Table Of Contents
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.
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.
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:
For terms and conditions for use, reproduction, and distribution, see the TensorRT Software License Agreement documentation.
Oct 2023: This is the first release of this README.md file.
- Types T=BFLOAT16 and T=INT8 are currently not supported.
- ONNX spec allows Tind=int32 : only INT64 is supported by this plugin