Documentation and formatting updates #1
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@ -1,4 +1,4 @@
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name: RIA Hub Workflow Demo
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name: Modulation Recognition Demo
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on:
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push:
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@ -11,9 +11,6 @@ on:
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jobs:
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ria-demo:
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runs-on: ubuntu-latest-2080
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env:
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RIAGIT_USERNAME: ${{ secrets.USERNAME }}
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RIAGIT_TOKEN: ${{ secrets.TOKEN }}
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steps:
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- name: Print GPU information
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run: |
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@ -24,7 +21,7 @@ jobs:
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echo "⚠️ No NVIDIA GPU found"
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fi
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- name: Checkout code
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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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@ -42,13 +39,10 @@ jobs:
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utils \
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-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_building/data_gen.py --output-dir data/recordings
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echo "recordings produced successfully"
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PYTHONPATH=. python scripts/dataset_manager/data_gen.py --output-dir data/recordings
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- name: ⬆️ Upload recordings
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uses: actions/upload-artifact@v3
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@ -59,11 +53,10 @@ jobs:
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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_building/produce_dataset.py
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echo "datasets produced successfully"
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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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- 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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@ -75,34 +68,30 @@ jobs:
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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/training/train.py 2>/dev/null
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echo "training model"
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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/training/plot_data.py 2>/dev/null
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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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- 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. Convert to ONNX file
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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/onnx/convert_to_onnx.py 2>/dev/null
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echo "building inference app"
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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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- 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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@ -110,21 +99,20 @@ jobs:
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- name: 6. Profile ONNX model
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run: |
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PYTHONPATH=. python scripts/onnx/profile_onnx.py
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PYTHONPATH=. python scripts/application_packager/profile_onnx.py
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- name: Upload JSON profiling data
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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 to ORT file
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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/ort/convert_to_ort.py
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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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- 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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