Liyu Xiao
af2d3fae90
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Modulation Recognition Demo / ria-demo (push) Failing after 30s
127 lines
3.5 KiB
YAML
127 lines
3.5 KiB
YAML
name: Modulation Recognition Demo
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on:
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push:
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branches: [main]
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pull_request:
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branches: [main]
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jobs:
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ria-demo:
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runs-on: ubuntu-latest-2080
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steps:
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- name: Print GPU information
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run: |
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if command -v nvidia-smi &> /dev/null; then
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echo "✅ NVIDIA GPU is available"
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nvidia-smi
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else
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echo "⚠️ No NVIDIA GPU found"
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fi
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- name: Checkout project code
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uses: actions/checkout@v4
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with:
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lfs: true
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: "3.10"
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- name: Install dependencies (incl. RIA Hub utils)
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run: |
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set -e
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python -m pip install --upgrade pip
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echo "Trying to install utils from RIA Hub..."
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if ! pip install \
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--index-url "https://${{ secrets.RIAHUB_USER }}:${{ secrets.RIAHUB_TOKEN }}@git.riahub.ai/api/packages/qoherent/pypi/simple/" \
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utils; then
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echo "RIA Hub install failed, falling back to local wheel..."
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pip install ./wheels/utils-*.whl
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fi
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pip install -r requirements.txt
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- name: 1. Generate Recordings
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run: |
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mkdir -p data/recordings
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PYTHONPATH=. python scripts/dataset_manager/data_gen.py --output-dir data/recordings
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- name: 📦 Compress Recordings
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run: tar -czf recordings.tar.gz -C data/recordings .
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- name: ⬆️ Upload recordings
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uses: actions/upload-artifact@v3
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with:
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name: recordings
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path: recordings.tar.gz
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- name: 2. Build HDF5 Dataset
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run: |
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mkdir -p data/dataset
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PYTHONPATH=. python scripts/dataset_manager/produce_dataset.py
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shell: bash
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- name: ⬆️ Upload Dataset
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uses: actions/upload-artifact@v3
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with:
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name: dataset
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path: data/dataset/**
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- name: 3. Train Model
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env:
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NO_NNPACK: 1
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PYTORCH_NO_NNPACK: 1
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run: |
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mkdir -p checkpoint_files
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PYTHONPATH=. python scripts/model_builder/train.py 2>/dev/null
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- name: 4. Plot Model
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env:
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NO_NNPACK: 1
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PYTORCH_NO_NNPACK: 1
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run: |
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PYTHONPATH=. python scripts/model_builder/plot_data.py 2>/dev/null
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- name: ⬆️ Upload Checkpoints
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uses: actions/upload-artifact@v3
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with:
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name: checkpoints
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path: checkpoint_files/*
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- name: 5. Export model to ONNX graph
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env:
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NO_NNPACK: 1
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PYTORCH_NO_NNPACK: 1
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run: |
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mkdir -p onnx_files
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MKL_DISABLE_FAST_MM=1 PYTHONPATH=. python scripts/application_packager/convert_to_onnx.py 2>/dev/null
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- name: ⬆️ Upload ONNX file
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uses: actions/upload-artifact@v3
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with:
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name: onnx-file
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path: onnx_files/inference_recognition_model.onnx
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- name: 6. Profile ONNX model
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run: |
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PYTHONPATH=. python scripts/application_packager/profile_onnx.py
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- name: ⬆️ Upload JSON trace
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uses: actions/upload-artifact@v3
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with:
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name: profile-data
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path: "**/onnxruntime_profile_*.json"
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- name: 7. Convert ONNX graph to an ORT file
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run: |
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PYTHONPATH=. python scripts/application_packager/convert_to_ort.py
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- name: ⬆️ Upload ORT file
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uses: actions/upload-artifact@v3
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with:
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name: ort-file
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path: ort_files/inference_recognition_model.ort
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