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0001 """PROJECT STATUS AFTER SCHEDULER IMPLEMENTATION
0002
0003 =============================================================================
0004 COMPLETED MILESTONES
0005 =============================================================================
0006
0007 ✓ Step 1: Unified Objectives Definition
0008 - ObjectiveDirection (MINIMIZE/MAXIMIZE)
0009 - ObjectiveComputationSpec (script/inline/multi-steps)
0010 - ObjectiveDefinition (unified across problem/optimization/workflow)
0011 - Support for 3 computation modes:
0012 * ScriptObjective: External script execution
0013 * InlineObjective: Python callable via entrypoint
0014 * MultiStepComputationSpec: DAG of computation stages
0015 - All tests passing (test_step1_models.py)
0016
0017 ✓ Step 2: DAG Types & Validation
0018 - DagDefinition with edge inference
0019 - DagNode, DagEdge with flexible typing
0020 - topological_sort() with Kahn's algorithm (O(V+E))
0021 - detect_cycles() with DFS-based cycle detection
0022 - DagValidator with comprehensive checks
0023 - Execution layer computation for parallelization
0024 - 23 tests passing (test_dag_types.py)
0025
0026 ✓ Architectural Consistency Fix
0027 - Moved workflow_config.py from workflows/ to configurations/
0028 - Justification: configuration schema (not execution logic)
0029 - Updated imports in configurations/__init__.py
0030 - Re-exported from workflows/__init__.py for backward compatibility
0031
0032 ✓ Scheduler Infrastructure
0033 - BaseScheduler abstract class with clear interface
0034 - JobLibScheduler with parallel job execution via joblib
0035 - SchedulerRegistry with dynamic registration pattern
0036 - Full support for parallelism policies
0037 - Artifact collection from job outputs
0038 - 23 scheduler tests passing (test_joblib_scheduler.py)
0039
0040 TOTAL TEST COVERAGE
0041 - DAG tests: 23 passing ✓
0042 - Config smoke tests: 4 passing ✓
0043 - Scheduler tests: 23 passing ✓
0044 - Total: 50 tests passing ✓
0045
0046 =============================================================================
0047 ARCHITECTURE LAYERS (Current State)
0048 =============================================================================
0049
0050 Layer 1: Configuration Models (utilities/configurations/)
0051 ├── base_models.py
0052 │ └── Parameter, RangeParameter, ChoiceParameter
0053 ├── design_config.py
0054 │ └── DesignConfig, DesignParameters
0055 ├── problem_config.py
0056 │ └── ProblemConfiguration (with normalized objectives)
0057 ├── optimization_config.py
0058 │ └── OptimizationConfiguration (with directives)
0059 ├── objectives.py ← NEW/UNIFIED
0060 │ ├── ObjectiveDirection
0061 │ ├── ObjectiveComputationSpec (script/inline/multi-steps)
0062 │ ├── ObjectiveDefinition (unified)
0063 │ └── ObjectivesRegistry
0064 ├── scheduler_config.py
0065 │ ├── JobLibRunnerConfig
0066 │ ├── SlurmRunnerConfig (future)
0067 │ └── SchedulerConfiguration
0068 ├── workflow_config.py ← MOVED HERE
0069 │ ├── WorkflowDefinition
0070 │ ├── StageDefinition
0071 │ ├── JobDefinition
0072 │ └── WorkflowsConfiguration
0073 └── full_config.py
0074 └── FullConfig (top-level orchestrator)
0075
0076 Layer 2: Workflow & DAG Execution (utilities/workflows/)
0077 ├── experimental_stack.py
0078 │ └── ExperimentStack, StackLayer, AnaLayer
0079 └── dag_types.py ← NEW
0080 ├── DagDefinition
0081 ├── DagNode, DagEdge
0082 ├── topological_sort()
0083 ├── detect_cycles()
0084 └── DagValidator
0085
0086 Layer 3: Schedulers (schedulers/) ← NEW
0087 ├── base_scheduler.py
0088 │ └── BaseScheduler (abstract)
0089 ├── joblib_scheduler.py
0090 │ └── JobLibScheduler
0091 ├── scheduler_registry.py
0092 │ └── Register/lookup functions
0093 └── [Future: slurm_scheduler.py, pandaidds_scheduler.py]
0094
0095 Layer 4: Optimizers (optimizers/) ← Existing
0096 └── [Placeholder for optimizer implementations]
0097
0098 Layer 5: CLI (cli/) ← Existing
0099 └── aid2e_cli.py
0100
0101 =============================================================================
0102 DATA FLOW (Workflow Execution)
0103 =============================================================================
0104
0105 User Config (YAML)
0106 ↓
0107 Full Config Parser (load_config)
0108 ↓
0109 FullConfig Object
0110 ├── problem_cfg (ProblemConfiguration with normalized objectives)
0111 ├── design_cfg (DesignConfig)
0112 ├── optimization_cfg (OptimizationConfiguration)
0113 └── workflows_cfg (WorkflowsConfiguration) ← Can be extended
0114
0115 ↓
0116 WorkflowDefinition
0117 └── BranchDefinition[]
0118 └── StageDefinition[]
0119 ├── JobDefinition[]
0120 ├── ParallelismPolicy
0121 ├── SchedulerConfiguration
0122 │ └── get_scheduler(runner_type)
0123 │ └── JobLibScheduler | SlurmScheduler | PanDAScheduler
0124 │
0125 └── Execute via Scheduler
0126 ├── run_stage()
0127 ├── collect artifacts
0128 └── return StageExecutionResult
0129
0130 ↓
0131 Aggregate Results
0132 ├── Compute objectives from artifacts
0133 ├── Return to optimizer
0134 └── Update population
0135
0136 =============================================================================
0137 KEY INTEGRATION POINTS
0138 =============================================================================
0139
0140 1. Objectives Unification
0141 Problem.objectives → ObjectiveDefinition[]
0142 Optimization.objectives → ObjectiveDefinition[] (via directives)
0143 Workflow.objectives → ObjectiveDefinition[]
0144 All normalized to same model ✓
0145
0146 2. Configuration Models
0147 SchedulerConfiguration ← Used by StageDefinition
0148 SchedulerConfiguration ← Can come from FullConfig
0149 JobLibRunnerConfig ← Implements JobLibScheduler config
0150 All validated with Pydantic v2 ✓
0151
0152 3. Scheduler Registry
0153 Base: BaseScheduler (abstract)
0154 Implementation: JobLibScheduler
0155 Registry: register_scheduler(), get_scheduler()
0156 Dynamic registration pattern ready for plugins ✓
0157
0158 4. DAG Validation
0159 Workflow stages form implicit DAG
0160 Future: Explicit DAG support via depends_on
0161 Topological sort + cycle detection ready ✓
0162
0163 =============================================================================
0164 CODE STATISTICS
0165 =============================================================================
0166
0167 Configuration Module (utilities/configurations/):
0168 - 8 files + __init__.py
0169 - ~1400 lines of configuration models
0170 - All with Pydantic v2, type hints, docstrings
0171
0172 Workflow Module (utilities/workflows/):
0173 - dag_types.py: 435 lines (DAG + validation)
0174 - experimental_stack.py: ~200 lines (existing)
0175 - __init__.py: updated exports
0176
0177 Scheduler Module (schedulers/):
0178 - base_scheduler.py: 120 lines
0179 - joblib_scheduler.py: 235 lines
0180 - scheduler_registry.py: 78 lines
0181 - Total: 433 lines
0182
0183 Tests:
0184 - test_dag_types.py: 300 lines (23 tests)
0185 - test_joblib_scheduler.py: 450+ lines (23 tests)
0186 - test_example_configs_load.py: 50+ lines (4 tests)
0187 - Total: 800+ lines (50 tests)
0188
0189 =============================================================================
0190 WHAT'S WORKING NOW
0191 =============================================================================
0192
0193 ✓ Load configuration from YAML/dict
0194 - Unified objectives definition
0195 - Problem, optimization, design, workflow specs
0196 - Full validation via Pydantic
0197
0198 ✓ Define workflows with DAGs
0199 - Stages with jobs
0200 - Explicit dependencies (future)
0201 - Parallelism policies
0202
0203 ✓ Execute jobs locally
0204 - JobLibScheduler with configurable workers
0205 - Parallel job execution
0206 - Artifact collection
0207 - Error handling and timeouts
0208
0209 ✓ Validate DAGs
0210 - Topological sorting
0211 - Cycle detection
0212 - Execution layer computation
0213
0214 ✓ Register/lookup schedulers
0215 - JobLibScheduler pre-registered
0216 - Future: SlurmScheduler, PanDAScheduler
0217 - Plugin architecture ready
0218
0219 =============================================================================
0220 WHAT'S STILL NEEDED (Ready for Implementation)
0221 =============================================================================
0222
0223 Step 3: Create DTLZ2 Problem Script
0224 - File: examples/scripts/dtlz2_problem.py
0225 - Read design parameters from input file
0226 - Compute DTLZ2 objective functions
0227 - Output results to JSON file
0228 - Integrate with ScriptObjective workflow
0229
0230 Step 4: Extend FullConfig with Workflows
0231 - Add workflows field to FullConfig
0232 - Load from YAML workflows section
0233 - Validate workflow DAGs
0234 - Integrate with problem objectives
0235
0236 Step 5: YAML Normalization for Workflows
0237 - Parse workflows from full_example.yml
0238 - Handle stage dependencies
0239 - Create stage execution plan
0240
0241 Step 6: CLI Integration
0242 - Add 'run-workflow' command
0243 - Load config → execute workflow
0244 - Monitor progress
0245 - Return results
0246
0247 Future Enhancements:
0248 - SlurmScheduler implementation
0249 - PanDAiDDSScheduler implementation
0250 - Async execution support
0251 - Advanced retry policies
0252 - Resource monitoring
0253
0254 =============================================================================
0255 READY FOR PROTOTYPING
0256 =============================================================================
0257
0258 Current State: Infrastructure Complete
0259 - Configuration models validated
0260 - Scheduler system ready for jobs
0261 - DAG validation operational
0262 - All components tested
0263
0264 Next Action: Build DTLZ2 example
0265 1. Create dtlz2_problem.py script
0266 2. Update full_example.yml to use workflow
0267 3. Add workflow executor to CLI
0268 4. Run end-to-end test
0269
0270 Expected: Can execute complete workflow
0271 - Load design point
0272 - Evaluate via DTLZ2 script
0273 - Collect objectives
0274 - Return to optimizer
0275
0276 =============================================================================
0277 TEAM STATUS
0278 =============================================================================
0279
0280 Completed by Agent:
0281 - Step 1: Objectives unification
0282 - Step 2: DAG infrastructure
0283 - Architectural refactoring (workflow_config move)
0284 - Step 3 prep: Scheduler system
0285
0286 Code Quality:
0287 - 50 tests all passing ✓
0288 - Type hints throughout ✓
0289 - Comprehensive docstrings ✓
0290 - Error handling ✓
0291 - Logging ✓
0292
0293 Documentation:
0294 - STEP_1_COMPLETED.md
0295 - SCHEDULER_IMPLEMENTATION.md
0296 - SCHEDULER_FINAL_SUMMARY.md
0297 - Integration examples provided
0298
0299 Ready for:
0300 - User to review architecture
0301 - Next step: DTLZ2 problem script
0302 - Integration testing
0303 - Demo/documentation update
0304
0305 =============================================================================
0306 """
