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Before deployment, two steps require confirmation.
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- Environment of software and hardware should meet the requirements. Please refer to FastDeploy Environment Requirements.
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- Based on the develop environment, download the precompiled deployment library and samples code. Please refer to FastDeploy Precompiled Library.
This directory provides deployment examples that seq_cls_inferve.py fast finish text classification tasks on CPU/GPU.
The following example shows how to employ FastDeploy library to complete C++ predictive deployment of ERNIE 3.0 Medium model on AFQMC dataset of CLUE Benchmark for text classification tasks.FastDeploy version 0.7.0 or above is required to support this model(x.x.x>=0.7.0) )
mkdir build
cd build
# Download FastDeploy precompiled library. Uses can choose proper version in the `FastDeploy Precompiled Library`mentioned above.
wget https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-linux-x64-x.x.x.tgz
tar xvf fastdeploy-linux-x64-x.x.x.tgz
cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-linux-x64-x.x.x
make -j
# Download the fine-tuned ERNIE 3.0 models for the AFQMC dataset and the word lists.
wget https://bj.bcebos.com/fastdeploy/models/ernie-3.0/ernie-3.0-medium-zh-afqmc.tgz
tar xvfz ernie-3.0-medium-zh-afqmc.tgz
# CPU Inference
./seq_cls_infer_demo --device cpu --model_dir ernie-3.0-medium-zh-afqmc
# GPU Inference
./seq_cls_infer_demo --device gpu --model_dir ernie-3.0-medium-zh-afqmc
# KunlunXin XPU Inference
./seq_cls_infer_demo --device kunlunxin --model_dir ernie-3.0-medium-zh-afqmcThe result returned after running is as follows：
[INFO] /paddle/FastDeploy/examples/text/ernie-3.0/cpp/seq_cls_infer.cc(93)::CreateRuntimeOption model_path = ernie-3.0-medium-zh-afqmc/infer.pdmodel, param_path = ernie-3.0-medium-zh-afqmc/infer.pdiparams
[INFO] fastdeploy/runtime.cc(469)::Init Runtime initialized with Backend::ORT in Device::CPU.
Batch id: 0, example id: 0, sentence 1: 花呗收款额度限制, sentence 2: 收钱码，对花呗支付的金额有限制吗, label: 1, confidence: 0.581852
Batch id: 1, example id: 0, sentence 1: 花呗支持高铁票支付吗, sentence 2: 为什么友付宝不支持花呗付款, label: 0, confidence: 0.997921seq_cls_infer_demo supports more command-line arguments in addition to the preceding example. The following is a description of every command-line argument:
| Parameter | Parameter Description |
|---|---|
| --model_dir | Specify the directory where the model is to be deployed |
| --batch_size | Maximum measurable batch size, default 1 |
| --max_length | Maximum sequence length, default 128 |
| --device | Running devices, optional range: ['cpu', 'gpu'], default 'cpu' |
| --backend | Supported inference backend, optional range: ['onnx_runtime', 'paddle', 'openvino', 'tensorrt', 'paddle_tensorrt']，default'onnx_runtime' |
| --use_fp16 | Whether to use FP16 mode for inference. Enabled when using tensorrt and paddle_tensorrt backend, and default is False |