diff --git a/README_HYDRA.md b/README_HYDRA.md new file mode 100644 index 0000000..2f01c8e --- /dev/null +++ b/README_HYDRA.md @@ -0,0 +1,96 @@ +# Hydra Configuration System - Quick Start + +## ๐Ÿš€ Installation + +```bash +# Install pip and create virtual environment +sudo apt install python3-pip python3.12-venv -y +python3 -m venv venv +source venv/bin/activate + +# Install minimal requirements for Hydra +pip install -r requirements-minimal.txt +``` + +## ๐Ÿ“‹ Usage Examples + +### Basic Configuration +```bash +# Use default configuration +python test_config.py + +# Override parameters +python test_config.py experiments.training.lr=0.001 experiments.model.hidden_dims=[128,64] +``` + +### Pre-configured Experiments +```bash +# Debug experiment (small model, 10 epochs) +python test_config.py --config-name experiments/debug + +# Baseline experiment (standard settings) +python test_config.py --config-name experiments/baseline +``` + +### Command-line Overrides +```bash +# Learning rate override +python test_config.py experiments.training.lr=0.001 + +# Model architecture override +python test_config.py experiments.model.hidden_dims=[32] + +# Multiple overrides +python test_config.py experiments.training.lr=0.001 experiments.model.hidden_dims=[128,64] experiments.training.epochs=300 +``` + +## ๐Ÿ“ Configuration Structure + +``` +configs/ +โ”œโ”€โ”€ config.yaml # Main configuration +โ”œโ”€โ”€ model/gcn.yaml # GCN model configs +โ”œโ”€โ”€ training/default.yaml # Training configs +โ”œโ”€โ”€ data/cora.yaml # Dataset configs +โ””โ”€โ”€ experiments/ + โ”œโ”€โ”€ debug.yaml # Debug experiment + โ”œโ”€โ”€ baseline.yaml # Baseline experiment + โ””โ”€โ”€ hyperparameter_search.yaml # Parameter sweep +``` + +## ๐ŸŽฏ Key Features + +- **Easy Parameter Override**: `experiments.training.lr=0.001` +- **Pre-configured Experiments**: Debug, baseline, hyperparameter search +- **Automatic Output Organization**: Results saved to timestamped directories +- **Configuration Tracking**: Full config saved with results + +## ๐Ÿ“Š Test Results + +The system successfully demonstrates: +- โœ… Configuration loading and merging +- โœ… Command-line parameter overrides +- โœ… Pre-configured experiment selection +- โœ… Automatic output organization +- โœ… Configuration tracking and logging + +## ๐Ÿ”„ Next Steps + +1. Install full PyTorch dependencies when needed: + ```bash + pip install -r requirements.txt # May take time due to large downloads + ``` + +2. Use the full training script: + ```bash + python train.py experiments.training.lr=0.001 + ``` + +3. Run hyperparameter sweeps: + ```bash + python train.py --multirun experiments.training.lr=0.001,0.01,0.1 + ``` + +--- + +**The Hydra configuration system is ready for easy experiment management!** ๐Ÿš€ diff --git a/configs/config.yaml b/configs/config.yaml new file mode 100644 index 0000000..e400ba1 --- /dev/null +++ b/configs/config.yaml @@ -0,0 +1,22 @@ +# Default configuration for AstroML training experiments +defaults: + - model: gcn + - training: default + - data: cora + - _self_ + +# Experiment settings +experiment: + name: "astroml_experiment" + seed: 42 + device: "auto" # auto, cpu, cuda + save_dir: "outputs" + log_level: "INFO" + +# Hydra settings +hydra: + run: + dir: outputs/${experiment.name}/${now:%Y-%m-%d_%H-%M-%S} + sweep: + dir: outputs/${experiment.name}/multirun + subdir: ${hydra.job.override_dirname} diff --git a/configs/data/cora.yaml b/configs/data/cora.yaml new file mode 100644 index 0000000..9162ea3 --- /dev/null +++ b/configs/data/cora.yaml @@ -0,0 +1,23 @@ +# Cora dataset configuration +_target_: torch_geometric.datasets.Planetoid + +name: "Cora" +root: "data" +transform: + _target_: torch_geometric.transforms.NormalizeFeatures + +# Dataset-specific settings +num_classes: 7 +num_node_features: 1433 + +# Alternative datasets +variants: + citeseer: + name: "CiteSeer" + num_classes: 6 + num_node_features: 3703 + + pubmed: + name: "PubMed" + num_classes: 3 + num_node_features: 5003 diff --git a/configs/experiments/baseline.yaml b/configs/experiments/baseline.yaml new file mode 100644 index 0000000..031f326 --- /dev/null +++ b/configs/experiments/baseline.yaml @@ -0,0 +1,26 @@ +# Baseline experiment configuration +defaults: + - /model: gcn + - /training: default + - /data: cora + - _self_ + +# Baseline settings +experiment: + name: "baseline_experiment" + seed: 42 + +# Model settings +model: + hidden_dims: [64, 32] + dropout: 0.5 + +# Training settings +training: + epochs: 200 + lr: 0.01 + weight_decay: 5e-4 + +# Data settings +data: + name: "Cora" diff --git a/configs/experiments/debug.yaml b/configs/experiments/debug.yaml new file mode 100644 index 0000000..66cf9c3 --- /dev/null +++ b/configs/experiments/debug.yaml @@ -0,0 +1,29 @@ +# Debug experiment configuration +defaults: + - /model: gcn + - /training: default + - /data: cora + - _self_ + +# Debug settings +experiment: + name: "debug_experiment" + seed: 42 + device: "auto" + save_dir: "outputs" + log_level: "INFO" + +# Model overrides +model: + hidden_dims: [16] # Small model for fast debugging + dropout: 0.1 + +# Training overrides +training: + epochs: 10 # Short training for debugging + lr: 0.01 + log_interval: 1 + +# Data overrides +data: + name: "Cora" diff --git a/configs/experiments/hyperparameter_search.yaml b/configs/experiments/hyperparameter_search.yaml new file mode 100644 index 0000000..ab541d5 --- /dev/null +++ b/configs/experiments/hyperparameter_search.yaml @@ -0,0 +1,37 @@ +# Hyperparameter search experiment configuration +defaults: + - /model: gcn + - /training: default + - /data: cora + - _self_ + +# Hyperparameter search settings +experiment: + name: "hyperparameter_search" + seed: 42 + +# Model parameter grid +model: + hidden_dims: + - [32] + - [64, 32] + - [128, 64] + dropout: + - 0.2 + - 0.5 + - 0.7 + +# Training parameter grid +training: + lr: + - 0.001 + - 0.01 + - 0.1 + weight_decay: + - 1e-5 + - 5e-4 + - 1e-3 + +# Data settings +data: + name: "Cora" diff --git a/configs/model/gcn.yaml b/configs/model/gcn.yaml new file mode 100644 index 0000000..964d638 --- /dev/null +++ b/configs/model/gcn.yaml @@ -0,0 +1,28 @@ +# Graph Convolutional Network model configuration +_target_: astroml.models.gcn.GCN + +input_dim: ??? +hidden_dims: [64, 32] +output_dim: ??? +dropout: 0.5 +activation: "relu" +batch_norm: false +residual: false + +# Alternative model configurations +variants: + small: + hidden_dims: [32] + dropout: 0.2 + + medium: + hidden_dims: [64, 32] + dropout: 0.5 + + large: + hidden_dims: [128, 64, 32] + dropout: 0.6 + + very_large: + hidden_dims: [256, 128, 64] + dropout: 0.7 diff --git a/configs/training/default.yaml b/configs/training/default.yaml new file mode 100644 index 0000000..7736585 --- /dev/null +++ b/configs/training/default.yaml @@ -0,0 +1,38 @@ +# Training configuration +epochs: 200 +lr: 0.01 +weight_decay: 5e-4 +optimizer: "adam" +scheduler: null +early_stopping: + patience: 50 + min_delta: 1e-4 + monitor: "val_loss" + mode: "min" + +# Training settings +batch_size: null # Full batch for graph data +val_split: 0.1 +test_split: 0.1 +shuffle: true + +# Logging +log_interval: 20 +save_best_only: true +save_last: true + +# Optimizer configurations +optimizer_configs: + adam: + betas: [0.9, 0.999] + eps: 1e-8 + amsgrad: false + + sgd: + momentum: 0.9 + nesterov: true + + adamw: + betas: [0.9, 0.999] + eps: 1e-8 + weight_decay: 1e-2 diff --git a/docs/_build/.buildinfo b/docs/_build/.buildinfo new file mode 100644 index 0000000..fc28cf5 --- /dev/null +++ b/docs/_build/.buildinfo @@ -0,0 +1,4 @@ +# Sphinx build info version 1 +# This file records the configuration used when building these files. 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a/docs/_build/.doctrees/index.doctree b/docs/_build/.doctrees/index.doctree new file mode 100644 index 0000000..d8597de Binary files /dev/null and b/docs/_build/.doctrees/index.doctree differ diff --git a/docs/_build/.doctrees/schema.doctree b/docs/_build/.doctrees/schema.doctree new file mode 100644 index 0000000..4f7f026 Binary files /dev/null and b/docs/_build/.doctrees/schema.doctree differ diff --git a/docs/_build/_sources/docker-deployment.md.txt b/docs/_build/_sources/docker-deployment.md.txt new file mode 100644 index 0000000..4b4e6cb --- /dev/null +++ b/docs/_build/_sources/docker-deployment.md.txt @@ -0,0 +1,400 @@ +# Docker Deployment Guide for AstroML + +This guide provides comprehensive instructions for deploying AstroML using Docker and Docker Compose. + +## ๐Ÿณ Overview + +The AstroML Docker setup includes: + +- **Multi-stage Dockerfile** with optimized images for different use cases +- **Docker Compose** configuration for complete environment setup +- **GPU support** for ML training +- **Development**, **production**, and **monitoring** profiles + +## ๐Ÿ— Docker Build Stages + +### Available Build Targets + +| Stage | Purpose | Base Image | Use Case | +|-------|---------|------------|----------| +| `base` | Common dependencies | `python:3.11-slim` | Foundation for all stages | +| `ingestion` | Data ingestion & streaming | `base` | Stellar data ingestion | +| `training` | GPU-enabled ML training | `nvidia/cuda:12.1-runtime` | GPU training environments | +| `training-cpu` | CPU-only ML training | `base` | CPU training environments | +| `development` | Development with tools | `base` | Local development | +| `production` | Minimal production image | `base` | Production deployment | + +## ๐Ÿš€ Quick Start + +### Prerequisites + +- Docker Engine 20.10+ +- Docker Compose 2.0+ +- NVIDIA Docker (for GPU support) + +### Basic Setup + +1. **Clone and navigate to the project:** + ```bash + git clone https://github.com/tecch-wiz/astroml.git + cd astroml + ``` + +2. **Start the basic environment:** + ```bash + docker-compose up -d postgres redis + ``` + +3. **Run database migrations:** + ```bash + docker-compose run --rm ingestion python -m alembic upgrade head + ``` + +4. **Start ingestion service:** + ```bash + docker-compose up -d ingestion + ``` + +## ๐Ÿ“‹ Docker Compose Services + +### Core Services + +- **postgres**: PostgreSQL database with health checks +- **redis**: Redis for caching and job queues +- **ingestion**: Main data ingestion service +- **streaming**: Enhanced streaming service + +### Training Services + +- **training-gpu**: GPU-enabled training (requires NVIDIA Docker) +- **training-cpu**: CPU-only training + +### Optional Services + +- **dev**: Development environment with Jupyter +- **production**: Production-optimized service +- **prometheus**: Monitoring and metrics +- **grafana**: Visualization dashboard + +## ๐Ÿ›  Usage Examples + +### Development Environment + +```bash +# Start development services +docker-compose --profile dev up -d + +# Access Jupyter Lab +open http://localhost:8888 +``` + +### GPU Training + +```bash +# Start GPU training service +docker-compose --profile gpu up -d training-gpu + +# Run training +docker-compose exec training-gpu python -m astroml.training.train_gcn +``` + +### CPU Training + +```bash +# Start CPU training service +docker-compose --profile cpu up -d training-cpu + +# Run training +docker-compose exec training-cpu python -m astroml.training.train_gcn +``` + +### Production Deployment + +```bash +# Deploy production services +docker-compose --profile prod up -d production +``` + +### Monitoring Stack + +```bash +# Start monitoring services +docker-compose --profile monitoring up -d prometheus grafana + +# Access Grafana +open http://localhost:3000 # admin/admin +``` + +## ๐Ÿ”ง Configuration + +### Environment Variables + +Key environment variables for services: + +```yaml +# Database +DATABASE_URL: postgresql://astroml:astroml_password@postgres:5432/astroml + +# Redis +REDIS_URL: redis://redis:6379/0 + +# Stellar Network +STELLAR_NETWORK_PASSPHRASE: "Public Global Stellar Network ; September 2015" +STELLAR_HORIZON_URL: https://horizon.stellar.org + +# Logging +LOG_LEVEL: INFO +``` + +### Custom Configuration + +Create `docker-compose.override.yml` for local customizations: + +```yaml +version: '3.8' + +services: + ingestion: + environment: + - LOG_LEVEL=DEBUG + volumes: + - ./local_config:/app/config:ro + + postgres: + ports: + - "5433:5432" # Different port to avoid conflicts +``` + +## ๐Ÿ“Š GPU Support + +### NVIDIA Docker Setup + +1. **Install NVIDIA Container Toolkit:** + ```bash + # Ubuntu/Debian + distribution=$(. /etc/os-release;echo $ID$VERSION_ID) + curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - + curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list + + sudo apt-get update && sudo apt-get install -y nvidia-docker2 + sudo systemctl restart docker + ``` + +2. **Test GPU support:** + ```bash + docker run --rm --gpus all nvidia/cuda:12.1-base-ubuntu22.04 nvidia-smi + ``` + +### GPU Training + +```bash +# Build GPU image +docker build --target training -t astroml:training-gpu . + +# Run with GPU +docker run --gpus all -v $(pwd):/app astroml:training-gpu python -m astroml.training.train_gcn +``` + +## ๐Ÿ” Monitoring and Logging + +### Log Access + +```bash +# View ingestion logs +docker-compose logs -f ingestion + +# View all service logs +docker-compose logs -f + +# View specific number of lines +docker-compose logs --tail=100 training-gpu +``` + +### Health Checks + +All services include health checks: + +```bash +# Check service health +docker-compose ps + +# Detailed health status +curl http://localhost:8000/health # If health endpoint is exposed +``` + +### Monitoring Stack + +With the monitoring profile enabled: + +- **Prometheus**: http://localhost:9090 +- **Grafana**: http://localhost:3000 (admin/admin) + +## ๐Ÿ—‚ Data Persistence + +### Volume Structure + +``` +volumes/ +โ”œโ”€โ”€ postgres_data/ # PostgreSQL data +โ”œโ”€โ”€ redis_data/ # Redis data +โ”œโ”€โ”€ ingestion_logs/ # Ingestion logs +โ”œโ”€โ”€ ingestion_data/ # Ingestion data +โ”œโ”€โ”€ training_models/ # Trained models +โ”œโ”€โ”€ training_data/ # Training datasets +โ”œโ”€โ”€ training_logs/ # Training logs +โ””โ”€โ”€ production_data/ # Production data +``` + +### Backup and Restore + +```bash +# Backup database +docker-compose exec postgres pg_dump -U astroml astroml > backup.sql + +# Restore database +docker-compose exec -T postgres psql -U astroml astroml < backup.sql + +# Backup volumes +docker run --rm -v astroml_postgres_data:/data -v $(pwd):/backup ubuntu tar czf /backup/postgres_backup.tar.gz -C /data . +``` + +## ๐Ÿงช Testing + +### Running Tests in Docker + +```bash +# Run all tests +docker-compose run --rm dev python -m pytest tests/ -v + +# Run with coverage +docker-compose run --rm dev python -m pytest tests/ --cov=astroml --cov-report=html + +# Run specific test file +docker-compose run --rm dev python -m pytest tests/test_structural_importance.py -v +``` + +### Integration Testing + +```bash +# Test ingestion pipeline +docker-compose run --rm ingestion python -c "import astroml.ingestion; print('OK')" + +# Test training environment +docker-compose run --rm training-cpu python -c "import torch; import torch_geometric; print('OK')" +``` + +## ๐Ÿš€ Production Deployment + +### Production Checklist + +- [ ] Use `production` build target +- [ ] Configure proper secrets management +- [ ] Set up monitoring and alerting +- [ ] Configure log rotation +- [ ] Set up backup strategy +- [ ] Review resource limits +- [ ] Test disaster recovery + +### Production Commands + +```bash +# Build production image +docker build --target production -t astroml:prod . + +# Deploy with production profile +docker-compose --profile prod up -d production + +# Scale services +docker-compose --profile prod up -d --scale production=3 +``` + +## ๐Ÿ”ง Troubleshooting + +### Common Issues + +1. **GPU not detected:** + ```bash + # Check NVIDIA Docker installation + docker run --rm --gpus all nvidia/cuda:12.1-base nvidia-smi + ``` + +2. **Database connection issues:** + ```bash + # Check database health + docker-compose exec postgres pg_isready -U astroml + ``` + +3. **Permission issues:** + ```bash + # Fix volume permissions + sudo chown -R $USER:$USER .dockerignore + ``` + +4. **Out of memory:** + ```bash + # Check resource usage + docker stats + + # Increase memory limits in docker-compose.yml + ``` + +### Debug Mode + +```bash +# Run with shell access +docker-compose run --rm ingestion bash + +# Debug with environment variables +docker-compose run --rm -e DEBUG=1 ingestion python -m astroml.ingestion +``` + +## ๐Ÿ“š Advanced Usage + +### Custom Images + +```bash +# Build custom stage +docker build --target development -t astroml:dev . + +# Build with custom arguments +docker build --build-arg PYTHON_VERSION=3.10 -t astroml:custom . +``` + +### Multi-Node Deployment + +```bash +# Initialize Docker Swarm +docker swarm init + +# Deploy stack +docker stack deploy -c docker-compose.yml astroml +``` + +### Performance Tuning + +```yaml +# docker-compose.yml performance tweaks +services: + training-gpu: + deploy: + resources: + limits: + memory: 16G + cpus: '8' + reservations: + devices: + - driver: nvidia + count: 1 + capabilities: [gpu] +``` + +## ๐Ÿ†˜ Support + +For Docker-related issues: + +1. Check the [troubleshooting section](#-troubleshooting) +2. Review service logs: `docker-compose logs ` +3. Verify resource usage: `docker stats` +4. Test with minimal configuration + +For application issues, refer to the main AstroML documentation. diff --git a/docs/_build/_sources/experiment-configs.md.txt b/docs/_build/_sources/experiment-configs.md.txt new file mode 100644 index 0000000..f3475b4 --- /dev/null +++ b/docs/_build/_sources/experiment-configs.md.txt @@ -0,0 +1,340 @@ +# Experiment Configuration Guide + +This guide explains how to use the Hydra configuration system to run ML experiments with AstroML. + +## ๐Ÿš€ Quick Start + +### Basic Usage + +```bash +# Run with default configuration +python train.py + +# Override learning rate +python train.py training.lr=0.001 + +# Use debug experiment +python train.py experiment=debug + +# Override multiple parameters +python train.py model.hidden_dims=[128,64] training.lr=0.01 training.epochs=300 +``` + +### Hyperparameter Sweeps + +```bash +# Grid search over learning rates +python train.py --multirun training.lr=0.001,0.01,0.1 + +# Grid search over multiple parameters +python train.py --multirun model.hidden_dims=[32],[64,32],[128,64] training.lr=0.001,0.01 + +# Use pre-configured sweep +python train.py --config-name experiments/hyperparameter_search --multirun +``` + +## ๐Ÿ“ Configuration Structure + +``` +configs/ +โ”œโ”€โ”€ config.yaml # Main configuration file +โ”œโ”€โ”€ model/ +โ”‚ โ””โ”€โ”€ gcn.yaml # GCN model configurations +โ”œโ”€โ”€ training/ +โ”‚ โ””โ”€โ”€ default.yaml # Training configurations +โ”œโ”€โ”€ data/ +โ”‚ โ””โ”€โ”€ cora.yaml # Dataset configurations +โ””โ”€โ”€ experiments/ + โ”œโ”€โ”€ debug.yaml # Debug experiment + โ”œโ”€โ”€ baseline.yaml # Baseline experiment + โ””โ”€โ”€ hyperparameter_search.yaml # Hyperparameter sweep +``` + +## โš™๏ธ Configuration Files + +### Main Config (`configs/config.yaml`) + +The main configuration file that sets up defaults and experiment settings: + +```yaml +defaults: + - model: gcn # Use GCN model + - training: default # Use default training config + - data: cora # Use Cora dataset + - _self_ # Include this file's settings + +experiment: + name: "astroml_experiment" + seed: 42 + device: "auto" + save_dir: "outputs" + log_level: "INFO" +``` + +### Model Config (`configs/model/gcn.yaml`) + +Configures the Graph Convolutional Network: + +```yaml +_target_: astroml.models.gcn.GCN +input_dim: ??? # Will be set from dataset +hidden_dims: [64, 32] # Hidden layer sizes +output_dim: ??? # Will be set from dataset +dropout: 0.5 +activation: "relu" +batch_norm: false +residual: false +``` + +### Training Config (`configs/training/default.yaml`) + +Training hyperparameters and settings: + +```yaml +epochs: 200 +lr: 0.01 +weight_decay: 5e-4 +optimizer: "adam" +scheduler: null +early_stopping: + patience: 50 + min_delta: 1e-4 + monitor: "val_loss" + mode: "min" +``` + +### Data Config (`configs/data/cora.yaml`) + +Dataset configuration: + +```yaml +_target_: torch_geometric.datasets.Planetoid +name: "Cora" +root: "data" +transform: + _target_: torch_geometric.transforms.NormalizeFeatures +``` + +## ๐Ÿ”ง Configuration Overrides + +### Command Line Overrides + +You can override any configuration parameter from the command line: + +```bash +# Override learning rate +python train.py training.lr=0.001 + +# Override model architecture +python train.py model.hidden_dims=[128,64,32] model.dropout=0.6 + +# Override dataset +python train.py data.name=CiteSeer + +# Override experiment settings +python train.py experiment.name=my_experiment experiment.seed=123 +``` + +### Using Experiments + +Pre-configured experiments provide complete setups: + +```bash +# Debug experiment (small model, few epochs) +python train.py --config-name experiments/debug + +# Baseline experiment (standard settings) +python train.py --config-name experiments/baseline + +# Hyperparameter search experiment +python train.py --config-name experiments/hyperparameter_search --multirun +``` + +## ๐Ÿ“Š Hyperparameter Sweeps + +### Basic Grid Search + +```bash +# Search over learning rates +python train.py --multirun training.lr=0.001,0.01,0.1 + +# Search over model architectures +python train.py --multirun model.hidden_dims=[32],[64,32],[128,64] + +# Combined search +python train.py --multirun training.lr=0.001,0.01 model.dropout=0.3,0.5,0.7 +``` + +### Using Sweep Configurations + +The `hyperparameter_search.yaml` experiment defines a parameter grid: + +```bash +python train.py --config-name experiments/hyperparameter_search --multirun +``` + +This will run experiments for all combinations of: +- `model.hidden_dims`: [32], [64,32], [128,64] +- `model.dropout`: 0.2, 0.5, 0.7 +- `training.lr`: 0.001, 0.01, 0.1 +- `training.weight_decay`: 1e-5, 5e-4, 1e-3 + +## ๐Ÿ“ Output Structure + +Hydra automatically organizes experiment outputs: + +``` +outputs/ +โ””โ”€โ”€ astroml_experiment/ + โ””โ”€โ”€ 2024-03-24_10-30-45/ + โ”œโ”€โ”€ .hydra/ + โ”‚ โ”œโ”€โ”€ config.yaml # Full configuration + โ”‚ โ”œโ”€โ”€ hydra.yaml # Hydra settings + โ”‚ โ””โ”€โ”€ overrides.yaml # Command line overrides + โ”œโ”€โ”€ best_model.pth # Best model checkpoint + โ”œโ”€โ”€ last_model.pth # Final model checkpoint + โ”œโ”€โ”€ results.yaml # Training results + โ””โ”€โ”€ train.log # Training logs +``` + +For multirun experiments: + +``` +outputs/ +โ””โ”€โ”€ astroml_experiment/ + โ””โ”€โ”€ multirun/ + โ”œโ”€โ”€ model.hidden_dims=32,training.lr=0.001/ + โ”œโ”€โ”€ model.hidden_dims=64,training.lr=0.001/ + โ””โ”€โ”€ ... +``` + +## ๐ŸŽฏ Common Use Cases + +### 1. Quick Debugging + +```bash +# Small model, few epochs for fast iteration +python train.py experiment=debug +``` + +### 2. Baseline Comparison + +```bash +# Run baseline experiment +python train.py --config-name experiments/baseline + +# Compare with different learning rate +python train.py --config-name experiments/baseline training.lr=0.001 +``` + +### 3. Architecture Search + +```bash +# Test different model sizes +python train.py --multirun model.hidden_dims=[32],[64,32],[128,64,32] +``` + +### 4. Learning Rate Tuning + +```bash +# Fine-grained learning rate search +python train.py --multirun training.lr=0.001,0.003,0.01,0.03,0.1 +``` + +### 5. Regularization Experiments + +```bash +# Test different dropout rates +python train.py --multirun model.dropout=0.1,0.3,0.5,0.7 + +# Test weight decay +python train.py --multirun training.weight_decay=0,1e-5,5e-4,1e-3 +``` + +## ๐Ÿ” Advanced Features + +### Custom Configurations + +Create your own experiment configurations: + +```yaml +# configs/experiments/my_experiment.yaml +defaults: + - override /model: gcn + - override /training: default + - override /data: cora + +experiment: + name: "my_custom_experiment" + +model: + hidden_dims: [256, 128] + dropout: 0.6 + +training: + epochs: 500 + lr: 0.003 +``` + +### Environment Variables + +Use environment variables in configs: + +```yaml +# In config.yaml +experiment: + name: "${oc.env:USER}_experiment" + seed: ${oc.env:RANDOM_SEED:42} +``` + +### Conditional Configuration + +Use conditional logic in configs: + +```yaml +# Conditional model size based on dataset +model: + hidden_dims: ${select:${data.name},CiteSeer:[64],PubMed:[128,64],default:[64,32]} +``` + +## ๐Ÿ“ Best Practices + +1. **Use descriptive experiment names** for easy identification +2. **Set random seeds** for reproducible results +3. **Use early stopping** to prevent overfitting +4. **Save both best and last models** for comparison +5. **Log frequently** during training for debugging +6. **Use multirun for systematic hyperparameter searches** +7. **Keep configuration files under version control** + +## ๐Ÿ†˜ Troubleshooting + +### Common Issues + +1. **Config not found**: Check file paths and YAML syntax +2. **Override not working**: Use dot notation (e.g., `model.lr` not `lr`) +3. **Multirun not working**: Ensure `--multirun` flag is used +4. **Output directory issues**: Check write permissions + +### Debugging Configurations + +```bash +# Print configuration without running +python train.py --cfg + +# Print specific config section +python train.py --cfg model + +# Dry run to check config +python train.py --dry-run +``` + +## ๐Ÿ“š Additional Resources + +- [Hydra Documentation](https://hydra.cc/) +- [OmegaConf Documentation](https://omegaconf.readthedocs.io/) +- [PyTorch Lightning Integration](https://pytorch-lightning.readthedocs.io/) + +--- + +For more examples and advanced configurations, see the `configs/experiments/` directory. diff --git a/docs/_build/_sources/index.md.txt b/docs/_build/_sources/index.md.txt new file mode 100644 index 0000000..e8ea0f9 --- /dev/null +++ b/docs/_build/_sources/index.md.txt @@ -0,0 +1,108 @@ +# AstroML Documentation + +Welcome to the AstroML documentation! + +## ๐Ÿš€ Quick Start + +AstroML is a comprehensive machine learning framework for the Stellar network, providing tools for: + +- **Graph Machine Learning**: Advanced GNN models for transaction analysis +- **Fraud Detection**: Sophisticated algorithms for identifying suspicious activity +- **Feature Engineering**: Comprehensive feature extraction and processing +- **Data Ingestion**: Real-time Stellar ledger data processing + +## ๐Ÿ“š Documentation Sections + +### Machine Learning +- [Structural Importance Metrics](structural_importance.md) +- [Transaction Graph Analysis](transaction_graph.md) +- [Feature Engineering Pipeline](feature_pipeline.md) + +### Configuration & Experiments +- [Experiment Configuration](experiment-configs.md) +- [Hydra Setup Guide](hydra-setup.md) + +### Deployment +- [Docker Deployment](docker-deployment.md) +- [Soroban Contract Integration](soroban-contract.md) + +### API Reference +- [Models API](api/models.md) +- [Features API](api/features.md) +- [Training API](api/training.md) + +## ๐Ÿ”ง Installation + +```bash +# Clone the repository +git clone https://github.com/tecch-wiz/astroml.git +cd astroml + +# Create virtual environment +python3 -m venv venv +source venv/bin/activate + +# Install dependencies +pip install -r requirements.txt + +# For documentation only +pip install -r docs/requirements.txt +``` + +## ๐ŸŽฏ Quick Examples + +### Running Experiments with Hydra + +```bash +# Basic experiment +python train.py + +# Override parameters +python train.py training.lr=0.001 model.hidden_dims=[128,64] + +# Use pre-configured experiments +python train.py --config-name experiments/debug +python train.py --config-name experiments/baseline +``` + +### Docker Deployment + +```bash +# Build and run all services +docker-compose up -d + +# Run specific services +docker-compose up postgres redis +docker-compose up ingestion +``` + +## ๐Ÿ“Š Features + +### Machine Learning +- **Graph Neural Networks**: GCN, GraphSAGE, GAT implementations +- **Structural Analysis**: Centrality measures, importance metrics +- **Temporal Modeling**: Time-series analysis for transaction patterns + +### Data Processing +- **Real-time Ingestion**: Stellar ledger streaming +- **Feature Engineering**: Automated feature extraction +- **Data Validation**: Quality checks and integrity verification + +### Deployment +- **Docker Support**: Multi-stage builds for different environments +- **Configuration Management**: Hydra-based experiment tracking +- **Monitoring**: Comprehensive logging and metrics + +## ๐Ÿ”— Links + +- [GitHub Repository](https://github.com/tecch-wiz/astroml) +- [Stellar Network](https://www.stellar.org/) +- [PyTorch Geometric](https://pytorch-geometric.readthedocs.io/) + +## ๐Ÿ“– Contributing + +We welcome contributions! Please see our [Contributing Guide](contributing.md) for details. + +## ๐Ÿ“„ License + +This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. diff --git a/docs/_build/_sources/schema.md.txt b/docs/_build/_sources/schema.md.txt new file mode 100644 index 0000000..f781698 --- /dev/null +++ b/docs/_build/_sources/schema.md.txt @@ -0,0 +1,152 @@ +# AstroML Raw Data Storage Schema + +## Overview + +AstroML stores raw Stellar blockchain data in PostgreSQL. The schema models the five core entities needed for dynamic graph ML: **ledgers**, **transactions**, **operations**, **accounts**, and **assets**. + +The graph mapping is: + +| Blockchain Concept | Graph Representation | Table | +|--------------------|---------------------|-------| +| Accounts | Nodes | `accounts` | +| Operations | Directed edges | `operations` | +| Assets | Edge types | `assets` | +| Time (ledger close) | Dynamic dimension | `ledgers` | + +## ER Diagram + +```mermaid +erDiagram + ledgers ||--o{ transactions : contains + transactions ||--o{ operations : contains + + ledgers { + int sequence PK + varchar hash UK + varchar prev_hash + timestamptz closed_at + int successful_transaction_count + int failed_transaction_count + int operation_count + numeric total_coins + numeric fee_pool + int base_fee_in_stroops + int protocol_version + } + + transactions { + varchar hash PK + int ledger_sequence FK + varchar source_account + timestamptz created_at + bigint fee + smallint operation_count + boolean successful + varchar memo_type + text memo + } + + operations { + bigint id PK + varchar transaction_hash FK + smallint application_order + varchar type + varchar source_account + varchar destination_account + numeric amount + varchar asset_code + varchar asset_issuer + timestamptz created_at + jsonb details + } + + accounts { + varchar account_id PK + numeric balance + bigint sequence + varchar home_domain + int flags + int last_modified_ledger + timestamptz created_at + timestamptz updated_at + } + + assets { + int id PK + varchar asset_type + varchar asset_code + varchar asset_issuer + int first_seen_ledger + } +``` + +## Table Details + +### `ledgers` + +Temporal anchor โ€” one row per closed Stellar ledger (~5-6 seconds apart). + +**Indexes:** +- `PK` on `sequence` +- `UNIQUE` on `hash` +- `ix_ledgers_closed_at` on `closed_at` + +### `transactions` + +One row per Stellar transaction. Linked to a ledger via `ledger_sequence`. + +**Indexes:** +- `PK` on `hash` +- `ix_transactions_source_account_created_at` on `(source_account, created_at)` โ€” composite index for account+timestamp queries +- `ix_transactions_ledger_sequence` on `ledger_sequence` + +### `operations` + +One row per operation โ€” the primary graph-edge table. Common columns (`source_account`, `destination_account`, `amount`, `asset_code`, `asset_issuer`) cover the majority of graph-relevant operation types. The `details` JSONB column stores type-specific fields. + +`created_at` is denormalized from the parent transaction to support efficient temporal range queries without JOINs. + +**Indexes:** +- `PK` on `id` +- `ix_operations_source_created_at` on `(source_account, created_at)` โ€” composite index for account+timestamp queries +- `ix_operations_dest_created_at` on `(destination_account, created_at)` โ€” partial index (WHERE destination_account IS NOT NULL) +- `ix_operations_transaction_hash` on `transaction_hash` +- `ix_operations_type` on `type` + +### `accounts` + +Latest known state of a Stellar account. + +**Indexes:** +- `PK` on `account_id` +- `ix_accounts_updated_at` on `updated_at` + +### `assets` + +Asset registry โ€” unique by (code, issuer). Native XLM has `asset_issuer = NULL`. + +**Indexes:** +- `PK` on `id` +- `ix_assets_code_issuer` on `(asset_code, COALESCE(asset_issuer, ''))` โ€” unique expression index handling NULL issuer for native XLM + +## Relationships + +``` +ledgers 1 โ”€โ”€< N transactions (ledger_sequence โ†’ sequence) +transactions 1 โ”€โ”€< N operations (transaction_hash โ†’ hash) +``` + +`accounts` and `assets` are reference tables โ€” not FK-constrained from operations to keep bulk ingestion fast and avoid ordering dependencies. + +## Running Migrations + +```bash +# Apply all migrations +alembic upgrade head + +# Rollback all migrations +alembic downgrade base + +# Create a new migration +alembic revision --autogenerate -m "description" +``` diff --git a/docs/_build/_static/_sphinx_javascript_frameworks_compat.js b/docs/_build/_static/_sphinx_javascript_frameworks_compat.js new file mode 100644 index 0000000..8141580 --- /dev/null +++ b/docs/_build/_static/_sphinx_javascript_frameworks_compat.js @@ -0,0 +1,123 @@ +/* Compatability shim for jQuery and underscores.js. + * + * Copyright Sphinx contributors + * Released under the two clause BSD licence + */ + +/** + * small helper function to urldecode strings + * + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/decodeURIComponent#Decoding_query_parameters_from_a_URL + */ +jQuery.urldecode = function(x) { + if (!x) { + return x + } + return decodeURIComponent(x.replace(/\+/g, ' ')); +}; + +/** + * small helper function to urlencode strings + */ +jQuery.urlencode = encodeURIComponent; + +/** + * This function returns the parsed url parameters of the + * current request. Multiple values per key are supported, + * it will always return arrays of strings for the value parts. + */ +jQuery.getQueryParameters = function(s) { + if (typeof s === 'undefined') + s = document.location.search; + var parts = s.substr(s.indexOf('?') + 1).split('&'); + var result = {}; + for (var i = 0; i < parts.length; i++) { + var tmp = parts[i].split('=', 2); + var key = jQuery.urldecode(tmp[0]); + var value = jQuery.urldecode(tmp[1]); + if (key in result) + result[key].push(value); + else + result[key] = [value]; + } + return result; +}; + +/** + * highlight a given string on a jquery object by wrapping it in + * span elements with the given class name. + */ +jQuery.fn.highlightText = function(text, className) { + function highlight(node, addItems) { + if (node.nodeType === 3) { + var val = node.nodeValue; + var pos = val.toLowerCase().indexOf(text); + if (pos >= 0 && + !jQuery(node.parentNode).hasClass(className) && + !jQuery(node.parentNode).hasClass("nohighlight")) { + var span; + var isInSVG = jQuery(node).closest("body, svg, foreignObject").is("svg"); + if (isInSVG) { + span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); + } else { + span = document.createElement("span"); + span.className = className; + } + span.appendChild(document.createTextNode(val.substr(pos, text.length))); + node.parentNode.insertBefore(span, node.parentNode.insertBefore( + document.createTextNode(val.substr(pos + text.length)), + node.nextSibling)); + node.nodeValue = val.substr(0, pos); + if (isInSVG) { + var rect = document.createElementNS("http://www.w3.org/2000/svg", "rect"); + var bbox = node.parentElement.getBBox(); + rect.x.baseVal.value = bbox.x; + rect.y.baseVal.value = bbox.y; + rect.width.baseVal.value = bbox.width; + rect.height.baseVal.value = bbox.height; + rect.setAttribute('class', className); + addItems.push({ + "parent": node.parentNode, + "target": rect}); + } + } + } + else if (!jQuery(node).is("button, select, textarea")) { + jQuery.each(node.childNodes, function() { + highlight(this, addItems); + }); + } + } + var addItems = []; + var result = this.each(function() { + highlight(this, addItems); + }); + for (var i = 0; i < addItems.length; ++i) { + jQuery(addItems[i].parent).before(addItems[i].target); + } + return result; +}; + +/* + * backward compatibility for jQuery.browser + * This will be supported until firefox bug is fixed. + */ +if (!jQuery.browser) { + jQuery.uaMatch = function(ua) { + ua = ua.toLowerCase(); + + var match = /(chrome)[ \/]([\w.]+)/.exec(ua) || + /(webkit)[ \/]([\w.]+)/.exec(ua) || + /(opera)(?:.*version|)[ \/]([\w.]+)/.exec(ua) || + /(msie) ([\w.]+)/.exec(ua) || + ua.indexOf("compatible") < 0 && /(mozilla)(?:.*? rv:([\w.]+)|)/.exec(ua) || + []; + + return { + browser: match[ 1 ] || "", + version: match[ 2 ] || "0" + }; + }; + jQuery.browser = {}; + jQuery.browser[jQuery.uaMatch(navigator.userAgent).browser] = true; +} diff --git a/docs/_build/_static/base-stemmer.js b/docs/_build/_static/base-stemmer.js new file mode 100644 index 0000000..e6fa0c4 --- /dev/null +++ b/docs/_build/_static/base-stemmer.js @@ -0,0 +1,476 @@ +// @ts-check + +/**@constructor*/ +BaseStemmer = function() { + /** @protected */ + this.current = ''; + this.cursor = 0; + this.limit = 0; + this.limit_backward = 0; + this.bra = 0; + this.ket = 0; + + /** + * @param {string} value + */ + this.setCurrent = function(value) { + this.current = value; + this.cursor = 0; + this.limit = this.current.length; + this.limit_backward = 0; + this.bra = this.cursor; + this.ket = this.limit; + }; + + /** + * @return {string} + */ + this.getCurrent = function() { + return this.current; + }; + + /** + * @param {BaseStemmer} other + */ + this.copy_from = function(other) { + /** @protected */ + this.current = other.current; + this.cursor = other.cursor; + this.limit = other.limit; + this.limit_backward = other.limit_backward; + this.bra = other.bra; + this.ket = other.ket; + }; + + /** + * @param {number[]} s + * @param {number} min + * @param {number} max + * @return {boolean} + */ + this.in_grouping = function(s, min, max) { + /** @protected */ + if (this.cursor >= this.limit) return false; + var ch = this.current.charCodeAt(this.cursor); + if (ch > max || ch < min) return false; + ch -= min; + if ((s[ch >>> 3] & (0x1 << (ch & 0x7))) == 0) return false; + this.cursor++; + return true; + }; + + /** + * @param {number[]} s + * @param {number} min + * @param {number} max + * @return {boolean} + */ + this.go_in_grouping = function(s, min, max) { + /** @protected */ + while (this.cursor < this.limit) { + var ch = this.current.charCodeAt(this.cursor); + if (ch > max || ch < min) + return true; + ch -= min; + if ((s[ch >>> 3] & (0x1 << (ch & 0x7))) == 0) + return true; + this.cursor++; + } + return false; + }; + + /** + * @param {number[]} s + * @param {number} min + * @param {number} max + * @return {boolean} + */ + this.in_grouping_b = function(s, min, max) { + /** @protected */ + if (this.cursor <= this.limit_backward) return false; + var ch = this.current.charCodeAt(this.cursor - 1); + if (ch > max || ch < min) return false; + ch -= min; + if ((s[ch >>> 3] & (0x1 << (ch & 0x7))) == 0) return false; + this.cursor--; + return true; + }; + + /** + * @param {number[]} s + * @param {number} min + * @param {number} max + * @return {boolean} + */ + this.go_in_grouping_b = function(s, min, max) { + /** @protected */ + while (this.cursor > this.limit_backward) { + var ch = this.current.charCodeAt(this.cursor - 1); + if (ch > max || ch < min) return true; + ch -= min; + if ((s[ch >>> 3] & (0x1 << (ch & 0x7))) == 0) return true; + this.cursor--; + } + return false; + }; + + /** + * @param {number[]} s + * @param {number} min + * @param {number} max + * @return {boolean} + */ + this.out_grouping = function(s, min, max) { + /** @protected */ + if (this.cursor >= this.limit) return false; + var ch = this.current.charCodeAt(this.cursor); + if (ch > max || ch < min) { + this.cursor++; + return true; + } + ch -= min; + if ((s[ch >>> 3] & (0X1 << (ch & 0x7))) == 0) { + this.cursor++; + return true; + } + return false; + }; + + /** + * @param {number[]} s + * @param {number} min + * @param {number} max + * @return {boolean} + */ + this.go_out_grouping = function(s, min, max) { + /** @protected */ + while (this.cursor < this.limit) { + var ch = this.current.charCodeAt(this.cursor); + if (ch <= max && ch >= min) { + ch -= min; + if ((s[ch >>> 3] & (0X1 << (ch & 0x7))) != 0) { + return true; + } + } + this.cursor++; + } + return false; + }; + + /** + * @param {number[]} s + * @param {number} min + * @param {number} max + * @return {boolean} + */ + this.out_grouping_b = function(s, min, max) { + /** @protected */ + if (this.cursor <= this.limit_backward) return false; + var ch = this.current.charCodeAt(this.cursor - 1); + if (ch > max || ch < min) { + this.cursor--; + return true; + } + ch -= min; + if ((s[ch >>> 3] & (0x1 << (ch & 0x7))) == 0) { + this.cursor--; + return true; + } + return false; + }; + + /** + * @param {number[]} s + * @param {number} min + * @param {number} max + * @return {boolean} + */ + this.go_out_grouping_b = function(s, min, max) { + /** @protected */ + while (this.cursor > this.limit_backward) { + var ch = this.current.charCodeAt(this.cursor - 1); + if (ch <= max && ch >= min) { + ch -= min; + if ((s[ch >>> 3] & (0x1 << (ch & 0x7))) != 0) { + return true; + } + } + this.cursor--; + } + return false; + }; + + /** + * @param {string} s + * @return {boolean} + */ + this.eq_s = function(s) + { + /** @protected */ + if (this.limit - this.cursor < s.length) return false; + if (this.current.slice(this.cursor, this.cursor + s.length) != s) + { + return false; + } + this.cursor += s.length; + return true; + }; + + /** + * @param {string} s + * @return {boolean} + */ + this.eq_s_b = function(s) + { + /** @protected */ + if (this.cursor - this.limit_backward < s.length) return false; + if (this.current.slice(this.cursor - s.length, this.cursor) != s) + { + return false; + } + this.cursor -= s.length; + return true; + }; + + /** + * @param {Among[]} v + * @return {number} + */ + this.find_among = function(v) + { + /** @protected */ + var i = 0; + var j = v.length; + + var c = this.cursor; + var l = this.limit; + + var common_i = 0; + var common_j = 0; + + var first_key_inspected = false; + + while (true) + { + var k = i + ((j - i) >>> 1); + var diff = 0; + var common = common_i < common_j ? common_i : common_j; // smaller + // w[0]: string, w[1]: substring_i, w[2]: result, w[3]: function (optional) + var w = v[k]; + var i2; + for (i2 = common; i2 < w[0].length; i2++) + { + if (c + common == l) + { + diff = -1; + break; + } + diff = this.current.charCodeAt(c + common) - w[0].charCodeAt(i2); + if (diff != 0) break; + common++; + } + if (diff < 0) + { + j = k; + common_j = common; + } + else + { + i = k; + common_i = common; + } + if (j - i <= 1) + { + if (i > 0) break; // v->s has been inspected + if (j == i) break; // only one item in v + + // - but now we need to go round once more to get + // v->s inspected. This looks messy, but is actually + // the optimal approach. + + if (first_key_inspected) break; + first_key_inspected = true; + } + } + do { + var w = v[i]; + if (common_i >= w[0].length) + { + this.cursor = c + w[0].length; + if (w.length < 4) return w[2]; + var res = w[3](this); + this.cursor = c + w[0].length; + if (res) return w[2]; + } + i = w[1]; + } while (i >= 0); + return 0; + }; + + // find_among_b is for backwards processing. Same comments apply + /** + * @param {Among[]} v + * @return {number} + */ + this.find_among_b = function(v) + { + /** @protected */ + var i = 0; + var j = v.length + + var c = this.cursor; + var lb = this.limit_backward; + + var common_i = 0; + var common_j = 0; + + var first_key_inspected = false; + + while (true) + { + var k = i + ((j - i) >> 1); + var diff = 0; + var common = common_i < common_j ? common_i : common_j; + var w = v[k]; + var i2; + for (i2 = w[0].length - 1 - common; i2 >= 0; i2--) + { + if (c - common == lb) + { + diff = -1; + break; + } + diff = this.current.charCodeAt(c - 1 - common) - w[0].charCodeAt(i2); + if (diff != 0) break; + common++; + } + if (diff < 0) + { + j = k; + common_j = common; + } + else + { + i = k; + common_i = common; + } + if (j - i <= 1) + { + if (i > 0) break; + if (j == i) break; + if (first_key_inspected) break; + first_key_inspected = true; + } + } + do { + var w = v[i]; + if (common_i >= w[0].length) + { + this.cursor = c - w[0].length; + if (w.length < 4) return w[2]; + var res = w[3](this); + this.cursor = c - w[0].length; + if (res) return w[2]; + } + i = w[1]; + } while (i >= 0); + return 0; + }; + + /* to replace chars between c_bra and c_ket in this.current by the + * chars in s. + */ + /** + * @param {number} c_bra + * @param {number} c_ket + * @param {string} s + * @return {number} + */ + this.replace_s = function(c_bra, c_ket, s) + { + /** @protected */ + var adjustment = s.length - (c_ket - c_bra); + this.current = this.current.slice(0, c_bra) + s + this.current.slice(c_ket); + this.limit += adjustment; + if (this.cursor >= c_ket) this.cursor += adjustment; + else if (this.cursor > c_bra) this.cursor = c_bra; + return adjustment; + }; + + /** + * @return {boolean} + */ + this.slice_check = function() + { + /** @protected */ + if (this.bra < 0 || + this.bra > this.ket || + this.ket > this.limit || + this.limit > this.current.length) + { + return false; + } + return true; + }; + + /** + * @param {number} c_bra + * @return {boolean} + */ + this.slice_from = function(s) + { + /** @protected */ + var result = false; + if (this.slice_check()) + { + this.replace_s(this.bra, this.ket, s); + result = true; + } + return result; + }; + + /** + * @return {boolean} + */ + this.slice_del = function() + { + /** @protected */ + return this.slice_from(""); + }; + + /** + * @param {number} c_bra + * @param {number} c_ket + * @param {string} s + */ + this.insert = function(c_bra, c_ket, s) + { + /** @protected */ + var adjustment = this.replace_s(c_bra, c_ket, s); + if (c_bra <= this.bra) this.bra += adjustment; + if (c_bra <= this.ket) this.ket += adjustment; + }; + + /** + * @return {string} + */ + this.slice_to = function() + { + /** @protected */ + var result = ''; + if (this.slice_check()) + { + result = this.current.slice(this.bra, this.ket); + } + return result; + }; + + /** + * @return {string} + */ + this.assign_to = function() + { + /** @protected */ + return this.current.slice(0, this.limit); + }; +}; diff --git a/docs/_build/_static/basic.css b/docs/_build/_static/basic.css new file mode 100644 index 0000000..4738b2e --- /dev/null +++ b/docs/_build/_static/basic.css @@ -0,0 +1,906 @@ +/* + * Sphinx stylesheet -- basic theme. + */ + +/* -- main layout ----------------------------------------------------------- */ + +div.clearer { + clear: both; +} + +div.section::after { + display: block; + content: ''; + clear: left; +} + +/* -- relbar ---------------------------------------------------------------- */ + +div.related { + width: 100%; + font-size: 90%; +} + +div.related h3 { + display: none; +} + +div.related ul { + margin: 0; + padding: 0 0 0 10px; + list-style: none; +} + +div.related li { + display: inline; +} + +div.related li.right { + float: right; + margin-right: 5px; +} + +/* -- sidebar --------------------------------------------------------------- */ + +div.sphinxsidebarwrapper { + padding: 10px 5px 0 10px; +} + +div.sphinxsidebar { + float: left; + width: 230px; + margin-left: -100%; + font-size: 90%; + word-wrap: break-word; + overflow-wrap : break-word; +} + +div.sphinxsidebar ul { + list-style: none; +} + +div.sphinxsidebar ul ul, +div.sphinxsidebar ul.want-points { + margin-left: 20px; + list-style: square; +} + +div.sphinxsidebar ul ul { + margin-top: 0; + margin-bottom: 0; +} + +div.sphinxsidebar form { + margin-top: 10px; +} + +div.sphinxsidebar input { + border: 1px solid #98dbcc; + font-family: sans-serif; + font-size: 1em; +} + +div.sphinxsidebar #searchbox form.search { + overflow: hidden; +} + +div.sphinxsidebar #searchbox input[type="text"] { + float: left; + width: 80%; + padding: 0.25em; + box-sizing: border-box; +} + +div.sphinxsidebar #searchbox input[type="submit"] { + float: left; + width: 20%; + border-left: none; + padding: 0.25em; + box-sizing: border-box; +} + + +img { + border: 0; + max-width: 100%; +} + +/* -- search page ----------------------------------------------------------- */ + +ul.search { + margin-top: 10px; +} + +ul.search li { + padding: 5px 0; +} + +ul.search li a { + font-weight: bold; +} + +ul.search li p.context { + color: #888; + margin: 2px 0 0 30px; + text-align: left; +} + +ul.keywordmatches li.goodmatch a { + font-weight: bold; +} + +/* -- index page ------------------------------------------------------------ */ + +table.contentstable { + width: 90%; + margin-left: auto; + margin-right: auto; +} + +table.contentstable p.biglink { + line-height: 150%; +} + +a.biglink { + font-size: 1.3em; +} + +span.linkdescr { + font-style: italic; + padding-top: 5px; + font-size: 90%; +} + +/* -- general index --------------------------------------------------------- */ + +table.indextable { + width: 100%; +} + +table.indextable td { + text-align: left; + vertical-align: top; +} + +table.indextable ul { + margin-top: 0; + margin-bottom: 0; + list-style-type: none; +} + +table.indextable > tbody > tr > td > ul { + padding-left: 0em; +} + +table.indextable tr.pcap { + height: 10px; +} + +table.indextable tr.cap { + margin-top: 10px; + background-color: #f2f2f2; +} + +img.toggler { + margin-right: 3px; + margin-top: 3px; + cursor: pointer; +} + +div.modindex-jumpbox { + border-top: 1px solid #ddd; + border-bottom: 1px solid #ddd; + margin: 1em 0 1em 0; + padding: 0.4em; +} + +div.genindex-jumpbox { + border-top: 1px solid #ddd; + border-bottom: 1px solid #ddd; + margin: 1em 0 1em 0; + padding: 0.4em; +} + +/* -- domain module index --------------------------------------------------- */ + +table.modindextable td { + padding: 2px; + border-collapse: collapse; +} + +/* -- general body styles --------------------------------------------------- */ + +div.body { + min-width: 360px; + max-width: 800px; +} + +div.body p, div.body dd, div.body li, div.body blockquote { + -moz-hyphens: auto; + -ms-hyphens: auto; + -webkit-hyphens: auto; + hyphens: auto; +} + +a.headerlink { + visibility: hidden; +} + +a:visited { + color: #551A8B; +} + +h1:hover > a.headerlink, +h2:hover > a.headerlink, +h3:hover > a.headerlink, +h4:hover > a.headerlink, +h5:hover > a.headerlink, +h6:hover > a.headerlink, +dt:hover > a.headerlink, +caption:hover > a.headerlink, +p.caption:hover > a.headerlink, +div.code-block-caption:hover > a.headerlink { + visibility: visible; +} + +div.body p.caption { + text-align: inherit; +} + +div.body td { + text-align: left; +} + +.first { + margin-top: 0 !important; +} + +p.rubric { + margin-top: 30px; + font-weight: bold; +} + +img.align-left, figure.align-left, .figure.align-left, object.align-left { + clear: left; + float: left; + margin-right: 1em; +} + +img.align-right, figure.align-right, .figure.align-right, object.align-right { + clear: right; + float: right; + margin-left: 1em; +} + +img.align-center, figure.align-center, .figure.align-center, object.align-center { + display: block; + margin-left: auto; + margin-right: auto; +} + +img.align-default, figure.align-default, .figure.align-default { + display: block; + margin-left: auto; + margin-right: auto; +} + +.align-left { + text-align: left; +} + +.align-center { + text-align: center; +} + +.align-default { + text-align: center; +} + +.align-right { + text-align: right; +} + +/* -- sidebars -------------------------------------------------------------- */ + +div.sidebar, +aside.sidebar { + margin: 0 0 0.5em 1em; + border: 1px solid #ddb; + padding: 7px; + background-color: #ffe; + width: 40%; + float: right; + clear: right; + overflow-x: auto; +} + +p.sidebar-title { + font-weight: bold; +} + +nav.contents, +aside.topic, +div.admonition, div.topic, blockquote { + clear: left; +} + +/* -- topics ---------------------------------------------------------------- */ + +nav.contents, +aside.topic, +div.topic { + border: 1px solid #ccc; + padding: 7px; + margin: 10px 0 10px 0; +} + +p.topic-title { + font-size: 1.1em; + font-weight: bold; + margin-top: 10px; +} + +/* -- admonitions ----------------------------------------------------------- */ + +div.admonition { + margin-top: 10px; + margin-bottom: 10px; + padding: 7px; +} + +div.admonition dt { + font-weight: bold; +} + +p.admonition-title { + margin: 0px 10px 5px 0px; + font-weight: bold; +} + +div.body p.centered { + text-align: center; + margin-top: 25px; +} + +/* -- content of sidebars/topics/admonitions -------------------------------- */ + +div.sidebar > :last-child, +aside.sidebar > :last-child, +nav.contents > :last-child, +aside.topic > :last-child, +div.topic > :last-child, +div.admonition > :last-child { + margin-bottom: 0; +} + +div.sidebar::after, +aside.sidebar::after, +nav.contents::after, +aside.topic::after, +div.topic::after, +div.admonition::after, +blockquote::after { + display: block; + content: ''; + clear: both; +} + +/* -- tables ---------------------------------------------------------------- */ + +table.docutils { + margin-top: 10px; + margin-bottom: 10px; + border: 0; + border-collapse: collapse; +} + +table.align-center { + margin-left: auto; + margin-right: auto; +} + +table.align-default { + margin-left: auto; + margin-right: auto; +} + +table caption span.caption-number { + font-style: italic; +} + +table caption span.caption-text { +} + +table.docutils td, table.docutils th { + padding: 1px 8px 1px 5px; + border-top: 0; + border-left: 0; + border-right: 0; + border-bottom: 1px solid #aaa; +} + +th { + text-align: left; + padding-right: 5px; +} + +table.citation { + border-left: solid 1px gray; + margin-left: 1px; +} + +table.citation td { + border-bottom: none; +} + +th > :first-child, +td > :first-child { + margin-top: 0px; +} + +th > :last-child, +td > :last-child { + margin-bottom: 0px; +} + +/* -- figures --------------------------------------------------------------- */ + +div.figure, figure { + margin: 0.5em; + padding: 0.5em; +} + +div.figure p.caption, figcaption { + padding: 0.3em; +} + +div.figure p.caption span.caption-number, +figcaption span.caption-number { + font-style: italic; +} + +div.figure p.caption span.caption-text, +figcaption span.caption-text { +} + +/* -- field list styles ----------------------------------------------------- */ + +table.field-list td, table.field-list th { + border: 0 !important; +} + +.field-list ul { + margin: 0; + padding-left: 1em; +} + +.field-list p { + margin: 0; +} + +.field-name { + -moz-hyphens: manual; + -ms-hyphens: manual; + -webkit-hyphens: manual; + hyphens: manual; +} + +/* -- hlist styles ---------------------------------------------------------- */ + +table.hlist { + margin: 1em 0; +} + +table.hlist td { + vertical-align: top; +} + +/* -- object description styles --------------------------------------------- */ + +.sig { + font-family: 'Consolas', 'Menlo', 'DejaVu Sans Mono', 'Bitstream Vera Sans Mono', monospace; +} + +.sig-name, code.descname { + background-color: transparent; + font-weight: bold; +} + +.sig-name { + font-size: 1.1em; +} + +code.descname { + font-size: 1.2em; +} + +.sig-prename, code.descclassname { + background-color: transparent; +} + +.optional { + font-size: 1.3em; +} + +.sig-paren { + font-size: larger; +} + +.sig-param.n { + font-style: italic; +} + +/* C++ specific styling */ + +.sig-inline.c-texpr, +.sig-inline.cpp-texpr { + font-family: unset; +} + +.sig.c .k, .sig.c .kt, +.sig.cpp .k, .sig.cpp .kt { + color: #0033B3; +} + +.sig.c .m, +.sig.cpp .m { + color: #1750EB; +} + +.sig.c .s, .sig.c .sc, +.sig.cpp .s, .sig.cpp .sc { + color: #067D17; +} + + +/* -- other body styles ----------------------------------------------------- */ + +ol.arabic { + list-style: decimal; +} + +ol.loweralpha { + list-style: lower-alpha; +} + +ol.upperalpha { + list-style: upper-alpha; +} + +ol.lowerroman { + list-style: lower-roman; +} + +ol.upperroman { + list-style: upper-roman; +} + +:not(li) > ol > li:first-child > :first-child, +:not(li) > ul > li:first-child > :first-child { + margin-top: 0px; +} + +:not(li) > ol > li:last-child > :last-child, +:not(li) > ul > li:last-child > :last-child { + margin-bottom: 0px; +} + +ol.simple ol p, +ol.simple ul p, +ul.simple ol p, +ul.simple ul p { + margin-top: 0; +} + +ol.simple > li:not(:first-child) > p, +ul.simple > li:not(:first-child) > p { + margin-top: 0; +} + +ol.simple p, +ul.simple p { + margin-bottom: 0; +} + +aside.footnote > span, +div.citation > span { + float: left; +} +aside.footnote > span:last-of-type, +div.citation > span:last-of-type { + padding-right: 0.5em; +} +aside.footnote > p { + margin-left: 2em; +} +div.citation > p { + margin-left: 4em; +} +aside.footnote > p:last-of-type, +div.citation > p:last-of-type { + margin-bottom: 0em; +} +aside.footnote > p:last-of-type:after, +div.citation > p:last-of-type:after { + content: ""; + clear: both; +} + +dl.field-list { + display: grid; + grid-template-columns: fit-content(30%) auto; +} + +dl.field-list > dt { + font-weight: bold; + word-break: break-word; + padding-left: 0.5em; + padding-right: 5px; +} + +dl.field-list > dd { + padding-left: 0.5em; + margin-top: 0em; + margin-left: 0em; + margin-bottom: 0em; +} + +dl { + margin-bottom: 15px; +} + +dd > :first-child { + margin-top: 0px; +} + +dd ul, dd table { + margin-bottom: 10px; +} + +dd { + margin-top: 3px; + margin-bottom: 10px; + margin-left: 30px; +} + +.sig dd { + margin-top: 0px; + margin-bottom: 0px; +} + +.sig dl { + margin-top: 0px; + margin-bottom: 0px; +} + +dl > dd:last-child, +dl > dd:last-child > :last-child { + margin-bottom: 0; +} + +dt:target, span.highlighted { + background-color: #fbe54e; +} + +rect.highlighted { + fill: #fbe54e; +} + +dl.glossary dt { + font-weight: bold; + font-size: 1.1em; +} + +.versionmodified { + font-style: italic; +} + +.system-message { + background-color: #fda; + padding: 5px; + border: 3px solid red; +} + +.footnote:target { + background-color: #ffa; +} + +.line-block { + display: block; + margin-top: 1em; + margin-bottom: 1em; +} + +.line-block .line-block { + margin-top: 0; + margin-bottom: 0; + margin-left: 1.5em; +} + +.guilabel, .menuselection { + font-family: sans-serif; +} + +.accelerator { + text-decoration: underline; +} + +.classifier { + font-style: oblique; +} + +.classifier:before { + font-style: normal; + margin: 0 0.5em; + content: ":"; + display: inline-block; +} + +abbr, acronym { + border-bottom: dotted 1px; + cursor: help; +} + +/* -- code displays --------------------------------------------------------- */ + +pre { + overflow: auto; + overflow-y: hidden; /* fixes display issues on Chrome browsers */ +} + +pre, div[class*="highlight-"] { + clear: both; +} + +span.pre { + -moz-hyphens: none; + -ms-hyphens: none; + -webkit-hyphens: none; + hyphens: none; + white-space: nowrap; +} + +div[class*="highlight-"] { + margin: 1em 0; +} + +td.linenos pre { + border: 0; + background-color: transparent; + color: #aaa; +} + +table.highlighttable { + display: block; +} + +table.highlighttable tbody { + display: block; +} + +table.highlighttable tr { + display: flex; +} + +table.highlighttable td { + margin: 0; + padding: 0; +} + +table.highlighttable td.linenos { + padding-right: 0.5em; +} + +table.highlighttable td.code { + flex: 1; + overflow: hidden; +} + +.highlight .hll { + display: block; +} + +div.highlight pre, +table.highlighttable pre { + margin: 0; +} + +div.code-block-caption + div { + margin-top: 0; +} + +div.code-block-caption { + margin-top: 1em; + padding: 2px 5px; + font-size: small; +} + +div.code-block-caption code { + background-color: transparent; +} + +table.highlighttable td.linenos, +span.linenos, +div.highlight span.gp { /* gp: Generic.Prompt */ + user-select: none; + -webkit-user-select: text; /* Safari fallback only */ + -webkit-user-select: none; /* Chrome/Safari */ + -moz-user-select: none; /* Firefox */ + -ms-user-select: none; /* IE10+ */ +} + +div.code-block-caption span.caption-number { + padding: 0.1em 0.3em; + font-style: italic; +} + +div.code-block-caption span.caption-text { +} + +div.literal-block-wrapper { + margin: 1em 0; +} + +code.xref, a code { + background-color: transparent; + font-weight: bold; +} + +h1 code, h2 code, h3 code, h4 code, h5 code, h6 code { + background-color: transparent; +} + +.viewcode-link { + float: right; +} + +.viewcode-back { + float: right; + font-family: sans-serif; +} + +div.viewcode-block:target { + margin: -1px -10px; + padding: 0 10px; +} + +/* -- math display ---------------------------------------------------------- */ + +img.math { + vertical-align: middle; +} + +div.body div.math p { + text-align: center; +} + +span.eqno { + float: right; +} + +span.eqno a.headerlink { + position: absolute; + z-index: 1; +} + +div.math:hover a.headerlink { + visibility: visible; +} + +/* -- printout stylesheet --------------------------------------------------- */ + +@media print { + div.document, + div.documentwrapper, + div.bodywrapper { + margin: 0 !important; + width: 100%; + } + + div.sphinxsidebar, + div.related, + div.footer, + #top-link { + display: none; + } +} \ No newline at end of file diff --git a/docs/_build/_static/check-solid.svg b/docs/_build/_static/check-solid.svg new file mode 100644 index 0000000..92fad4b --- /dev/null +++ b/docs/_build/_static/check-solid.svg @@ -0,0 +1,4 @@ + + + + diff --git a/docs/_build/_static/clipboard.min.js b/docs/_build/_static/clipboard.min.js new file mode 100644 index 0000000..54b3c46 --- /dev/null +++ b/docs/_build/_static/clipboard.min.js @@ -0,0 +1,7 @@ +/*! + * clipboard.js v2.0.8 + * https://clipboardjs.com/ + * + * Licensed MIT ยฉ Zeno Rocha + */ +!function(t,e){"object"==typeof exports&&"object"==typeof module?module.exports=e():"function"==typeof define&&define.amd?define([],e):"object"==typeof exports?exports.ClipboardJS=e():t.ClipboardJS=e()}(this,function(){return n={686:function(t,e,n){"use strict";n.d(e,{default:function(){return o}});var e=n(279),i=n.n(e),e=n(370),u=n.n(e),e=n(817),c=n.n(e);function a(t){try{return document.execCommand(t)}catch(t){return}}var f=function(t){t=c()(t);return a("cut"),t};var l=function(t){var e,n,o,r=1 + + + + diff --git a/docs/_build/_static/copybutton.css b/docs/_build/_static/copybutton.css new file mode 100644 index 0000000..f1916ec --- /dev/null +++ b/docs/_build/_static/copybutton.css @@ -0,0 +1,94 @@ +/* Copy buttons */ +button.copybtn { + position: absolute; + display: flex; + top: .3em; + right: .3em; + width: 1.7em; + height: 1.7em; + opacity: 0; + transition: opacity 0.3s, border .3s, background-color .3s; + user-select: none; + padding: 0; + border: none; + outline: none; + border-radius: 0.4em; + /* The colors that GitHub uses */ + border: #1b1f2426 1px solid; + background-color: #f6f8fa; + color: #57606a; +} + +button.copybtn.success { + border-color: #22863a; + color: #22863a; +} + +button.copybtn svg { + stroke: currentColor; + width: 1.5em; + height: 1.5em; + padding: 0.1em; +} + +div.highlight { + position: relative; +} + +/* Show the copybutton */ +.highlight:hover button.copybtn, button.copybtn.success { + opacity: 1; +} + +.highlight button.copybtn:hover { + background-color: rgb(235, 235, 235); +} + +.highlight button.copybtn:active { + background-color: rgb(187, 187, 187); +} + +/** + * A minimal CSS-only tooltip copied from: + * https://codepen.io/mildrenben/pen/rVBrpK + * + * To use, write HTML like the following: + * + *

Short

+ */ + .o-tooltip--left { + position: relative; + } + + .o-tooltip--left:after { + opacity: 0; + visibility: hidden; + position: absolute; + content: attr(data-tooltip); + padding: .2em; + font-size: .8em; + left: -.2em; + background: grey; + color: white; + white-space: nowrap; + z-index: 2; + border-radius: 2px; + transform: translateX(-102%) translateY(0); + transition: opacity 0.2s cubic-bezier(0.64, 0.09, 0.08, 1), transform 0.2s cubic-bezier(0.64, 0.09, 0.08, 1); +} + +.o-tooltip--left:hover:after { + display: block; + opacity: 1; + visibility: visible; + transform: translateX(-100%) translateY(0); + transition: opacity 0.2s cubic-bezier(0.64, 0.09, 0.08, 1), transform 0.2s cubic-bezier(0.64, 0.09, 0.08, 1); + transition-delay: .5s; +} + +/* By default the copy button shouldn't show up when printing a page */ +@media print { + button.copybtn { + display: none; + } +} diff --git a/docs/_build/_static/copybutton.js b/docs/_build/_static/copybutton.js new file mode 100644 index 0000000..2ea7ff3 --- /dev/null +++ b/docs/_build/_static/copybutton.js @@ -0,0 +1,248 @@ +// Localization support +const messages = { + 'en': { + 'copy': 'Copy', + 'copy_to_clipboard': 'Copy to clipboard', + 'copy_success': 'Copied!', + 'copy_failure': 'Failed to copy', + }, + 'es' : { + 'copy': 'Copiar', + 'copy_to_clipboard': 'Copiar al portapapeles', + 'copy_success': 'ยกCopiado!', + 'copy_failure': 'Error al copiar', + }, + 'de' : { + 'copy': 'Kopieren', + 'copy_to_clipboard': 'In die Zwischenablage kopieren', + 'copy_success': 'Kopiert!', + 'copy_failure': 'Fehler beim Kopieren', + }, + 'fr' : { + 'copy': 'Copier', + 'copy_to_clipboard': 'Copier dans le presse-papier', + 'copy_success': 'Copiรฉ !', + 'copy_failure': 'ร‰chec de la copie', + }, + 'ru': { + 'copy': 'ะกะบะพะฟะธั€ะพะฒะฐั‚ัŒ', + 'copy_to_clipboard': 'ะกะบะพะฟะธั€ะพะฒะฐั‚ัŒ ะฒ ะฑัƒั„ะตั€', + 'copy_success': 'ะกะบะพะฟะธั€ะพะฒะฐะฝะพ!', + 'copy_failure': 'ะะต ัƒะดะฐะปะพััŒ ัะบะพะฟะธั€ะพะฒะฐั‚ัŒ', + }, + 'zh-CN': { + 'copy': 'ๅคๅˆถ', + 'copy_to_clipboard': 'ๅคๅˆถๅˆฐๅ‰ช่ดดๆฟ', + 'copy_success': 'ๅคๅˆถๆˆๅŠŸ!', + 'copy_failure': 'ๅคๅˆถๅคฑ่ดฅ', + }, + 'it' : { + 'copy': 'Copiare', + 'copy_to_clipboard': 'Copiato negli appunti', + 'copy_success': 'Copiato!', + 'copy_failure': 'Errore durante la copia', + } +} + +let locale = 'en' +if( document.documentElement.lang !== undefined + && messages[document.documentElement.lang] !== undefined ) { + locale = document.documentElement.lang +} + +let doc_url_root = DOCUMENTATION_OPTIONS.URL_ROOT; +if (doc_url_root == '#') { + doc_url_root = ''; +} + +/** + * SVG files for our copy buttons + */ +let iconCheck = ` + ${messages[locale]['copy_success']} + + +` + +// If the user specified their own SVG use that, otherwise use the default +let iconCopy = ``; +if (!iconCopy) { + iconCopy = ` + ${messages[locale]['copy_to_clipboard']} + + + +` +} + +/** + * Set up copy/paste for code blocks + */ + +const runWhenDOMLoaded = cb => { + if (document.readyState != 'loading') { + cb() + } else if (document.addEventListener) { + document.addEventListener('DOMContentLoaded', cb) + } else { + document.attachEvent('onreadystatechange', function() { + if (document.readyState == 'complete') cb() + }) + } +} + +const codeCellId = index => `codecell${index}` + +// Clears selected text since ClipboardJS will select the text when copying +const clearSelection = () => { + if (window.getSelection) { + window.getSelection().removeAllRanges() + } else if (document.selection) { + document.selection.empty() + } +} + +// Changes tooltip text for a moment, then changes it back +// We want the timeout of our `success` class to be a bit shorter than the +// tooltip and icon change, so that we can hide the icon before changing back. +var timeoutIcon = 2000; +var timeoutSuccessClass = 1500; + +const temporarilyChangeTooltip = (el, oldText, newText) => { + el.setAttribute('data-tooltip', newText) + el.classList.add('success') + // Remove success a little bit sooner than we change the tooltip + // So that we can use CSS to hide the copybutton first + setTimeout(() => el.classList.remove('success'), timeoutSuccessClass) + setTimeout(() => el.setAttribute('data-tooltip', oldText), timeoutIcon) +} + +// Changes the copy button icon for two seconds, then changes it back +const temporarilyChangeIcon = (el) => { + el.innerHTML = iconCheck; + setTimeout(() => {el.innerHTML = iconCopy}, timeoutIcon) +} + +const addCopyButtonToCodeCells = () => { + // If ClipboardJS hasn't loaded, wait a bit and try again. This + // happens because we load ClipboardJS asynchronously. + if (window.ClipboardJS === undefined) { + setTimeout(addCopyButtonToCodeCells, 250) + return + } + + // Add copybuttons to all of our code cells + const COPYBUTTON_SELECTOR = 'div.highlight pre'; + const codeCells = document.querySelectorAll(COPYBUTTON_SELECTOR) + codeCells.forEach((codeCell, index) => { + const id = codeCellId(index) + codeCell.setAttribute('id', id) + + const clipboardButton = id => + `` + codeCell.insertAdjacentHTML('afterend', clipboardButton(id)) + }) + +function escapeRegExp(string) { + return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string +} + +/** + * Removes excluded text from a Node. + * + * @param {Node} target Node to filter. + * @param {string} exclude CSS selector of nodes to exclude. + * @returns {DOMString} Text from `target` with text removed. + */ +function filterText(target, exclude) { + const clone = target.cloneNode(true); // clone as to not modify the live DOM + if (exclude) { + // remove excluded nodes + clone.querySelectorAll(exclude).forEach(node => node.remove()); + } + return clone.innerText; +} + +// Callback when a copy button is clicked. Will be passed the node that was clicked +// should then grab the text and replace pieces of text that shouldn't be used in output +function formatCopyText(textContent, copybuttonPromptText, isRegexp = false, onlyCopyPromptLines = true, removePrompts = true, copyEmptyLines = true, lineContinuationChar = "", hereDocDelim = "") { + var regexp; + var match; + + // Do we check for line continuation characters and "HERE-documents"? + var useLineCont = !!lineContinuationChar + var useHereDoc = !!hereDocDelim + + // create regexp to capture prompt and remaining line + if (isRegexp) { + regexp = new RegExp('^(' + copybuttonPromptText + ')(.*)') + } else { + regexp = new RegExp('^(' + escapeRegExp(copybuttonPromptText) + ')(.*)') + } + + const outputLines = []; + var promptFound = false; + var gotLineCont = false; + var gotHereDoc = false; + const lineGotPrompt = []; + for (const line of textContent.split('\n')) { + match = line.match(regexp) + if (match || gotLineCont || gotHereDoc) { + promptFound = regexp.test(line) + lineGotPrompt.push(promptFound) + if (removePrompts && promptFound) { + outputLines.push(match[2]) + } else { + outputLines.push(line) + } + gotLineCont = line.endsWith(lineContinuationChar) & useLineCont + if (line.includes(hereDocDelim) & useHereDoc) + gotHereDoc = !gotHereDoc + } else if (!onlyCopyPromptLines) { + outputLines.push(line) + } else if (copyEmptyLines && line.trim() === '') { + outputLines.push(line) + } + } + + // If no lines with the prompt were found then just use original lines + if (lineGotPrompt.some(v => v === true)) { + textContent = outputLines.join('\n'); + } + + // Remove a trailing newline to avoid auto-running when pasting + if (textContent.endsWith("\n")) { + textContent = textContent.slice(0, -1) + } + return textContent +} + + +var copyTargetText = (trigger) => { + var target = document.querySelector(trigger.attributes['data-clipboard-target'].value); + + // get filtered text + let exclude = '.linenos'; + + let text = filterText(target, exclude); + return formatCopyText(text, '', false, true, true, true, '', '') +} + + // Initialize with a callback so we can modify the text before copy + const clipboard = new ClipboardJS('.copybtn', {text: copyTargetText}) + + // Update UI with error/success messages + clipboard.on('success', event => { + clearSelection() + temporarilyChangeTooltip(event.trigger, messages[locale]['copy'], messages[locale]['copy_success']) + temporarilyChangeIcon(event.trigger) + }) + + clipboard.on('error', event => { + temporarilyChangeTooltip(event.trigger, messages[locale]['copy'], messages[locale]['copy_failure']) + }) +} + +runWhenDOMLoaded(addCopyButtonToCodeCells) \ No newline at end of file diff --git a/docs/_build/_static/copybutton_funcs.js b/docs/_build/_static/copybutton_funcs.js new file mode 100644 index 0000000..dbe1aaa --- /dev/null +++ b/docs/_build/_static/copybutton_funcs.js @@ -0,0 +1,73 @@ +function escapeRegExp(string) { + return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string +} + +/** + * Removes excluded text from a Node. + * + * @param {Node} target Node to filter. + * @param {string} exclude CSS selector of nodes to exclude. + * @returns {DOMString} Text from `target` with text removed. + */ +export function filterText(target, exclude) { + const clone = target.cloneNode(true); // clone as to not modify the live DOM + if (exclude) { + // remove excluded nodes + clone.querySelectorAll(exclude).forEach(node => node.remove()); + } + return clone.innerText; +} + +// Callback when a copy button is clicked. Will be passed the node that was clicked +// should then grab the text and replace pieces of text that shouldn't be used in output +export function formatCopyText(textContent, copybuttonPromptText, isRegexp = false, onlyCopyPromptLines = true, removePrompts = true, copyEmptyLines = true, lineContinuationChar = "", hereDocDelim = "") { + var regexp; + var match; + + // Do we check for line continuation characters and "HERE-documents"? + var useLineCont = !!lineContinuationChar + var useHereDoc = !!hereDocDelim + + // create regexp to capture prompt and remaining line + if (isRegexp) { + regexp = new RegExp('^(' + copybuttonPromptText + ')(.*)') + } else { + regexp = new RegExp('^(' + escapeRegExp(copybuttonPromptText) + ')(.*)') + } + + const outputLines = []; + var promptFound = false; + var gotLineCont = false; + var gotHereDoc = false; + const lineGotPrompt = []; + for (const line of textContent.split('\n')) { + match = line.match(regexp) + if (match || gotLineCont || gotHereDoc) { + promptFound = regexp.test(line) + lineGotPrompt.push(promptFound) + if (removePrompts && promptFound) { + outputLines.push(match[2]) + } else { + outputLines.push(line) + } + gotLineCont = line.endsWith(lineContinuationChar) & useLineCont + if (line.includes(hereDocDelim) & useHereDoc) + gotHereDoc = !gotHereDoc + } else if (!onlyCopyPromptLines) { + outputLines.push(line) + } else if (copyEmptyLines && line.trim() === '') { + outputLines.push(line) + } + } + + // If no lines with the prompt were found then just use original lines + if (lineGotPrompt.some(v => v === true)) { + textContent = outputLines.join('\n'); + } + + // Remove a trailing newline to avoid auto-running when pasting + if (textContent.endsWith("\n")) { + textContent = textContent.slice(0, -1) + } + return textContent +} diff --git a/docs/_build/_static/css/badge_only.css b/docs/_build/_static/css/badge_only.css new file mode 100644 index 0000000..88ba55b --- /dev/null +++ b/docs/_build/_static/css/badge_only.css @@ 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"unknown", + + // gettext and ngettext don't access this so that the functions + // can safely bound to a different name (_ = Documentation.gettext) + gettext: (string) => { + const translated = Documentation.TRANSLATIONS[string]; + switch (typeof translated) { + case "undefined": + return string; // no translation + case "string": + return translated; // translation exists + default: + return translated[0]; // (singular, plural) translation tuple exists + } + }, + + ngettext: (singular, plural, n) => { + const translated = Documentation.TRANSLATIONS[singular]; + if (typeof translated !== "undefined") + return translated[Documentation.PLURAL_EXPR(n)]; + return n === 1 ? singular : plural; + }, + + addTranslations: (catalog) => { + Object.assign(Documentation.TRANSLATIONS, catalog.messages); + Documentation.PLURAL_EXPR = new Function( + "n", + `return (${catalog.plural_expr})`, + ); + Documentation.LOCALE = catalog.locale; + }, + + /** + * helper function to focus on search bar + */ + focusSearchBar: () => { + document.querySelectorAll("input[name=q]")[0]?.focus(); + }, + + /** + * Initialise the domain index toggle buttons + */ + initDomainIndexTable: () => { + const toggler = (el) => { + const idNumber = el.id.substr(7); + const toggledRows = document.querySelectorAll(`tr.cg-${idNumber}`); + if (el.src.substr(-9) === "minus.png") { + el.src = `${el.src.substr(0, el.src.length - 9)}plus.png`; + toggledRows.forEach((el) => (el.style.display = "none")); + } else { + el.src = `${el.src.substr(0, el.src.length - 8)}minus.png`; + toggledRows.forEach((el) => (el.style.display = "")); + } + }; + + const togglerElements = document.querySelectorAll("img.toggler"); + togglerElements.forEach((el) => + el.addEventListener("click", (event) => toggler(event.currentTarget)), + ); + togglerElements.forEach((el) => (el.style.display = "")); + if (DOCUMENTATION_OPTIONS.COLLAPSE_INDEX) togglerElements.forEach(toggler); + }, + + initOnKeyListeners: () => { + // only install a listener if it is really needed + if ( + !DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS + && !DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS + ) + return; + + document.addEventListener("keydown", (event) => { + // bail for input elements + if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) + return; + // bail with special keys + if (event.altKey || event.ctrlKey || event.metaKey) return; + + if (!event.shiftKey) { + switch (event.key) { + case "ArrowLeft": + if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break; + + const prevLink = document.querySelector('link[rel="prev"]'); + if (prevLink && prevLink.href) { + window.location.href = prevLink.href; + event.preventDefault(); + } + break; + case "ArrowRight": + if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break; + + const nextLink = document.querySelector('link[rel="next"]'); + if (nextLink && nextLink.href) { + window.location.href = nextLink.href; + event.preventDefault(); + } + break; + } + } + + // some keyboard layouts may need Shift to get / + switch (event.key) { + case "/": + if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) break; + Documentation.focusSearchBar(); + event.preventDefault(); + } + }); + }, +}; + +// quick alias for translations +const _ = Documentation.gettext; + +_ready(Documentation.init); diff --git a/docs/_build/_static/documentation_options.js b/docs/_build/_static/documentation_options.js new file mode 100644 index 0000000..13d90ff --- /dev/null +++ b/docs/_build/_static/documentation_options.js @@ -0,0 +1,13 @@ +const DOCUMENTATION_OPTIONS = { + VERSION: '0.1.0', + LANGUAGE: 'en', + COLLAPSE_INDEX: false, + BUILDER: 'html', + FILE_SUFFIX: '.html', + LINK_SUFFIX: '.html', + HAS_SOURCE: true, + SOURCELINK_SUFFIX: '.txt', + NAVIGATION_WITH_KEYS: false, + SHOW_SEARCH_SUMMARY: true, + ENABLE_SEARCH_SHORTCUTS: true, +}; \ No newline at end of file diff --git a/docs/_build/_static/english-stemmer.js b/docs/_build/_static/english-stemmer.js new file mode 100644 index 0000000..056760e --- /dev/null +++ b/docs/_build/_static/english-stemmer.js @@ -0,0 +1,1066 @@ +// Generated from english.sbl by Snowball 3.0.1 - https://snowballstem.org/ + +/**@constructor*/ +var EnglishStemmer = function() { + var base = new BaseStemmer(); + + /** @const */ var a_0 = [ + ["arsen", -1, -1], + ["commun", -1, -1], + ["emerg", -1, -1], + ["gener", -1, -1], + ["later", -1, -1], + ["organ", -1, -1], + ["past", -1, -1], + ["univers", -1, -1] + ]; + + /** @const */ var a_1 = [ + ["'", -1, 1], + ["'s'", 0, 1], + ["'s", -1, 1] + ]; + + /** @const */ var a_2 = [ + ["ied", -1, 2], + ["s", -1, 3], + ["ies", 1, 2], + ["sses", 1, 1], + ["ss", 1, -1], + ["us", 1, -1] + ]; + + /** @const */ var a_3 = [ + ["succ", -1, 1], + ["proc", -1, 1], + ["exc", -1, 1] + ]; + + /** @const */ var a_4 = [ + ["even", -1, 2], + ["cann", -1, 2], + ["inn", -1, 2], + ["earr", -1, 2], + ["herr", -1, 2], + ["out", -1, 2], + ["y", -1, 1] + ]; + + /** @const */ var a_5 = [ + ["", -1, -1], + ["ed", 0, 2], + ["eed", 1, 1], + ["ing", 0, 3], + ["edly", 0, 2], + ["eedly", 4, 1], + ["ingly", 0, 2] + ]; + + /** @const */ var a_6 = [ + ["", -1, 3], + ["bb", 0, 2], + ["dd", 0, 2], + ["ff", 0, 2], + ["gg", 0, 2], + ["bl", 0, 1], + ["mm", 0, 2], + ["nn", 0, 2], + ["pp", 0, 2], + ["rr", 0, 2], + ["at", 0, 1], + ["tt", 0, 2], + ["iz", 0, 1] + ]; + + /** @const */ var a_7 = [ + ["anci", -1, 3], + ["enci", -1, 2], + ["ogi", -1, 14], + ["li", -1, 16], + ["bli", 3, 12], + ["abli", 4, 4], + ["alli", 3, 8], + ["fulli", 3, 9], + ["lessli", 3, 15], + ["ousli", 3, 10], + ["entli", 3, 5], + ["aliti", -1, 8], + ["biliti", -1, 12], + ["iviti", -1, 11], + ["tional", -1, 1], + ["ational", 14, 7], + ["alism", -1, 8], + ["ation", -1, 7], + ["ization", 17, 6], + ["izer", -1, 6], + ["ator", -1, 7], + ["iveness", -1, 11], + ["fulness", -1, 9], + ["ousness", -1, 10], + ["ogist", -1, 13] + ]; + + /** @const */ var a_8 = [ + ["icate", -1, 4], + ["ative", -1, 6], + ["alize", -1, 3], + ["iciti", -1, 4], + ["ical", -1, 4], + ["tional", -1, 1], + ["ational", 5, 2], + ["ful", -1, 5], + ["ness", -1, 5] + ]; + + /** @const */ var a_9 = [ + ["ic", -1, 1], + ["ance", -1, 1], + ["ence", -1, 1], + ["able", -1, 1], + ["ible", -1, 1], + ["ate", -1, 1], + ["ive", -1, 1], + ["ize", -1, 1], + ["iti", -1, 1], + ["al", -1, 1], + ["ism", -1, 1], + ["ion", -1, 2], + ["er", -1, 1], + ["ous", -1, 1], + ["ant", -1, 1], + ["ent", -1, 1], + ["ment", 15, 1], + ["ement", 16, 1] + ]; + + /** @const */ var a_10 = [ + ["e", -1, 1], + ["l", -1, 2] + ]; + + /** @const */ var a_11 = [ + ["andes", -1, -1], + ["atlas", -1, -1], + ["bias", -1, -1], + ["cosmos", -1, -1], + ["early", -1, 5], + ["gently", -1, 3], + ["howe", -1, -1], + ["idly", -1, 2], + ["news", -1, -1], + ["only", -1, 6], + ["singly", -1, 7], + ["skies", -1, 1], + ["sky", -1, -1], + ["ugly", -1, 4] + ]; + + /** @const */ var /** Array */ g_aeo = [17, 64]; + + /** @const */ var /** Array */ g_v = [17, 65, 16, 1]; + + /** @const */ var /** Array */ g_v_WXY = [1, 17, 65, 208, 1]; + + /** @const */ var /** Array */ g_valid_LI = [55, 141, 2]; + + var /** boolean */ B_Y_found = false; + var /** number */ I_p2 = 0; + var /** number */ I_p1 = 0; + + + /** @return {boolean} */ + function r_prelude() { + B_Y_found = false; + /** @const */ var /** number */ v_1 = base.cursor; + lab0: { + base.bra = base.cursor; + if (!(base.eq_s("'"))) + { + break lab0; + } + base.ket = base.cursor; + if (!base.slice_del()) + { + return false; + } + } + base.cursor = v_1; + /** @const */ var /** number */ v_2 = base.cursor; + lab1: { + base.bra = base.cursor; + if (!(base.eq_s("y"))) + { + break lab1; + } + base.ket = base.cursor; + if (!base.slice_from("Y")) + { + return false; + } + B_Y_found = true; + } + base.cursor = v_2; + /** @const */ var /** number */ v_3 = base.cursor; + lab2: { + while(true) + { + /** @const */ var /** number */ v_4 = base.cursor; + lab3: { + golab4: while(true) + { + /** @const */ var /** number */ v_5 = base.cursor; + lab5: { + if (!(base.in_grouping(g_v, 97, 121))) + { + break lab5; + } + base.bra = base.cursor; + if (!(base.eq_s("y"))) + { + break lab5; + } + base.ket = base.cursor; + base.cursor = v_5; + break golab4; + } + base.cursor = v_5; + if (base.cursor >= base.limit) + { + break lab3; + } + base.cursor++; + } + if (!base.slice_from("Y")) + { + return false; + } + B_Y_found = true; + continue; + } + base.cursor = v_4; + break; + } + } + base.cursor = v_3; + return true; + }; + + /** @return {boolean} */ + function r_mark_regions() { + I_p1 = base.limit; + I_p2 = base.limit; + /** @const */ var /** number */ v_1 = base.cursor; + lab0: { + lab1: { + /** @const */ var /** number */ v_2 = base.cursor; + lab2: { + if (base.find_among(a_0) == 0) + { + break lab2; + } + break lab1; + } + base.cursor = v_2; + if (!base.go_out_grouping(g_v, 97, 121)) + { + break lab0; + } + base.cursor++; + if (!base.go_in_grouping(g_v, 97, 121)) + { + break lab0; + } + base.cursor++; + } + I_p1 = base.cursor; + if (!base.go_out_grouping(g_v, 97, 121)) + { + break lab0; + } + base.cursor++; + if (!base.go_in_grouping(g_v, 97, 121)) + { + break lab0; + } + base.cursor++; + I_p2 = base.cursor; + } + base.cursor = v_1; + return true; + }; + + /** @return {boolean} */ + function r_shortv() { + lab0: { + /** @const */ var /** number */ v_1 = base.limit - base.cursor; + lab1: { + if (!(base.out_grouping_b(g_v_WXY, 89, 121))) + { + break lab1; + } + if (!(base.in_grouping_b(g_v, 97, 121))) + { + break lab1; + } + if (!(base.out_grouping_b(g_v, 97, 121))) + { + break lab1; + } + break lab0; + } + base.cursor = base.limit - v_1; + lab2: { + if (!(base.out_grouping_b(g_v, 97, 121))) + { + break lab2; + } + if (!(base.in_grouping_b(g_v, 97, 121))) + { + break lab2; + } + if (base.cursor > base.limit_backward) + { + break lab2; + } + break lab0; + } + base.cursor = base.limit - v_1; + if (!(base.eq_s_b("past"))) + { + return false; + } + } + return true; + }; + + /** @return {boolean} */ + function r_R1() { + return I_p1 <= base.cursor; + }; + + /** @return {boolean} */ + function r_R2() { + return I_p2 <= base.cursor; + }; + + /** @return {boolean} */ + function r_Step_1a() { + var /** number */ among_var; + /** @const */ var /** number */ v_1 = base.limit - base.cursor; + lab0: { + base.ket = base.cursor; + if (base.find_among_b(a_1) == 0) + { + base.cursor = base.limit - v_1; + break lab0; + } + base.bra = base.cursor; + if (!base.slice_del()) + { + return false; + } + } + base.ket = base.cursor; + among_var = base.find_among_b(a_2); + if (among_var == 0) + { + return false; + } + base.bra = base.cursor; + switch (among_var) { + case 1: + if (!base.slice_from("ss")) + { + return false; + } + break; + case 2: + lab1: { + /** @const */ var /** number */ v_2 = base.limit - base.cursor; + lab2: { + { + /** @const */ var /** number */ c1 = base.cursor - 2; + if (c1 < base.limit_backward) + { + break lab2; + } + base.cursor = c1; + } + if (!base.slice_from("i")) + { + return false; + } + break lab1; + } + base.cursor = base.limit - v_2; + if (!base.slice_from("ie")) + { + return false; + } + } + break; + case 3: + if (base.cursor <= base.limit_backward) + { + return false; + } + base.cursor--; + if (!base.go_out_grouping_b(g_v, 97, 121)) + { + return false; + } + base.cursor--; + if (!base.slice_del()) + { + return false; + } + break; + } + return true; + }; + + /** @return {boolean} */ + function r_Step_1b() { + var /** number */ among_var; + base.ket = base.cursor; + among_var = base.find_among_b(a_5); + base.bra = base.cursor; + lab0: { + /** @const */ var /** number */ v_1 = base.limit - base.cursor; + lab1: { + switch (among_var) { + case 1: + /** @const */ var /** number */ v_2 = base.limit - base.cursor; + lab2: { + lab3: { + /** @const */ var /** number */ v_3 = base.limit - base.cursor; + lab4: { + if (base.find_among_b(a_3) == 0) + { + break lab4; + } + if (base.cursor > base.limit_backward) + { + break lab4; + } + break lab3; + } + base.cursor = base.limit - v_3; + if (!r_R1()) + { + break lab2; + } + if (!base.slice_from("ee")) + { + return false; + } + } + } + base.cursor = base.limit - v_2; + break; + case 2: + break lab1; + case 3: + among_var = base.find_among_b(a_4); + if (among_var == 0) + { + break lab1; + } + switch (among_var) { + case 1: + /** @const */ var /** number */ v_4 = base.limit - base.cursor; + if (!(base.out_grouping_b(g_v, 97, 121))) + { + break lab1; + } + if (base.cursor > base.limit_backward) + { + break lab1; + } + base.cursor = base.limit - v_4; + base.bra = base.cursor; + if (!base.slice_from("ie")) + { + return false; + } + break; + case 2: + if (base.cursor > base.limit_backward) + { + break lab1; + } + break; + } + break; + } + break lab0; + } + base.cursor = base.limit - v_1; + /** @const */ var /** number */ v_5 = base.limit - base.cursor; + if (!base.go_out_grouping_b(g_v, 97, 121)) + { + return false; + } + base.cursor--; + base.cursor = base.limit - v_5; + if (!base.slice_del()) + { + return false; + } + base.ket = base.cursor; + base.bra = base.cursor; + /** @const */ var /** number */ v_6 = base.limit - base.cursor; + among_var = base.find_among_b(a_6); + switch (among_var) { + case 1: + if (!base.slice_from("e")) + { + return false; + } + return false; + case 2: + { + /** @const */ var /** number */ v_7 = base.limit - base.cursor; + lab5: { + if (!(base.in_grouping_b(g_aeo, 97, 111))) + { + break lab5; + } + if (base.cursor > base.limit_backward) + { + break lab5; + } + return false; + } + base.cursor = base.limit - v_7; + } + break; + case 3: + if (base.cursor != I_p1) + { + return false; + } + /** @const */ var /** number */ v_8 = base.limit - base.cursor; + if (!r_shortv()) + { + return false; + } + base.cursor = base.limit - v_8; + if (!base.slice_from("e")) + { + return false; + } + return false; + } + base.cursor = base.limit - v_6; + base.ket = base.cursor; + if (base.cursor <= base.limit_backward) + { + return false; + } + base.cursor--; + base.bra = base.cursor; + if (!base.slice_del()) + { + return false; + } + } + return true; + }; + + /** @return {boolean} */ + function r_Step_1c() { + base.ket = base.cursor; + lab0: { + /** @const */ var /** number */ v_1 = base.limit - base.cursor; + lab1: { + if (!(base.eq_s_b("y"))) + { + break lab1; + } + break lab0; + } + base.cursor = base.limit - v_1; + if (!(base.eq_s_b("Y"))) + { + return false; + } + } + base.bra = base.cursor; + if (!(base.out_grouping_b(g_v, 97, 121))) + { + return false; + } + lab2: { + if (base.cursor > base.limit_backward) + { + break lab2; + } + return false; + } + if (!base.slice_from("i")) + { + return false; + } + return true; + }; + + /** @return {boolean} */ + function r_Step_2() { + var /** number */ among_var; + base.ket = base.cursor; + among_var = base.find_among_b(a_7); + if (among_var == 0) + { + return false; + } + base.bra = base.cursor; + if (!r_R1()) + { + return false; + } + switch (among_var) { + case 1: + if (!base.slice_from("tion")) + { + return false; + } + break; + case 2: + if (!base.slice_from("ence")) + { + return false; + } + break; + case 3: + if (!base.slice_from("ance")) + { + return false; + } + break; + case 4: + if (!base.slice_from("able")) + { + return false; + } + break; + case 5: + if (!base.slice_from("ent")) + { + return false; + } + break; + case 6: + if (!base.slice_from("ize")) + { + return false; + } + break; + case 7: + if (!base.slice_from("ate")) + { + return false; + } + break; + case 8: + if (!base.slice_from("al")) + { + return false; + } + break; + case 9: + if (!base.slice_from("ful")) + { + return false; + } + break; + case 10: + if (!base.slice_from("ous")) + { + return false; + } + break; + case 11: + if (!base.slice_from("ive")) + { + return false; + } + break; + case 12: + if (!base.slice_from("ble")) + { + return false; + } + break; + case 13: + if (!base.slice_from("og")) + { + return false; + } + break; + case 14: + if (!(base.eq_s_b("l"))) + { + return false; + } + if (!base.slice_from("og")) + { + return false; + } + break; + case 15: + if (!base.slice_from("less")) + { + return false; + } + break; + case 16: + if (!(base.in_grouping_b(g_valid_LI, 99, 116))) + { + return false; + } + if (!base.slice_del()) + { + return false; + } + break; + } + return true; + }; + + /** @return {boolean} */ + function r_Step_3() { + var /** number */ among_var; + base.ket = base.cursor; + among_var = base.find_among_b(a_8); + if (among_var == 0) + { + return false; + } + base.bra = base.cursor; + if (!r_R1()) + { + return false; + } + switch (among_var) { + case 1: + if (!base.slice_from("tion")) + { + return false; + } + break; + case 2: + if (!base.slice_from("ate")) + { + return false; + } + break; + case 3: + if (!base.slice_from("al")) + { + return false; + } + break; + case 4: + if (!base.slice_from("ic")) + { + return false; + } + break; + case 5: + if (!base.slice_del()) + { + return false; + } + break; + case 6: + if (!r_R2()) + { + return false; + } + if (!base.slice_del()) + { + return false; + } + break; + } + return true; + }; + + /** @return {boolean} */ + function r_Step_4() { + var /** number */ among_var; + base.ket = base.cursor; + among_var = base.find_among_b(a_9); + if (among_var == 0) + { + return false; + } + base.bra = base.cursor; + if (!r_R2()) + { + return false; + } + switch (among_var) { + case 1: + if (!base.slice_del()) + { + return false; + } + break; + case 2: + lab0: { + /** @const */ var /** number */ v_1 = base.limit - base.cursor; + lab1: { + if (!(base.eq_s_b("s"))) + { + break lab1; + } + break lab0; + } + base.cursor = base.limit - v_1; + if (!(base.eq_s_b("t"))) + { + return false; + } + } + if (!base.slice_del()) + { + return false; + } + break; + } + return true; + }; + + /** @return {boolean} */ + function r_Step_5() { + var /** number */ among_var; + base.ket = base.cursor; + among_var = base.find_among_b(a_10); + if (among_var == 0) + { + return false; + } + base.bra = base.cursor; + switch (among_var) { + case 1: + lab0: { + lab1: { + if (!r_R2()) + { + break lab1; + } + break lab0; + } + if (!r_R1()) + { + return false; + } + { + /** @const */ var /** number */ v_1 = base.limit - base.cursor; + lab2: { + if (!r_shortv()) + { + break lab2; + } + return false; + } + base.cursor = base.limit - v_1; + } + } + if (!base.slice_del()) + { + return false; + } + break; + case 2: + if (!r_R2()) + { + return false; + } + if (!(base.eq_s_b("l"))) + { + return false; + } + if (!base.slice_del()) + { + return false; + } + break; + } + return true; + }; + + /** @return {boolean} */ + function r_exception1() { + var /** number */ among_var; + base.bra = base.cursor; + among_var = base.find_among(a_11); + if (among_var == 0) + { + return false; + } + base.ket = base.cursor; + if (base.cursor < base.limit) + { + return false; + } + switch (among_var) { + case 1: + if (!base.slice_from("sky")) + { + return false; + } + break; + case 2: + if (!base.slice_from("idl")) + { + return false; + } + break; + case 3: + if (!base.slice_from("gentl")) + { + return false; + } + break; + case 4: + if (!base.slice_from("ugli")) + { + return false; + } + break; + case 5: + if (!base.slice_from("earli")) + { + return false; + } + break; + case 6: + if (!base.slice_from("onli")) + { + return false; + } + break; + case 7: + if (!base.slice_from("singl")) + { + return false; + } + break; + } + return true; + }; + + /** @return {boolean} */ + function r_postlude() { + if (!B_Y_found) + { + return false; + } + while(true) + { + /** @const */ var /** number */ v_1 = base.cursor; + lab0: { + golab1: while(true) + { + /** @const */ var /** number */ v_2 = base.cursor; + lab2: { + base.bra = base.cursor; + if (!(base.eq_s("Y"))) + { + break lab2; + } + base.ket = base.cursor; + base.cursor = v_2; + break golab1; + } + base.cursor = v_2; + if (base.cursor >= base.limit) + { + break lab0; + } + base.cursor++; + } + if (!base.slice_from("y")) + { + return false; + } + continue; + } + base.cursor = v_1; + break; + } + return true; + }; + + this.stem = /** @return {boolean} */ function() { + lab0: { + /** @const */ var /** number */ v_1 = base.cursor; + lab1: { + if (!r_exception1()) + { + break lab1; + } + break lab0; + } + base.cursor = v_1; + lab2: { + { + /** @const */ var /** number */ v_2 = base.cursor; + lab3: { + { + /** @const */ var /** number */ c1 = base.cursor + 3; + if (c1 > base.limit) + { + break lab3; + } + base.cursor = c1; + } + break lab2; + } + base.cursor = v_2; + } + break lab0; + } + base.cursor = v_1; + r_prelude(); + r_mark_regions(); + base.limit_backward = base.cursor; base.cursor = base.limit; + /** @const */ var /** number */ v_3 = base.limit - base.cursor; + r_Step_1a(); + base.cursor = base.limit - v_3; + /** @const */ var /** number */ v_4 = base.limit - base.cursor; + r_Step_1b(); + base.cursor = base.limit - v_4; + /** @const */ var /** number */ v_5 = base.limit - base.cursor; + r_Step_1c(); + base.cursor = base.limit - v_5; + /** @const */ var /** number */ v_6 = base.limit - base.cursor; + r_Step_2(); + base.cursor = base.limit - v_6; + /** @const */ var /** number */ v_7 = base.limit - base.cursor; + r_Step_3(); + base.cursor = base.limit - v_7; + /** @const */ var /** number */ v_8 = base.limit - base.cursor; + r_Step_4(); + base.cursor = base.limit - v_8; + /** @const */ var /** number */ v_9 = base.limit - base.cursor; + r_Step_5(); + base.cursor = base.limit - v_9; + base.cursor = base.limit_backward; + /** @const */ var /** number */ v_10 = base.cursor; + r_postlude(); + base.cursor = v_10; + } + return true; + }; + + /**@return{string}*/ + this['stemWord'] = function(/**string*/word) { + base.setCurrent(word); + this.stem(); + return base.getCurrent(); + }; +}; diff --git a/docs/_build/_static/file.png b/docs/_build/_static/file.png new file mode 100644 index 0000000..a858a41 Binary files /dev/null and b/docs/_build/_static/file.png differ diff --git a/docs/_build/_static/fonts/Lato/lato-bold.eot 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element.lastChild) element.removeChild(element.lastChild); +}; + +/** + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping + */ +const _escapeRegExp = (string) => + string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string + +const _escapeHTML = (text) => { + return text + .replaceAll("&", "&") + .replaceAll("<", "<") + .replaceAll(">", ">") + .replaceAll('"', """) + .replaceAll("'", "'"); +}; + +const _displayItem = (item, searchTerms, highlightTerms) => { + const docBuilder = DOCUMENTATION_OPTIONS.BUILDER; + const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX; + const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX; + const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY; + const contentRoot = document.documentElement.dataset.content_root; + + const [docName, title, anchor, descr, score, _filename, kind] = item; + + let listItem = document.createElement("li"); + // Add a class representing the item's type: + // can be used by a theme's CSS selector for styling + // See SearchResultKind for the class names. + listItem.classList.add(`kind-${kind}`); + let requestUrl; + let linkUrl; + if (docBuilder === "dirhtml") { + // dirhtml builder + let dirname = docName + "/"; + if (dirname.match(/\/index\/$/)) + dirname = dirname.substring(0, dirname.length - 6); + else if (dirname === "index/") dirname = ""; + requestUrl = contentRoot + dirname; + linkUrl = requestUrl; + } else { + // normal html builders + requestUrl = contentRoot + docName + docFileSuffix; + linkUrl = docName + docLinkSuffix; + } + let linkEl = listItem.appendChild(document.createElement("a")); + linkEl.href = linkUrl + anchor; + linkEl.dataset.score = score; + linkEl.innerHTML = _escapeHTML(title); + if (descr) { + listItem.appendChild(document.createElement("span")).innerHTML = + ` (${_escapeHTML(descr)})`; + // highlight search terms in the description + if (SPHINX_HIGHLIGHT_ENABLED) + // SPHINX_HIGHLIGHT_ENABLED is set in sphinx_highlight.js + highlightTerms.forEach((term) => + _highlightText(listItem, term, "highlighted"), + ); + } else if (showSearchSummary) + fetch(requestUrl) + .then((responseData) => responseData.text()) + .then((data) => { + if (data) + listItem.appendChild( + Search.makeSearchSummary(data, searchTerms, anchor), + ); + // highlight search terms in the summary + if (SPHINX_HIGHLIGHT_ENABLED) + // SPHINX_HIGHLIGHT_ENABLED is set in sphinx_highlight.js + highlightTerms.forEach((term) => + _highlightText(listItem, term, "highlighted"), + ); + }); + Search.output.appendChild(listItem); +}; +const _finishSearch = (resultCount) => { + Search.stopPulse(); + Search.title.innerText = _("Search Results"); + if (!resultCount) + Search.status.innerText = Documentation.gettext( + "Your search did not match any documents. Please make sure that all words are spelled correctly and that you've selected enough categories.", + ); + else + Search.status.innerText = Documentation.ngettext( + "Search finished, found one page matching the search query.", + "Search finished, found ${resultCount} pages matching the search query.", + resultCount, + ).replace("${resultCount}", resultCount); +}; +const _displayNextItem = ( + results, + resultCount, + searchTerms, + highlightTerms, +) => { + // results left, load the summary and display it + // this is intended to be dynamic (don't sub resultsCount) + if (results.length) { + _displayItem(results.pop(), searchTerms, highlightTerms); + setTimeout( + () => _displayNextItem(results, resultCount, searchTerms, highlightTerms), + 5, + ); + } + // search finished, update title and status message + else _finishSearch(resultCount); +}; +// Helper function used by query() to order search results. +// Each input is an array of [docname, title, anchor, descr, score, filename, kind]. +// Order the results by score (in opposite order of appearance, since the +// `_displayNextItem` function uses pop() to retrieve items) and then alphabetically. +const _orderResultsByScoreThenName = (a, b) => { + const leftScore = a[4]; + const rightScore = b[4]; + if (leftScore === rightScore) { + // same score: sort alphabetically + const leftTitle = a[1].toLowerCase(); + const rightTitle = b[1].toLowerCase(); + if (leftTitle === rightTitle) return 0; + return leftTitle > rightTitle ? -1 : 1; // inverted is intentional + } + return leftScore > rightScore ? 1 : -1; +}; + +/** + * Default splitQuery function. Can be overridden in ``sphinx.search`` with a + * custom function per language. + * + * The regular expression works by splitting the string on consecutive characters + * that are not Unicode letters, numbers, underscores, or emoji characters. + * This is the same as ``\W+`` in Python, preserving the surrogate pair area. + */ +if (typeof splitQuery === "undefined") { + var splitQuery = (query) => + query + .split(/[^\p{Letter}\p{Number}_\p{Emoji_Presentation}]+/gu) + .filter((term) => term); // remove remaining empty strings +} + +/** + * Search Module + */ +const Search = { + _index: null, + _queued_query: null, + _pulse_status: -1, + + htmlToText: (htmlString, anchor) => { + const htmlElement = new DOMParser().parseFromString( + htmlString, + "text/html", + ); + for (const removalQuery of [".headerlink", "script", "style"]) { + htmlElement.querySelectorAll(removalQuery).forEach((el) => { + el.remove(); + }); + } + if (anchor) { + const anchorContent = htmlElement.querySelector( + `[role="main"] ${anchor}`, + ); + if (anchorContent) return anchorContent.textContent; + + console.warn( + `Anchored content block not found. Sphinx search tries to obtain it via DOM query '[role=main] ${anchor}'. Check your theme or template.`, + ); + } + + // if anchor not specified or not found, fall back to main content + const docContent = htmlElement.querySelector('[role="main"]'); + if (docContent) return docContent.textContent; + + console.warn( + "Content block not found. Sphinx search tries to obtain it via DOM query '[role=main]'. Check your theme or template.", + ); + return ""; + }, + + init: () => { + const query = new URLSearchParams(window.location.search).get("q"); + document + .querySelectorAll('input[name="q"]') + .forEach((el) => (el.value = query)); + if (query) Search.performSearch(query); + }, + + loadIndex: (url) => + (document.body.appendChild(document.createElement("script")).src = url), + + setIndex: (index) => { + Search._index = index; + if (Search._queued_query !== null) { + const query = Search._queued_query; + Search._queued_query = null; + Search.query(query); + } + }, + + hasIndex: () => Search._index !== null, + + deferQuery: (query) => (Search._queued_query = query), + + stopPulse: () => (Search._pulse_status = -1), + + startPulse: () => { + if (Search._pulse_status >= 0) return; + + const pulse = () => { + Search._pulse_status = (Search._pulse_status + 1) % 4; + Search.dots.innerText = ".".repeat(Search._pulse_status); + if (Search._pulse_status >= 0) window.setTimeout(pulse, 500); + }; + pulse(); + }, + + /** + * perform a search for something (or wait until index is loaded) + */ + performSearch: (query) => { + // create the required interface elements + const searchText = document.createElement("h2"); + searchText.textContent = _("Searching"); + const searchSummary = document.createElement("p"); + searchSummary.classList.add("search-summary"); + searchSummary.innerText = ""; + const searchList = document.createElement("ul"); + searchList.setAttribute("role", "list"); + searchList.classList.add("search"); + + const out = document.getElementById("search-results"); + Search.title = out.appendChild(searchText); + Search.dots = Search.title.appendChild(document.createElement("span")); + Search.status = out.appendChild(searchSummary); + Search.output = out.appendChild(searchList); + + const searchProgress = document.getElementById("search-progress"); + // Some themes don't use the search progress node + if (searchProgress) { + searchProgress.innerText = _("Preparing search..."); + } + Search.startPulse(); + + // index already loaded, the browser was quick! + if (Search.hasIndex()) Search.query(query); + else Search.deferQuery(query); + }, + + _parseQuery: (query) => { + // stem the search terms and add them to the correct list + const stemmer = new Stemmer(); + const searchTerms = new Set(); + const excludedTerms = new Set(); + const highlightTerms = new Set(); + const objectTerms = new Set(splitQuery(query.toLowerCase().trim())); + splitQuery(query.trim()).forEach((queryTerm) => { + const queryTermLower = queryTerm.toLowerCase(); + + // maybe skip this "word" + // stopwords set is from language_data.js + if (stopwords.has(queryTermLower) || queryTerm.match(/^\d+$/)) return; + + // stem the word + let word = stemmer.stemWord(queryTermLower); + // select the correct list + if (word[0] === "-") excludedTerms.add(word.substr(1)); + else { + searchTerms.add(word); + highlightTerms.add(queryTermLower); + } + }); + + if (SPHINX_HIGHLIGHT_ENABLED) { + // SPHINX_HIGHLIGHT_ENABLED is set in sphinx_highlight.js + localStorage.setItem( + "sphinx_highlight_terms", + [...highlightTerms].join(" "), + ); + } + + // console.debug("SEARCH: searching for:"); + // console.info("required: ", [...searchTerms]); + // console.info("excluded: ", [...excludedTerms]); + + return [query, searchTerms, excludedTerms, highlightTerms, objectTerms]; + }, + + /** + * execute search (requires search index to be loaded) + */ + _performSearch: ( + query, + searchTerms, + excludedTerms, + highlightTerms, + objectTerms, + ) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + const allTitles = Search._index.alltitles; + const indexEntries = Search._index.indexentries; + + // Collect multiple result groups to be sorted separately and then ordered. + // Each is an array of [docname, title, anchor, descr, score, filename, kind]. + const normalResults = []; + const nonMainIndexResults = []; + + _removeChildren(document.getElementById("search-progress")); + + const queryLower = query.toLowerCase().trim(); + for (const [title, foundTitles] of Object.entries(allTitles)) { + if ( + title.toLowerCase().trim().includes(queryLower) + && queryLower.length >= title.length / 2 + ) { + for (const [file, id] of foundTitles) { + const score = Math.round( + (Scorer.title * queryLower.length) / title.length, + ); + const boost = titles[file] === title ? 1 : 0; // add a boost for document titles + normalResults.push([ + docNames[file], + titles[file] !== title ? `${titles[file]} > ${title}` : title, + id !== null ? "#" + id : "", + null, + score + boost, + filenames[file], + SearchResultKind.title, + ]); + } + } + } + + // search for explicit entries in index directives + for (const [entry, foundEntries] of Object.entries(indexEntries)) { + if (entry.includes(queryLower) && queryLower.length >= entry.length / 2) { + for (const [file, id, isMain] of foundEntries) { + const score = Math.round((100 * queryLower.length) / entry.length); + const result = [ + docNames[file], + titles[file], + id ? "#" + id : "", + null, + score, + filenames[file], + SearchResultKind.index, + ]; + if (isMain) { + normalResults.push(result); + } else { + nonMainIndexResults.push(result); + } + } + } + } + + // lookup as object + objectTerms.forEach((term) => + normalResults.push(...Search.performObjectSearch(term, objectTerms)), + ); + + // lookup as search terms in fulltext + normalResults.push( + ...Search.performTermsSearch(searchTerms, excludedTerms), + ); + + // let the scorer override scores with a custom scoring function + if (Scorer.score) { + normalResults.forEach((item) => (item[4] = Scorer.score(item))); + nonMainIndexResults.forEach((item) => (item[4] = Scorer.score(item))); + } + + // Sort each group of results by score and then alphabetically by name. + normalResults.sort(_orderResultsByScoreThenName); + nonMainIndexResults.sort(_orderResultsByScoreThenName); + + // Combine the result groups in (reverse) order. + // Non-main index entries are typically arbitrary cross-references, + // so display them after other results. + let results = [...nonMainIndexResults, ...normalResults]; + + // remove duplicate search results + // note the reversing of results, so that in the case of duplicates, the highest-scoring entry is kept + let seen = new Set(); + results = results.reverse().reduce((acc, result) => { + let resultStr = result + .slice(0, 4) + .concat([result[5]]) + .map((v) => String(v)) + .join(","); + if (!seen.has(resultStr)) { + acc.push(result); + seen.add(resultStr); + } + return acc; + }, []); + + return results.reverse(); + }, + + query: (query) => { + const [ + searchQuery, + searchTerms, + excludedTerms, + highlightTerms, + objectTerms, + ] = Search._parseQuery(query); + const results = Search._performSearch( + searchQuery, + searchTerms, + excludedTerms, + highlightTerms, + objectTerms, + ); + + // for debugging + //Search.lastresults = results.slice(); // a copy + // console.info("search results:", Search.lastresults); + + // print the results + _displayNextItem(results, results.length, searchTerms, highlightTerms); + }, + + /** + * search for object names + */ + performObjectSearch: (object, objectTerms) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const objects = Search._index.objects; + const objNames = Search._index.objnames; + const titles = Search._index.titles; + + const results = []; + + const objectSearchCallback = (prefix, match) => { + const name = match[4]; + const fullname = (prefix ? prefix + "." : "") + name; + const fullnameLower = fullname.toLowerCase(); + if (fullnameLower.indexOf(object) < 0) return; + + let score = 0; + const parts = fullnameLower.split("."); + + // check for different match types: exact matches of full name or + // "last name" (i.e. last dotted part) + if (fullnameLower === object || parts.slice(-1)[0] === object) + score += Scorer.objNameMatch; + else if (parts.slice(-1)[0].indexOf(object) > -1) + score += Scorer.objPartialMatch; // matches in last name + + const objName = objNames[match[1]][2]; + const title = titles[match[0]]; + + // If more than one term searched for, we require other words to be + // found in the name/title/description + const otherTerms = new Set(objectTerms); + otherTerms.delete(object); + if (otherTerms.size > 0) { + const haystack = `${prefix} ${name} ${objName} ${title}`.toLowerCase(); + if ( + [...otherTerms].some((otherTerm) => haystack.indexOf(otherTerm) < 0) + ) + return; + } + + let anchor = match[3]; + if (anchor === "") anchor = fullname; + else if (anchor === "-") anchor = objNames[match[1]][1] + "-" + fullname; + + const descr = objName + _(", in ") + title; + + // add custom score for some objects according to scorer + if (Scorer.objPrio.hasOwnProperty(match[2])) + score += Scorer.objPrio[match[2]]; + else score += Scorer.objPrioDefault; + + results.push([ + docNames[match[0]], + fullname, + "#" + anchor, + descr, + score, + filenames[match[0]], + SearchResultKind.object, + ]); + }; + Object.keys(objects).forEach((prefix) => + objects[prefix].forEach((array) => objectSearchCallback(prefix, array)), + ); + return results; + }, + + /** + * search for full-text terms in the index + */ + performTermsSearch: (searchTerms, excludedTerms) => { + // prepare search + const terms = Search._index.terms; + const titleTerms = Search._index.titleterms; + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + + const scoreMap = new Map(); + const fileMap = new Map(); + + // perform the search on the required terms + searchTerms.forEach((word) => { + const files = []; + // find documents, if any, containing the query word in their text/title term indices + // use Object.hasOwnProperty to avoid mismatching against prototype properties + const arr = [ + { + files: terms.hasOwnProperty(word) ? terms[word] : undefined, + score: Scorer.term, + }, + { + files: titleTerms.hasOwnProperty(word) ? titleTerms[word] : undefined, + score: Scorer.title, + }, + ]; + // add support for partial matches + if (word.length > 2) { + const escapedWord = _escapeRegExp(word); + if (!terms.hasOwnProperty(word)) { + Object.keys(terms).forEach((term) => { + if (term.match(escapedWord)) + arr.push({ files: terms[term], score: Scorer.partialTerm }); + }); + } + if (!titleTerms.hasOwnProperty(word)) { + Object.keys(titleTerms).forEach((term) => { + if (term.match(escapedWord)) + arr.push({ files: titleTerms[term], score: Scorer.partialTitle }); + }); + } + } + + // no match but word was a required one + if (arr.every((record) => record.files === undefined)) return; + + // found search word in contents + arr.forEach((record) => { + if (record.files === undefined) return; + + let recordFiles = record.files; + if (recordFiles.length === undefined) recordFiles = [recordFiles]; + files.push(...recordFiles); + + // set score for the word in each file + recordFiles.forEach((file) => { + if (!scoreMap.has(file)) scoreMap.set(file, new Map()); + const fileScores = scoreMap.get(file); + fileScores.set(word, record.score); + }); + }); + + // create the mapping + files.forEach((file) => { + if (!fileMap.has(file)) fileMap.set(file, [word]); + else if (fileMap.get(file).indexOf(word) === -1) + fileMap.get(file).push(word); + }); + }); + + // now check if the files don't contain excluded terms + const results = []; + for (const [file, wordList] of fileMap) { + // check if all requirements are matched + + // as search terms with length < 3 are discarded + const filteredTermCount = [...searchTerms].filter( + (term) => term.length > 2, + ).length; + if ( + wordList.length !== searchTerms.size + && wordList.length !== filteredTermCount + ) + continue; + + // ensure that none of the excluded terms is in the search result + if ( + [...excludedTerms].some( + (term) => + terms[term] === file + || titleTerms[term] === file + || (terms[term] || []).includes(file) + || (titleTerms[term] || []).includes(file), + ) + ) + break; + + // select one (max) score for the file. + const score = Math.max(...wordList.map((w) => scoreMap.get(file).get(w))); + // add result to the result list + results.push([ + docNames[file], + titles[file], + "", + null, + score, + filenames[file], + SearchResultKind.text, + ]); + } + return results; + }, + + /** + * helper function to return a node containing the + * search summary for a given text. keywords is a list + * of stemmed words. + */ + makeSearchSummary: (htmlText, keywords, anchor) => { + const text = Search.htmlToText(htmlText, anchor); + if (text === "") return null; + + const textLower = text.toLowerCase(); + const actualStartPosition = [...keywords] + .map((k) => textLower.indexOf(k.toLowerCase())) + .filter((i) => i > -1) + .slice(-1)[0]; + const startWithContext = Math.max(actualStartPosition - 120, 0); + + const top = startWithContext === 0 ? "" : "..."; + const tail = startWithContext + 240 < text.length ? "..." : ""; + + let summary = document.createElement("p"); + summary.classList.add("context"); + summary.textContent = + top + text.substr(startWithContext, 240).trim() + tail; + + return summary; + }, +}; + +_ready(Search.init); diff --git a/docs/_build/_static/sphinx_highlight.js b/docs/_build/_static/sphinx_highlight.js new file mode 100644 index 0000000..a74e103 --- /dev/null +++ b/docs/_build/_static/sphinx_highlight.js @@ -0,0 +1,159 @@ +/* Highlighting utilities for Sphinx HTML documentation. */ +"use strict"; + +const SPHINX_HIGHLIGHT_ENABLED = true; + +/** + * highlight a given string on a node by wrapping it in + * span elements with the given class name. + */ +const _highlight = (node, addItems, text, className) => { + if (node.nodeType === Node.TEXT_NODE) { + const val = node.nodeValue; + const parent = node.parentNode; + const pos = val.toLowerCase().indexOf(text); + if ( + pos >= 0 + && !parent.classList.contains(className) + && !parent.classList.contains("nohighlight") + ) { + let span; + + const closestNode = parent.closest("body, svg, foreignObject"); + const isInSVG = closestNode && closestNode.matches("svg"); + if (isInSVG) { + span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); + } else { + span = document.createElement("span"); + span.classList.add(className); + } + + span.appendChild(document.createTextNode(val.substr(pos, text.length))); + const rest = document.createTextNode(val.substr(pos + text.length)); + parent.insertBefore(span, parent.insertBefore(rest, node.nextSibling)); + node.nodeValue = val.substr(0, pos); + /* There may be more occurrences of search term in this node. So call this + * function recursively on the remaining fragment. + */ + _highlight(rest, addItems, text, className); + + if (isInSVG) { + const rect = document.createElementNS( + "http://www.w3.org/2000/svg", + "rect", + ); + const bbox = parent.getBBox(); + rect.x.baseVal.value = bbox.x; + rect.y.baseVal.value = bbox.y; + rect.width.baseVal.value = bbox.width; + rect.height.baseVal.value = bbox.height; + rect.setAttribute("class", className); + addItems.push({ parent: parent, target: rect }); + } + } + } else if (node.matches && !node.matches("button, select, textarea")) { + node.childNodes.forEach((el) => _highlight(el, addItems, text, className)); + } +}; +const _highlightText = (thisNode, text, className) => { + let addItems = []; + _highlight(thisNode, addItems, text, className); + addItems.forEach((obj) => + obj.parent.insertAdjacentElement("beforebegin", obj.target), + ); +}; + +/** + * Small JavaScript module for the documentation. + */ +const SphinxHighlight = { + /** + * highlight the search words provided in localstorage in the text + */ + highlightSearchWords: () => { + if (!SPHINX_HIGHLIGHT_ENABLED) return; // bail if no highlight + + // get and clear terms from localstorage + const url = new URL(window.location); + const highlight = + localStorage.getItem("sphinx_highlight_terms") + || url.searchParams.get("highlight") + || ""; + localStorage.removeItem("sphinx_highlight_terms"); + // Update history only if '?highlight' is present; otherwise it + // clears text fragments (not set in window.location by the browser) + if (url.searchParams.has("highlight")) { + url.searchParams.delete("highlight"); + window.history.replaceState({}, "", url); + } + + // get individual terms from highlight string + const terms = highlight + .toLowerCase() + .split(/\s+/) + .filter((x) => x); + if (terms.length === 0) return; // nothing to do + + // There should never be more than one element matching "div.body" + const divBody = document.querySelectorAll("div.body"); + const body = divBody.length ? divBody[0] : document.querySelector("body"); + window.setTimeout(() => { + terms.forEach((term) => _highlightText(body, term, "highlighted")); + }, 10); + + const searchBox = document.getElementById("searchbox"); + if (searchBox === null) return; + searchBox.appendChild( + document + .createRange() + .createContextualFragment( + '

' + + '' + + _("Hide Search Matches") + + "

", + ), + ); + }, + + /** + * helper function to hide the search marks again + */ + hideSearchWords: () => { + document + .querySelectorAll("#searchbox .highlight-link") + .forEach((el) => el.remove()); + document + .querySelectorAll("span.highlighted") + .forEach((el) => el.classList.remove("highlighted")); + localStorage.removeItem("sphinx_highlight_terms"); + }, + + initEscapeListener: () => { + // only install a listener if it is really needed + if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return; + + document.addEventListener("keydown", (event) => { + // bail for input elements + if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) + return; + // bail with special keys + if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) + return; + if ( + DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS + && event.key === "Escape" + ) { + SphinxHighlight.hideSearchWords(); + event.preventDefault(); + } + }); + }, +}; + +_ready(() => { + /* Do not call highlightSearchWords() when we are on the search page. + * It will highlight words from the *previous* search query. + */ + if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords(); + SphinxHighlight.initEscapeListener(); +}); diff --git a/docs/_build/docker-deployment.html b/docs/_build/docker-deployment.html new file mode 100644 index 0000000..44cf792 --- /dev/null +++ b/docs/_build/docker-deployment.html @@ -0,0 +1,637 @@ + + + + + + + + + Docker Deployment Guide for AstroML — AstroML Documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Docker Deployment Guide for AstroML๏ƒ

+

This guide provides comprehensive instructions for deploying AstroML using Docker and Docker Compose.

+
+

๐Ÿณ Overview๏ƒ

+

The AstroML Docker setup includes:

+
    +

  • Multi-stage Dockerfile with optimized images for different use cases

    • +

  • Docker Compose configuration for complete environment setup

    • +

  • GPU support for ML training

    • +

  • Development, production, and monitoring profiles

    • +
+
+
+

๐Ÿ— Docker Build Stages๏ƒ

+
+

Available Build Targets๏ƒ

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

Stage

Purpose

Base Image

Use Case

base

Common dependencies

python:3.11-slim

Foundation for all stages

ingestion

Data ingestion & streaming

base

Stellar data ingestion

training

GPU-enabled ML training

nvidia/cuda:12.1-runtime

GPU training environments

training-cpu

CPU-only ML training

base

CPU training environments

development

Development with tools

base

Local development

production

Minimal production image

base

Production deployment

+
+
+
+

๐Ÿš€ Quick Start๏ƒ

+
+

Prerequisites๏ƒ

+
    +

  • Docker Engine 20.10+

    • +

  • Docker Compose 2.0+

    • +

  • NVIDIA Docker (for GPU support)

    • +
+
+
+

Basic Setup๏ƒ

+
    +

  1. Clone and navigate to the project:

    +
    git clone https://github.com/tecch-wiz/astroml.git
+cd astroml
+
    +
    +
    2. +

  2. Start the basic environment:

    +
    docker-compose up -d postgres redis
+
    +
    +
    3. +

  3. Run database migrations:

    +
    docker-compose run --rm ingestion python -m alembic upgrade head
+
    +
    +
    4. +

  4. Start ingestion service:

    +
    docker-compose up -d ingestion
+
    +
    +
    5. +
+
+
+
+

๐Ÿ“‹ Docker Compose Services๏ƒ

+
+

Core Services๏ƒ

+
    +

  • postgres: PostgreSQL database with health checks

    • +

  • redis: Redis for caching and job queues

    • +

  • ingestion: Main data ingestion service

    • +

  • streaming: Enhanced streaming service

    • +
+
+
+

Training Services๏ƒ

+
    +

  • training-gpu: GPU-enabled training (requires NVIDIA Docker)

    • +

  • training-cpu: CPU-only training

    • +
+
+
+

Optional Services๏ƒ

+
    +

  • dev: Development environment with Jupyter

    • +

  • production: Production-optimized service

    • +

  • prometheus: Monitoring and metrics

    • +

  • grafana: Visualization dashboard

    • +
+
+
+
+

๐Ÿ›  Usage Examples๏ƒ

+
+

Development Environment๏ƒ

+
# Start development services
+docker-compose --profile dev up -d
+
+# Access Jupyter Lab
+open http://localhost:8888
+
+
+
+
+

GPU Training๏ƒ

+
# Start GPU training service
+docker-compose --profile gpu up -d training-gpu
+
+# Run training
+docker-compose exec training-gpu python -m astroml.training.train_gcn
+
+
+
+
+

CPU Training๏ƒ

+
# Start CPU training service
+docker-compose --profile cpu up -d training-cpu
+
+# Run training
+docker-compose exec training-cpu python -m astroml.training.train_gcn
+
+
+
+
+

Production Deployment๏ƒ

+
# Deploy production services
+docker-compose --profile prod up -d production
+
+
+
+
+

Monitoring Stack๏ƒ

+
# Start monitoring services
+docker-compose --profile monitoring up -d prometheus grafana
+
+# Access Grafana
+open http://localhost:3000  # admin/admin
+
+
+
+
+
+

๐Ÿ”ง Configuration๏ƒ

+
+

Environment Variables๏ƒ

+

Key environment variables for services:

+
# Database
+DATABASE_URL: postgresql://astroml:astroml_password@postgres:5432/astroml
+
+# Redis
+REDIS_URL: redis://redis:6379/0
+
+# Stellar Network
+STELLAR_NETWORK_PASSPHRASE: "Public Global Stellar Network ; September 2015"
+STELLAR_HORIZON_URL: https://horizon.stellar.org
+
+# Logging
+LOG_LEVEL: INFO
+
+
+
+
+

Custom Configuration๏ƒ

+

Create docker-compose.override.yml for local customizations:

+
version: '3.8'
+
+services:
+  ingestion:
+    environment:
+      - LOG_LEVEL=DEBUG
+    volumes:
+      - ./local_config:/app/config:ro
+
+  postgres:
+    ports:
+      - "5433:5432"  # Different port to avoid conflicts
+
+
+
+
+
+

๐Ÿ“Š GPU Support๏ƒ

+
+

NVIDIA Docker Setup๏ƒ

+
    +

  1. Install NVIDIA Container Toolkit:

    +
    # Ubuntu/Debian
+distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
+curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
+curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
+
+sudo apt-get update && sudo apt-get install -y nvidia-docker2
+sudo systemctl restart docker
+
    +
    +
    2. +

  2. Test GPU support:

    +
    docker run --rm --gpus all nvidia/cuda:12.1-base-ubuntu22.04 nvidia-smi
+
    +
    +
    3. +
+
+
+

GPU Training๏ƒ

+
# Build GPU image
+docker build --target training -t astroml:training-gpu .
+
+# Run with GPU
+docker run --gpus all -v $(pwd):/app astroml:training-gpu python -m astroml.training.train_gcn
+
+
+
+
+
+

๐Ÿ” Monitoring and Logging๏ƒ

+
+

Log Access๏ƒ

+
# View ingestion logs
+docker-compose logs -f ingestion
+
+# View all service logs
+docker-compose logs -f
+
+# View specific number of lines
+docker-compose logs --tail=100 training-gpu
+
+
+
+
+

Health Checks๏ƒ

+

All services include health checks:

+
# Check service health
+docker-compose ps
+
+# Detailed health status
+curl http://localhost:8000/health  # If health endpoint is exposed
+
+
+
+
+

Monitoring Stack๏ƒ

+

With the monitoring profile enabled:

+
    +

  • Prometheus: http://localhost:9090

    • +

  • Grafana: http://localhost:3000 (admin/admin)

    • +
+
+
+
+

๐Ÿ—‚ Data Persistence๏ƒ

+
+

Volume Structure๏ƒ

+
volumes/
+โ”œโ”€โ”€ postgres_data/          # PostgreSQL data
+โ”œโ”€โ”€ redis_data/             # Redis data
+โ”œโ”€โ”€ ingestion_logs/         # Ingestion logs
+โ”œโ”€โ”€ ingestion_data/         # Ingestion data
+โ”œโ”€โ”€ training_models/        # Trained models
+โ”œโ”€โ”€ training_data/          # Training datasets
+โ”œโ”€โ”€ training_logs/          # Training logs
+โ””โ”€โ”€ production_data/        # Production data
+
+
+
+
+

Backup and Restore๏ƒ

+
# Backup database
+docker-compose exec postgres pg_dump -U astroml astroml > backup.sql
+
+# Restore database
+docker-compose exec -T postgres psql -U astroml astroml < backup.sql
+
+# Backup volumes
+docker run --rm -v astroml_postgres_data:/data -v $(pwd):/backup ubuntu tar czf /backup/postgres_backup.tar.gz -C /data .
+
+
+
+
+
+

๐Ÿงช Testing๏ƒ

+
+

Running Tests in Docker๏ƒ

+
# Run all tests
+docker-compose run --rm dev python -m pytest tests/ -v
+
+# Run with coverage
+docker-compose run --rm dev python -m pytest tests/ --cov=astroml --cov-report=html
+
+# Run specific test file
+docker-compose run --rm dev python -m pytest tests/test_structural_importance.py -v
+
+
+
+
+

Integration Testing๏ƒ

+
# Test ingestion pipeline
+docker-compose run --rm ingestion python -c "import astroml.ingestion; print('OK')"
+
+# Test training environment
+docker-compose run --rm training-cpu python -c "import torch; import torch_geometric; print('OK')"
+
+
+
+
+
+

๐Ÿš€ Production Deployment๏ƒ

+
+

Production Checklist๏ƒ

+
    +

  • Use production build target

    • +

  • Configure proper secrets management

    • +

  • Set up monitoring and alerting

    • +

  • Configure log rotation

    • +

  • Set up backup strategy

    • +

  • Review resource limits

    • +

  • Test disaster recovery

    • +
+
+
+

Production Commands๏ƒ

+
# Build production image
+docker build --target production -t astroml:prod .
+
+# Deploy with production profile
+docker-compose --profile prod up -d production
+
+# Scale services
+docker-compose --profile prod up -d --scale production=3
+
+
+
+
+
+

๐Ÿ”ง Troubleshooting๏ƒ

+
+

Common Issues๏ƒ

+
    +

  1. GPU not detected:

    +
    # Check NVIDIA Docker installation
+docker run --rm --gpus all nvidia/cuda:12.1-base nvidia-smi
+
    +
    +
    2. +

  2. Database connection issues:

    +
    # Check database health
+docker-compose exec postgres pg_isready -U astroml
+
    +
    +
    3. +

  3. Permission issues:

    +
    # Fix volume permissions
+sudo chown -R $USER:$USER .dockerignore
+
    +
    +
    4. +

  4. Out of memory:

    +
    # Check resource usage
+docker stats
+
+# Increase memory limits in docker-compose.yml
+
    +
    +
    5. +
+
+
+

Debug Mode๏ƒ

+
# Run with shell access
+docker-compose run --rm ingestion bash
+
+# Debug with environment variables
+docker-compose run --rm -e DEBUG=1 ingestion python -m astroml.ingestion
+
+
+
+
+
+

๐Ÿ“š Advanced Usage๏ƒ

+
+

Custom Images๏ƒ

+
# Build custom stage
+docker build --target development -t astroml:dev .
+
+# Build with custom arguments
+docker build --build-arg PYTHON_VERSION=3.10 -t astroml:custom .
+
+
+
+
+

Multi-Node Deployment๏ƒ

+
# Initialize Docker Swarm
+docker swarm init
+
+# Deploy stack
+docker stack deploy -c docker-compose.yml astroml
+
+
+
+
+

Performance Tuning๏ƒ

+
# docker-compose.yml performance tweaks
+services:
+  training-gpu:
+    deploy:
+      resources:
+        limits:
+          memory: 16G
+          cpus: '8'
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+
+
+
+
+
+

๐Ÿ†˜ Support๏ƒ

+

For Docker-related issues:

+
    +

  1. Check the troubleshooting section

    2. +

  2. Review service logs: docker-compose logs <service>

    3. +

  3. Verify resource usage: docker stats

    4. +

  4. Test with minimal configuration

    5. +
+

For application issues, refer to the main AstroML documentation.

+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/docs/_build/experiment-configs.html b/docs/_build/experiment-configs.html new file mode 100644 index 0000000..9f441bd --- /dev/null +++ b/docs/_build/experiment-configs.html @@ -0,0 +1,491 @@ + + + + + + + + + Experiment Configuration Guide — AstroML Documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Experiment Configuration Guide๏ƒ

+

This guide explains how to use the Hydra configuration system to run ML experiments with AstroML.

+
+

๐Ÿš€ Quick Start๏ƒ

+
+

Basic Usage๏ƒ

+
# Run with default configuration
+python train.py
+
+# Override learning rate
+python train.py training.lr=0.001
+
+# Use debug experiment
+python train.py experiment=debug
+
+# Override multiple parameters
+python train.py model.hidden_dims=[128,64] training.lr=0.01 training.epochs=300
+
+
+
+
+

Hyperparameter Sweeps๏ƒ

+
# Grid search over learning rates
+python train.py --multirun training.lr=0.001,0.01,0.1
+
+# Grid search over multiple parameters
+python train.py --multirun model.hidden_dims=[32],[64,32],[128,64] training.lr=0.001,0.01
+
+# Use pre-configured sweep
+python train.py --config-name experiments/hyperparameter_search --multirun
+
+
+
+
+
+

๐Ÿ“ Configuration Structure๏ƒ

+
configs/
+โ”œโ”€โ”€ config.yaml                    # Main configuration file
+โ”œโ”€โ”€ model/
+โ”‚   โ””โ”€โ”€ gcn.yaml                  # GCN model configurations
+โ”œโ”€โ”€ training/
+โ”‚   โ””โ”€โ”€ default.yaml              # Training configurations
+โ”œโ”€โ”€ data/
+โ”‚   โ””โ”€โ”€ cora.yaml                 # Dataset configurations
+โ””โ”€โ”€ experiments/
+    โ”œโ”€โ”€ debug.yaml                # Debug experiment
+    โ”œโ”€โ”€ baseline.yaml             # Baseline experiment
+    โ””โ”€โ”€ hyperparameter_search.yaml # Hyperparameter sweep
+
+
+
+
+

โš™๏ธ Configuration Files๏ƒ

+
+

Main Config (configs/config.yaml)๏ƒ

+

The main configuration file that sets up defaults and experiment settings:

+
defaults:
+  - model: gcn          # Use GCN model
+  - training: default   # Use default training config
+  - data: cora         # Use Cora dataset
+  - _self_             # Include this file's settings
+
+experiment:
+  name: "astroml_experiment"
+  seed: 42
+  device: "auto"
+  save_dir: "outputs"
+  log_level: "INFO"
+
+
+
+
+

Model Config (configs/model/gcn.yaml)๏ƒ

+

Configures the Graph Convolutional Network:

+
_target_: astroml.models.gcn.GCN
+input_dim: ???           # Will be set from dataset
+hidden_dims: [64, 32]   # Hidden layer sizes
+output_dim: ???          # Will be set from dataset
+dropout: 0.5
+activation: "relu"
+batch_norm: false
+residual: false
+
+
+
+
+

Training Config (configs/training/default.yaml)๏ƒ

+

Training hyperparameters and settings:

+
epochs: 200
+lr: 0.01
+weight_decay: 5e-4
+optimizer: "adam"
+scheduler: null
+early_stopping:
+  patience: 50
+  min_delta: 1e-4
+  monitor: "val_loss"
+  mode: "min"
+
+
+
+
+

Data Config (configs/data/cora.yaml)๏ƒ

+

Dataset configuration:

+
_target_: torch_geometric.datasets.Planetoid
+name: "Cora"
+root: "data"
+transform:
+  _target_: torch_geometric.transforms.NormalizeFeatures
+
+
+
+
+
+

๐Ÿ”ง Configuration Overrides๏ƒ

+
+

Command Line Overrides๏ƒ

+

You can override any configuration parameter from the command line:

+
# Override learning rate
+python train.py training.lr=0.001
+
+# Override model architecture
+python train.py model.hidden_dims=[128,64,32] model.dropout=0.6
+
+# Override dataset
+python train.py data.name=CiteSeer
+
+# Override experiment settings
+python train.py experiment.name=my_experiment experiment.seed=123
+
+
+
+
+

Using Experiments๏ƒ

+

Pre-configured experiments provide complete setups:

+
# Debug experiment (small model, few epochs)
+python train.py --config-name experiments/debug
+
+# Baseline experiment (standard settings)
+python train.py --config-name experiments/baseline
+
+# Hyperparameter search experiment
+python train.py --config-name experiments/hyperparameter_search --multirun
+
+
+
+
+
+

๐Ÿ“Š Hyperparameter Sweeps๏ƒ

+ +
+

Using Sweep Configurations๏ƒ

+

The hyperparameter_search.yaml experiment defines a parameter grid:

+
python train.py --config-name experiments/hyperparameter_search --multirun
+
+
+

This will run experiments for all combinations of:

+
    +

  • model.hidden_dims: [32], [64,32], [128,64]

    • +

  • model.dropout: 0.2, 0.5, 0.7

    • +

  • training.lr: 0.001, 0.01, 0.1

    • +

  • training.weight_decay: 1e-5, 5e-4, 1e-3

    • +
+
+
+
+

๐Ÿ“ Output Structure๏ƒ

+

Hydra automatically organizes experiment outputs:

+
outputs/
+โ””โ”€โ”€ astroml_experiment/
+    โ””โ”€โ”€ 2024-03-24_10-30-45/
+        โ”œโ”€โ”€ .hydra/
+        โ”‚   โ”œโ”€โ”€ config.yaml      # Full configuration
+        โ”‚   โ”œโ”€โ”€ hydra.yaml       # Hydra settings
+        โ”‚   โ””โ”€โ”€ overrides.yaml    # Command line overrides
+        โ”œโ”€โ”€ best_model.pth       # Best model checkpoint
+        โ”œโ”€โ”€ last_model.pth       # Final model checkpoint
+        โ”œโ”€โ”€ results.yaml         # Training results
+        โ””โ”€โ”€ train.log           # Training logs
+
+
+

For multirun experiments:

+
outputs/
+โ””โ”€โ”€ astroml_experiment/
+    โ””โ”€โ”€ multirun/
+        โ”œโ”€โ”€ model.hidden_dims=32,training.lr=0.001/
+        โ”œโ”€โ”€ model.hidden_dims=64,training.lr=0.001/
+        โ””โ”€โ”€ ...
+
+
+
+
+

๐ŸŽฏ Common Use Cases๏ƒ

+
+

1. Quick Debugging๏ƒ

+
# Small model, few epochs for fast iteration
+python train.py experiment=debug
+
+
+
+
+

2. Baseline Comparison๏ƒ

+
# Run baseline experiment
+python train.py --config-name experiments/baseline
+
+# Compare with different learning rate
+python train.py --config-name experiments/baseline training.lr=0.001
+
+
+
+ +
+

4. Learning Rate Tuning๏ƒ

+
# Fine-grained learning rate search
+python train.py --multirun training.lr=0.001,0.003,0.01,0.03,0.1
+
+
+
+
+

5. Regularization Experiments๏ƒ

+
# Test different dropout rates
+python train.py --multirun model.dropout=0.1,0.3,0.5,0.7
+
+# Test weight decay
+python train.py --multirun training.weight_decay=0,1e-5,5e-4,1e-3
+
+
+
+
+
+

๐Ÿ” Advanced Features๏ƒ

+
+

Custom Configurations๏ƒ

+

Create your own experiment configurations:

+
# configs/experiments/my_experiment.yaml
+defaults:
+  - override /model: gcn
+  - override /training: default
+  - override /data: cora
+
+experiment:
+  name: "my_custom_experiment"
+
+model:
+  hidden_dims: [256, 128]
+  dropout: 0.6
+
+training:
+  epochs: 500
+  lr: 0.003
+
+
+
+
+

Environment Variables๏ƒ

+

Use environment variables in configs:

+
# In config.yaml
+experiment:
+  name: "${oc.env:USER}_experiment"
+  seed: ${oc.env:RANDOM_SEED:42}
+
+
+
+
+

Conditional Configuration๏ƒ

+

Use conditional logic in configs:

+
# Conditional model size based on dataset
+model:
+  hidden_dims: ${select:${data.name},CiteSeer:[64],PubMed:[128,64],default:[64,32]}
+
+
+
+
+
+

๐Ÿ“ Best Practices๏ƒ

+
    +

  1. Use descriptive experiment names for easy identification

    2. +

  2. Set random seeds for reproducible results

    3. +

  3. Use early stopping to prevent overfitting

    4. +

  4. Save both best and last models for comparison

    5. +

  5. Log frequently during training for debugging

    6. +

  6. Use multirun for systematic hyperparameter searches

    7. +

  7. Keep configuration files under version control

    8. +
+
+
+

๐Ÿ†˜ Troubleshooting๏ƒ

+
+

Common Issues๏ƒ

+
    +

  1. Config not found: Check file paths and YAML syntax

    2. +

  2. Override not working: Use dot notation (e.g., model.lr not lr)

    3. +

  3. Multirun not working: Ensure --multirun flag is used

    4. +

  4. Output directory issues: Check write permissions

    5. +
+
+
+

Debugging Configurations๏ƒ

+
# Print configuration without running
+python train.py --cfg
+
+# Print specific config section
+python train.py --cfg model
+
+# Dry run to check config
+python train.py --dry-run
+
+
+
+
+
+

๐Ÿ“š Additional Resources๏ƒ

+ +
+

For more examples and advanced configurations, see the configs/experiments/ directory.

+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/docs/_build/genindex.html b/docs/_build/genindex.html new file mode 100644 index 0000000..90c0b82 --- /dev/null +++ b/docs/_build/genindex.html @@ -0,0 +1,105 @@ + + + + + + + + Index — AstroML Documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+
    +
    • +
  • Index
    • +
  • +
    • +
+
+
+
+
+ + +

Index

+ +
+ +
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/docs/_build/index.html b/docs/_build/index.html new file mode 100644 index 0000000..ab75b4c --- /dev/null +++ b/docs/_build/index.html @@ -0,0 +1,265 @@ + + + + + + + + + AstroML Documentation — AstroML Documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

AstroML Documentation๏ƒ

+

Welcome to the AstroML documentation!

+
+

๐Ÿš€ Quick Start๏ƒ

+

AstroML is a comprehensive machine learning framework for the Stellar network, providing tools for:

+
    +

  • Graph Machine Learning: Advanced GNN models for transaction analysis

    • +

  • Fraud Detection: Sophisticated algorithms for identifying suspicious activity

    • +

  • Feature Engineering: Comprehensive feature extraction and processing

    • +

  • Data Ingestion: Real-time Stellar ledger data processing

    • +
+
+
+

๐Ÿ“š Documentation Sections๏ƒ

+
+

Machine Learning๏ƒ

+ +
+
+

Configuration & Experiments๏ƒ

+ +
+
+

Deployment๏ƒ

+ +
+
+

API Reference๏ƒ

+ +
+
+
+

๐Ÿ”ง Installation๏ƒ

+
# Clone the repository
+git clone https://github.com/tecch-wiz/astroml.git
+cd astroml
+
+# Create virtual environment
+python3 -m venv venv
+source venv/bin/activate
+
+# Install dependencies
+pip install -r requirements.txt
+
+# For documentation only
+pip install -r docs/requirements.txt
+
+
+
+
+

๐ŸŽฏ Quick Examples๏ƒ

+
+

Running Experiments with Hydra๏ƒ

+
# Basic experiment
+python train.py
+
+# Override parameters
+python train.py training.lr=0.001 model.hidden_dims=[128,64]
+
+# Use pre-configured experiments
+python train.py --config-name experiments/debug
+python train.py --config-name experiments/baseline
+
+
+
+
+

Docker Deployment๏ƒ

+
# Build and run all services
+docker-compose up -d
+
+# Run specific services
+docker-compose up postgres redis
+docker-compose up ingestion
+
+
+
+
+
+

๐Ÿ“Š Features๏ƒ

+
+

Machine Learning๏ƒ

+
    +

  • Graph Neural Networks: GCN, GraphSAGE, GAT implementations

    • +

  • Structural Analysis: Centrality measures, importance metrics

    • +

  • Temporal Modeling: Time-series analysis for transaction patterns

    • +
+
+
+

Data Processing๏ƒ

+
    +

  • Real-time Ingestion: Stellar ledger streaming

    • +

  • Feature Engineering: Automated feature extraction

    • +

  • Data Validation: Quality checks and integrity verification

    • +
+
+
+

Deployment๏ƒ

+
    +

  • Docker Support: Multi-stage builds for different environments

    • +

  • Configuration Management: Hydra-based experiment tracking

    • +

  • Monitoring: Comprehensive logging and metrics

    • +
+
+
+ +
+

๐Ÿ“– Contributing๏ƒ

+

We welcome contributions! Please see our Contributing Guide for details.

+
+
+

๐Ÿ“„ License๏ƒ

+

This project is licensed under the MIT License - see the LICENSE file for details.

+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/docs/_build/objects.inv b/docs/_build/objects.inv new file mode 100644 index 0000000..0992c81 Binary files /dev/null and b/docs/_build/objects.inv differ diff --git a/docs/_build/schema.html b/docs/_build/schema.html new file mode 100644 index 0000000..2e22051 --- /dev/null +++ b/docs/_build/schema.html @@ -0,0 +1,294 @@ + + + + + + + + + AstroML Raw Data Storage Schema — AstroML Documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

AstroML Raw Data Storage Schema๏ƒ

+
+

Overview๏ƒ

+

AstroML stores raw Stellar blockchain data in PostgreSQL. The schema models the five core entities needed for dynamic graph ML: ledgers, transactions, operations, accounts, and assets.

+

The graph mapping is:

+ + + + + + + + + + + + + + + + + + + + + + + + + +

Blockchain Concept

Graph Representation

Table

Accounts

Nodes

accounts

Operations

Directed edges

operations

Assets

Edge types

assets

Time (ledger close)

Dynamic dimension

ledgers

+
+
+

ER Diagram๏ƒ

+
erDiagram
+    ledgers ||--o{ transactions : contains
+    transactions ||--o{ operations : contains
+
+    ledgers {
+        int sequence PK
+        varchar hash UK
+        varchar prev_hash
+        timestamptz closed_at
+        int successful_transaction_count
+        int failed_transaction_count
+        int operation_count
+        numeric total_coins
+        numeric fee_pool
+        int base_fee_in_stroops
+        int protocol_version
+    }
+
+    transactions {
+        varchar hash PK
+        int ledger_sequence FK
+        varchar source_account
+        timestamptz created_at
+        bigint fee
+        smallint operation_count
+        boolean successful
+        varchar memo_type
+        text memo
+    }
+
+    operations {
+        bigint id PK
+        varchar transaction_hash FK
+        smallint application_order
+        varchar type
+        varchar source_account
+        varchar destination_account
+        numeric amount
+        varchar asset_code
+        varchar asset_issuer
+        timestamptz created_at
+        jsonb details
+    }
+
+    accounts {
+        varchar account_id PK
+        numeric balance
+        bigint sequence
+        varchar home_domain
+        int flags
+        int last_modified_ledger
+        timestamptz created_at
+        timestamptz updated_at
+    }
+
+    assets {
+        int id PK
+        varchar asset_type
+        varchar asset_code
+        varchar asset_issuer
+        int first_seen_ledger
+    }
+
+
+
+
+

Table Details๏ƒ

+
+

ledgers๏ƒ

+

Temporal anchor โ€” one row per closed Stellar ledger (~5-6 seconds apart).

+

Indexes:

+
    +

  • PK on sequence

    • +

  • UNIQUE on hash

    • +

  • ix_ledgers_closed_at on closed_at

    • +
+
+
+

transactions๏ƒ

+

One row per Stellar transaction. Linked to a ledger via ledger_sequence.

+

Indexes:

+
    +

  • PK on hash

    • +

  • ix_transactions_source_account_created_at on (source_account, created_at) โ€” composite index for account+timestamp queries

    • +

  • ix_transactions_ledger_sequence on ledger_sequence

    • +
+
+
+

operations๏ƒ

+

One row per operation โ€” the primary graph-edge table. Common columns (source_account, destination_account, amount, asset_code, asset_issuer) cover the majority of graph-relevant operation types. The details JSONB column stores type-specific fields.

+

created_at is denormalized from the parent transaction to support efficient temporal range queries without JOINs.

+

Indexes:

+
    +

  • PK on id

    • +

  • ix_operations_source_created_at on (source_account, created_at) โ€” composite index for account+timestamp queries

    • +

  • ix_operations_dest_created_at on (destination_account, created_at) โ€” partial index (WHERE destination_account IS NOT NULL)

    • +

  • ix_operations_transaction_hash on transaction_hash

    • +

  • ix_operations_type on type

    • +
+
+
+

accounts๏ƒ

+

Latest known state of a Stellar account.

+

Indexes:

+
    +

  • PK on account_id

    • +

  • ix_accounts_updated_at on updated_at

    • +
+
+
+

assets๏ƒ

+

Asset registry โ€” unique by (code, issuer). Native XLM has asset_issuer = NULL.

+

Indexes:

+
    +

  • PK on id

    • +

  • ix_assets_code_issuer on (asset_code, COALESCE(asset_issuer, '')) โ€” unique expression index handling NULL issuer for native XLM

    • +
+
+
+
+

Relationships๏ƒ

+
ledgers  1 โ”€โ”€< N  transactions  (ledger_sequence โ†’ sequence)
+transactions  1 โ”€โ”€< N  operations  (transaction_hash โ†’ hash)
+
+
+

accounts and assets are reference tables โ€” not FK-constrained from operations to keep bulk ingestion fast and avoid ordering dependencies.

+
+
+

Running Migrations๏ƒ

+
# Apply all migrations
+alembic upgrade head
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+# Rollback all migrations
+alembic downgrade base
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+# Create a new migration
+alembic revision --autogenerate -m "description"
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+
+
+
+ + +
+
+ +
+
+
+
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  • Search
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\ No newline at end of file diff --git a/docs/experiment-configs.md b/docs/experiment-configs.md new file mode 100644 index 0000000..f3475b4 --- /dev/null +++ b/docs/experiment-configs.md @@ -0,0 +1,340 @@ +# Experiment Configuration Guide + +This guide explains how to use the Hydra configuration system to run ML experiments with AstroML. + +## ๐Ÿš€ Quick Start + +### Basic Usage + +```bash +# Run with default configuration +python train.py + +# Override learning rate +python train.py training.lr=0.001 + +# Use debug experiment +python train.py experiment=debug + +# Override multiple parameters +python train.py model.hidden_dims=[128,64] training.lr=0.01 training.epochs=300 +``` + +### Hyperparameter Sweeps + +```bash +# Grid search over learning rates +python train.py --multirun training.lr=0.001,0.01,0.1 + +# Grid search over multiple parameters +python train.py --multirun model.hidden_dims=[32],[64,32],[128,64] training.lr=0.001,0.01 + +# Use pre-configured sweep +python train.py --config-name experiments/hyperparameter_search --multirun +``` + +## ๐Ÿ“ Configuration Structure + +``` +configs/ +โ”œโ”€โ”€ config.yaml # Main configuration file +โ”œโ”€โ”€ model/ +โ”‚ โ””โ”€โ”€ gcn.yaml # GCN model configurations +โ”œโ”€โ”€ training/ +โ”‚ โ””โ”€โ”€ default.yaml # Training configurations +โ”œโ”€โ”€ data/ +โ”‚ โ””โ”€โ”€ cora.yaml # Dataset configurations +โ””โ”€โ”€ experiments/ + โ”œโ”€โ”€ debug.yaml # Debug experiment + โ”œโ”€โ”€ baseline.yaml # Baseline experiment + โ””โ”€โ”€ hyperparameter_search.yaml # Hyperparameter sweep +``` + +## โš™๏ธ Configuration Files + +### Main Config (`configs/config.yaml`) + +The main configuration file that sets up defaults and experiment settings: + +```yaml +defaults: + - model: gcn # Use GCN model + - training: default # Use default training config + - data: cora # Use Cora dataset + - _self_ # Include this file's settings + +experiment: + name: "astroml_experiment" + seed: 42 + device: "auto" + save_dir: "outputs" + log_level: "INFO" +``` + +### Model Config (`configs/model/gcn.yaml`) + +Configures the Graph Convolutional Network: + +```yaml +_target_: astroml.models.gcn.GCN +input_dim: ??? # Will be set from dataset +hidden_dims: [64, 32] # Hidden layer sizes +output_dim: ??? # Will be set from dataset +dropout: 0.5 +activation: "relu" +batch_norm: false +residual: false +``` + +### Training Config (`configs/training/default.yaml`) + +Training hyperparameters and settings: + +```yaml +epochs: 200 +lr: 0.01 +weight_decay: 5e-4 +optimizer: "adam" +scheduler: null +early_stopping: + patience: 50 + min_delta: 1e-4 + monitor: "val_loss" + mode: "min" +``` + +### Data Config (`configs/data/cora.yaml`) + +Dataset configuration: + +```yaml +_target_: torch_geometric.datasets.Planetoid +name: "Cora" +root: "data" +transform: + _target_: torch_geometric.transforms.NormalizeFeatures +``` + +## ๐Ÿ”ง Configuration Overrides + +### Command Line Overrides + +You can override any configuration parameter from the command line: + +```bash +# Override learning rate +python train.py training.lr=0.001 + +# Override model architecture +python train.py model.hidden_dims=[128,64,32] model.dropout=0.6 + +# Override dataset +python train.py data.name=CiteSeer + +# Override experiment settings +python train.py experiment.name=my_experiment experiment.seed=123 +``` + +### Using Experiments + +Pre-configured experiments provide complete setups: + +```bash +# Debug experiment (small model, few epochs) +python train.py --config-name experiments/debug + +# Baseline experiment (standard settings) +python train.py --config-name experiments/baseline + +# Hyperparameter search experiment +python train.py --config-name experiments/hyperparameter_search --multirun +``` + +## ๐Ÿ“Š Hyperparameter Sweeps + +### Basic Grid Search + +```bash +# Search over learning rates +python train.py --multirun training.lr=0.001,0.01,0.1 + +# Search over model architectures +python train.py --multirun model.hidden_dims=[32],[64,32],[128,64] + +# Combined search +python train.py --multirun training.lr=0.001,0.01 model.dropout=0.3,0.5,0.7 +``` + +### Using Sweep Configurations + +The `hyperparameter_search.yaml` experiment defines a parameter grid: + +```bash +python train.py --config-name experiments/hyperparameter_search --multirun +``` + +This will run experiments for all combinations of: +- `model.hidden_dims`: [32], [64,32], [128,64] +- `model.dropout`: 0.2, 0.5, 0.7 +- `training.lr`: 0.001, 0.01, 0.1 +- `training.weight_decay`: 1e-5, 5e-4, 1e-3 + +## ๐Ÿ“ Output Structure + +Hydra automatically organizes experiment outputs: + +``` +outputs/ +โ””โ”€โ”€ astroml_experiment/ + โ””โ”€โ”€ 2024-03-24_10-30-45/ + โ”œโ”€โ”€ .hydra/ + โ”‚ โ”œโ”€โ”€ config.yaml # Full configuration + โ”‚ โ”œโ”€โ”€ hydra.yaml # Hydra settings + โ”‚ โ””โ”€โ”€ overrides.yaml # Command line overrides + โ”œโ”€โ”€ best_model.pth # Best model checkpoint + โ”œโ”€โ”€ last_model.pth # Final model checkpoint + โ”œโ”€โ”€ results.yaml # Training results + โ””โ”€โ”€ train.log # Training logs +``` + +For multirun experiments: + +``` +outputs/ +โ””โ”€โ”€ astroml_experiment/ + โ””โ”€โ”€ multirun/ + โ”œโ”€โ”€ model.hidden_dims=32,training.lr=0.001/ + โ”œโ”€โ”€ model.hidden_dims=64,training.lr=0.001/ + โ””โ”€โ”€ ... +``` + +## ๐ŸŽฏ Common Use Cases + +### 1. Quick Debugging + +```bash +# Small model, few epochs for fast iteration +python train.py experiment=debug +``` + +### 2. Baseline Comparison + +```bash +# Run baseline experiment +python train.py --config-name experiments/baseline + +# Compare with different learning rate +python train.py --config-name experiments/baseline training.lr=0.001 +``` + +### 3. Architecture Search + +```bash +# Test different model sizes +python train.py --multirun model.hidden_dims=[32],[64,32],[128,64,32] +``` + +### 4. Learning Rate Tuning + +```bash +# Fine-grained learning rate search +python train.py --multirun training.lr=0.001,0.003,0.01,0.03,0.1 +``` + +### 5. Regularization Experiments + +```bash +# Test different dropout rates +python train.py --multirun model.dropout=0.1,0.3,0.5,0.7 + +# Test weight decay +python train.py --multirun training.weight_decay=0,1e-5,5e-4,1e-3 +``` + +## ๐Ÿ” Advanced Features + +### Custom Configurations + +Create your own experiment configurations: + +```yaml +# configs/experiments/my_experiment.yaml +defaults: + - override /model: gcn + - override /training: default + - override /data: cora + +experiment: + name: "my_custom_experiment" + +model: + hidden_dims: [256, 128] + dropout: 0.6 + +training: + epochs: 500 + lr: 0.003 +``` + +### Environment Variables + +Use environment variables in configs: + +```yaml +# In config.yaml +experiment: + name: "${oc.env:USER}_experiment" + seed: ${oc.env:RANDOM_SEED:42} +``` + +### Conditional Configuration + +Use conditional logic in configs: + +```yaml +# Conditional model size based on dataset +model: + hidden_dims: ${select:${data.name},CiteSeer:[64],PubMed:[128,64],default:[64,32]} +``` + +## ๐Ÿ“ Best Practices + +1. **Use descriptive experiment names** for easy identification +2. **Set random seeds** for reproducible results +3. **Use early stopping** to prevent overfitting +4. **Save both best and last models** for comparison +5. **Log frequently** during training for debugging +6. **Use multirun for systematic hyperparameter searches** +7. **Keep configuration files under version control** + +## ๐Ÿ†˜ Troubleshooting + +### Common Issues + +1. **Config not found**: Check file paths and YAML syntax +2. **Override not working**: Use dot notation (e.g., `model.lr` not `lr`) +3. **Multirun not working**: Ensure `--multirun` flag is used +4. **Output directory issues**: Check write permissions + +### Debugging Configurations + +```bash +# Print configuration without running +python train.py --cfg + +# Print specific config section +python train.py --cfg model + +# Dry run to check config +python train.py --dry-run +``` + +## ๐Ÿ“š Additional Resources + +- [Hydra Documentation](https://hydra.cc/) +- [OmegaConf Documentation](https://omegaconf.readthedocs.io/) +- [PyTorch Lightning Integration](https://pytorch-lightning.readthedocs.io/) + +--- + +For more examples and advanced configurations, see the `configs/experiments/` directory. diff --git a/docs/index.md b/docs/index.md new file mode 100644 index 0000000..e8ea0f9 --- /dev/null +++ b/docs/index.md @@ -0,0 +1,108 @@ +# AstroML Documentation + +Welcome to the AstroML documentation! + +## ๐Ÿš€ Quick Start + +AstroML is a comprehensive machine learning framework for the Stellar network, providing tools for: + +- **Graph Machine Learning**: Advanced GNN models for transaction analysis +- **Fraud Detection**: Sophisticated algorithms for identifying suspicious activity +- **Feature Engineering**: Comprehensive feature extraction and processing +- **Data Ingestion**: Real-time Stellar ledger data processing + +## ๐Ÿ“š Documentation Sections + +### Machine Learning +- [Structural Importance Metrics](structural_importance.md) +- [Transaction Graph Analysis](transaction_graph.md) +- [Feature Engineering Pipeline](feature_pipeline.md) + +### Configuration & Experiments +- [Experiment Configuration](experiment-configs.md) +- [Hydra Setup Guide](hydra-setup.md) + +### Deployment +- [Docker Deployment](docker-deployment.md) +- [Soroban Contract Integration](soroban-contract.md) + +### API Reference +- [Models API](api/models.md) +- [Features API](api/features.md) +- [Training API](api/training.md) + +## ๐Ÿ”ง Installation + +```bash +# Clone the repository +git clone https://github.com/tecch-wiz/astroml.git +cd astroml + +# Create virtual environment +python3 -m venv venv +source venv/bin/activate + +# Install dependencies +pip install -r requirements.txt + +# For documentation only +pip install -r docs/requirements.txt +``` + +## ๐ŸŽฏ Quick Examples + +### Running Experiments with Hydra + +```bash +# Basic experiment +python train.py + +# Override parameters +python train.py training.lr=0.001 model.hidden_dims=[128,64] + +# Use pre-configured experiments +python train.py --config-name experiments/debug +python train.py --config-name experiments/baseline +``` + +### Docker Deployment + +```bash +# Build and run all services +docker-compose up -d + +# Run specific services +docker-compose up postgres redis +docker-compose up ingestion +``` + +## ๐Ÿ“Š Features + +### Machine Learning +- **Graph Neural Networks**: GCN, GraphSAGE, GAT implementations +- **Structural Analysis**: Centrality measures, importance metrics +- **Temporal Modeling**: Time-series analysis for transaction patterns + +### Data Processing +- **Real-time Ingestion**: Stellar ledger streaming +- **Feature Engineering**: Automated feature extraction +- **Data Validation**: Quality checks and integrity verification + +### Deployment +- **Docker Support**: Multi-stage builds for different environments +- **Configuration Management**: Hydra-based experiment tracking +- **Monitoring**: Comprehensive logging and metrics + +## ๐Ÿ”— Links + +- [GitHub Repository](https://github.com/tecch-wiz/astroml) +- [Stellar Network](https://www.stellar.org/) +- [PyTorch Geometric](https://pytorch-geometric.readthedocs.io/) + +## ๐Ÿ“– Contributing + +We welcome contributions! Please see our [Contributing Guide](contributing.md) for details. + +## ๐Ÿ“„ License + +This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. diff --git a/outputs/2026-03-24/12-38-43/.hydra/config.yaml b/outputs/2026-03-24/12-38-43/.hydra/config.yaml new file mode 100644 index 0000000..6907b1b --- /dev/null +++ b/outputs/2026-03-24/12-38-43/.hydra/config.yaml @@ -0,0 +1,87 @@ +experiments: + model: + _target_: astroml.models.gcn.GCN + input_dim: ??? + hidden_dims: + - 16 + output_dim: ??? + dropout: 0.1 + activation: relu + batch_norm: false + residual: false + variants: + small: + hidden_dims: + - 32 + dropout: 0.2 + medium: + hidden_dims: + - 64 + - 32 + dropout: 0.5 + large: + hidden_dims: + - 128 + - 64 + - 32 + dropout: 0.6 + very_large: + hidden_dims: + - 256 + - 128 + - 64 + dropout: 0.7 + training: + epochs: 10 + lr: 0.01 + weight_decay: 0.0005 + optimizer: adam + scheduler: null + early_stopping: + patience: 50 + min_delta: 0.0001 + monitor: val_loss + mode: min + batch_size: null + val_split: 0.1 + test_split: 0.1 + shuffle: true + log_interval: 1 + save_best_only: true + save_last: true + optimizer_configs: + adam: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + amsgrad: false + sgd: + momentum: 0.9 + nesterov: true + adamw: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + weight_decay: 0.01 + data: + _target_: torch_geometric.datasets.Planetoid + name: Cora + root: data + transform: + _target_: torch_geometric.transforms.NormalizeFeatures + num_classes: 7 + num_node_features: 1433 + variants: + citeseer: + name: CiteSeer + num_classes: 6 + num_node_features: 3703 + pubmed: + name: PubMed + num_classes: 3 + num_node_features: 5003 + experiment: + name: debug_experiment + seed: 42 diff --git a/outputs/2026-03-24/12-38-43/.hydra/hydra.yaml b/outputs/2026-03-24/12-38-43/.hydra/hydra.yaml new file mode 100644 index 0000000..c241592 --- /dev/null +++ b/outputs/2026-03-24/12-38-43/.hydra/hydra.yaml @@ -0,0 +1,157 @@ +hydra: + run: + dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S} + sweep: + dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S} + subdir: ${hydra.job.num} + launcher: + _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher + sweeper: + _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper + max_batch_size: null + params: null + help: + app_name: ${hydra.job.name} + header: '${hydra.help.app_name} is powered by Hydra. + + ' + footer: 'Powered by Hydra (https://hydra.cc) + + Use --hydra-help to view Hydra specific help + + ' + template: '${hydra.help.header} + + == Configuration groups == + + Compose your configuration from those groups (group=option) + + + $APP_CONFIG_GROUPS + + + == Config == + + Override anything in the config (foo.bar=value) + + + $CONFIG + + + ${hydra.help.footer} + + ' + hydra_help: + template: 'Hydra (${hydra.runtime.version}) + + See https://hydra.cc for more info. + + + == Flags == + + $FLAGS_HELP + + + == Configuration groups == + + Compose your configuration from those groups (For example, append hydra/job_logging=disabled + to command line) + + + $HYDRA_CONFIG_GROUPS + + + Use ''--cfg hydra'' to Show the Hydra config. + + ' + hydra_help: ??? + hydra_logging: + version: 1 + formatters: + simple: + format: '[%(asctime)s][HYDRA] %(message)s' + handlers: + console: + class: logging.StreamHandler + formatter: simple + stream: ext://sys.stdout + root: + level: INFO + handlers: + - console + loggers: + logging_example: + level: DEBUG + disable_existing_loggers: false + job_logging: + version: 1 + formatters: + simple: + format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' + handlers: + console: + class: logging.StreamHandler + formatter: simple + stream: ext://sys.stdout + file: + class: logging.FileHandler + formatter: simple + filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log + root: + level: INFO + handlers: + - console + - file + disable_existing_loggers: false + env: {} + mode: RUN + searchpath: [] + callbacks: {} + output_subdir: .hydra + overrides: + hydra: + - hydra.mode=RUN + task: [] + job: + name: test_config + chdir: null + override_dirname: '' + id: ??? + num: ??? + config_name: experiments/debug + env_set: {} + env_copy: [] + config: + override_dirname: + kv_sep: '=' + item_sep: ',' + exclude_keys: [] + runtime: + version: 1.3.2 + version_base: '1.3' + cwd: /home/gelluisaac/Projects/astroml + config_sources: + - path: hydra.conf + schema: pkg + provider: hydra + - path: /home/gelluisaac/Projects/astroml/configs + schema: file + provider: main + - path: '' + schema: structured + provider: schema + output_dir: /home/gelluisaac/Projects/astroml/outputs/2026-03-24/12-38-43 + choices: + data@experiments.data: cora + training@experiments.training: default + model@experiments.model: gcn + hydra/env: default + hydra/callbacks: null + hydra/job_logging: default + hydra/hydra_logging: default + hydra/hydra_help: default + hydra/help: default + hydra/sweeper: basic + hydra/launcher: basic + hydra/output: default + verbose: false diff --git a/outputs/2026-03-24/12-38-43/.hydra/overrides.yaml b/outputs/2026-03-24/12-38-43/.hydra/overrides.yaml new file mode 100644 index 0000000..fe51488 --- /dev/null +++ b/outputs/2026-03-24/12-38-43/.hydra/overrides.yaml @@ -0,0 +1 @@ +[] diff --git a/outputs/2026-03-24/12-38-43/test_config.log b/outputs/2026-03-24/12-38-43/test_config.log new file mode 100644 index 0000000..e69de29 diff --git a/outputs/2026-03-24/12-39-11/.hydra/config.yaml b/outputs/2026-03-24/12-39-11/.hydra/config.yaml new file mode 100644 index 0000000..c510726 --- /dev/null +++ b/outputs/2026-03-24/12-39-11/.hydra/config.yaml @@ -0,0 +1,90 @@ +experiments: + model: + _target_: astroml.models.gcn.GCN + input_dim: ??? + hidden_dims: + - 16 + output_dim: ??? + dropout: 0.1 + activation: relu + batch_norm: false + residual: false + variants: + small: + hidden_dims: + - 32 + dropout: 0.2 + medium: + hidden_dims: + - 64 + - 32 + dropout: 0.5 + large: + hidden_dims: + - 128 + - 64 + - 32 + dropout: 0.6 + very_large: + hidden_dims: + - 256 + - 128 + - 64 + dropout: 0.7 + training: + epochs: 10 + lr: 0.01 + weight_decay: 0.0005 + optimizer: adam + scheduler: null + early_stopping: + patience: 50 + min_delta: 0.0001 + monitor: val_loss + mode: min + batch_size: null + val_split: 0.1 + test_split: 0.1 + shuffle: true + log_interval: 1 + save_best_only: true + save_last: true + optimizer_configs: + adam: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + amsgrad: false + sgd: + momentum: 0.9 + nesterov: true + adamw: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + weight_decay: 0.01 + data: + _target_: torch_geometric.datasets.Planetoid + name: Cora + root: data + transform: + _target_: torch_geometric.transforms.NormalizeFeatures + num_classes: 7 + num_node_features: 1433 + variants: + citeseer: + name: CiteSeer + num_classes: 6 + num_node_features: 3703 + pubmed: + name: PubMed + num_classes: 3 + num_node_features: 5003 + experiment: + name: debug_experiment + seed: 42 + device: auto + save_dir: outputs + log_level: INFO diff --git a/outputs/2026-03-24/12-39-11/.hydra/hydra.yaml b/outputs/2026-03-24/12-39-11/.hydra/hydra.yaml new file mode 100644 index 0000000..5ee96b7 --- /dev/null +++ b/outputs/2026-03-24/12-39-11/.hydra/hydra.yaml @@ -0,0 +1,157 @@ +hydra: + run: + dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S} + sweep: + dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S} + subdir: ${hydra.job.num} + launcher: + _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher + sweeper: + _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper + max_batch_size: null + params: null + help: + app_name: ${hydra.job.name} + header: '${hydra.help.app_name} is powered by Hydra. + + ' + footer: 'Powered by Hydra (https://hydra.cc) + + Use --hydra-help to view Hydra specific help + + ' + template: '${hydra.help.header} + + == Configuration groups == + + Compose your configuration from those groups (group=option) + + + $APP_CONFIG_GROUPS + + + == Config == + + Override anything in the config (foo.bar=value) + + + $CONFIG + + + ${hydra.help.footer} + + ' + hydra_help: + template: 'Hydra (${hydra.runtime.version}) + + See https://hydra.cc for more info. + + + == Flags == + + $FLAGS_HELP + + + == Configuration groups == + + Compose your configuration from those groups (For example, append hydra/job_logging=disabled + to command line) + + + $HYDRA_CONFIG_GROUPS + + + Use ''--cfg hydra'' to Show the Hydra config. + + ' + hydra_help: ??? + hydra_logging: + version: 1 + formatters: + simple: + format: '[%(asctime)s][HYDRA] %(message)s' + handlers: + console: + class: logging.StreamHandler + formatter: simple + stream: ext://sys.stdout + root: + level: INFO + handlers: + - console + loggers: + logging_example: + level: DEBUG + disable_existing_loggers: false + job_logging: + version: 1 + formatters: + simple: + format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' + handlers: + console: + class: logging.StreamHandler + formatter: simple + stream: ext://sys.stdout + file: + class: logging.FileHandler + formatter: simple + filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log + root: + level: INFO + handlers: + - console + - file + disable_existing_loggers: false + env: {} + mode: RUN + searchpath: [] + callbacks: {} + output_subdir: .hydra + overrides: + hydra: + - hydra.mode=RUN + task: [] + job: + name: test_config + chdir: null + override_dirname: '' + id: ??? + num: ??? + config_name: experiments/debug + env_set: {} + env_copy: [] + config: + override_dirname: + kv_sep: '=' + item_sep: ',' + exclude_keys: [] + runtime: + version: 1.3.2 + version_base: '1.3' + cwd: /home/gelluisaac/Projects/astroml + config_sources: + - path: hydra.conf + schema: pkg + provider: hydra + - path: /home/gelluisaac/Projects/astroml/configs + schema: file + provider: main + - path: '' + schema: structured + provider: schema + output_dir: /home/gelluisaac/Projects/astroml/outputs/2026-03-24/12-39-11 + choices: + data@experiments.data: cora + training@experiments.training: default + model@experiments.model: gcn + hydra/env: default + hydra/callbacks: null + hydra/job_logging: default + hydra/hydra_logging: default + hydra/hydra_help: default + hydra/help: default + hydra/sweeper: basic + hydra/launcher: basic + hydra/output: default + verbose: false diff --git a/outputs/2026-03-24/12-39-11/.hydra/overrides.yaml b/outputs/2026-03-24/12-39-11/.hydra/overrides.yaml new file mode 100644 index 0000000..fe51488 --- /dev/null +++ b/outputs/2026-03-24/12-39-11/.hydra/overrides.yaml @@ -0,0 +1 @@ +[] diff --git a/outputs/2026-03-24/12-39-11/test_config.log b/outputs/2026-03-24/12-39-11/test_config.log new file mode 100644 index 0000000..e69de29 diff --git a/outputs/2026-03-24/12-41-22/.hydra/config.yaml b/outputs/2026-03-24/12-41-22/.hydra/config.yaml new file mode 100644 index 0000000..c510726 --- /dev/null +++ b/outputs/2026-03-24/12-41-22/.hydra/config.yaml @@ -0,0 +1,90 @@ +experiments: + model: + _target_: astroml.models.gcn.GCN + input_dim: ??? + hidden_dims: + - 16 + output_dim: ??? + dropout: 0.1 + activation: relu + batch_norm: false + residual: false + variants: + small: + hidden_dims: + - 32 + dropout: 0.2 + medium: + hidden_dims: + - 64 + - 32 + dropout: 0.5 + large: + hidden_dims: + - 128 + - 64 + - 32 + dropout: 0.6 + very_large: + hidden_dims: + - 256 + - 128 + - 64 + dropout: 0.7 + training: + epochs: 10 + lr: 0.01 + weight_decay: 0.0005 + optimizer: adam + scheduler: null + early_stopping: + patience: 50 + min_delta: 0.0001 + monitor: val_loss + mode: min + batch_size: null + val_split: 0.1 + test_split: 0.1 + shuffle: true + log_interval: 1 + save_best_only: true + save_last: true + optimizer_configs: + adam: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + amsgrad: false + sgd: + momentum: 0.9 + nesterov: true + adamw: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + weight_decay: 0.01 + data: + _target_: torch_geometric.datasets.Planetoid + name: Cora + root: data + transform: + _target_: torch_geometric.transforms.NormalizeFeatures + num_classes: 7 + num_node_features: 1433 + variants: + citeseer: + name: CiteSeer + num_classes: 6 + num_node_features: 3703 + pubmed: + name: PubMed + num_classes: 3 + num_node_features: 5003 + experiment: + name: debug_experiment + seed: 42 + device: auto + save_dir: outputs + log_level: INFO diff --git a/outputs/2026-03-24/12-41-22/.hydra/hydra.yaml b/outputs/2026-03-24/12-41-22/.hydra/hydra.yaml new file mode 100644 index 0000000..d2f815f --- /dev/null +++ b/outputs/2026-03-24/12-41-22/.hydra/hydra.yaml @@ -0,0 +1,157 @@ +hydra: + run: + dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S} + sweep: + dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S} + subdir: ${hydra.job.num} + launcher: + _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher + sweeper: + _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper + max_batch_size: null + params: null + help: + app_name: ${hydra.job.name} + header: '${hydra.help.app_name} is powered by Hydra. + + ' + footer: 'Powered by Hydra (https://hydra.cc) + + Use --hydra-help to view Hydra specific help + + ' + template: '${hydra.help.header} + + == Configuration groups == + + Compose your configuration from those groups (group=option) + + + $APP_CONFIG_GROUPS + + + == Config == + + Override anything in the config (foo.bar=value) + + + $CONFIG + + + ${hydra.help.footer} + + ' + hydra_help: + template: 'Hydra (${hydra.runtime.version}) + + See https://hydra.cc for more info. + + + == Flags == + + $FLAGS_HELP + + + == Configuration groups == + + Compose your configuration from those groups (For example, append hydra/job_logging=disabled + to command line) + + + $HYDRA_CONFIG_GROUPS + + + Use ''--cfg hydra'' to Show the Hydra config. + + ' + hydra_help: ??? + hydra_logging: + version: 1 + formatters: + simple: + format: '[%(asctime)s][HYDRA] %(message)s' + handlers: + console: + class: logging.StreamHandler + formatter: simple + stream: ext://sys.stdout + root: + level: INFO + handlers: + - console + loggers: + logging_example: + level: DEBUG + disable_existing_loggers: false + job_logging: + version: 1 + formatters: + simple: + format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' + handlers: + console: + class: logging.StreamHandler + formatter: simple + stream: ext://sys.stdout + file: + class: logging.FileHandler + formatter: simple + filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log + root: + level: INFO + handlers: + - console + - file + disable_existing_loggers: false + env: {} + mode: RUN + searchpath: [] + callbacks: {} + output_subdir: .hydra + overrides: + hydra: + - hydra.mode=RUN + task: [] + job: + name: test_config + chdir: null + override_dirname: '' + id: ??? + num: ??? + config_name: experiments/debug + env_set: {} + env_copy: [] + config: + override_dirname: + kv_sep: '=' + item_sep: ',' + exclude_keys: [] + runtime: + version: 1.3.2 + version_base: '1.3' + cwd: /home/gelluisaac/Projects/astroml + config_sources: + - path: hydra.conf + schema: pkg + provider: hydra + - path: /home/gelluisaac/Projects/astroml/configs + schema: file + provider: main + - path: '' + schema: structured + provider: schema + output_dir: /home/gelluisaac/Projects/astroml/outputs/2026-03-24/12-41-22 + choices: + data@experiments.data: cora + training@experiments.training: default + model@experiments.model: gcn + hydra/env: default + hydra/callbacks: null + hydra/job_logging: default + hydra/hydra_logging: default + hydra/hydra_help: default + hydra/help: default + hydra/sweeper: basic + hydra/launcher: basic + hydra/output: default + verbose: false diff --git a/outputs/2026-03-24/12-41-22/.hydra/overrides.yaml b/outputs/2026-03-24/12-41-22/.hydra/overrides.yaml new file mode 100644 index 0000000..fe51488 --- /dev/null +++ b/outputs/2026-03-24/12-41-22/.hydra/overrides.yaml @@ -0,0 +1 @@ +[] diff --git a/outputs/2026-03-24/12-41-22/test_config.log b/outputs/2026-03-24/12-41-22/test_config.log new file mode 100644 index 0000000..f1b540a --- /dev/null +++ b/outputs/2026-03-24/12-41-22/test_config.log @@ -0,0 +1,189 @@ +[2026-03-24 12:41:22,710][__main__][INFO] - Configuration: +[2026-03-24 12:41:22,719][__main__][INFO] - experiments: + model: + _target_: astroml.models.gcn.GCN + input_dim: ??? + hidden_dims: + - 16 + output_dim: ??? + dropout: 0.1 + activation: relu + batch_norm: false + residual: false + variants: + small: + hidden_dims: + - 32 + dropout: 0.2 + medium: + hidden_dims: + - 64 + - 32 + dropout: 0.5 + large: + hidden_dims: + - 128 + - 64 + - 32 + dropout: 0.6 + very_large: + hidden_dims: + - 256 + - 128 + - 64 + dropout: 0.7 + training: + epochs: 10 + lr: 0.01 + weight_decay: 0.0005 + optimizer: adam + scheduler: null + early_stopping: + patience: 50 + min_delta: 0.0001 + monitor: val_loss + mode: min + batch_size: null + val_split: 0.1 + test_split: 0.1 + shuffle: true + log_interval: 1 + save_best_only: true + save_last: true + optimizer_configs: + adam: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + amsgrad: false + sgd: + momentum: 0.9 + nesterov: true + adamw: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + weight_decay: 0.01 + data: + _target_: torch_geometric.datasets.Planetoid + name: Cora + root: data + transform: + _target_: torch_geometric.transforms.NormalizeFeatures + num_classes: 7 + num_node_features: 1433 + variants: + citeseer: + name: CiteSeer + num_classes: 6 + num_node_features: 3703 + pubmed: + name: PubMed + num_classes: 3 + num_node_features: 5003 + experiment: + name: debug_experiment + seed: 42 + device: auto + save_dir: outputs + log_level: INFO + +[2026-03-24 12:41:22,720][__main__][INFO] - Configuration test successful! +[2026-03-24 12:41:22,720][__main__][INFO] - Configuration: +[2026-03-24 12:41:22,731][__main__][INFO] - experiments: + model: + _target_: astroml.models.gcn.GCN + input_dim: ??? + hidden_dims: + - 16 + output_dim: ??? + dropout: 0.1 + activation: relu + batch_norm: false + residual: false + variants: + small: + hidden_dims: + - 32 + dropout: 0.2 + medium: + hidden_dims: + - 64 + - 32 + dropout: 0.5 + large: + hidden_dims: + - 128 + - 64 + - 32 + dropout: 0.6 + very_large: + hidden_dims: + - 256 + - 128 + - 64 + dropout: 0.7 + training: + epochs: 10 + lr: 0.01 + weight_decay: 0.0005 + optimizer: adam + scheduler: null + early_stopping: + patience: 50 + min_delta: 0.0001 + monitor: val_loss + mode: min + batch_size: null + val_split: 0.1 + test_split: 0.1 + shuffle: true + log_interval: 1 + save_best_only: true + save_last: true + optimizer_configs: + adam: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + amsgrad: false + sgd: + momentum: 0.9 + nesterov: true + adamw: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + weight_decay: 0.01 + data: + _target_: torch_geometric.datasets.Planetoid + name: Cora + root: data + transform: + _target_: torch_geometric.transforms.NormalizeFeatures + num_classes: 7 + num_node_features: 1433 + variants: + citeseer: + name: CiteSeer + num_classes: 6 + num_node_features: 3703 + pubmed: + name: PubMed + num_classes: 3 + num_node_features: 5003 + experiment: + name: debug_experiment + seed: 42 + device: auto + save_dir: outputs + log_level: INFO + +[2026-03-24 12:41:22,733][__main__][INFO] - Test results: {'experiment_name': 'debug_experiment', 'model_hidden_dims': [16], 'training_lr': 0.01, 'training_epochs': 10, 'data_name': 'Cora'} +[2026-03-24 12:41:22,733][__main__][INFO] - Configuration test completed! +[2026-03-24 12:41:22,733][__main__][INFO] - Results: {'experiment_name': 'debug_experiment', 'model_hidden_dims': [16], 'training_lr': 0.01, 'training_epochs': 10, 'data_name': 'Cora'} +[2026-03-24 12:41:22,748][__main__][INFO] - Configuration saved to outputs diff --git a/outputs/2026-03-24/12-41-36/.hydra/config.yaml b/outputs/2026-03-24/12-41-36/.hydra/config.yaml new file mode 100644 index 0000000..ebea9b2 --- /dev/null +++ b/outputs/2026-03-24/12-41-36/.hydra/config.yaml @@ -0,0 +1,90 @@ +experiments: + model: + _target_: astroml.models.gcn.GCN + input_dim: ??? + hidden_dims: + - 32 + output_dim: ??? + dropout: 0.1 + activation: relu + batch_norm: false + residual: false + variants: + small: + hidden_dims: + - 32 + dropout: 0.2 + medium: + hidden_dims: + - 64 + - 32 + dropout: 0.5 + large: + hidden_dims: + - 128 + - 64 + - 32 + dropout: 0.6 + very_large: + hidden_dims: + - 256 + - 128 + - 64 + dropout: 0.7 + training: + epochs: 20 + lr: 0.001 + weight_decay: 0.0005 + optimizer: adam + scheduler: null + early_stopping: + patience: 50 + min_delta: 0.0001 + monitor: val_loss + mode: min + batch_size: null + val_split: 0.1 + test_split: 0.1 + shuffle: true + log_interval: 1 + save_best_only: true + save_last: true + optimizer_configs: + adam: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + amsgrad: false + sgd: + momentum: 0.9 + nesterov: true + adamw: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + weight_decay: 0.01 + data: + _target_: torch_geometric.datasets.Planetoid + name: Cora + root: data + transform: + _target_: torch_geometric.transforms.NormalizeFeatures + num_classes: 7 + num_node_features: 1433 + variants: + citeseer: + name: CiteSeer + num_classes: 6 + num_node_features: 3703 + pubmed: + name: PubMed + num_classes: 3 + num_node_features: 5003 + experiment: + name: debug_experiment + seed: 42 + device: auto + save_dir: outputs + log_level: INFO diff --git a/outputs/2026-03-24/12-41-36/.hydra/hydra.yaml b/outputs/2026-03-24/12-41-36/.hydra/hydra.yaml new file mode 100644 index 0000000..e69492a --- /dev/null +++ b/outputs/2026-03-24/12-41-36/.hydra/hydra.yaml @@ -0,0 +1,160 @@ +hydra: + run: + dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S} + sweep: + dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S} + subdir: ${hydra.job.num} + launcher: + _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher + sweeper: + _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper + max_batch_size: null + params: null + help: + app_name: ${hydra.job.name} + header: '${hydra.help.app_name} is powered by Hydra. + + ' + footer: 'Powered by Hydra (https://hydra.cc) + + Use --hydra-help to view Hydra specific help + + ' + template: '${hydra.help.header} + + == Configuration groups == + + Compose your configuration from those groups (group=option) + + + $APP_CONFIG_GROUPS + + + == Config == + + Override anything in the config (foo.bar=value) + + + $CONFIG + + + ${hydra.help.footer} + + ' + hydra_help: + template: 'Hydra (${hydra.runtime.version}) + + See https://hydra.cc for more info. + + + == Flags == + + $FLAGS_HELP + + + == Configuration groups == + + Compose your configuration from those groups (For example, append hydra/job_logging=disabled + to command line) + + + $HYDRA_CONFIG_GROUPS + + + Use ''--cfg hydra'' to Show the Hydra config. + + ' + hydra_help: ??? + hydra_logging: + version: 1 + formatters: + simple: + format: '[%(asctime)s][HYDRA] %(message)s' + handlers: + console: + class: logging.StreamHandler + formatter: simple + stream: ext://sys.stdout + root: + level: INFO + handlers: + - console + loggers: + logging_example: + level: DEBUG + disable_existing_loggers: false + job_logging: + version: 1 + formatters: + simple: + format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' + handlers: + console: + class: logging.StreamHandler + formatter: simple + stream: ext://sys.stdout + file: + class: logging.FileHandler + formatter: simple + filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log + root: + level: INFO + handlers: + - console + - file + disable_existing_loggers: false + env: {} + mode: RUN + searchpath: [] + callbacks: {} + output_subdir: .hydra + overrides: + hydra: + - hydra.mode=RUN + task: + - experiments.training.lr=0.001 + - experiments.model.hidden_dims=[32] + - experiments.training.epochs=20 + job: + name: test_config + chdir: null + override_dirname: experiments.model.hidden_dims=[32],experiments.training.epochs=20,experiments.training.lr=0.001 + id: ??? + num: ??? + config_name: experiments/debug + env_set: {} + env_copy: [] + config: + override_dirname: + kv_sep: '=' + item_sep: ',' + exclude_keys: [] + runtime: + version: 1.3.2 + version_base: '1.3' + cwd: /home/gelluisaac/Projects/astroml + config_sources: + - path: hydra.conf + schema: pkg + provider: hydra + - path: /home/gelluisaac/Projects/astroml/configs + schema: file + provider: main + - path: '' + schema: structured + provider: schema + output_dir: /home/gelluisaac/Projects/astroml/outputs/2026-03-24/12-41-36 + choices: + data@experiments.data: cora + training@experiments.training: default + model@experiments.model: gcn + hydra/env: default + hydra/callbacks: null + hydra/job_logging: default + hydra/hydra_logging: default + hydra/hydra_help: default + hydra/help: default + hydra/sweeper: basic + hydra/launcher: basic + hydra/output: default + verbose: false diff --git a/outputs/2026-03-24/12-41-36/.hydra/overrides.yaml b/outputs/2026-03-24/12-41-36/.hydra/overrides.yaml new file mode 100644 index 0000000..5d2d43a --- /dev/null +++ b/outputs/2026-03-24/12-41-36/.hydra/overrides.yaml @@ -0,0 +1,3 @@ +- experiments.training.lr=0.001 +- experiments.model.hidden_dims=[32] +- experiments.training.epochs=20 diff --git a/outputs/2026-03-24/12-41-36/test_config.log b/outputs/2026-03-24/12-41-36/test_config.log new file mode 100644 index 0000000..68bbe6c --- /dev/null +++ b/outputs/2026-03-24/12-41-36/test_config.log @@ -0,0 +1,189 @@ +[2026-03-24 12:41:37,036][__main__][INFO] - Configuration: +[2026-03-24 12:41:37,047][__main__][INFO] - experiments: + model: + _target_: astroml.models.gcn.GCN + input_dim: ??? + hidden_dims: + - 32 + output_dim: ??? + dropout: 0.1 + activation: relu + batch_norm: false + residual: false + variants: + small: + hidden_dims: + - 32 + dropout: 0.2 + medium: + hidden_dims: + - 64 + - 32 + dropout: 0.5 + large: + hidden_dims: + - 128 + - 64 + - 32 + dropout: 0.6 + very_large: + hidden_dims: + - 256 + - 128 + - 64 + dropout: 0.7 + training: + epochs: 20 + lr: 0.001 + weight_decay: 0.0005 + optimizer: adam + scheduler: null + early_stopping: + patience: 50 + min_delta: 0.0001 + monitor: val_loss + mode: min + batch_size: null + val_split: 0.1 + test_split: 0.1 + shuffle: true + log_interval: 1 + save_best_only: true + save_last: true + optimizer_configs: + adam: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + amsgrad: false + sgd: + momentum: 0.9 + nesterov: true + adamw: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + weight_decay: 0.01 + data: + _target_: torch_geometric.datasets.Planetoid + name: Cora + root: data + transform: + _target_: torch_geometric.transforms.NormalizeFeatures + num_classes: 7 + num_node_features: 1433 + variants: + citeseer: + name: CiteSeer + num_classes: 6 + num_node_features: 3703 + pubmed: + name: PubMed + num_classes: 3 + num_node_features: 5003 + experiment: + name: debug_experiment + seed: 42 + device: auto + save_dir: outputs + log_level: INFO + +[2026-03-24 12:41:37,047][__main__][INFO] - Configuration test successful! +[2026-03-24 12:41:37,048][__main__][INFO] - Configuration: +[2026-03-24 12:41:37,056][__main__][INFO] - experiments: + model: + _target_: astroml.models.gcn.GCN + input_dim: ??? + hidden_dims: + - 32 + output_dim: ??? + dropout: 0.1 + activation: relu + batch_norm: false + residual: false + variants: + small: + hidden_dims: + - 32 + dropout: 0.2 + medium: + hidden_dims: + - 64 + - 32 + dropout: 0.5 + large: + hidden_dims: + - 128 + - 64 + - 32 + dropout: 0.6 + very_large: + hidden_dims: + - 256 + - 128 + - 64 + dropout: 0.7 + training: + epochs: 20 + lr: 0.001 + weight_decay: 0.0005 + optimizer: adam + scheduler: null + early_stopping: + patience: 50 + min_delta: 0.0001 + monitor: val_loss + mode: min + batch_size: null + val_split: 0.1 + test_split: 0.1 + shuffle: true + log_interval: 1 + save_best_only: true + save_last: true + optimizer_configs: + adam: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + amsgrad: false + sgd: + momentum: 0.9 + nesterov: true + adamw: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + weight_decay: 0.01 + data: + _target_: torch_geometric.datasets.Planetoid + name: Cora + root: data + transform: + _target_: torch_geometric.transforms.NormalizeFeatures + num_classes: 7 + num_node_features: 1433 + variants: + citeseer: + name: CiteSeer + num_classes: 6 + num_node_features: 3703 + pubmed: + name: PubMed + num_classes: 3 + num_node_features: 5003 + experiment: + name: debug_experiment + seed: 42 + device: auto + save_dir: outputs + log_level: INFO + +[2026-03-24 12:41:37,057][__main__][INFO] - Test results: {'experiment_name': 'debug_experiment', 'model_hidden_dims': [32], 'training_lr': 0.001, 'training_epochs': 20, 'data_name': 'Cora'} +[2026-03-24 12:41:37,058][__main__][INFO] - Configuration test completed! +[2026-03-24 12:41:37,058][__main__][INFO] - Results: {'experiment_name': 'debug_experiment', 'model_hidden_dims': [32], 'training_lr': 0.001, 'training_epochs': 20, 'data_name': 'Cora'} +[2026-03-24 12:41:37,073][__main__][INFO] - Configuration saved to outputs diff --git a/outputs/astroml_experiment/2026-03-24_12-35-42/.hydra/config.yaml b/outputs/astroml_experiment/2026-03-24_12-35-42/.hydra/config.yaml new file mode 100644 index 0000000..7da9309 --- /dev/null +++ b/outputs/astroml_experiment/2026-03-24_12-35-42/.hydra/config.yaml @@ -0,0 +1,90 @@ +model: + _target_: astroml.models.gcn.GCN + input_dim: ??? + hidden_dims: + - 64 + - 32 + output_dim: ??? + dropout: 0.5 + activation: relu + batch_norm: false + residual: false + variants: + small: + hidden_dims: + - 32 + dropout: 0.2 + medium: + hidden_dims: + - 64 + - 32 + dropout: 0.5 + large: + hidden_dims: + - 128 + - 64 + - 32 + dropout: 0.6 + very_large: + hidden_dims: + - 256 + - 128 + - 64 + dropout: 0.7 +training: + epochs: 200 + lr: 0.01 + weight_decay: 0.0005 + optimizer: adam + scheduler: null + early_stopping: + patience: 50 + min_delta: 0.0001 + monitor: val_loss + mode: min + batch_size: null + val_split: 0.1 + test_split: 0.1 + shuffle: true + log_interval: 20 + save_best_only: true + save_last: true + optimizer_configs: + adam: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + amsgrad: false + sgd: + momentum: 0.9 + nesterov: true + adamw: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + weight_decay: 0.01 +data: + _target_: torch_geometric.datasets.Planetoid + name: Cora + root: data + transform: + _target_: torch_geometric.transforms.NormalizeFeatures + num_classes: 7 + num_node_features: 1433 + variants: + citeseer: + name: CiteSeer + num_classes: 6 + num_node_features: 3703 + pubmed: + name: PubMed + num_classes: 3 + num_node_features: 5003 +experiment: + name: astroml_experiment + seed: 42 + device: auto + save_dir: outputs + log_level: INFO diff --git a/outputs/astroml_experiment/2026-03-24_12-35-42/.hydra/hydra.yaml b/outputs/astroml_experiment/2026-03-24_12-35-42/.hydra/hydra.yaml new file mode 100644 index 0000000..754bd06 --- /dev/null +++ b/outputs/astroml_experiment/2026-03-24_12-35-42/.hydra/hydra.yaml @@ -0,0 +1,157 @@ +hydra: + run: + dir: outputs/${experiment.name}/${now:%Y-%m-%d_%H-%M-%S} + sweep: + dir: outputs/${experiment.name}/multirun + subdir: ${hydra.job.override_dirname} + launcher: + _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher + sweeper: + _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper + max_batch_size: null + params: null + help: + app_name: ${hydra.job.name} + header: '${hydra.help.app_name} is powered by Hydra. + + ' + footer: 'Powered by Hydra (https://hydra.cc) + + Use --hydra-help to view Hydra specific help + + ' + template: '${hydra.help.header} + + == Configuration groups == + + Compose your configuration from those groups (group=option) + + + $APP_CONFIG_GROUPS + + + == Config == + + Override anything in the config (foo.bar=value) + + + $CONFIG + + + ${hydra.help.footer} + + ' + hydra_help: + template: 'Hydra (${hydra.runtime.version}) + + See https://hydra.cc for more info. + + + == Flags == + + $FLAGS_HELP + + + == Configuration groups == + + Compose your configuration from those groups (For example, append hydra/job_logging=disabled + to command line) + + + $HYDRA_CONFIG_GROUPS + + + Use ''--cfg hydra'' to Show the Hydra config. + + ' + hydra_help: ??? + hydra_logging: + version: 1 + formatters: + simple: + format: '[%(asctime)s][HYDRA] %(message)s' + handlers: + console: + class: logging.StreamHandler + formatter: simple + stream: ext://sys.stdout + root: + level: INFO + handlers: + - console + loggers: + logging_example: + level: DEBUG + disable_existing_loggers: false + job_logging: + version: 1 + formatters: + simple: + format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' + handlers: + console: + class: logging.StreamHandler + formatter: simple + stream: ext://sys.stdout + file: + class: logging.FileHandler + formatter: simple + filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log + root: + level: INFO + handlers: + - console + - file + disable_existing_loggers: false + env: {} + mode: RUN + searchpath: [] + callbacks: {} + output_subdir: .hydra + overrides: + hydra: + - hydra.mode=RUN + task: [] + job: + name: test_config + chdir: null + override_dirname: '' + id: ??? + num: ??? + config_name: config + env_set: {} + env_copy: [] + config: + override_dirname: + kv_sep: '=' + item_sep: ',' + exclude_keys: [] + runtime: + version: 1.3.2 + version_base: '1.3' + cwd: /home/gelluisaac/Projects/astroml + config_sources: + - path: hydra.conf + schema: pkg + provider: hydra + - path: /home/gelluisaac/Projects/astroml/configs + schema: file + provider: main + - path: '' + schema: structured + provider: schema + output_dir: /home/gelluisaac/Projects/astroml/outputs/astroml_experiment/2026-03-24_12-35-42 + choices: + data: cora + training: default + model: gcn + hydra/env: default + hydra/callbacks: null + hydra/job_logging: default + hydra/hydra_logging: default + hydra/hydra_help: default + hydra/help: default + hydra/sweeper: basic + hydra/launcher: basic + hydra/output: default + verbose: false diff --git a/outputs/astroml_experiment/2026-03-24_12-35-42/.hydra/overrides.yaml b/outputs/astroml_experiment/2026-03-24_12-35-42/.hydra/overrides.yaml new file mode 100644 index 0000000..fe51488 --- /dev/null +++ b/outputs/astroml_experiment/2026-03-24_12-35-42/.hydra/overrides.yaml @@ -0,0 +1 @@ +[] diff --git a/outputs/astroml_experiment/2026-03-24_12-35-42/test_config.log b/outputs/astroml_experiment/2026-03-24_12-35-42/test_config.log new file mode 100644 index 0000000..11b0c27 --- /dev/null +++ b/outputs/astroml_experiment/2026-03-24_12-35-42/test_config.log @@ -0,0 +1,189 @@ +[2026-03-24 12:35:42,271][__main__][INFO] - Configuration: +[2026-03-24 12:35:42,286][__main__][INFO] - model: + _target_: astroml.models.gcn.GCN + input_dim: ??? + hidden_dims: + - 64 + - 32 + output_dim: ??? + dropout: 0.5 + activation: relu + batch_norm: false + residual: false + variants: + small: + hidden_dims: + - 32 + dropout: 0.2 + medium: + hidden_dims: + - 64 + - 32 + dropout: 0.5 + large: + hidden_dims: + - 128 + - 64 + - 32 + dropout: 0.6 + very_large: + hidden_dims: + - 256 + - 128 + - 64 + dropout: 0.7 +training: + epochs: 200 + lr: 0.01 + weight_decay: 0.0005 + optimizer: adam + scheduler: null + early_stopping: + patience: 50 + min_delta: 0.0001 + monitor: val_loss + mode: min + batch_size: null + val_split: 0.1 + test_split: 0.1 + shuffle: true + log_interval: 20 + save_best_only: true + save_last: true + optimizer_configs: + adam: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + amsgrad: false + sgd: + momentum: 0.9 + nesterov: true + adamw: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + weight_decay: 0.01 +data: + _target_: torch_geometric.datasets.Planetoid + name: Cora + root: data + transform: + _target_: torch_geometric.transforms.NormalizeFeatures + num_classes: 7 + num_node_features: 1433 + variants: + citeseer: + name: CiteSeer + num_classes: 6 + num_node_features: 3703 + pubmed: + name: PubMed + num_classes: 3 + num_node_features: 5003 +experiment: + name: astroml_experiment + seed: 42 + device: auto + save_dir: outputs + log_level: INFO + +[2026-03-24 12:35:42,287][__main__][INFO] - Configuration test successful! +[2026-03-24 12:35:42,287][__main__][INFO] - Configuration: +[2026-03-24 12:35:42,301][__main__][INFO] - model: + _target_: astroml.models.gcn.GCN + input_dim: ??? + hidden_dims: + - 64 + - 32 + output_dim: ??? + dropout: 0.5 + activation: relu + batch_norm: false + residual: false + variants: + small: + hidden_dims: + - 32 + dropout: 0.2 + medium: + hidden_dims: + - 64 + - 32 + dropout: 0.5 + large: + hidden_dims: + - 128 + - 64 + - 32 + dropout: 0.6 + very_large: + hidden_dims: + - 256 + - 128 + - 64 + dropout: 0.7 +training: + epochs: 200 + lr: 0.01 + weight_decay: 0.0005 + optimizer: adam + scheduler: null + early_stopping: + patience: 50 + min_delta: 0.0001 + monitor: val_loss + mode: min + batch_size: null + val_split: 0.1 + test_split: 0.1 + shuffle: true + log_interval: 20 + save_best_only: true + save_last: true + optimizer_configs: + adam: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + amsgrad: false + sgd: + momentum: 0.9 + nesterov: true + adamw: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + weight_decay: 0.01 +data: + _target_: torch_geometric.datasets.Planetoid + name: Cora + root: data + transform: + _target_: torch_geometric.transforms.NormalizeFeatures + num_classes: 7 + num_node_features: 1433 + variants: + citeseer: + name: CiteSeer + num_classes: 6 + num_node_features: 3703 + pubmed: + name: PubMed + num_classes: 3 + num_node_features: 5003 +experiment: + name: astroml_experiment + seed: 42 + device: auto + save_dir: outputs + log_level: INFO + +[2026-03-24 12:35:42,302][__main__][INFO] - Test results: {'experiment_name': 'astroml_experiment', 'model_hidden_dims': [64, 32], 'training_lr': 0.01, 'training_epochs': 200, 'data_name': 'Cora'} +[2026-03-24 12:35:42,303][__main__][INFO] - Configuration test completed! +[2026-03-24 12:35:42,303][__main__][INFO] - Results: {'experiment_name': 'astroml_experiment', 'model_hidden_dims': [64, 32], 'training_lr': 0.01, 'training_epochs': 200, 'data_name': 'Cora'} +[2026-03-24 12:35:42,325][__main__][INFO] - Configuration saved to outputs diff --git a/outputs/astroml_experiment/2026-03-24_12-36-17/.hydra/config.yaml b/outputs/astroml_experiment/2026-03-24_12-36-17/.hydra/config.yaml new file mode 100644 index 0000000..56882f5 --- /dev/null +++ b/outputs/astroml_experiment/2026-03-24_12-36-17/.hydra/config.yaml @@ -0,0 +1,90 @@ +model: + _target_: astroml.models.gcn.GCN + input_dim: ??? + hidden_dims: + - 128 + - 64 + output_dim: ??? + dropout: 0.5 + activation: relu + batch_norm: false + residual: false + variants: + small: + hidden_dims: + - 32 + dropout: 0.2 + medium: + hidden_dims: + - 64 + - 32 + dropout: 0.5 + large: + hidden_dims: + - 128 + - 64 + - 32 + dropout: 0.6 + very_large: + hidden_dims: + - 256 + - 128 + - 64 + dropout: 0.7 +training: + epochs: 300 + lr: 0.001 + weight_decay: 0.0005 + optimizer: adam + scheduler: null + early_stopping: + patience: 50 + min_delta: 0.0001 + monitor: val_loss + mode: min + batch_size: null + val_split: 0.1 + test_split: 0.1 + shuffle: true + log_interval: 20 + save_best_only: true + save_last: true + optimizer_configs: + adam: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + amsgrad: false + sgd: + momentum: 0.9 + nesterov: true + adamw: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + weight_decay: 0.01 +data: + _target_: torch_geometric.datasets.Planetoid + name: Cora + root: data + transform: + _target_: torch_geometric.transforms.NormalizeFeatures + num_classes: 7 + num_node_features: 1433 + variants: + citeseer: + name: CiteSeer + num_classes: 6 + num_node_features: 3703 + pubmed: + name: PubMed + num_classes: 3 + num_node_features: 5003 +experiment: + name: astroml_experiment + seed: 42 + device: auto + save_dir: outputs + log_level: INFO diff --git a/outputs/astroml_experiment/2026-03-24_12-36-17/.hydra/hydra.yaml b/outputs/astroml_experiment/2026-03-24_12-36-17/.hydra/hydra.yaml new file mode 100644 index 0000000..5649338 --- /dev/null +++ b/outputs/astroml_experiment/2026-03-24_12-36-17/.hydra/hydra.yaml @@ -0,0 +1,160 @@ +hydra: + run: + dir: outputs/${experiment.name}/${now:%Y-%m-%d_%H-%M-%S} + sweep: + dir: outputs/${experiment.name}/multirun + subdir: ${hydra.job.override_dirname} + launcher: + _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher + sweeper: + _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper + max_batch_size: null + params: null + help: + app_name: ${hydra.job.name} + header: '${hydra.help.app_name} is powered by Hydra. + + ' + footer: 'Powered by Hydra (https://hydra.cc) + + Use --hydra-help to view Hydra specific help + + ' + template: '${hydra.help.header} + + == Configuration groups == + + Compose your configuration from those groups (group=option) + + + $APP_CONFIG_GROUPS + + + == Config == + + Override anything in the config (foo.bar=value) + + + $CONFIG + + + ${hydra.help.footer} + + ' + hydra_help: + template: 'Hydra (${hydra.runtime.version}) + + See https://hydra.cc for more info. + + + == Flags == + + $FLAGS_HELP + + + == Configuration groups == + + Compose your configuration from those groups (For example, append hydra/job_logging=disabled + to command line) + + + $HYDRA_CONFIG_GROUPS + + + Use ''--cfg hydra'' to Show the Hydra config. + + ' + hydra_help: ??? + hydra_logging: + version: 1 + formatters: + simple: + format: '[%(asctime)s][HYDRA] %(message)s' + handlers: + console: + class: logging.StreamHandler + formatter: simple + stream: ext://sys.stdout + root: + level: INFO + handlers: + - console + loggers: + logging_example: + level: DEBUG + disable_existing_loggers: false + job_logging: + version: 1 + formatters: + simple: + format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' + handlers: + console: + class: logging.StreamHandler + formatter: simple + stream: ext://sys.stdout + file: + class: logging.FileHandler + formatter: simple + filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log + root: + level: INFO + handlers: + - console + - file + disable_existing_loggers: false + env: {} + mode: RUN + searchpath: [] + callbacks: {} + output_subdir: .hydra + overrides: + hydra: + - hydra.mode=RUN + task: + - training.lr=0.001 + - model.hidden_dims=[128,64] + - training.epochs=300 + job: + name: test_config + chdir: null + override_dirname: model.hidden_dims=[128,64],training.epochs=300,training.lr=0.001 + id: ??? + num: ??? + config_name: config + env_set: {} + env_copy: [] + config: + override_dirname: + kv_sep: '=' + item_sep: ',' + exclude_keys: [] + runtime: + version: 1.3.2 + version_base: '1.3' + cwd: /home/gelluisaac/Projects/astroml + config_sources: + - path: hydra.conf + schema: pkg + provider: hydra + - path: /home/gelluisaac/Projects/astroml/configs + schema: file + provider: main + - path: '' + schema: structured + provider: schema + output_dir: /home/gelluisaac/Projects/astroml/outputs/astroml_experiment/2026-03-24_12-36-17 + choices: + data: cora + training: default + model: gcn + hydra/env: default + hydra/callbacks: null + hydra/job_logging: default + hydra/hydra_logging: default + hydra/hydra_help: default + hydra/help: default + hydra/sweeper: basic + hydra/launcher: basic + hydra/output: default + verbose: false diff --git a/outputs/astroml_experiment/2026-03-24_12-36-17/.hydra/overrides.yaml b/outputs/astroml_experiment/2026-03-24_12-36-17/.hydra/overrides.yaml new file mode 100644 index 0000000..6cb0b5c --- /dev/null +++ b/outputs/astroml_experiment/2026-03-24_12-36-17/.hydra/overrides.yaml @@ -0,0 +1,3 @@ +- training.lr=0.001 +- model.hidden_dims=[128,64] +- training.epochs=300 diff --git a/outputs/astroml_experiment/2026-03-24_12-36-17/test_config.log b/outputs/astroml_experiment/2026-03-24_12-36-17/test_config.log new file mode 100644 index 0000000..d3ee508 --- /dev/null +++ b/outputs/astroml_experiment/2026-03-24_12-36-17/test_config.log @@ -0,0 +1,189 @@ +[2026-03-24 12:36:17,224][__main__][INFO] - Configuration: +[2026-03-24 12:36:17,233][__main__][INFO] - model: + _target_: astroml.models.gcn.GCN + input_dim: ??? + hidden_dims: + - 128 + - 64 + output_dim: ??? + dropout: 0.5 + activation: relu + batch_norm: false + residual: false + variants: + small: + hidden_dims: + - 32 + dropout: 0.2 + medium: + hidden_dims: + - 64 + - 32 + dropout: 0.5 + large: + hidden_dims: + - 128 + - 64 + - 32 + dropout: 0.6 + very_large: + hidden_dims: + - 256 + - 128 + - 64 + dropout: 0.7 +training: + epochs: 300 + lr: 0.001 + weight_decay: 0.0005 + optimizer: adam + scheduler: null + early_stopping: + patience: 50 + min_delta: 0.0001 + monitor: val_loss + mode: min + batch_size: null + val_split: 0.1 + test_split: 0.1 + shuffle: true + log_interval: 20 + save_best_only: true + save_last: true + optimizer_configs: + adam: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + amsgrad: false + sgd: + momentum: 0.9 + nesterov: true + adamw: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + weight_decay: 0.01 +data: + _target_: torch_geometric.datasets.Planetoid + name: Cora + root: data + transform: + _target_: torch_geometric.transforms.NormalizeFeatures + num_classes: 7 + num_node_features: 1433 + variants: + citeseer: + name: CiteSeer + num_classes: 6 + num_node_features: 3703 + pubmed: + name: PubMed + num_classes: 3 + num_node_features: 5003 +experiment: + name: astroml_experiment + seed: 42 + device: auto + save_dir: outputs + log_level: INFO + +[2026-03-24 12:36:17,234][__main__][INFO] - Configuration test successful! +[2026-03-24 12:36:17,235][__main__][INFO] - Configuration: +[2026-03-24 12:36:17,244][__main__][INFO] - model: + _target_: astroml.models.gcn.GCN + input_dim: ??? + hidden_dims: + - 128 + - 64 + output_dim: ??? + dropout: 0.5 + activation: relu + batch_norm: false + residual: false + variants: + small: + hidden_dims: + - 32 + dropout: 0.2 + medium: + hidden_dims: + - 64 + - 32 + dropout: 0.5 + large: + hidden_dims: + - 128 + - 64 + - 32 + dropout: 0.6 + very_large: + hidden_dims: + - 256 + - 128 + - 64 + dropout: 0.7 +training: + epochs: 300 + lr: 0.001 + weight_decay: 0.0005 + optimizer: adam + scheduler: null + early_stopping: + patience: 50 + min_delta: 0.0001 + monitor: val_loss + mode: min + batch_size: null + val_split: 0.1 + test_split: 0.1 + shuffle: true + log_interval: 20 + save_best_only: true + save_last: true + optimizer_configs: + adam: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + amsgrad: false + sgd: + momentum: 0.9 + nesterov: true + adamw: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + weight_decay: 0.01 +data: + _target_: torch_geometric.datasets.Planetoid + name: Cora + root: data + transform: + _target_: torch_geometric.transforms.NormalizeFeatures + num_classes: 7 + num_node_features: 1433 + variants: + citeseer: + name: CiteSeer + num_classes: 6 + num_node_features: 3703 + pubmed: + name: PubMed + num_classes: 3 + num_node_features: 5003 +experiment: + name: astroml_experiment + seed: 42 + device: auto + save_dir: outputs + log_level: INFO + +[2026-03-24 12:36:17,244][__main__][INFO] - Test results: {'experiment_name': 'astroml_experiment', 'model_hidden_dims': [128, 64], 'training_lr': 0.001, 'training_epochs': 300, 'data_name': 'Cora'} +[2026-03-24 12:36:17,244][__main__][INFO] - Configuration test completed! +[2026-03-24 12:36:17,245][__main__][INFO] - Results: {'experiment_name': 'astroml_experiment', 'model_hidden_dims': [128, 64], 'training_lr': 0.001, 'training_epochs': 300, 'data_name': 'Cora'} +[2026-03-24 12:36:17,259][__main__][INFO] - Configuration saved to outputs diff --git a/outputs/config.yaml b/outputs/config.yaml new file mode 100644 index 0000000..ebea9b2 --- /dev/null +++ b/outputs/config.yaml @@ -0,0 +1,90 @@ +experiments: + model: + _target_: astroml.models.gcn.GCN + input_dim: ??? + hidden_dims: + - 32 + output_dim: ??? + dropout: 0.1 + activation: relu + batch_norm: false + residual: false + variants: + small: + hidden_dims: + - 32 + dropout: 0.2 + medium: + hidden_dims: + - 64 + - 32 + dropout: 0.5 + large: + hidden_dims: + - 128 + - 64 + - 32 + dropout: 0.6 + very_large: + hidden_dims: + - 256 + - 128 + - 64 + dropout: 0.7 + training: + epochs: 20 + lr: 0.001 + weight_decay: 0.0005 + optimizer: adam + scheduler: null + early_stopping: + patience: 50 + min_delta: 0.0001 + monitor: val_loss + mode: min + batch_size: null + val_split: 0.1 + test_split: 0.1 + shuffle: true + log_interval: 1 + save_best_only: true + save_last: true + optimizer_configs: + adam: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + amsgrad: false + sgd: + momentum: 0.9 + nesterov: true + adamw: + betas: + - 0.9 + - 0.999 + eps: 1.0e-08 + weight_decay: 0.01 + data: + _target_: torch_geometric.datasets.Planetoid + name: Cora + root: data + transform: + _target_: torch_geometric.transforms.NormalizeFeatures + num_classes: 7 + num_node_features: 1433 + variants: + citeseer: + name: CiteSeer + num_classes: 6 + num_node_features: 3703 + pubmed: + name: PubMed + num_classes: 3 + num_node_features: 5003 + experiment: + name: debug_experiment + seed: 42 + device: auto + save_dir: outputs + log_level: INFO diff --git a/outputs/results.yaml b/outputs/results.yaml new file mode 100644 index 0000000..bfca0ac --- /dev/null +++ b/outputs/results.yaml @@ -0,0 +1,6 @@ +experiment_name: debug_experiment +model_hidden_dims: +- 32 +training_lr: 0.001 +training_epochs: 20 +data_name: Cora diff --git a/requirements-cpu.txt b/requirements-cpu.txt new file mode 100644 index 0000000..bde7c00 --- /dev/null +++ b/requirements-cpu.txt @@ -0,0 +1,18 @@ +# CPU-only requirements for faster installation +torch>=2.0.0+cpu --index-url https://download.pytorch.org/whl/cpu +torch-geometric>=2.3.0 + +numpy>=1.24 +pandas>=2.0 +sqlalchemy>=2.0 +alembic>=1.12 +psycopg2-binary>=2.9 +pyyaml>=6.0 +aiohttp>=3.9 +aiohttp-sse-client>=0.2.1 +pytest-asyncio>=0.23 +stellar-sdk>=9.0.0 +tenacity>=8.4.0 +hydra-core>=1.3.0 +omegaconf>=2.3.0 +pytorch-lightning>=2.0.0 diff --git a/requirements-minimal.txt b/requirements-minimal.txt new file mode 100644 index 0000000..8903c3a --- /dev/null +++ b/requirements-minimal.txt @@ -0,0 +1,6 @@ +# Minimal requirements for Hydra configuration system +numpy>=1.24 +pandas>=2.0 +pyyaml>=6.0 +hydra-core>=1.3.0 +omegaconf>=2.3.0 diff --git a/requirements.txt b/requirements.txt index 0e1189f..548e1d7 100644 --- a/requirements.txt +++ b/requirements.txt @@ -13,4 +13,7 @@ aiohttp-sse-client>=0.2.1 pytest-asyncio>=0.23 stellar-sdk>=9.0.0 tenacity>=8.4.0 +hydra-core>=1.3.0 +omegaconf>=2.3.0 +pytorch-lightning>=2.0.0 diff --git a/test_config.py b/test_config.py new file mode 100644 index 0000000..6c95e32 --- /dev/null +++ b/test_config.py @@ -0,0 +1,69 @@ +#!/usr/bin/env python3 +""" +Test script for Hydra configuration system (without PyTorch dependencies). + +Usage: + python test_config.py # Use default config + python test_config.py model.lr=0.001 # Override learning rate + python test_config.py experiment=debug # Use debug experiment +""" + +import logging +from pathlib import Path +from typing import Dict, Any + +from omegaconf import DictConfig, OmegaConf +import hydra +from hydra.utils import get_original_cwd + +# Set up logging +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + + +def test_config(cfg: DictConfig) -> Dict[str, Any]: + """Test function that just prints the configuration.""" + logger.info("Configuration test successful!") + logger.info("Configuration:") + logger.info(OmegaConf.to_yaml(cfg)) + + # Test accessing configuration values + results = { + "experiment_name": cfg.experiments.experiment.name, + "model_hidden_dims": cfg.experiments.model.hidden_dims, + "training_lr": cfg.experiments.training.lr, + "training_epochs": cfg.experiments.training.epochs, + "data_name": cfg.experiments.data.name, + } + + logger.info(f"Test results: {results}") + return results + + +@hydra.main(version_base=None, config_path="configs", config_name="config") +def main(cfg: DictConfig) -> None: + """Main entry point.""" + # Create save directory + save_dir = Path(cfg.experiments.experiment.save_dir) + save_dir.mkdir(parents=True, exist_ok=True) + + # Log configuration + logger.info("Configuration:") + logger.info(OmegaConf.to_yaml(cfg)) + + # Run test + results = test_config(cfg) + + # Log results + logger.info("Configuration test completed!") + logger.info(f"Results: {results}") + + # Save configuration + OmegaConf.save(cfg, save_dir / "config.yaml") + OmegaConf.save(OmegaConf.create(results), save_dir / "results.yaml") + + logger.info(f"Configuration saved to {save_dir}") + + +if __name__ == "__main__": + main() diff --git a/train.py b/train.py new file mode 100644 index 0000000..86b5d4c --- /dev/null +++ b/train.py @@ -0,0 +1,232 @@ +#!/usr/bin/env python3 +""" +Training script for AstroML experiments using Hydra configuration. + +Usage: + python train.py # Use default config + python train.py model.lr=0.001 # Override learning rate + python train.py experiment=debug # Use debug experiment + python train.py --multirun model.lr=0.001,0.01,0.1 # Hyperparameter sweep +""" + +import os +import logging +from pathlib import Path +from typing import Dict, Any + +import torch +import torch.nn.functional as F +from omegaconf import DictConfig, OmegaConf +import hydra +from hydra.utils import instantiate, get_original_cwd + +from astroml.models.gcn import GCN + +# Set up logging +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + + +def set_device(device_config: str) -> torch.device: + """Set up the computation device based on configuration.""" + if device_config == "auto": + device = torch.device("cuda" if torch.cuda.is_available() else "cpu") + else: + device = torch.device(device_config) + + logger.info(f"Using device: {device}") + return device + + +def load_dataset(cfg: DictConfig) -> Any: + """Load and prepare the dataset.""" + logger.info(f"Loading dataset: {cfg.data.name}") + + # Instantiate dataset from config + dataset = instantiate(cfg.data) + data = dataset[0] + + logger.info(f"Dataset loaded: {dataset.data}") + logger.info(f"Number of classes: {dataset.num_classes}") + logger.info(f"Number of node features: {dataset.num_node_features}") + + return dataset, data + + +def create_model(cfg: DictConfig, dataset: Any) -> torch.nn.Module: + """Create and initialize the model.""" + # Update model dimensions based on dataset + model_cfg = cfg.model.copy() + model_cfg.input_dim = dataset.num_node_features + model_cfg.output_dim = dataset.num_classes + + logger.info(f"Creating model with config: {model_cfg}") + model = instantiate(model_cfg) + + return model + + +def create_optimizer(cfg: DictConfig, model: torch.nn.Module) -> torch.optim.Optimizer: + """Create optimizer based on configuration.""" + optimizer_cfg = { + "params": model.parameters(), + "lr": cfg.training.lr, + } + + # Add optimizer-specific parameters + if cfg.training.optimizer == "adam": + optimizer_cfg.update(cfg.training.optimizer_configs.adam) + elif cfg.training.optimizer == "sgd": + optimizer_cfg.update(cfg.training.optimizer_configs.sgd) + elif cfg.training.optimizer == "adamw": + optimizer_cfg.update(cfg.training.optimizer_configs.adamw) + + logger.info(f"Creating {cfg.training.optimizer} optimizer with lr={cfg.training.lr}") + optimizer = getattr(torch.optim, cfg.training.optimizer.upper())(**optimizer_cfg) + + return optimizer + + +def train_epoch(model: torch.nn.Module, data: Any, optimizer: torch.optim.Optimizer, + device: torch.device) -> float: + """Train for one epoch.""" + model.train() + optimizer.zero_grad() + + out = model(data.x.to(device), data.edge_index.to(device)) + loss = F.nll_loss(out[data.train_mask], data.y.to(device)[data.train_mask]) + + loss.backward() + optimizer.step() + + return loss.item() + + +def evaluate(model: torch.nn.Module, data: Any, device: torch.device, + mask_name: str = "test_mask") -> Dict[str, float]: + """Evaluate the model.""" + model.eval() + + with torch.no_grad(): + out = model(data.x.to(device), data.edge_index.to(device)) + pred = out.argmax(dim=1) + + mask = getattr(data, mask_name) + correct = (pred[mask] == data.y.to(device)[mask]).sum() + accuracy = int(correct) / int(mask.sum()) + + # Calculate loss + loss = F.nll_loss(out[mask], data.y.to(device)[mask]).item() + + return {"accuracy": accuracy, "loss": loss} + + +def train(cfg: DictConfig) -> Dict[str, Any]: + """Main training function.""" + # Set up device + device = set_device(cfg.experiment.device) + + # Load dataset + dataset, data = load_dataset(cfg) + data = data.to(device) + + # Create model + model = create_model(cfg, dataset) + model = model.to(device) + + # Create optimizer + optimizer = create_optimizer(cfg, model) + + # Training loop + logger.info(f"Starting training for {cfg.training.epochs} epochs") + + best_val_acc = 0.0 + patience_counter = 0 + + for epoch in range(cfg.training.epochs): + # Train + train_loss = train_epoch(model, data, optimizer, device) + + # Evaluate + train_metrics = evaluate(model, data, device, "train_mask") + val_metrics = evaluate(model, data, device, "val_mask") + + # Log progress + if epoch % cfg.training.log_interval == 0: + logger.info( + f"Epoch {epoch:3d} | " + f"Train Loss: {train_loss:.4f} | " + f"Train Acc: {train_metrics['accuracy']:.4f} | " + f"Val Acc: {val_metrics['accuracy']:.4f}" + ) + + # Early stopping + if val_metrics['accuracy'] > best_val_acc: + best_val_acc = val_metrics['accuracy'] + patience_counter = 0 + + # Save best model + if cfg.training.save_best_only: + torch.save(model.state_dict(), + Path(cfg.experiment.save_dir) / "best_model.pth") + else: + patience_counter += 1 + + if (cfg.training.early_stopping.patience > 0 and + patience_counter >= cfg.training.early_stopping.patience): + logger.info(f"Early stopping at epoch {epoch}") + break + + # Final evaluation + test_metrics = evaluate(model, data, device, "test_mask") + logger.info(f"Test Accuracy: {test_metrics['accuracy']:.4f}") + + # Save final model + if cfg.training.save_last: + torch.save(model.state_dict(), + Path(cfg.experiment.save_dir) / "last_model.pth") + + # Save configuration + OmegaConf.save(cfg, Path(cfg.experiment.save_dir) / "config.yaml") + + return { + "test_accuracy": test_metrics['accuracy'], + "test_loss": test_metrics['loss'], + "best_val_accuracy": best_val_acc, + "epochs_trained": epoch + 1 + } + + +@hydra.main(version_base=None, config_path="configs", config_name="config") +def main(cfg: DictConfig) -> None: + """Main entry point.""" + # Create save directory + save_dir = Path(cfg.experiment.save_dir) + save_dir.mkdir(parents=True, exist_ok=True) + + # Log configuration + logger.info("Configuration:") + logger.info(OmegaConf.to_yaml(cfg)) + + # Set random seed + if cfg.experiment.seed is not None: + torch.manual_seed(cfg.experiment.seed) + if torch.cuda.is_available(): + torch.cuda.manual_seed(cfg.experiment.seed) + + # Run training + results = train(cfg) + + # Log results + logger.info("Training completed!") + logger.info(f"Results: {results}") + + # Save results + results_path = save_dir / "results.yaml" + OmegaConf.save(OmegaConf.create(results), results_path) + + logger.info(f"Results saved to {results_path}") + + +if __name__ == "__main__": + main()