2df1ea92e1
BREAKING CHANGES: - Removed orphaned dqn.rs monolithic trainer (4,975 lines) - Removed orphaned dqn_ensemble.rs module (816 lines) - Removed orphaned tft.rs and tft_complete_int8_integration_test.rs - TFT trainer split into modular directory structure DQN Module Refactoring: - Split trainers/dqn.rs into modular structure (config.rs, statistics.rs, trainer.rs) - Fixed hyperopt 39D search space (continuous params only) - Boolean flags (use_dueling, use_double_dqn, use_per, use_noisy_nets) are now FIXED architectural decisions - use_distributional defaults to false (Candle BUG #36 - scatter_add gradient issues) Clean Module Structure: - ml/src/trainers/dqn/ directory with proper mod.rs exports - ml/src/trainers/tft/ directory with config.rs, types.rs, model.rs, trainer.rs, tests.rs - All P0 features validated: TD-error clamping, batch diversity, LR scheduler, priority staleness Documentation: - Added comprehensive docs in docs/codebase-cleanup/ - ADR-001 for DQN refactoring decisions - Rainbow DQN component matrix and quick reference guides Build Status: Compiles with zero errors 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
65 lines
1.8 KiB
Bash
Executable File
65 lines
1.8 KiB
Bash
Executable File
#!/bin/bash
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# Test script for DQN evaluation orchestrator
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set -e # Exit on error
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echo "=================================================="
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echo "DQN Evaluation Orchestrator - Architecture Fix Test"
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echo "=================================================="
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echo ""
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# Check if model file exists
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MODEL_PATH="/tmp/dqn_final_model.safetensors"
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DATA_PATH="test_data/ES_FUT_unseen.parquet"
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if [ ! -f "$MODEL_PATH" ]; then
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echo "❌ ERROR: Model file not found: $MODEL_PATH"
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echo ""
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echo "Please train the DQN model first:"
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echo " cargo run -p ml --example train_dqn --release --features cuda"
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exit 1
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fi
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if [ ! -f "$DATA_PATH" ]; then
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echo "❌ ERROR: Test data not found: $DATA_PATH"
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echo ""
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echo "Please ensure test data exists:"
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echo " ls -lh test_data/"
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exit 1
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fi
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echo "✅ Prerequisites check passed"
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echo " Model: $MODEL_PATH"
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echo " Data: $DATA_PATH"
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echo ""
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# Run evaluation
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echo "Running DQN evaluation..."
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echo "Command: cargo run -p ml --example evaluate_dqn_main_orchestrator --release --features cuda -- \\"
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echo " --model-path $MODEL_PATH \\"
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echo " --parquet-file $DATA_PATH \\"
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echo " --warmup-bars 50"
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echo ""
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cargo run -p ml --example evaluate_dqn_main_orchestrator --release --features cuda -- \
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--model-path "$MODEL_PATH" \
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--parquet-file "$DATA_PATH" \
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--warmup-bars 50
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EXIT_CODE=$?
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echo ""
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if [ $EXIT_CODE -eq 0 ]; then
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echo "✅ Evaluation completed successfully!"
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echo ""
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echo "Expected output:"
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echo " - ✅ DQN checkpoint loaded successfully (8 tensors)"
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echo " - Model architecture: 225 → [128, 64, 32] → 3"
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echo " - Action distribution (BUY/SELL/HOLD percentages)"
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echo " - Latency statistics (P50, P95, P99)"
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echo " - Production readiness check"
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else
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echo "❌ Evaluation failed with exit code: $EXIT_CODE"
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exit $EXIT_CODE
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fi
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