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iXnYvjfU62dXc2wHW2ig3qG283mo1jk/Li5vb37+/Dt4fjl/u63W3413j8e3j9+/3Z4d/zwANnvEN3e0qunhU+LnBY9LXZa/LS00xKnJU9LX4+f1ax6eFXEqyZeVfGqi1dlvGrjxPJ2Z+Rf3z8/Hr9+PsKHi7FMRMt6lZwf/Fn260d++WeZHsY19PL5ZrGQW14cWLS75PomQkvj6OdwiOTC2KzrOy3G4m0NhoQtqm6uUxC+fPz4cHh8DsDriy3//4mmh/+4f/PjcCulr1l9jYhpSJPLr0lKHpvXbOeUj1fR5EsIiDhCLi7/efzw4XD/7vv98cnfJ3zd3W+d//H0H9I3fJGNv+enoVZCiFa4XWTZvG9FMMZMXGQrlMUd9u03ymLUk62cpjQ7g3sV8uKduO+O8xKmvttmC5OotqKwKWdmEaZQy3q1G+VeJy+s0c5xf/YwpPs+EEFq5wycZWzc69Gg5lyF2i1aOdy4pfJF9PbVv2Wlde65N5okdH8zZCUIunSEi2W/S4mJs8paUA2gSopPuRPLVoXAtZPunVMjTa+nkSluBSOszq2ADlggqmlmCqC+COEfCmXvTos+Zc8T2C63MAt7K/usu8e1pADZ3JViXwJ98JhPSIquujcQYPdWspfkPfs+f95IO5dKEdsXgCyDGqzUTjNUci9HOy7eo3DkmdkspqSwRHUlPcKkgLi5RE4lYMIlAdaSuPqiHE3qadjt093M2S2v5WXQbXJrWn0MlYpQUVBoFNx1t4leuqlJL95Et64TvME5vRYq0Z4qh0YeBhWN5s2ymBPWS3ABntSwKiM00GIia68bIUxJrQEXY+q2x5QpU5NaQ+qhE76hU66zGMDt1iagSAktKN6cJ+JuaPS9RgJgdpmylVZrZuS65d6bUUjg+Jxx5mQFFYxqrbGgjglFStU0qwSAoAXbXEnxPAk8wwcMUJGig1snokC2axZSNWXymiLatdQgjtqsxHEQCCJWiBWISK5U4YrUFvR0NIl6FixohQetme35CO3Yo04HwAlatFVMoMX45DOF2h49uoh7q+WmgNnU3ALjSi0O9x69UEfi3nngSOR54hMrgRiMOdrOVSaTUVlmpXszkNMr5EW8ex29SDA+emkU3WuvFEOjrvDsGE3VSv60NynkhllMJvqWUQVl1Bm0WjxJMCBnpSyMHCVchlG3FZnOwwHw4RNf2a8qKsm8YA5EgjZ9NSUYqMADqbUAEML9LKbDwmyF2Az9UyuHjYTSROfNnSdic/TKkhQ0bvWaFHTpmDo3w8a9iZgDo9dhjHCxFwYDOcTUFBUTY0myOJXpDjKENqtIpz6QGDbqPu09bJOUm5Kcuz/2nzJII+hkS/1PzTJkm218QhjM3MRn+ALJdmQYaXGQ1V7kmOC35A4R4te3KRl9KjGzTaa+kRe+uvD9Ia1CYBCHTFOxtql5Y/S2MugBpxigrTZBI2BgmiYxvnn9uGiYT/r1lo57ZdJHWugEUx4aMlfqTybi+gGDzl9nVrIWUl1hpaSKl0Drby/hRQpeBGpkYxdyHIrPlputhp+Xr+xP7x8P0HD3cLz/9Plwd/Pz5h+Bidnw","weights_sha256":"058c2af38034b617b3d4e5c4a9f7869a739368c1b42ba2182db7445771584ed0","IA_patch_zb64":"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","IA_patch_sha256":"2b1cd0b4278962d3e68fab51fee530b3d379adfbf3efaffd9b332ab5d6cb8d82","decode_instructions":"Inside the pinned checkout, for each api.files entry k -> filename, b=zlib.decompress(base64.b64decode(result[k+\"_zb64\"])); assert hashlib.sha256(b).hexdigest()==result[k+\"_sha256\"]; write to scratch/kit/filename. Decode all files as siblings. Write the complete result JSON as scratch/kit/result.json. Use the exact SETUP script in the goal once before decoding; its hash is recorded. Restore the exact original IA offline with: . scratch/env.sh && python scratch/kit/harness.py restore-ia --out scratch/kit/IA.sol. HA.sol and T.sol are intentionally not included. paired_deltas_zb64 decodes to 612 rows of three little-endian float64 values: IAD minus IA edge, retail edge, arb edge. First 100 rows map to seeds 0..99; last 512 map to 7277824..7278335. Verify paired_deltas_sha256 before reading.","api":{"files":{"sim":"sim.py","port":"port.py","harness":"harness.py","diff_test":"diff_test.py","tests":"test_kit.py","IAD.sol":"IAD.sol","weights":"weights.json","IA_patch":"IA.patch.json"},"weights":"weights.json v1: feature_ids[n] select/reorder/repeat IDs 0..18; feature_multipliers[n], feature_offsets[n], hidden_units=h; nets of W1[h,n],b1[h],W2[2,h],b2[2]. gate=single or firstInStep (net0 first print, net1 subsequent). n,h=1..64 subject to compile/code-size/gas gates. IA=178 weights; 19-16-2=354; two nets=708.","feature_names":["sigmaHat","lambdaHat","sizeHat","toxEma","actEma","direction","(spot-staleHat)/staleHat","signed_trade_ratio","arb_probability","first_in_step","uncertainty","min(silent,8)/8","anchor_mean","raw_size","step_trade_count","prev_bid_fee","prev_ask_fee","steps_since_arb_like_print","router_implied_vanilla_spot_dev"],"numerical_convention":"Real-unit raw features; affine scaling, clip [-4,4], ReLU clip [0,4], output in bps added at 1e-4 and fee clamp [0,.1]. Quantize coefficients to 1e-6. Solidity divisions truncate toward zero; A/C measure float-port error.","port":"policy(spec) or load(weights_path) -> W. strat_init(S,W,x0,y0); strat_after(S,W,is_buy,amount_x,amount_y,timestamp,reserve_x,reserve_y). Fresh zeros(40) each market. W=[enabled,n,h,nets,ids[n],mult[n],off[n],each net W1/b1/W2/b2]. PT/TH_BASE_VALUES retain RS2 constants; audit literal entries are not tunable.","sim":"run_market(W,seed,mean_size,rate,sigma,n_steps); run_many(W,seeds,procs=8,n_steps=10000) -> rows [edge,retail_edge,arb_edge,retail_volume]. Each policy runs alone against 30 bps Vanilla.","harness":"policy(w,spec), weights(W), with_weights(spec,w), expand(spec,h), emit_solidity(spec), freeze(directory,spec,checkpoint=None), train, holdout, real, aggregate. Both backends use one normalized weights JSON. At most eight units per Solidity function; combine partial sums before final output division.","validation":"train requires measured A/B/C, bound port/sim and policy/code hashes. Freeze is hashed; holdout once-only; locked ledger reserves before evaluation. Any OOG/error or afterSwap peak >245000 invalidates real results.","references":"restore-ia recovers exact pinned IA offline from IAD.sol + IA.patch.json, checking both hashes. Replica T is port.TH_T."},"commands":{"setup":"Clone the pinned commit inside the workspace; save the goal SETUP script as scratch/setup.sh and run sh scratch/setup.sh once from checkout root. Decode files to scratch/kit/.","tests":"python scratch/kit/test_kit.py","speed":"python scratch/kit/harness.py speed --n 512 --procs 8 --out scratch/speed.json","restore_ia":"python scratch/kit/harness.py restore-ia --out scratch/kit/IA.sol","gate_A":"python scratch/kit/diff_test.py --source scratch/kit/IA.sol --threshold .01 --sequences 50 --out scratch/A.json","gate_B":"python scratch/kit/harness.py replica --start 7116384 --n 512 --procs 8 --out scratch/B.json; compare mean_diff with 1.513, absolute error <.15","freeze":"python scratch/kit/harness.py freeze --weights scratch/kit/weights.json --directory scratch/frozen","gate_C":"python scratch/kit/diff_test.py --source scratch/frozen/Candidate.sol --weights scratch/frozen/weights.json --reference scratch/kit/IA.sol --threshold .1 --sequences 50 --out scratch/C.json","expand":"python scratch/kit/harness.py expand --units 16 --out scratch/weights16.json","train":"python scratch/kit/harness.py train --weights scratch/kit/weights.json --validation scratch/kit/result.json --checkpoint scratch/train.pkl --generations 1 --train-n 256 --procs 8 --seconds 420","freeze_trained":"python scratch/kit/harness.py freeze --checkpoint scratch/train.pkl --directory scratch/trained_frozen","holdout":"python scratch/kit/harness.py holdout --frozen scratch/trained_frozen --ledger scratch/evaluation_seeds.jsonl --procs 8 --out scratch/holdout.json","real":"python scratch/kit/harness.py real --start FRESH_START --n 64 --arm IA=scratch/kit/IA.sol --arm Candidate=scratch/trained_frozen/Candidate.sol --ledger scratch/evaluation_seeds.jsonl --out scratch/real_FRESH_START.json","aggregate":"python scratch/kit/harness.py aggregate --out scratch/summary.json scratch/real_CHUNK1.json scratch/real_CHUNK2.json","regression":"python scratch/kit/harness.py real --regression --start START --n COUNT --arm IA=scratch/kit/IA.sol --arm IAD=scratch/kit/IAD.sol --ledger scratch/regression_seeds.jsonl --out scratch/regression_START.json (START,COUNT: 0,8; 8,46; 54,46)","future_confirmation":"Train/holdout/future real are not run here. Use unused >=7000000 seeds. Changed weights require C and gas checks; omit --reference IA for changed policies.","prefix":". scratch/env.sh && timeout 470 ","usage":"Prepend commands.prefix to each CLI string from checkout root. Setup is separate. Uppercase parameters are supplied explicitly."},"hashes":{"repository_commit":"6b6921f8d463314aa7c96234e1be25a25245f704","wheel_sha256":"aedb68280aca34c110968f00148387c95885207913fb2cf19a1ab4c5cfd6887a","inputs":{"HA":"2801efc8190e86318dd922d4a7179f63684d77a226047fc2f3c78232963eb690","T":"6ac5e013b7b1fb4c5e7bdcdfec0aba28b16824e18ccf39500f258533879faffe","replica":"e8a7a2af9039c24b8bb2d3b5fa1c9113606cbf5a480ac07d02ca26750f1752ea","RS2":"d845a4b94eab87f23956fd1939c0135d955df212d1f3037f2a761c178cef7a0e","KIT":"0d8194e9f6e0017dc4e515cdb04c048efc292935bb1d18e3336091fe81154786","IA":"df0ddfdf122c88641513dd179980fce475f42a912a184f812d213f27db7c14df","DIET":"19160955248c44ac54623ad40112d2b6c3b1c6f6745d9101a5e9b278f512192a"},"decoded":{"HA.sol":"99e3a2eceae0e5543d27473859e10b005d0ce0aa7067f2e1a24d1e0e4a7390fe","T.sol":"ebd9de9bf6af6e55d5e308fd15dbb88edec11fd684891d02a30aec185acd19b3","replica_original.py":"1e4c44b4bffbdeed65872ee15d46dbde209bf5aa11014329d13d100507b4040c","rs2_original.py":"9eac3553357528b06eeae3ed8d18283d83401e1968145ceba16be356a147e271","kit/sim.py":"d003c663b94968b58aaefb65fef8e910638ee1664e19f96c809b45e499910638","kit/port.py":"9aa80ce98b31cb18b14192a87a9b6d133e4c9c2d7adc4a51a5f170be95d92fef","kit/harness.py":"24169a30bddafe5f82fa6873adcd7d6c15892f883d1af25eebaa9b5f623606bc","kit/diff_test.py":"32345abab9b1ea77ebe084b02e1c4b7bb692b5202af7c62572e36f96d3e2cb5b","kit/test_kit.py":"2ff44560ef5b8ee5d5e1c32daf4e2c63b05fb858b9a4646640884fc66ca22bcd","kit/HA.sol":"99e3a2eceae0e5543d27473859e10b005d0ce0aa7067f2e1a24d1e0e4a7390fe","kit/T.sol":"ebd9de9bf6af6e55d5e308fd15dbb88edec11fd684891d02a30aec185acd19b3","IA.sol":"956566e95f46dc1ed5980fae5e550de7b9da10f9b3ad8eed62f265682cfcecf2","ia_port.py":"b29cd2a078b4c3fc57945a79e927624dd346c44d8cc149dae43f4929aa6d736b","DIET.sol":"269c03a4f7758b2ec15ee9f4ae74d64c59d0aacfa00b6d40c9dde87d4aec1e31"},"setup_script_sha256":"f3abb169ae32d5b1c3d8604d693fa1c646dcbda1a527aab6cc6c8402724f392b","artifact_base_url":"https://api.imdnotdead.fun/artifacts/"},"speed":{"original_kit":{"n":512,"n_steps":10000,"requested_processes":8,"created_processes":8,"active_processes":8,"seconds":0.6688634080346674,"markets_per_second":765.4776653194682,"warm_compile_excluded":true,"pool_startup_included":true},"supplied_IA_port":{"seconds":0.8057476538233459,"markets_per_second":635.4346768129121,"procs":8,"n_steps":10000,"warm_compile_excluded":true},"generalized_port":{"n":512,"n_steps":10000,"requested_processes":8,"created_processes":8,"active_processes":8,"seconds":1.561448693042621,"markets_per_second":327.9006234923561,"warm_compile_excluded":true,"pool_startup_included":true},"search_budget":0,"search_sizing":"No search requested or performed; benchmark precedes implementation/evaluation."},"gates":{"A":{"sequences":50,"swap_callbacks":100000,"max_abs_fee_difference_bps":6.501554232485329e-05,"seed_start":310000,"seed_end":310049,"passed":true,"threshold_bps":0.01,"starting_code_sha256":"956566e95f46dc1ed5980fae5e550de7b9da10f9b3ad8eed62f265682cfcecf2","starting_port_sha256":"b29cd2a078b4c3fc57945a79e927624dd346c44d8cc149dae43f4929aa6d736b","fee_share_above_threshold":0.0},"B":{"n":512,"mean_diff":1.4654026984931672,"se":0.04614738409203076,"worst5":[[7116659,-4.081829157716129],[7116587,-2.3538707050371954],[7116521,-2.072809979759313],[7116459,-1.9394058801563006],[7116428,-1.1341120579523931]],"retail_delta":4.6780451091284165,"arb_delta":-3.21264241063525,"seeds":[7116384,7116895],"policy_sha256":"74d370d4b5210ae2bc782a374f8d0d762f57f875ba74bd670abf3aaaea616bee","passed":true,"error":0.04759730150683272,"threshold_gain_error":0.15,"reference_real":1.513,"reference_source_url":"https://api.imdnotdead.fun/artifacts/df0ddfdf122c88641513dd179980fce475f42a912a184f812d213f27db7c14df"},"C":{"IAD":{"passed":true,"sequences":50,"swap_callbacks":100000,"max_abs_fee_difference_bps":6.501554232485329e-05,"threshold_bps":0.1,"exact_reference_callback_mismatches":0,"seed_start":310000,"seed_end":310049,"code_sha256":"7f6998c8df1b738dbd9715053edae7c9c8fdad71bf7228d67b6f1b7573c7126b","policy_sha256":"74d370d4b5210ae2bc782a374f8d0d762f57f875ba74bd670abf3aaaea616bee"},"wide16":{"passed":true,"sequences":50,"swap_callbacks":100000,"max_abs_fee_difference_bps":6.501554232485329e-05,"threshold_bps":0.1,"exact_reference_callback_mismatches":0,"seed_start":310000,"seed_end":310049,"code_sha256":"31b6409cbf742ba6f6df2fa36baba069262d68bee56901ebdec8d4bdd4d1c797","policy_sha256":"e8085752793be9bc038f6003712e9578fbe9890f11992de5a828dc3401f20ff4"},"emitted":{"passed":true,"sequences":50,"swap_callbacks":100000,"max_abs_fee_difference_bps":6.501554232485329e-05,"threshold_bps":0.1,"exact_reference_callback_mismatches":0,"seed_start":310000,"seed_end":310049,"code_sha256":"c20b170819e86adc7f59fd0d2a56b1a3463883ad29e471957538037d62da99a4","policy_sha256":"74d370d4b5210ae2bc782a374f8d0d762f57f875ba74bd670abf3aaaea616bee"}}},"regression":{"n":100,"identical":100,"paired":{"n":100,"mean_diff":0.0,"se":0.0,"worst5":[[0,0.0],[1,0.0],[2,0.0],[3,0.0],[4,0.0]]},"max_abs_difference":0.0,"retail_delta":0.0,"arb_delta":0.0,"gas":{"IA":{"afterInitialize":{"peak":243237,"calls":100,"ok":100,"oog":0},"afterSwap":{"peak":237739,"calls":1082151,"ok":1082151,"oog":0},"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0,"baseline_and_submission_valid":true},"IAD":{"afterInitialize":{"peak":176917,"calls":100,"ok":100,"oog":0},"afterSwap":{"peak":131825,"calls":1082151,"ok":1082151,"oog":0},"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0,"baseline_and_submission_valid":true}},"valid":true,"code_sha256":{"IA":"956566e95f46dc1ed5980fae5e550de7b9da10f9b3ad8eed62f265682cfcecf2","IAD":"7f6998c8df1b738dbd9715053edae7c9c8fdad71bf7228d67b6f1b7573c7126b"}},"real":{"IAD_vs_IA":{"paired":{"n":512,"mean_diff":0.0,"se":0.0,"worst5":[[7277824,0.0],[7277825,0.0],[7277826,0.0],[7277827,0.0],[7277828,0.0]]},"identical":512,"max_abs_difference":0.0,"retail_delta":0.0,"arb_delta":0.0},"means":{"IA":{"edge":527.8076958235192,"retail":557.1588082804727,"arb":-29.351112456953988},"IAD":{"edge":527.8076958235192,"retail":557.1588082804727,"arb":-29.351112456953988}},"code_sha256":{"IA":"956566e95f46dc1ed5980fae5e550de7b9da10f9b3ad8eed62f265682cfcecf2","IAD":"7f6998c8df1b738dbd9715053edae7c9c8fdad71bf7228d67b6f1b7573c7126b"},"engine":"amm_sim_rs.run_batch(X, VanillaStrategy, configs, 8), independently for each 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7 content IDs matched","decoded_file_hashes":"all named SHA-256 checks passed","kit_original_tests":{"n":9,"passed":9},"unit_tests":{"n":15,"passed":15,"log_sha256":"a180021ea2fd8c7910ef4d9f9dfcce26d45cdf6fc4a57c0d4fa04655b761402b"},"kit_gate_A_HA":{"sequences":50,"swap_callbacks":100000,"max_abs_fee_difference_bps":7.60422131512728e-05,"seed_start":310000,"seed_end":310049,"passed":true},"kit_gate_A_T":{"sequences":50,"swap_callbacks":100000,"max_abs_fee_difference_bps":1.2216616607219066e-09,"seed_start":310000,"seed_end":310049,"passed":true},"kit_gate_C":{"sequences":50,"swap_callbacks":100000,"max_abs_fee_difference_bps":7.60422131512728e-05,"seed_start":310000,"seed_end":310049,"passed":true},"kit_gate_B":{"replica_HA_minus_T":1.141450774002562,"reference_real":1.257,"error":0.115549225997438,"passed":true},"generic_compile_and_parity":"Nonzero 19-16-2 compiles; reordered gated 5-9-2 passes 400 callbacks; 20-input port tested.","source_bound_gates":"default and wide16 validation guards accept the measured evidence","restored_IA":"byte-for-byte equal to pinned IA","dependency_versions":{"amm-sim-rs":"0.1.0.post1","numpy":"2.5.4","numba":"0.68.1","cma":"4.5.0","py-solc-x":"2.1.0","pyrevm":"0.3.7"},"decode_roundtrip":true,"live_source_quotes":9},"notes":["Local measurements, no search or ranking claim. Gate B reference +1.513 comes from pinned IA; T real was not rerun.","Port adapts supplied IA; simulator, differential callbacks, paired statistics and edge decomposition adapt KIT. No Solidity-to-port translation.","Eight live storage words: 0=bid/ask; 3=direction/activity/sigma/count; 6=lambda/size/toxicity; 13=uncertainty/runMean/anchor count/first direction; other slots 2,5,14,15 unchanged. DIET packing bounds apply.","IAD, emitted 8-unit and zero-output 16-unit variants each match IA exactly on 100050 shared EVM callbacks. Wider nonzero heads are compile tests, not trained candidates.","Replica and Rust seeds match configuration distributions, not random paths. Generalized port reproduced supplied IA Gate B rows exactly.","Goal SETUP runtime and solc 0.8.24 are prerequisites. Delivered sources use no network at evaluation; binary installations are not embedded in this size-bounded kit. No submodules.","Local checkpoints preserve CMA state/RNG. Default weights are frozen IA params; upstream covariance and optimizer-mean restart are not claimed as resumed.","IA is reconstructed offline via a checked delta; HA.sol and T.sol are excluded."],"paired_deltas_zb64":"eNrtwQEBAAAAgiD/r25IQAEAAAAAAAAAAAAAAAAAfBk5YAAB","paired_deltas_sha256":"efdcd9711462dd6cd659259af0ff1738e60f9b15fedad68ce123cd56741fc33b","measurement_row_sha256":{"regression_IA":"6bf3bbc57f9fddedbf778db8c06efbeca859d224297005564ef6d85f7ef232fa","regression_IAD":"6bf3bbc57f9fddedbf778db8c06efbeca859d224297005564ef6d85f7ef232fa","real_IA":"2fea84d2f2e9c9f94f15da6cb1f9d8216637945a7be9e914146ff2cceee76562","real_IAD":"2fea84d2f2e9c9f94f15da6cb1f9d8216637945a7be9e914146ff2cceee76562"},"measurement_origin":"Local run_batch/gas_stats measurements; paired_deltas contains all per-seed differences. External inputs are in sources.json."}