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Lewis Tunstall 2022-01-11 16:07:56 +01:00
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@ -228,9 +228,9 @@ Let's start with the ONNX configuration object. We provide three abstract
classes that you should inherit from, depending on the type of model classes that you should inherit from, depending on the type of model
architecture you wish to export: architecture you wish to export:
* Encoder-based models inherit from [`OnnxConfig`](https://github.com/huggingface/transformers/blob/c4fa908fa98c3d538462c537d29b7613dd71306e/src/transformers/onnx/config.py#L52) * Encoder-based models inherit from [`OnnxConfig`]
* Decoder-based models inherit from [`OnnxConfigWithPast`](https://github.com/huggingface/transformers/blob/c4fa908fa98c3d538462c537d29b7613dd71306e/src/transformers/onnx/config.py#L264) * Decoder-based models inherit from [`OnnxConfigWithPast`]
* Encoder-decoder models inherit from [`OnnxSeq2SeqConfigWithPast`](https://github.com/huggingface/transformers/blob/c4fa908fa98c3d538462c537d29b7613dd71306e/src/transformers/onnx/config.py#L399) * Encoder-decoder models inherit from [`OnnxSeq2SeqConfigWithPast`]
<Tip> <Tip>
@ -401,7 +401,7 @@ to the library, you will need to:
* Implement the ONNX configuration in the corresponding `configuration_<model_name>.py` * Implement the ONNX configuration in the corresponding `configuration_<model_name>.py`
file file
* Include the model architecture and corresponding features in * Include the model architecture and corresponding features in
[`onnx.features.FeatureManager`](https://github.com/huggingface/transformers/blob/c4fa908fa98c3d538462c537d29b7613dd71306e/src/transformers/onnx/features.py#L71) [`~onnx.features.FeatureManager`]
* Add your model architecture to the tests in * Add your model architecture to the tests in
`test_onnx_v2.py` `test_onnx_v2.py`