azure-pipelines.yml

pr:
- main

pool:
  vmImage: ubuntu-latest

variables:
  PYTHON: 'python3.8'
  INC_VER: '1.12'
  IMAGE_NAME: 'neural-compressor'
  IMAGE_TAG: '1.12'
  INC_BRANCH: 'master'

stages:
- stage: Build
  displayName: 'Build and push stage'
  jobs:
  - job: Build
    displayName: 'Build'
    steps:
    - task: Docker@2
      displayName: 'Login to repo'
      inputs:
        command: login
        containerRegistry: inc-internal
        
    - script: docker build --build-arg PYTHON=${PYTHON} --build-arg INC_BRANCH=${INC_BRANCH} -f docker/Dockerfile.devel -t ${IMAGE_NAME}:${IMAGE_TAG} .
      displayName: 'Build Container'

- stage: Tuning
  dependsOn: Build
  displayName: Tuning Pytorch Model
  jobs:
  - job: Quantization
    displayName: Run Tuning
    steps:
      - script: 
          pip install transformers==4.10.0
          pip install -r neural-compressor/examples/pytorch/nlp/huggingface_models/text-classification/quantization/ptq_static/fx/requirements.txt
          pip install torch
        displayName: 'Install requirements'
      - script: 
          python -u neural-compressor/examples/pytorch/nlp/huggingface_models/text-classification/quantization/ptq_static/fx/run_qa.py 
          --model_name_or_path "bert-large-uncased-whole-word-masking-finetuned-squad" 
          --dataset_name "squad" 
          --do_eval 
          --do_train 
          --max_seq_length 128 
          --per_device_eval_batch_size ${batch_size} 
          --no_cuda 
          --output_dir /path/to/checkpoint/dir 
          --tune 
          --overwrite_output_dir 
          --dataloader_drop_last
        displayName: 'Tuning'