|`float` |`epsilon` |A small number to prevent being divided by zero during normalization.
|
|
|`Weights *` |`scale` |A pointer to weights which contains information about scale factors for normalization. The definition of `Weights` can be found in the [NvInfer.h](https://docs.nvidia.com/deeplearning/sdk/tensorrt-api/c_api/_nv_infer_8h_source.html) header.
|
|
|`Weights *` |`bias` |A pointer to weights which contains information about the bias values for normalization. The definition of `Weights` can be found in the [NvInfer.h](https://docs.nvidia.com/deeplearning/sdk/tensorrt-api/c_api/_nv_infer_8h_source.html) header.
|
|
|`int` |`relu` |A value used to enable leaky relu activation
|
|
|`float` |`alpha` |A small negative slope for the leaky relu activation
|
|
|
|
|
|
## Additional resources
|
|
|
|
The following resources provide a deeper understanding of the `InstanceNormalizationPlugin` plugin:
|
|
|
|
**Networks**
|
|
- [ONNX Operator Definition](https://github.com/onnx/onnx/blob/master/docs/Operators.md#InstanceNormalization)
|
|
- [Instance Normalization Paper](https://arxiv.org/abs/1607.08022)
|
|
|
|
## License
|
|
|
|
For terms and conditions for use, reproduction, and distribution, see the [TensorRT Software License Agreement](https://docs.nvidia.com/deeplearning/sdk/tensorrt-sla/index.html)
|
|
documentation.
|
|
|
|
|
|
## Changelog
|
|
|
|
May 2025
|
|
Deprecated version 2 of this plugin.
|
|
|
|
July 2024
|
|
Deprecated version 1 of this plugin.
|
|
|
|
September 2019
|
|
This is the first release of this `README.md` file.
|
|
|
|
|
|
## Known issues
|
|
|
|
There are no known issues in this plugin.
|