✅ Validation Results: - PPO training: 24.2s (1 epoch, 950 samples, dim=225) - Feature extraction: 105μs/bar (9.5x faster than target) - Model checkpoint: 293KB (147KB actor + 146KB critic) - GPU memory: 145MB used (96.4% headroom) - Zero dimension mismatches 📊 Success Criteria (5/5): ✅ Feature dimension = 225 (Wave C 201 + Wave D 24) ✅ Model state_dim = 225 ✅ Training completed without errors ✅ Checkpoint saved successfully ✅ No dimension mismatch errors 📁 Training Data Ready: - ES.FUT: 2.9MB, 180 days - NQ.FUT: 4.4MB, 180 days - 6E.FUT: 2.8MB, 180 days - ZN.FUT: 65KB, 90 days (clean) 🚀 Next: Full production model retraining (4 models, ~10min GPU time) 🤖 Generated with Claude Code (https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
65 lines
1.2 KiB
Markdown
65 lines
1.2 KiB
Markdown
# GPU Errors Troubleshooting Guide
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**Last Updated**: 2025-10-22
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---
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## GPU Not Detected
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### Symptom: `nvidia-smi: command not found` in container
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**Diagnosis**:
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```bash
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# Check GPU availability on node
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kubectl get nodes -o json | jq '.items[].status.allocatable | select(.["nvidia.com/gpu"] != null)'
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# Check NVIDIA device plugin
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kubectl get pods -n kube-system | grep nvidia-device-plugin
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```
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**Resolution**:
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```bash
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# Install NVIDIA GPU Operator
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helm install gpu-operator nvidia/gpu-operator \
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--namespace gpu-operator-resources \
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--create-namespace
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# Verify GPU detected
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kubectl describe node gpu-node-1 | grep nvidia.com/gpu
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```
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---
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## CUDA Out of Memory
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### Symptom: `CUDA error: out of memory`
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**Diagnosis**:
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```bash
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# Check GPU memory usage
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kubectl exec -n foxhunt foxhunt-ml-training-service-xxxxx -- nvidia-smi
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# Output:
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# GPU Memory-Usage
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# 0 3800MiB / 4096MiB (93% - CRITICAL)
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```
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**Resolution**:
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```python
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# Reduce batch size
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batch_size = 16 # Reduced from 32
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# Enable gradient checkpointing
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model.gradient_checkpointing_enable()
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# Use mixed precision training
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from torch.cuda.amp import autocast, GradScaler
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scaler = GradScaler()
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with autocast():
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output = model(input)
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```
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---
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**End of GPU Errors Troubleshooting Guide**
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