44 lines
1.7 KiB
Markdown
44 lines
1.7 KiB
Markdown
<!---
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Copyright 2021 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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-->
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# Bart + Beam Search to ONNX
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Author: [@fatcat-z](https://github.com/fatcat-z)
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This folder contains an example of exporting Bart + Beam Search generation (`BartForConditionalGeneration`) to ONNX.
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Beam Search contains a for-loop workflow, so we need to make them TorchScript-compatible for exporting to ONNX. This example shows how to make a Bart model be TorchScript-compatible by wrapping up it into a new model. In addition, some changes were made to the `beam_search()` function to make it TorchScript-compatible.
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## How to run the example
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To make sure you can successfully run the latest versions of the example scripts, you have to **install the library from source** and install some example-specific requirements. To do this, execute the following steps in a new virtual environment:
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```bash
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git clone https://github.com/huggingface/transformers
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cd transformers
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pip install '.[onnxruntime]'
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```
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Then cd in this example folder and run
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```bash
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pip install -r requirements.txt
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```
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Now you can run the example command below to get the example ONNX file:
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```bash
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python run_onnx_exporter.py --model_name_or_path facebook/bart-base
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```
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