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every api.files key k with k+\"_zb64\", decode b=zlib.decompress(base64.b64decode(result[k+\"_zb64\"])); assert sha256(b).hexdigest()==result[k+\"_sha256\"]; write b to scratch/kit/filename. For unchanged keys (hash only), take the identically named file from KIT-B artifact 48cd6a10f39fc22a79c5f12398474bd65282803d59314819acd586f187015808 and verify this hash. Keep files as siblings and save this JSON as scratch/kit/result.json. Use the goal SETUP first. per_seed_deltas decodes to 612x3 little-endian float64: IBD minus IB [edge,retail,arb], rows 0..99 = regression seeds 0..99, rows 100..611 = fresh seeds 8028672..8029183. All are measured zeros. Each gas arm gas_stats_zb64 is a zlib/base64 UTF-8 JSON list of the complete gas_stats() rows, checked by gas_stats_sha256. Reference IB source/port and HA params are the separate immutable artifacts in references; validation inputs, not kit library files.","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_ib":"weights_ib.json","IBD.sol":"IBD.sol","relay_checks":"check_relay.py"},"weights":"v1 schema, IDs0..24 selectable/repeatable. weights.json=IA; weights_ib.json=frozen IB19-8-2, IDs0..12,19..24, exact params/multipliers/offsets. expand adds zero output weights.","new_feature_ids":{"19":{"name":"raw_amountY","raw":"amount_y (Y units)","ib_affine":"raw*0.05-1"},"20":{"name":"step_trade_count","raw":"in-step count AFTER this print, capped 64","ib_affine":"raw*0.5-0.5"},"21":{"name":"prev_bid_fee","raw":"bid fee at callback entry, fraction","ib_affine":"raw*333.333333-1"},"22":{"name":"prev_ask_fee","raw":"ask fee at callback entry, fraction","ib_affine":"raw*333.333333-1"},"23":{"name":"steps_since_arb_like_print","raw":"min(timestamp-lastArbTs,16); update lastArbTs on CURRENT first-in-step print with arbProbability>=0.5; initial 0","ib_affine":"raw*0.125-1"},"24":{"name":"router_implied_vanilla_spot","raw":"(heldRouterSpot-spot)/spot, or 0 before first retail print; on later-in-step prints with gamma>0 update heldRouterSpot = isBuy ? spot*gamma/0.997 : spot*0.997/gamma","ib_affine":"raw*500"}},"storage":"Diet layout retained. Existing IA 16-bit timestamp remains in slot15 bits240..255, with its original >0.5 rule. Independent IB lastArbTs: uint64 in slot13 bits146..209, after two-bit firstDir at144..145. IB routerSpot: high144 bits of slot14; fastHat low112 bits. Store slot14 after router update. Port uses S[20] for full IB timestamp, S[21] for held router spot; IA S[18] unchanged. Fresh zero state per market.","arithmetic":"Affine scaling, input clip[-4,4], ReLU clip[0,4]. IDs21/22 canonical multiplier333.333333 lowers to feeWad/3000000000; other multipliers use generic division. Float uses rounded metadata. IDs0..18/default IA unchanged.","expansion":"1..64 inputs/units; single/firstInStep; <=8 units/function, divide after output sum. Existing compile/size/gas gates apply."},"references":{"KIT_B":{"url":"https://api.imd.fun/artifacts/48cd6a10f39fc22a79c5f12398474bd65282803d59314819acd586f187015808","json_sha256":"48cd6a10f39fc22a79c5f12398474bd65282803d59314819acd586f187015808"},"IB":{"url":"https://api.imd.fun/artifacts/afd5183e9ff3235334e041c00b0cd19079599a2c6464db95f8c1586712105557","json_sha256":"afd5183e9ff3235334e041c00b0cd19079599a2c6464db95f8c1586712105557","code_sha256":"301941829a44bb60977bb28181a5e4bfa6544f3696763f987054789b2611d686","port_sha256":"f63227c5e0f63633efd132d6fb402ede665e5c9cb24481911471e8dc20a3362d"},"HA":{"url":"https://api.imd.fun/artifacts/2801efc8190e86318dd922d4a7179f63684d77a226047fc2f3c78232963eb690","code_sha256":"99e3a2eceae0e5543d27473859e10b005d0ce0aa7067f2e1a24d1e0e4a7390fe"}},"commands":{"checkout":"git clone https://github.com/benedictbrady/amm-challenge test/scratch/amm-challenge; git -C test/scratch/amm-challenge checkout 6b6921f8d463314aa7c96234e1be25a25245f704","setup":"sh scratch/setup.sh","setup_sha256":"f3abb169ae32d5b1c3d8604d693fa1c646dcbda1a527aab6cc6c8402724f392b","cwd":"test/scratch/amm-challenge","prefix":". scratch/env.sh && timeout 470 ","runs":["test_kit.py","harness.py restore-ia --out scratch/kit/IA.sol","harness.py freeze --weights scratch/kit/weights_ib.json --directory scratch/ibd","diff_test.py --source scratch/ibd/Candidate.sol --weights scratch/kit/weights_ib.json --reference scratch/kit/IB.sol --threshold .01 --sequences 2 --callbacks 200 --out scratch/preflight.json","diff_test.py --source scratch/ibd/Candidate.sol --weights scratch/kit/weights_ib.json --reference scratch/kit/IB.sol --ib-port scratch/kit/ib_port.py --threshold .01 --sequences 50 --out scratch/identity_callbacks.json","check_relay.py tests","check_relay.py prepare","harness.py expand --weights scratch/kit/weights_ib.json --units 16 --out scratch/expanded_cli.json","check_relay.py replica --ha ../ha.json --out scratch/replica_ha_fixed.json","check_relay.py ia --kit-b ../kit.json --out scratch/ia_unchanged_final.json","harness.py real --regression --start 0 --n 8 --arm IB=scratch/kit/IB.sol --arm IBD=scratch/ibd/Candidate.sol --ledger scratch/regression_ledger.jsonl --out scratch/regression_0.json","harness.py real --regression --start 8 --n 46 --arm IB=scratch/kit/IB.sol --arm IBD=scratch/kit/IBD.sol --ledger scratch/regression_ledger.jsonl --out scratch/regression_8.json","harness.py real --regression --start 54 --n 46 --arm IB=scratch/kit/IB.sol --arm IBD=scratch/kit/IBD.sol --ledger scratch/regression_ledger.jsonl --out scratch/regression_54.json","harness.py real --start 8029184 --n 16 --arm IB=scratch/kit/IB.sol --arm Wide16=scratch/kit/IBD16_probe.sol --ledger scratch/fresh_ledger.jsonl --out scratch/wide16_probe.json","diff_test.py --source scratch/kit/IBD16.sol --weights scratch/kit/weights_ib16.json --reference scratch/kit/IB.sol --threshold .01 --sequences 25 --start 310000 --out scratch/wide_callbacks_0.json","diff_test.py --source scratch/kit/IBD16.sol --weights scratch/kit/weights_ib16.json --reference scratch/kit/IB.sol --threshold .01 --sequences 25 --start 310025 --out scratch/wide_callbacks_25.json","harness.py aggregate --out scratch/regression_summary.json scratch/regression_0.json scratch/regression_8.json scratch/regression_54.json","harness.py aggregate --out scratch/fresh_summary.json scratch/fresh_8028672.json scratch/fresh_8028736.json scratch/fresh_8028800.json scratch/fresh_8028864.json scratch/fresh_8028928.json scratch/fresh_8028992.json scratch/fresh_8029056.json scratch/fresh_8029120.json","harness.py freeze --weights scratch/kit/weights_ib.json --directory scratch/final_ibd","harness.py speed --weights scratch/kit/weights_ib.json --n 512 --procs 8 --out scratch/speed_ib_final.json"],"logging":"Outputs logged under scratch/. Setup validated StarterStrategy.","fresh_real":{"starts":[8028672,8028736,8028800,8028864,8028928,8028992,8029056,8029120],"template":"python scratch/kit/harness.py real --start {start} --n 64 --arm IB=scratch/kit/IB.sol --arm IBD=scratch/kit/IBD.sol --ledger scratch/fresh_ledger.jsonl --out scratch/fresh_{start}.json"},"python_prefix":"python scratch/kit/"},"identity":{"regression":{"seeds":[0,99],"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]],"retail_delta":0.0,"arb_delta":0.0,"identical":100,"max_abs_difference":0.0},"fresh":{"seeds":[8028672,8029183],"n":512,"mean_diff":0.0,"se":0.0,"worst5":[[8028672,0.0],[8028673,0.0],[8028674,0.0],[8028675,0.0],[8028676,0.0]],"retail_delta":0.0,"arb_delta":0.0,"identical":512,"max_abs_difference":0.0},"IA_unchanged":{"n":100,"n_steps":10000,"identical":100,"max_abs_difference":0.0,"source_identical":true,"default_source_sha256":"c20b170819e86adc7f59fd0d2a56b1a3463883ad29e471957538037d62da99a4"}},"gates":{"port_vs_ib_port":{"sequences":50,"swap_callbacks":100000,"max_abs_fee_difference_bps":1.239206653957936e-07,"ib_port_vs_evm_max_bps":6.641806184898291e-05,"passed":true},"port_vs_evm":{"passed":true,"sequences":50,"swap_callbacks":100000,"max_abs_fee_difference_bps":6.638269694353438e-05},"ibd_vs_ib_mismatches":0,"expanded16":{"sequences":50,"swap_callbacks":100000,"max_abs_fee_difference_bps":5.2213429101166664e-05,"ibd16_vs_ib_mismatches":0,"passed":true},"A":{"passed":true,"sequences":50,"swap_callbacks":100000,"max_abs_fee_difference_bps":6.641806184898291e-05},"B":{"passed":true,"error":0.1017367578843521,"n":512,"mean_diff":0.6933098100136202,"se":0.03201776626718028,"worst5":[[8000745,-1.3822057771513983],[8000673,-1.3182279518163114],[8000625,-1.263090793879428],[8000857,-1.2181401687219022],[8000945,-1.131524988563683]],"retail_delta":1.017909537705326,"arb_delta":-0.32459972769170914,"seeds":[8000512,8001023],"reported_real_gain_over_HA":0.5915730521292681},"C":{"passed":true,"sequences":50,"swap_callbacks":100000,"max_abs_fee_difference_bps":6.638269694353438e-05,"code_sha256":"59a9403518843d01f5a0180690e41a23f487f6db4b761113b400529aea72ec5d","policy_sha256":"8d615ab7aa5ccc24f22d32ffcd2aa343ff032dc71e14d5fdb425b9a6c8823c55","port_sha256":"409c7d0c467b7eb4e0f1b5b9f91dfe5f92b962204cc60b1da3a5bb4f38ea2afc"}},"gas":{"IB":{"afterSwap_peak":237021,"afterInitialize_peak":243227,"oog":0,"gas_stats_zb64":"eNq9kz9PwzAQxb+L5wz2+X9GNpYuHRGKnGJSK06MHAcqEN8dUxJEmqWolO3enU/309Pz3RuKwVtUohszWO96iwq0M97XZtfmrnlMNt72Ljnj3es8HFApCBQotFPRmUMV2qoxeQJEalGgYey+W4RSqgn/3AgNKnGBon22MR3LkPY2Vnvjv2Q6VDbGEI+iNg9VtGmMfZbvxTmw2xfz9AOTq3yYTqizWOAC13CCy5QQWiiOybWRG5s2pjvTVw4rX4nMxv4d5HasOzcMLvSXx4BRALkyVnGmgf0P8EkUBJaM8Ql3FgtkKjGQJbLSFPJLLQRVV6f+VRok5atfhokCfCHm/QdMQETJ","gas_stats_sha256":"893de9cd18fdef097405a0609ee5ffdc8877200e5dca8e6f8661a050ad3eb2be"},"IBD":{"afterSwap_peak":131239,"afterInitialize_peak":176907,"oog":0,"gas_stats_zb64":"eNq9kz1PwzAURf+LZw/+iL8ysrF06YhQ9FJMasWJkeNABeK/Y0qCSLoUlbL5vifLR0fXd28oBm9RiW5gsN71FmG0A+9r2LV5Co/JxtveJQfevc7LAZWSMoxCOx06OFShrRrIG0aVkRgNY/c9opxzQ8XnjdCgkmAU7bON6XgMaW9jtQf/FdOhsjGGeAw1PFTRpjH2Ob7jc2C3L/D0A1Po/DCfUOewwGXCsBVuoaU0UgtCr43c2LSB7kyvgp14pSqL/TvI7Vh3bhhc6C+uAVXSELXiJZpJRXTxP8CrKkiiikJMuHNYIHPKuFkiS22yYEY5IdfX/Ks2KKFOflmuyMVy7z8APpREwQ==","gas_stats_sha256":"3662c6ebc6346923aec4621d979b0f9440d395e5adcae80b4cf142e57de1c02d"},"wide16_probe":{"seeds":[8029184,8029199],"n":16,"all_zero_weights_set_to":1e-06,"afterSwap_peak":132040,"afterInitialize_peak":176974,"oog":0,"gas_stats_zb64":"eNq9kjtPwzAUhf+L5wx+xY+MbCxdOqLKuikmteLEyHZKBeK/ExoFkbAUlTLdc449fDr3PryhGLxFFbqDZL3rLSrQHryvYd+OKTxlG+97lx149zo/JlQRUaDQTrODkwmtaWDMKZF6jNLQfUWMK8k+v4cGVbhA0R5tzGcZ8sFGcwA/2XwyNsYQz6aGRxNtHmI/2vfiEtDtCzx/R5Sa8hlz0gtUWmq6QpVKKSakUDfGbWzeQHdRnyX90Sfn5O/63A5151Jyob9y9UQKLfmSlSpGSsX/B3a9fo1LPKNOeoHLKOZ4iUuk4oJoNc6bI//iBBTl6xPQ5OpWdx/j80BG","gas_stats_sha256":"047c53da989afeeb0811ed4f8afad5ee159ecf97bca4460bb7f1eeacb4bc3cad"}},"speed":{"markets_per_s":380.9886921229445,"processes":8,"n":512,"n_steps":10000,"requested_processes":8,"created_processes":8,"active_processes":8,"seconds":1.3438719063997269,"markets_per_second":380.9886921229445,"warm_compile_excluded":true,"pool_startup_included":true},"checks":{"kit_tests":15,"relay_tests":3,"all_passed":true,"weights_exactly_match_IB_params":true,"freeze":{"policy_sha256":"8d615ab7aa5ccc24f22d32ffcd2aa343ff032dc71e14d5fdb425b9a6c8823c55","code_sha256":"59a9403518843d01f5a0180690e41a23f487f6db4b761113b400529aea72ec5d","port_sha256":"409c7d0c467b7eb4e0f1b5b9f91dfe5f92b962204cc60b1da3a5bb4f38ea2afc","sim_sha256":"8ba86f0c2ad07f30213b768737b584ad23f3a3ee5631e62a9c20fc814b07553c","selected_by":"provided weights, no search","weights_sha256":"3bad60b99b6e5d4879bc8da631b879714b551c7cc35018179d79b3aa99bbd8ea","policy_array_sha256":"0ef603e6041bec247e8c0601dfd582ed6bae23f1e45d7af1980bc27db9c0101d"}},"per_seed_deltas_zb64":"eNrtwQEBAAAAgiD/r25IQAEAAAAAAAAAAAAAAAAAfBk5YAAB","per_seed_deltas_sha256":"efdcd9711462dd6cd659259af0ff1738e60f9b15fedad68ce123cd56741fc33b","notes":["No search or weight selection. Real arms ran separately against30-bps Vanilla with run_batch(...,8), MatchRunner configs. Identity:100/100 regression and512/512 fresh markets have exactly equal edge, retail and arb values. Per-seed deltas are packed above.","IB metadata rounds previous-fee scaling; Solidity divides exactly. Canonical lowering preserves frozen fees. Float/truncation errors remain below measured gates.","Discarded initial replica: stale transitive Numba cache, -3.4781 vs HA on8000000..8000511. sim.py revision rebuilt cache; accepted512 seeds8000512..8001023. Initial speed used stale cache; intermediate rebuilt timing shared CPU with engine jobs. speed contains only final rebuilt timing.","Initial unsharded wide callbacks timed out at470s under CPU contention after80000 callbacks without mismatches. Accepted gate: two completed25-sequence shards. Synthetic callback seeds were reused; fresh engine seeds were not.","Probe replaces all zero weights with1e-6, intentionally changing fees/edges (max edge difference8.519130574313749e-6 vs IB). Its gas tests duplicated hidden rows from expand, not arbitrary future trained rows.","Not run: search, training/holdout CLI, other future weights/architectures, exhaustive calldata/storage bounds. Reference/expanded files in scratch are validation inputs/outputs; delivered prepare reproduces expansion/probe."],"valid":true}