Update README #24
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| name: Benchmark CI | |
| on: | |
| push: | |
| branches: [master] | |
| pull_request: | |
| branches: [master] | |
| jobs: | |
| lint-and-import: | |
| runs-on: ubuntu-latest | |
| strategy: | |
| matrix: | |
| python-version: ["3.10", "3.11", "3.12"] | |
| steps: | |
| - uses: actions/checkout@v4 | |
| - name: Set up Python ${{ matrix.python-version }} | |
| uses: actions/setup-python@v5 | |
| with: | |
| python-version: ${{ matrix.python-version }} | |
| - name: Install dependencies | |
| run: | | |
| pip install torch --index-url https://download.pytorch.org/whl/cpu | |
| pip install tonic torchaudio h5py numpy matplotlib | |
| - name: Verify all modules import | |
| run: | | |
| python -c "from common.neurons import LIFNeuron, AdaptiveLIFNeuron, ConvLIFLayer, surrogate_spike; print('neurons OK')" | |
| python -c "from common.training import train_epoch, evaluate, run_training; print('training OK')" | |
| python -c "from common.deploy import quantize_weights, compute_hardware_params; print('deploy OK')" | |
| python -c "from common.augmentation import event_drop, time_stretch, spatial_jitter; print('augmentation OK')" | |
| python -c "from common import LIFNeuron, AdaptiveLIFNeuron; print('common __init__ OK')" | |
| - name: Syntax check all scripts | |
| run: | | |
| python -m py_compile shd/train.py | |
| python -m py_compile shd/loader.py | |
| python -m py_compile shd/deploy.py | |
| python -m py_compile nmnist/train.py | |
| python -m py_compile nmnist/loader.py | |
| python -m py_compile nmnist/deploy.py | |
| python -m py_compile ssc/train.py | |
| python -m py_compile ssc/loader.py | |
| python -m py_compile ssc/deploy.py | |
| python -m py_compile dvs_gesture/train.py | |
| python -m py_compile dvs_gesture/loader.py | |
| python -m py_compile dvs_gesture/deploy.py | |
| python -m py_compile gsc_kws/train.py | |
| python -m py_compile gsc_kws/loader.py | |
| python -m py_compile gsc_kws/deploy.py | |
| python -m py_compile neurobench/submit.py | |
| python -m py_compile sweep.py | |
| echo "All scripts compile OK" | |
| - name: Test neuron forward pass | |
| run: | | |
| python -c " | |
| import torch | |
| from common.neurons import LIFNeuron, AdaptiveLIFNeuron | |
| # Test LIF | |
| lif = LIFNeuron(64) | |
| x = torch.randn(8, 64) | |
| v = torch.zeros(8, 64) | |
| v_new, spk = lif(x, v) | |
| assert v_new.shape == (8, 64), f'LIF v shape: {v_new.shape}' | |
| assert spk.shape == (8, 64), f'LIF spk shape: {spk.shape}' | |
| print(f'LIF: v={v_new.mean():.4f}, spikes={spk.sum():.0f}') | |
| # Test adLIF | |
| adlif = AdaptiveLIFNeuron(64) | |
| a = torch.zeros(8, 64) | |
| v_new, spk, a_new = adlif(x, v, a, torch.zeros(8, 64)) | |
| assert v_new.shape == (8, 64), f'adLIF v shape: {v_new.shape}' | |
| assert a_new.shape == (8, 64), f'adLIF a shape: {a_new.shape}' | |
| print(f'adLIF: v={v_new.mean():.4f}, a={a_new.mean():.4f}, spikes={spk.sum():.0f}') | |
| print('All neuron tests passed') | |
| " | |
| - name: Test quantization | |
| run: | | |
| python -c " | |
| import numpy as np | |
| from common.deploy import quantize_weights | |
| w = np.random.randn(20, 512).astype(np.float32) * 0.1 | |
| w_q = quantize_weights(w, threshold_float=1.0, threshold_hw=1000) | |
| assert w_q.shape == (512, 20), f'Expected (512,20), got {w_q.shape}' | |
| assert w_q.dtype == np.int32 | |
| assert w_q.min() >= -32768 | |
| assert w_q.max() <= 32767 | |
| print(f'Quantization: range [{w_q.min()}, {w_q.max()}], shape {w_q.shape}') | |
| print('Quantization test passed') | |
| " | |
| - name: Test augmentation | |
| run: | | |
| python -c " | |
| import torch | |
| from common.augmentation import event_drop, time_stretch, spatial_jitter | |
| x = torch.rand(4, 100, 700) | |
| y = event_drop(x) | |
| assert y.shape == x.shape, f'event_drop shape: {y.shape}' | |
| y = time_stretch(x, factor_range=(0.9, 1.1)) | |
| assert y.shape == x.shape, f'time_stretch shape: {y.shape}' | |
| x_dvs = torch.rand(4, 20, 2048) | |
| y = spatial_jitter(x_dvs, sigma=1.0, spatial_dims=(32, 32)) | |
| assert y.shape == x_dvs.shape, f'spatial_jitter shape: {y.shape}' | |
| print('All augmentation tests passed') | |
| " |