Add Google Colab and Google Cloud training commands for PlaNet model#1
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- colab_training.ipynb: step-by-step Jupyter notebook for Google Colab
- Auto-detects CUDA version and installs a compatible TensorFlow
- Optional Google Drive mount for checkpoint persistence across sessions
- Downloads the Zenodo dataset, patches config paths, streams training output
- TensorBoard integration and resume-from-checkpoint support
- Model export cell for SavedModel / TFLite output
- gcloud_train.sh: bash script for two GCP deployment modes
- MODE=gce: creates a Deep Learning VM (GPU), SSH-installs deps,
downloads dataset, streams training, syncs checkpoints to GCS
- MODE=vertex: uploads dataset to GCS, submits a Vertex AI Custom
Training Job using a pre-built TF GPU container
- planner_learning/config/train_settings_cloud.yaml: cloud-optimised
training config (batch_size=16, save_every_n_epochs=5, paths
overridden at runtime by the respective launch scripts)
https://claude.ai/code/session_01UCa2UAvFF9LBRLiqjDhTuf
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colab_training.ipynb: step-by-step Jupyter notebook for Google Colab
gcloud_train.sh: bash script for two GCP deployment modes
planner_learning/config/train_settings_cloud.yaml: cloud-optimised training config (batch_size=16, save_every_n_epochs=5, paths overridden at runtime by the respective launch scripts)
https://claude.ai/code/session_01UCa2UAvFF9LBRLiqjDhTuf