data/examples/attention_optimization/configs/failing_config.yaml

# OpenEvolve configuration for MLIR attention optimization

# LLM configuration
llm:
  primary_model: "gpt-4.1-nano"
  #  secondary_models: ["gpt-4.1-mini"]
  temperature: 0.7
  max_tokens: 2048

# Evolution parameters
evolution:
  max_iterations: 500
  population_size: 50
  mutation_rate: 0.15
  crossover_rate: 0.8
  selection_strategy: "tournament"
  tournament_size: 5

# Database configuration  
database:
  population_size: 100
  num_islands: 3
  migration_rate: 0.1

# Evaluation settings
evaluation:
  timeout_seconds: 120
  max_retries: 3
  parallel_evaluations: 4

# Checkpoint settings
checkpoints:
  enabled: true
  interval: 10
  keep_best: true
  save_all_programs: false

# Early stopping settings (moved to top level)
early_stopping_patience: 50          # Stop after 50 iterations without improvement
convergence_threshold: 0.001         # Minimum improvement required
early_stopping_metric: "speedup"     # Track speedup metric

# Optimization targets
optimization:
  target_metric: "speedup"
  target_value: 1.32  # 32% speedup like AlphaEvolve paper
  minimize: false

# Logging
logging:
  level: "INFO"
  save_logs: true
  verbose: true