Asfiya BaigscatterElements
Table Of Contents
Description
The scatterElements plugin implements the scatter operation described in (https://github.com/rusty1s/pytorch_scatter), in compliance with the ONNX specification for ScatterElements
Note: ScatterElements with reduce="none" is implemented in TRT core, not this plugin.
Structure
This plugin has the plugin creator class ScatterElementsPluginCreator and the plugin class ScatterElementsPlugin which extends IPluginV2DynamicExt.
The ScatterElements plugin consumes the following inputs:
data- T: Tensor of rank r >= 1.indices- Tind: Tensor of int64 indices, of r >= 1 (same rank as input). All index values are expected to be within bounds [-s, s-1] along axis of size s. It is an error if any of the index values are out of bounds.updates- T: Tensor of rank r >=1 (same rank and shape as indices)
The ScatterElements plugin produces the following output:
output- T: Tensor, same shape asdata.
Parameters
The ScatterElements plugin has the following parameters:
| Type | Parameter | Description |
|---|---|---|
int |
axis |
Which axis to scatter on. Default is 0. Negative value means counting dimensions from the back. Accepted range is [-r, r-1] where r = rank(data). |
char |
reduction |
Type of reduction to apply: add, mul, max, min. ‘add’: reduction using the addition operation. ‘mul’: reduction using the multiplication operation.‘max’: reduction using the maximum operation.‘min’: reduction using the minimum operation. |
The following resources provide a deeper understanding of the scatterElements plugin:
License
For terms and conditions for use, reproduction, and distribution, see the TensorRT Software License Agreement documentation.
Changelog
Oct 2023: This is the first release of this README.md file.
Known issues
- Types T=BFLOAT16 and T=INT8 are currently not supported.
- ONNX spec allows Tind=int32 : only INT64 is supported by this plugin