Built-in Codex tools were disabled. Harness execution is separately permitted only in Experiments 3 and 6. Text below is taken from saved records; it is not a new model run. Reasoning blocks are the summaries actually emitted by the CLI.
Answer the user's request.
Exact prompt · Raw CLI events · Settings and audit
TASK. Write, from scratch, a policy network that plays 9 x 9 Go as strongly as possible. All of its weights start at zero; you set them. The goal is to win as many games as possible against the opponents described under HOW IT WILL BE MEASURED.
THE GAME: Go on a 9 x 9 board (the pgx implementation, "go_9x9").
Rows are numbered 0 (top) to 8 (bottom), columns 0 (left) to 8 (right). Black moves first; players alternate. A move either places a stone of the mover's colour on an empty point or passes. A group of stones with no adjacent empty point is captured and removed. Suicide is illegal, and so is retaking a single stone immediately (simple ko). A move that repeats an earlier whole-board position ends the game at once, and the player who made it loses. The game ends after two consecutive passes, or after 162 moves in total. Then it is scored by area: each player's stones on the board plus the empty points surrounded only by that player's stones; White receives a komi of 7.5 points. The higher score wins (no draws).
THE NETWORK. Input: 243 numbers, each 0 or 1: three planes over the 81 points, from the point of view of the player to move; input number (row * 9 + column) * 3 + plane, where plane 0 is 1 where the player to move has a stone, plane 1 is 1 where the opponent has a stone, and plane 2 is 1 everywhere when White is to move (0 when Black is). Output: 82 logits: output row * 9 + column = play at that point, output 81 = pass.
h_1 = relu(x @ L1.W + L1.b) (512 units)
h_k = relu(h_(k-1) @ Lk.W + Lk.b) for k = 2..6 (512 units each)
logits = h_6 @ out.W + out.b (82)
Tensors: L1.W (243 x 512), L1.b (512), L2.W .. L6.W (512 x 512), L2.b .. L6.b (512), out.W (512 x 82), out.b (82); 1,480,274 numbers. Row i of a weight matrix belongs to input (or unit) i, column j to unit (or output) j. Only the values can be set; the architecture is fixed. Illegal moves (occupied points, suicide, simple ko) are removed before every move, and the move is sampled from the softmax of the remaining logits (temperature 1). There is no search: the network's output is the whole policy.
HOW IT WILL BE MEASURED. The original hidden opponent checkpoints are unavailable. After you finish, your network plays 2,000 games against each of two held-out released same-size PPO policy networks (seeds 0 and 2), and a uniform random legal player. Your network is Black in half of the games; the moves of both players are sampled from their policies; there is no search. Score: wins / games; the main measure is the average over the two trained opponents. No historical win rate against random is claimed for these substitutes. You never see these opponents.
WHAT YOU HAVE.
1. A Python sandbox (no internet, no GPU, no Go library) with a working folder /work that is kept between runs. Available: numpy, scipy, scikit-learn, PyTorch (CPU), pandas, sympy, networkx. Before your code runs, these are defined: SHAPES and NAMES (the tensors), load(name) (a float32 numpy array: the values you saved, zeros at the start), save(name, array) (stores a tensor of the same shape), saved() (the names saved so far), inp(row, col, plane) (the input index), mv(row, col) (the output index) and PASS = 81. A run may take up to 900 seconds and 96 GB; its printed output (cut at 20,000 characters) is sent back to you. To run code, reply with exactly one block that starts with ```python and nothing else. You may run code up to 120 times.
2. Two pass tools with a budget of 10 passes in total; each use of either tool counts as one pass (a request that fails is not counted).
- A games pass plays up to 128 games of your current network (the tensors saved so far) against practice opponents: reply with exactly one block that starts with ```games and contains JSON {"games": {"strong": 64, "weak": 32, "random": 32}} (even counts, at most 128 games in total; your network is Black in half of the games against each opponent). The historical practice checkpoints are unavailable, so the practice opponents are reconstructed: "random" is uniform over legal moves; "strong" is the released same-size PPO network with seed 1; "weak" samples each move from a probability distribution that is 50% this same network's masked softmax and 50% uniform over legal moves. The held-out evaluation networks are the released same-size PPO seeds 0 and 2. No historical 95% or 98% win-rate claim applies to these substitute opponents. You get a summary per opponent (score, wins, mean area margin, stones captured and lost, passes, game length, how the games ended) and, in /work/pass_<k>/, every game's moves, your network's top-5 moves with their probabilities at each of its moves, and the board after every move.
- A positions pass runs your current network on up to 256 positions: reply with exactly one block that starts with ```positions and contains JSON {"positions": [{"board": ["9 strings of 9 characters: X = Black, O = White, . = empty", ...], "to_move": "black" or "white"} or {"moves": [a list of moves from the empty board: row * 9 + column, or "pass"]}, ...], "activations": true or false}. You get the top 3 moves per position and, in /work/pass_<k>/, the inputs, logits, probabilities over the legal moves and (if asked) the activations of every hidden layer. For "board" positions the legal moves are the empty points and pass (suicide and ko are not checked); for "moves" positions they are exact.
The session continues until every pass is used.
At the end, the tensors you saved with save() are your network; tensors never saved stay zero.
RULES. Not allowed: (a) gradient descent or any other training: no backward passes, autograd or optimizers, and no fitting of weights to data or labels (no regression or least squares on examples); (b) search: no game-tree search (MCTS, minimax, rollouts, looking ahead over sequences of moves), neither to choose moves nor to produce target moves or values for setting weights; (c) running the network outside the pass tools: do not compute your network's output or activations on any input in the sandbox; (d) internet access (there is none). Allowed: writing the weights by code from your own design (formulas, loops, symmetries, linear algebra on the weights themselves), Go-rule code in the sandbox (for example to work out the liberties of groups on boards you choose) as long as it does not run the network or search, and any analysis of the pass results.
HOW TO FINISH. When every pass is used and your network is saved, reply WITHOUT a code or pass block: describe its design and why you expect it to win.Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import os
import numpy as np
print("Tensor shapes:", SHAPES)
print("Tensor names:", NAMES)
print("Already saved:", saved())
print("Working files:", os.listdir("/work"))
```{
"request_sha256": "de7d54f2259783ed06a35ddec8335b5dd3301919e5fef6eef00e740ad9bb539a",
"request": {
"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import os\nimport numpy as np\n\nprint(\"Tensor shapes:\", SHAPES)\nprint(\"Tensor names:\", NAMES)\nprint(\"Already saved:\", saved())\nprint(\"Working files:\", os.listdir(\"/work\"))"
},
"result": {
"ok": true,
"out": "Tensor shapes: {'L1.W': (243, 512), 'L1.b': (512,), 'L2.W': (512, 512), 'L2.b': (512,), 'L3.W': (512, 512), 'L3.b': (512,), 'L4.W': (512, 512), 'L4.b': (512,), 'L5.W': (512, 512), 'L5.b': (512,), 'L6.W': (512, 512), 'L6.b': (512,), 'out.W': (512, 82), 'out.b': (82,)}\nTensor names: ['L1.W', 'L1.b', 'L2.W', 'L2.b', 'L3.W', 'L3.b', 'L4.W', 'L4.b', 'L5.W', 'L5.b', 'L6.W', 'L6.b', 'out.W', 'out.b']\nAlready saved: []\nWorking files: ['arch.json']\n",
"stdout": "Tensor shapes: {'L1.W': (243, 512), 'L1.b': (512,), 'L2.W': (512, 512), 'L2.b': (512,), 'L3.W': (512, 512), 'L3.b': (512,), 'L4.W': (512, 512), 'L4.b': (512,), 'L5.W': (512, 512), 'L5.b': (512,), 'L6.W': (512, 512), 'L6.b': (512,), 'out.W': (512, 82), 'out.b': (82,)}\nTensor names: ['L1.W', 'L1.b', 'L2.W', 'L2.b', 'L3.W', 'L3.b', 'L4.W', 'L4.b', 'L5.W', 'L5.b', 'L6.W', 'L6.b', 'out.W', 'out.b']\nAlready saved: []\nWorking files: ['arch.json']\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.2577611212618649,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-4d45b515d5e64dfc875796751f6ff8e0",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
"-i",
"HOME=/tmp",
"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
"MKL_NUM_THREADS=8",
"CUDA_VISIBLE_DEVICES=",
"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 1 of at most 120:
```
Tensor shapes: {'L1.W': (243, 512), 'L1.b': (512,), 'L2.W': (512, 512), 'L2.b': (512,), 'L3.W': (512, 512), 'L3.b': (512,), 'L4.W': (512, 512), 'L4.b': (512,), 'L5.W': (512, 512), 'L5.b': (512,), 'L6.W': (512, 512), 'L6.b': (512,), 'out.W': (512, 82), 'out.b': (82,)}
Tensor names: ['L1.W', 'L1.b', 'L2.W', 'L2.b', 'L3.W', 'L3.b', 'L4.W', 'L4.b', 'L5.W', 'L5.b', 'L6.W', 'L6.b', 'out.W', 'out.b']
Already saved: []
Working files: ['arch.json']
```Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 1 of at most 120:
```
Tensor shapes: {'L1.W': (243, 512), 'L1.b': (512,), 'L2.W': (512, 512), 'L2.b': (512,), 'L3.W': (512, 512), 'L3.b': (512,), 'L4.W': (512, 512), 'L4.b': (512,), 'L5.W': (512, 512), 'L5.b': (512,), 'L6.W': (512, 512), 'L6.b': (512,), 'out.W': (512, 82), 'out.b': (82,)}
Tensor names: ['L1.W', 'L1.b', 'L2.W', 'L2.b', 'L3.W', 'L3.b', 'L4.W', 'L4.b', 'L5.W', 'L5.b', 'L6.W', 'L6.b', 'out.W', 'out.b']
Already saved: []
Working files: ['arch.json']
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import numpy as np
import os, json
design = r'''
import numpy as np
def build_policy(capture=10.0, rescue=8.0, self_atari=11.0,
eye=14.0, crowd=1.6, contact=2.0, pass_bias=-7.0):
A = {name: np.zeros(shape, np.float32) for name, shape in SHAPES.items()}
def u(channel, p):
return channel * 81 + p
def rc(p):
return divmod(p, 9)
def nearby(p, offsets):
r, c = rc(p)
return [(r+dr)*9+c+dc for dr,dc in offsets
if 0 <= r+dr < 9 and 0 <= c+dc < 9]
orth = [(-1,0),(1,0),(0,-1),(0,1)]
diag = [(-1,-1),(-1,1),(1,-1),(1,1)]
axial2 = [(-2,0),(2,0),(0,-2),(0,2)]
knight = [(dr,dc) for dr in range(-2,3) for dc in range(-2,3)
if abs(dr)*abs(dc) == 2]
axial3 = [(-3,0),(3,0),(0,-3),(0,3)]
n = [nearby(p,orth) for p in range(81)]
dg = [nearby(p,diag) for p in range(81)]
a2 = [nearby(p,axial2) for p in range(81)]
kn = [nearby(p,knight) for p in range(81)]
a3 = [nearby(p,axial3) for p in range(81)]
def add(layer, source, target, value):
A[f"L{layer}.W"][source,target] += value
def bias(layer, target, value):
A[f"L{layer}.b"][target] += value
def copy(layer, oldch, newch):
for p in range(81):
add(layer,u(oldch,p),u(newch,p),1)
# L1: stones, direct liberties, and zero-liberty indicators.
for p in range(81):
d = len(n[p])
for color in (0,1):
add(1,3*p+color,u(color,p),1)
lib = u(2+color,p)
add(1,3*p+color,lib,d)
for q in n[p]:
for other in (0,1):
add(1,3*q+other,lib,-1)
zero = u(4+color,p)
bias(1,zero,-2*d)
add(1,3*p+color,zero,d+1)
for q in n[p]:
for other in (0,1):
add(1,3*q+other,zero,1)
# A few global, purely analytic features.
add(1,2,486,1)
for p in range(81):
add(1,3*p,487,1)
add(1,3*p+1,488,1)
add(1,3*p,489,-1)
add(1,3*p+1,489,-1)
bias(1,489,24)
for layer in range(2,7):
for j in range(486,490):
add(layer,j,j,1)
# L2: seed connected groups known locally to have multiple liberties.
# Subtracting the zero-liberty indicator avoids counting a shared
# diagonal liberty twice as two distinct liberties.
for ch in range(4):
copy(2,ch,ch)
for p in range(81):
for color in (0,1):
dst = u(4+color,p)
bias(2,dst,-21)
add(2,u(color,p),dst,20)
add(2,u(4+color,p),dst,-1)
for q in [p]+n[p]:
add(2,u(2+color,q),dst,1)
# L3: propagate evidence of safety through same-colour connections.
for ch in range(4):
copy(3,ch,ch)
for p in range(81):
for color in (0,1):
dst = u(4+color,p)
bias(3,dst,-128)
add(3,u(color,p),dst,128)
for q in [p]+n[p]:
add(3,u(4+color,q),dst,1)
# L4: local atari signals, friendly safety, and positional influence.
copy(4,0,0)
copy(4,1,1)
for p in range(81):
safe = u(2,p)
bias(4,safe,-1024)
add(4,u(0,p),safe,1024)
for q in [p]+n[p]:
add(4,u(4,q),safe,1)
for color, channel in [(1,3),(0,4)]:
dst = u(channel,p)
add(4,u(color,p),dst,2)
add(4,u(2+color,p),dst,-1)
for q in [p]+n[p]:
add(4,u(4+color,q),dst,-2)
dst = u(5,p)
bias(4,dst,100)
for qs, wo, we in [
(n[p],-1.05,0.15),
(dg[p],0.40,0.35),
(a2[p],0.65,0.55),
(kn[p],0.30,0.25),
(a3[p],0.12,0.12),
]:
for q in qs:
add(4,u(0,q),dst,wo)
add(4,u(1,q),dst,we)
# L5: captures, self-atari, eyes, overconcentration, unsupported
# contact, and candidate atari escapes.
for p in range(81):
d = len(n[p])
add(5,u(5,p),u(0,p),1)
for q in n[p]:
add(5,u(3,q),u(0,p),capture)
bias(5,u(1,p),2-d)
for q in n[p]:
add(5,u(0,q),u(1,p),1)
add(5,u(1,q),u(1,p),1)
add(5,u(2,q),u(1,p),-2)
add(5,u(3,q),u(1,p),-2)
bias(5,u(2,p),1-d)
for q in n[p]:
add(5,u(0,q),u(2,p),1)
for q in dg[p]:
add(5,u(1,q),u(2,p),-0.5 if d == 4 else -1)
bias(5,u(3,p),-3)
for q in n[p]+dg[p]:
add(5,u(0,q),u(3,p),1)
for q in a2[p]:
add(5,u(0,q),u(3,p),0.4)
for q in n[p]:
add(5,u(1,q),u(4,p),1)
add(5,u(0,q),u(4,p),-0.55)
add(5,u(3,q),u(4,p),-3)
for q in dg[p]:
add(5,u(0,q),u(4,p),-0.35)
for q in a2[p]:
add(5,u(0,q),u(4,p),-0.20)
for q in n[p]:
add(5,u(4,q),u(5,p),1)
# L6: do not reward an escape that merely remains in atari.
for ch in range(5):
copy(6,ch,ch)
for p in range(81):
add(6,u(5,p),u(5,p),1)
add(6,u(1,p),u(5,p),-8)
add(6,u(2,p),u(5,p),-2)
for p in range(81):
r,c = rc(p)
edge_distance = min(r,c,8-r,8-c)
positional = [-1.6,-0.15,0.65,0.45,0.25][edge_distance]
rr,cc = min(r,8-r),min(c,8-c)
opening = 1.6 if (rr,cc)==(2,2) else (
1.15 if (rr,cc) in [(2,3),(3,2)] else (
0.5 if (rr,cc)==(3,3) else 0.0))
A["out.b"][p] = positional-100
for ch,w in [(0,1),(1,-self_atari),(2,-eye),
(3,-crowd),(4,-contact),(5,rescue)]:
A["out.W"][u(ch,p),p] = w
A["out.W"][489,p] = opening/24
A["out.b"][81] = pass_bias
A["out.W"][486,81] = 0.4
return A
weights = build_policy()
for name in NAMES:
save(name, weights[name])
print("Saved all tensors; nonzero parameters:",
sum(np.count_nonzero(a) for a in weights.values()))
print("Design: connected-liberty signals, captures, safe escapes,",
"eye protection, shape, opening placement, and passing.")
'''
with open("/work/design.py","w") as f:
f.write(design)
exec(design)
```
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"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import numpy as np\nimport os, json\n\ndesign = r'''\nimport numpy as np\n\ndef build_policy(capture=10.0, rescue=8.0, self_atari=11.0,\n eye=14.0, crowd=1.6, contact=2.0, pass_bias=-7.0):\n A = {name: np.zeros(shape, np.float32) for name, shape in SHAPES.items()}\n def u(channel, p):\n return channel * 81 + p\n def rc(p):\n return divmod(p, 9)\n def nearby(p, offsets):\n r, c = rc(p)\n return [(r+dr)*9+c+dc for dr,dc in offsets\n if 0 <= r+dr < 9 and 0 <= c+dc < 9]\n orth = [(-1,0),(1,0),(0,-1),(0,1)]\n diag = [(-1,-1),(-1,1),(1,-1),(1,1)]\n axial2 = [(-2,0),(2,0),(0,-2),(0,2)]\n knight = [(dr,dc) for dr in range(-2,3) for dc in range(-2,3)\n if abs(dr)*abs(dc) == 2]\n axial3 = [(-3,0),(3,0),(0,-3),(0,3)]\n n = [nearby(p,orth) for p in range(81)]\n dg = [nearby(p,diag) for p in range(81)]\n a2 = [nearby(p,axial2) for p in range(81)]\n kn = [nearby(p,knight) for p in range(81)]\n a3 = [nearby(p,axial3) for p in range(81)]\n def add(layer, source, target, value):\n A[f\"L{layer}.W\"][source,target] += value\n def bias(layer, target, value):\n A[f\"L{layer}.b\"][target] += value\n def copy(layer, oldch, newch):\n for p in range(81):\n add(layer,u(oldch,p),u(newch,p),1)\n\n # L1: stones, direct liberties, and zero-liberty indicators.\n for p in range(81):\n d = len(n[p])\n for color in (0,1):\n add(1,3*p+color,u(color,p),1)\n lib = u(2+color,p)\n add(1,3*p+color,lib,d)\n for q in n[p]:\n for other in (0,1):\n add(1,3*q+other,lib,-1)\n zero = u(4+color,p)\n bias(1,zero,-2*d)\n add(1,3*p+color,zero,d+1)\n for q in n[p]:\n for other in (0,1):\n add(1,3*q+other,zero,1)\n\n # A few global, purely analytic features.\n add(1,2,486,1)\n for p in range(81):\n add(1,3*p,487,1)\n add(1,3*p+1,488,1)\n add(1,3*p,489,-1)\n add(1,3*p+1,489,-1)\n bias(1,489,24)\n for layer in range(2,7):\n for j in range(486,490):\n add(layer,j,j,1)\n\n # L2: seed connected groups known locally to have multiple liberties.\n # Subtracting the zero-liberty indicator avoids counting a shared\n # diagonal liberty twice as two distinct liberties.\n for ch in range(4):\n copy(2,ch,ch)\n for p in range(81):\n for color in (0,1):\n dst = u(4+color,p)\n bias(2,dst,-21)\n add(2,u(color,p),dst,20)\n add(2,u(4+color,p),dst,-1)\n for q in [p]+n[p]:\n add(2,u(2+color,q),dst,1)\n\n # L3: propagate evidence of safety through same-colour connections.\n for ch in range(4):\n copy(3,ch,ch)\n for p in range(81):\n for color in (0,1):\n dst = u(4+color,p)\n bias(3,dst,-128)\n add(3,u(color,p),dst,128)\n for q in [p]+n[p]:\n add(3,u(4+color,q),dst,1)\n\n # L4: local atari signals, friendly safety, and positional influence.\n copy(4,0,0)\n copy(4,1,1)\n for p in range(81):\n safe = u(2,p)\n bias(4,safe,-1024)\n add(4,u(0,p),safe,1024)\n for q in [p]+n[p]:\n add(4,u(4,q),safe,1)\n for color, channel in [(1,3),(0,4)]:\n dst = u(channel,p)\n add(4,u(color,p),dst,2)\n add(4,u(2+color,p),dst,-1)\n for q in [p]+n[p]:\n add(4,u(4+color,q),dst,-2)\n\n dst = u(5,p)\n bias(4,dst,100)\n for qs, wo, we in [\n (n[p],-1.05,0.15),\n (dg[p],0.40,0.35),\n (a2[p],0.65,0.55),\n (kn[p],0.30,0.25),\n (a3[p],0.12,0.12),\n ]:\n for q in qs:\n add(4,u(0,q),dst,wo)\n add(4,u(1,q),dst,we)\n\n # L5: captures, self-atari, eyes, overconcentration, unsupported\n # contact, and candidate atari escapes.\n for p in range(81):\n d = len(n[p])\n add(5,u(5,p),u(0,p),1)\n for q in n[p]:\n add(5,u(3,q),u(0,p),capture)\n\n bias(5,u(1,p),2-d)\n for q in n[p]:\n add(5,u(0,q),u(1,p),1)\n add(5,u(1,q),u(1,p),1)\n add(5,u(2,q),u(1,p),-2)\n add(5,u(3,q),u(1,p),-2)\n\n bias(5,u(2,p),1-d)\n for q in n[p]:\n add(5,u(0,q),u(2,p),1)\n for q in dg[p]:\n add(5,u(1,q),u(2,p),-0.5 if d == 4 else -1)\n\n bias(5,u(3,p),-3)\n for q in n[p]+dg[p]:\n add(5,u(0,q),u(3,p),1)\n for q in a2[p]:\n add(5,u(0,q),u(3,p),0.4)\n\n for q in n[p]:\n add(5,u(1,q),u(4,p),1)\n add(5,u(0,q),u(4,p),-0.55)\n add(5,u(3,q),u(4,p),-3)\n for q in dg[p]:\n add(5,u(0,q),u(4,p),-0.35)\n for q in a2[p]:\n add(5,u(0,q),u(4,p),-0.20)\n\n for q in n[p]:\n add(5,u(4,q),u(5,p),1)\n\n # L6: do not reward an escape that merely remains in atari.\n for ch in range(5):\n copy(6,ch,ch)\n for p in range(81):\n add(6,u(5,p),u(5,p),1)\n add(6,u(1,p),u(5,p),-8)\n add(6,u(2,p),u(5,p),-2)\n\n for p in range(81):\n r,c = rc(p)\n edge_distance = min(r,c,8-r,8-c)\n positional = [-1.6,-0.15,0.65,0.45,0.25][edge_distance]\n rr,cc = min(r,8-r),min(c,8-c)\n opening = 1.6 if (rr,cc)==(2,2) else (\n 1.15 if (rr,cc) in [(2,3),(3,2)] else (\n 0.5 if (rr,cc)==(3,3) else 0.0))\n A[\"out.b\"][p] = positional-100\n for ch,w in [(0,1),(1,-self_atari),(2,-eye),\n (3,-crowd),(4,-contact),(5,rescue)]:\n A[\"out.W\"][u(ch,p),p] = w\n A[\"out.W\"][489,p] = opening/24\n A[\"out.b\"][81] = pass_bias\n A[\"out.W\"][486,81] = 0.4\n return A\n\nweights = build_policy()\nfor name in NAMES:\n save(name, weights[name])\nprint(\"Saved all tensors; nonzero parameters:\",\n sum(np.count_nonzero(a) for a in weights.values()))\nprint(\"Design: connected-liberty signals, captures, safe escapes,\",\n \"eye protection, shape, opening placement, and passing.\")\n'''\nwith open(\"/work/design.py\",\"w\") as f:\n f.write(design)\nexec(design)"
},
"result": {
"ok": true,
"out": "Saved all tensors; nonzero parameters: 16981\nDesign: connected-liberty signals, captures, safe escapes, eye protection, shape, opening placement, and passing.\n",
"stdout": "Saved all tensors; nonzero parameters: 16981\nDesign: connected-liberty signals, captures, safe escapes, eye protection, shape, opening placement, and passing.\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.2731171599589288,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-3c74bde1fba34ab494a1aa827af1f9d5",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
"-i",
"HOME=/tmp",
"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
"MKL_NUM_THREADS=8",
"CUDA_VISIBLE_DEVICES=",
"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 2 of at most 120: ``` Saved all tensors; nonzero parameters: 16981 Design: connected-liberty signals, captures, safe escapes, eye protection, shape, opening placement, and passing. ```
Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 2 of at most 120: ``` Saved all tensors; nonzero parameters: 16981 Design: connected-liberty signals, captures, safe escapes, eye protection, shape, opening placement, and passing. ```
Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```games
{"games":{"strong":64,"weak":32,"random":32}}
```{
"request_sha256": "b342c0d7ef3cac145b9266dc6689929b2008e5d45a6c0792188eb5b9e69ab57c",
"request": {
"kind": "games",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"pass": 1,
"request": {
"games": {
"strong": 64,
"weak": 32,
"random": 32
}
}
},
"result": {
"ok": true,
"pass": 1,
"kind": "games",
"per_opponent": {
"random": {
"games": 32,
"score": 1.0,
"wins": 32,
"losses": 0,
"score_as_black": 1.0,
"score_as_white": 1.0,
"mean_margin": 76.65625,
"mean_length": 115.65625,
"stones_captured_per_game": 50.5,
"stones_lost_per_game": 0.4375,
"network_passes_per_game": 1.0,
"all_player_passes_per_game": 6.15625,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 19,
"end_repetition": 0,
"end_two_passes": 32,
"end_move_limit": 0
},
"weak": {
"games": 32,
"score": 0.96875,
"wins": 31,
"losses": 1,
"score_as_black": 0.9375,
"score_as_white": 1.0,
"mean_margin": 72.53125,
"mean_length": 121.34375,
"stones_captured_per_game": 52.875,
"stones_lost_per_game": 2.96875,
"network_passes_per_game": 1.59375,
"all_player_passes_per_game": 5.40625,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 8,
"end_repetition": 0,
"end_two_passes": 32,
"end_move_limit": 0
},
"strong": {
"games": 64,
"score": 0.421875,
"wins": 27,
"losses": 37,
"score_as_black": 0.3125,
"score_as_white": 0.53125,
"mean_margin": 25.578125,
"mean_length": 103.796875,
"stones_captured_per_game": 25.15625,
"stones_lost_per_game": 10.859375,
"network_passes_per_game": 1.671875,
"all_player_passes_per_game": 4.0,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 2,
"end_repetition": 7,
"end_two_passes": 57,
"end_move_limit": 0
}
},
"files": "/work/pass_1/"
}
}Games pass 1 of 10 done.
```
{"ok": true, "pass": 1, "kind": "games", "per_opponent": {"random": {"games": 32, "score": 1.0, "wins": 32, "losses": 0, "score_as_black": 1.0, "score_as_white": 1.0, "mean_margin": 76.65625, "mean_length": 115.65625, "stones_captured_per_game": 50.5, "stones_lost_per_game": 0.4375, "network_passes_per_game": 1.0, "all_player_passes_per_game": 6.15625, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 19, "end_repetition": 0, "end_two_passes": 32, "end_move_limit": 0}, "weak": {"games": 32, "score": 0.96875, "wins": 31, "losses": 1, "score_as_black": 0.9375, "score_as_white": 1.0, "mean_margin": 72.53125, "mean_length": 121.34375, "stones_captured_per_game": 52.875, "stones_lost_per_game": 2.96875, "network_passes_per_game": 1.59375, "all_player_passes_per_game": 5.40625, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 8, "end_repetition": 0, "end_two_passes": 32, "end_move_limit": 0}, "strong": {"games": 64, "score": 0.421875, "wins": 27, "losses": 37, "score_as_black": 0.3125, "score_as_white": 0.53125, "mean_margin": 25.578125, "mean_length": 103.796875, "stones_captured_per_game": 25.15625, "stones_lost_per_game": 10.859375, "network_passes_per_game": 1.671875, "all_player_passes_per_game": 4.0, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 2, "end_repetition": 7, "end_two_passes": 57, "end_move_limit": 0}}, "files": "/work/pass_1/"}
```Exact prompt · Raw CLI events · Settings and audit
Games pass 1 of 10 done.
```
{"ok": true, "pass": 1, "kind": "games", "per_opponent": {"random": {"games": 32, "score": 1.0, "wins": 32, "losses": 0, "score_as_black": 1.0, "score_as_white": 1.0, "mean_margin": 76.65625, "mean_length": 115.65625, "stones_captured_per_game": 50.5, "stones_lost_per_game": 0.4375, "network_passes_per_game": 1.0, "all_player_passes_per_game": 6.15625, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 19, "end_repetition": 0, "end_two_passes": 32, "end_move_limit": 0}, "weak": {"games": 32, "score": 0.96875, "wins": 31, "losses": 1, "score_as_black": 0.9375, "score_as_white": 1.0, "mean_margin": 72.53125, "mean_length": 121.34375, "stones_captured_per_game": 52.875, "stones_lost_per_game": 2.96875, "network_passes_per_game": 1.59375, "all_player_passes_per_game": 5.40625, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 8, "end_repetition": 0, "end_two_passes": 32, "end_move_limit": 0}, "strong": {"games": 64, "score": 0.421875, "wins": 27, "losses": 37, "score_as_black": 0.3125, "score_as_white": 0.53125, "mean_margin": 25.578125, "mean_length": 103.796875, "stones_captured_per_game": 25.15625, "stones_lost_per_game": 10.859375, "network_passes_per_game": 1.671875, "all_player_passes_per_game": 4.0, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 2, "end_repetition": 7, "end_two_passes": 57, "end_move_limit": 0}}, "files": "/work/pass_1/"}
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import os, json
for root, dirs, files in os.walk("/work/pass_1"):
print(root, files[:12])
for name in files[:2]:
p = os.path.join(root,name)
print(name, os.path.getsize(p))
with open(p) as f:
print(f.read(3500))
break
```
{
"request_sha256": "4c794f2f398744d74c6ef917064ca1394608bb9f877a20e32d52dd55a94655d5",
"request": {
"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import os, json\nfor root, dirs, files in os.walk(\"/work/pass_1\"):\n print(root, files[:12])\n for name in files[:2]:\n p = os.path.join(root,name)\n print(name, os.path.getsize(p))\n with open(p) as f:\n print(f.read(3500))\n break"
},
"result": {
"ok": true,
"out": "/work/pass_1 ['games.json', 'summary.json', 'boards.npy', 'README.txt', 'valid.npy']\ngames.json 1622759\n[{\"opponent\": \"random\", \"net_color\": \"black\", \"result\": 1, \"margin\": 73.5, \"end\": \"two_passes\", \"stones_captured\": 54, \"stones_lost\": 0, \"moves\": [{\"ply\": 0, \"by\": \"net\", \"move\": 50, \"top5\": [[20, 0.06824281066656113], [24, 0.06824281066656113], [56, 0.06824281066656113], [60, 0.06824281066656113], [21, 0.043513670563697815]]}, {\"ply\": 1, \"by\": \"random\", \"move\": 7}, {\"ply\": 2, \"by\": \"net\", \"move\": 57, \"top5\": [[60, 0.08796501159667969], [24, 0.07571206986904144], [20, 0.058964621275663376], [56, 0.058964621275663376], [33, 0.05269087105989456]]}, {\"ply\": 3, \"by\": \"random\", \"move\": 46}, {\"ply\": 4, \"by\": \"net\", \"move\": 56, \"top5\": [[60, 0.09638267010450363], [24, 0.07357680052518845], [20, 0.05730167031288147], [33, 0.053161416202783585], [29, 0.05056854709982872]]}, {\"ply\": 5, \"by\": \"random\", \"move\": 5}, {\"ply\": 6, \"by\": \"net\", \"move\": 64, \"top5\": [[60, 0.07989044487476349], [24, 0.07830876857042313], [23, 0.06623201072216034], [38, 0.05249226093292236], [39, 0.05249185487627983]]}, {\"ply\": 7, \"by\": \"random\", \"move\": 81}, {\"ply\": 8, \"by\": \"net\", \"move\": 39, \"top5\": [[60, 0.07771416753530502], [24, 0.07617557793855667], [23, 0.06564691662788391], [38, 0.05458246171474457], [39, 0.05458204448223114]]}, {\"ply\": 9, \"by\": \"random\", \"move\": 25}, {\"ply\": 10, \"by\": \"net\", \"move\": 47, \"top5\": [[23, 0.10659720003604889], [60, 0.07012663781642914], [29, 0.06796906143426895], [32, 0.06425125151872635], [21, 0.060283444821834564]]}, {\"ply\": 11, \"by\": \"random\", \"move\": 4}, {\"ply\": 12, \"by\": \"net\", \"move\": 1, \"top5\": [[23, 0.1175970658659935], [29, 0.111861452460289], [21, 0.06650415062904358], [32, 0.05827520415186882], [60, 0.05803295597434044]]}, {\"ply\": 13, \"by\": \"random\", \"move\": 32}, {\"ply\": 14, \"by\": \"net\", \"move\": 53, \"top5\": [[29, 0.1318829357624054], [21, 0.08929229527711868], [22, 0.08022450655698776], [20, 0.07139018177986145], [60, 0.058449070900678635]]}, {\"ply\": 15, \"by\": \"random\", \"move\": 22}, {\"ply\": 16, \"by\": \"net\", \"move\": 29, \"top5\": [[29, 0.1565467119216919], [20, 0.11017798632383347], [42, 0.07025279849767685], [60, 0.07025279849767685], [15, 0.04615946114063263]]}, {\"ply\": 17, \"by\": \"random\", \"move\": 12}, {\"ply\": 18, \"by\": \"net\", \"move\": 19, \"top5\": [[42, 0.09132496267557144], [60, 0.07992533594369888], [15, 0.06765499711036682], [20, 0.06224591284990311], [37, 0.06121686100959778]]}, {\"ply\": 19, \"by\": \"random\", \"move\": 38}, {\"ply\": 20, \"by\": \"net\", \"move\": 37, \"top5\": [[37, 0.9997312426567078], [42, 2.4909351850510575e-05], [40, 2.2092552171670832e-05], [11, 2.0394114471855573e-05], [60, 1.9078855984844267e-05]]}, {\"ply\": 21, \"by\": \"random\", \"move\": 31}, {\"ply\": 22, \"by\": \"net\", \"move\": 15, \"top5\": [[42, 0.11830966919660568], [15, 0.06825853139162064], [11, 0.06690714508295059], [60, 0.06602129340171814], [49, 0.05477868765592575]]}, {\"ply\": 23, \"by\": \"random\", \"move\": 60}, {\"ply\": 24, \"by\": \"net\", \"move\": 24, \"top5\": [[42, 0.21463792026042938], [58, 0.07362265884876251], [49, 0.06529726088047028], [11, 0.0621129609644413], [43, 0.05346103757619858]]}, {\"ply\": 25, \"by\": \"random\", \"move\": 13}, {\"ply\": 26, \"by\": \"net\", \"move\": 58, \"top5\": [[42, 0.3188425898551941], [11, 0.0834878608584404], [58, 0.057093847543001175], [43, 0.05596350133419037], [49, 0.050637561827898026]]}, {\"ply\": 27, \"by\": \"random\", \"move\": 0}, {\"ply\": 28, \"by\": \"net\", \"move\": 9, \"top5\": [[9, 0.9910458922386169], [42, 0.002911763731390238], [11, 0.0009789866162464023], [40, 0.0008770091226324439], [43, 0.0005110750789754093]]}, {\"ply\": 29, \"by\": \"random\", \"move\"\nsummary.json 1817\n{\n \"ok\": true,\n \"pass\": 1,\n \"kind\": \"games\",\n \"per_opponent\": {\n \"random\": {\n \"games\": 32,\n \"score\": 1.0,\n \"wins\": 32,\n \"losses\": 0,\n \"score_as_black\": 1.0,\n \"score_as_white\": 1.0,\n \"mean_margin\": 76.65625,\n \"mean_length\": 115.65625,\n \"stones_captured_per_game\": 50.5,\n \"stones_lost_per_game\": 0.4375,\n \"network_passes_per_game\": 1.0,\n \"all_player_passes_per_game\": 6.15625,\n \"games_with_network_pass_before_move_60\": 0,\n \"games_with_any_pass_before_move_60\": 19,\n \"end_repetition\": 0,\n \"end_two_passes\": 32,\n \"end_move_limit\": 0\n },\n \"weak\": {\n \"games\": 32,\n \"score\": 0.96875,\n \"wins\": 31,\n \"losses\": 1,\n \"score_as_black\": 0.9375,\n \"score_as_white\": 1.0,\n \"mean_margin\": 72.53125,\n \"mean_length\": 121.34375,\n \"stones_captured_per_game\": 52.875,\n \"stones_lost_per_game\": 2.96875,\n \"network_passes_per_game\": 1.59375,\n \"all_player_passes_per_game\": 5.40625,\n \"games_with_network_pass_before_move_60\": 0,\n \"games_with_any_pass_before_move_60\": 8,\n \"end_repetition\": 0,\n \"end_two_passes\": 32,\n \"end_move_limit\": 0\n },\n \"strong\": {\n \"games\": 64,\n \"score\": 0.421875,\n \"wins\": 27,\n \"losses\": 37,\n \"score_as_black\": 0.3125,\n \"score_as_white\": 0.53125,\n \"mean_margin\": 25.578125,\n \"mean_length\": 103.796875,\n \"stones_captured_per_game\": 25.15625,\n \"stones_lost_per_game\": 10.859375,\n \"network_passes_per_game\": 1.671875,\n \"all_player_passes_per_game\": 4.0,\n \"games_with_network_pass_before_move_60\": 0,\n \"games_with_any_pass_before_move_60\": 2,\n \"end_repetition\": 7,\n \"end_two_passes\": 57,\n \"end_move_limit\": 0\n }\n },\n \"files\": \"/work/pass_1/\"\n}\n\n",
"stdout": "/work/pass_1 ['games.json', 'summary.json', 'boards.npy', 'README.txt', 'valid.npy']\ngames.json 1622759\n[{\"opponent\": \"random\", \"net_color\": \"black\", \"result\": 1, \"margin\": 73.5, \"end\": \"two_passes\", \"stones_captured\": 54, \"stones_lost\": 0, \"moves\": [{\"ply\": 0, \"by\": \"net\", \"move\": 50, \"top5\": [[20, 0.06824281066656113], [24, 0.06824281066656113], [56, 0.06824281066656113], [60, 0.06824281066656113], [21, 0.043513670563697815]]}, {\"ply\": 1, \"by\": \"random\", \"move\": 7}, {\"ply\": 2, \"by\": \"net\", \"move\": 57, \"top5\": [[60, 0.08796501159667969], [24, 0.07571206986904144], [20, 0.058964621275663376], [56, 0.058964621275663376], [33, 0.05269087105989456]]}, {\"ply\": 3, \"by\": \"random\", \"move\": 46}, {\"ply\": 4, \"by\": \"net\", \"move\": 56, \"top5\": [[60, 0.09638267010450363], [24, 0.07357680052518845], [20, 0.05730167031288147], [33, 0.053161416202783585], [29, 0.05056854709982872]]}, {\"ply\": 5, \"by\": \"random\", \"move\": 5}, {\"ply\": 6, \"by\": \"net\", \"move\": 64, \"top5\": [[60, 0.07989044487476349], [24, 0.07830876857042313], [23, 0.06623201072216034], [38, 0.05249226093292236], [39, 0.05249185487627983]]}, {\"ply\": 7, \"by\": \"random\", \"move\": 81}, {\"ply\": 8, \"by\": \"net\", \"move\": 39, \"top5\": [[60, 0.07771416753530502], [24, 0.07617557793855667], [23, 0.06564691662788391], [38, 0.05458246171474457], [39, 0.05458204448223114]]}, {\"ply\": 9, \"by\": \"random\", \"move\": 25}, {\"ply\": 10, \"by\": \"net\", \"move\": 47, \"top5\": [[23, 0.10659720003604889], [60, 0.07012663781642914], [29, 0.06796906143426895], [32, 0.06425125151872635], [21, 0.060283444821834564]]}, {\"ply\": 11, \"by\": \"random\", \"move\": 4}, {\"ply\": 12, \"by\": \"net\", \"move\": 1, \"top5\": [[23, 0.1175970658659935], [29, 0.111861452460289], [21, 0.06650415062904358], [32, 0.05827520415186882], [60, 0.05803295597434044]]}, {\"ply\": 13, \"by\": \"random\", \"move\": 32}, {\"ply\": 14, \"by\": \"net\", \"move\": 53, \"top5\": [[29, 0.1318829357624054], [21, 0.08929229527711868], [22, 0.08022450655698776], [20, 0.07139018177986145], [60, 0.058449070900678635]]}, {\"ply\": 15, \"by\": \"random\", \"move\": 22}, {\"ply\": 16, \"by\": \"net\", \"move\": 29, \"top5\": [[29, 0.1565467119216919], [20, 0.11017798632383347], [42, 0.07025279849767685], [60, 0.07025279849767685], [15, 0.04615946114063263]]}, {\"ply\": 17, \"by\": \"random\", \"move\": 12}, {\"ply\": 18, \"by\": \"net\", \"move\": 19, \"top5\": [[42, 0.09132496267557144], [60, 0.07992533594369888], [15, 0.06765499711036682], [20, 0.06224591284990311], [37, 0.06121686100959778]]}, {\"ply\": 19, \"by\": \"random\", \"move\": 38}, {\"ply\": 20, \"by\": \"net\", \"move\": 37, \"top5\": [[37, 0.9997312426567078], [42, 2.4909351850510575e-05], [40, 2.2092552171670832e-05], [11, 2.0394114471855573e-05], [60, 1.9078855984844267e-05]]}, {\"ply\": 21, \"by\": \"random\", \"move\": 31}, {\"ply\": 22, \"by\": \"net\", \"move\": 15, \"top5\": [[42, 0.11830966919660568], [15, 0.06825853139162064], [11, 0.06690714508295059], [60, 0.06602129340171814], [49, 0.05477868765592575]]}, {\"ply\": 23, \"by\": \"random\", \"move\": 60}, {\"ply\": 24, \"by\": \"net\", \"move\": 24, \"top5\": [[42, 0.21463792026042938], [58, 0.07362265884876251], [49, 0.06529726088047028], [11, 0.0621129609644413], [43, 0.05346103757619858]]}, {\"ply\": 25, \"by\": \"random\", \"move\": 13}, {\"ply\": 26, \"by\": \"net\", \"move\": 58, \"top5\": [[42, 0.3188425898551941], [11, 0.0834878608584404], [58, 0.057093847543001175], [43, 0.05596350133419037], [49, 0.050637561827898026]]}, {\"ply\": 27, \"by\": \"random\", \"move\": 0}, {\"ply\": 28, \"by\": \"net\", \"move\": 9, \"top5\": [[9, 0.9910458922386169], [42, 0.002911763731390238], [11, 0.0009789866162464023], [40, 0.0008770091226324439], [43, 0.0005110750789754093]]}, {\"ply\": 29, \"by\": \"random\", \"move\"\nsummary.json 1817\n{\n \"ok\": true,\n \"pass\": 1,\n \"kind\": \"games\",\n \"per_opponent\": {\n \"random\": {\n \"games\": 32,\n \"score\": 1.0,\n \"wins\": 32,\n \"losses\": 0,\n \"score_as_black\": 1.0,\n \"score_as_white\": 1.0,\n \"mean_margin\": 76.65625,\n \"mean_length\": 115.65625,\n \"stones_captured_per_game\": 50.5,\n \"stones_lost_per_game\": 0.4375,\n \"network_passes_per_game\": 1.0,\n \"all_player_passes_per_game\": 6.15625,\n \"games_with_network_pass_before_move_60\": 0,\n \"games_with_any_pass_before_move_60\": 19,\n \"end_repetition\": 0,\n \"end_two_passes\": 32,\n \"end_move_limit\": 0\n },\n \"weak\": {\n \"games\": 32,\n \"score\": 0.96875,\n \"wins\": 31,\n \"losses\": 1,\n \"score_as_black\": 0.9375,\n \"score_as_white\": 1.0,\n \"mean_margin\": 72.53125,\n \"mean_length\": 121.34375,\n \"stones_captured_per_game\": 52.875,\n \"stones_lost_per_game\": 2.96875,\n \"network_passes_per_game\": 1.59375,\n \"all_player_passes_per_game\": 5.40625,\n \"games_with_network_pass_before_move_60\": 0,\n \"games_with_any_pass_before_move_60\": 8,\n \"end_repetition\": 0,\n \"end_two_passes\": 32,\n \"end_move_limit\": 0\n },\n \"strong\": {\n \"games\": 64,\n \"score\": 0.421875,\n \"wins\": 27,\n \"losses\": 37,\n \"score_as_black\": 0.3125,\n \"score_as_white\": 0.53125,\n \"mean_margin\": 25.578125,\n \"mean_length\": 103.796875,\n \"stones_captured_per_game\": 25.15625,\n \"stones_lost_per_game\": 10.859375,\n \"network_passes_per_game\": 1.671875,\n \"all_player_passes_per_game\": 4.0,\n \"games_with_network_pass_before_move_60\": 0,\n \"games_with_any_pass_before_move_60\": 2,\n \"end_repetition\": 7,\n \"end_two_passes\": 57,\n \"end_move_limit\": 0\n }\n },\n \"files\": \"/work/pass_1/\"\n}\n\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.24471031315624714,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-df94e507ff364d50bb8c00aba2a16bac",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
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"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
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"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 3 of at most 120:
```
/work/pass_1 ['games.json', 'summary.json', 'boards.npy', 'README.txt', 'valid.npy']
games.json 1622759
[{"opponent": "random", "net_color": "black", "result": 1, "margin": 73.5, "end": "two_passes", "stones_captured": 54, "stones_lost": 0, "moves": [{"ply": 0, "by": "net", "move": 50, "top5": [[20, 0.06824281066656113], [24, 0.06824281066656113], [56, 0.06824281066656113], [60, 0.06824281066656113], [21, 0.043513670563697815]]}, {"ply": 1, "by": "random", "move": 7}, {"ply": 2, "by": "net", "move": 57, "top5": [[60, 0.08796501159667969], [24, 0.07571206986904144], [20, 0.058964621275663376], [56, 0.058964621275663376], [33, 0.05269087105989456]]}, {"ply": 3, "by": "random", "move": 46}, {"ply": 4, "by": "net", "move": 56, "top5": [[60, 0.09638267010450363], [24, 0.07357680052518845], [20, 0.05730167031288147], [33, 0.053161416202783585], [29, 0.05056854709982872]]}, {"ply": 5, "by": "random", "move": 5}, {"ply": 6, "by": "net", "move": 64, "top5": [[60, 0.07989044487476349], [24, 0.07830876857042313], [23, 0.06623201072216034], [38, 0.05249226093292236], [39, 0.05249185487627983]]}, {"ply": 7, "by": "random", "move": 81}, {"ply": 8, "by": "net", "move": 39, "top5": [[60, 0.07771416753530502], [24, 0.07617557793855667], [23, 0.06564691662788391], [38, 0.05458246171474457], [39, 0.05458204448223114]]}, {"ply": 9, "by": "random", "move": 25}, {"ply": 10, "by": "net", "move": 47, "top5": [[23, 0.10659720003604889], [60, 0.07012663781642914], [29, 0.06796906143426895], [32, 0.06425125151872635], [21, 0.060283444821834564]]}, {"ply": 11, "by": "random", "move": 4}, {"ply": 12, "by": "net", "move": 1, "top5": [[23, 0.1175970658659935], [29, 0.111861452460289], [21, 0.06650415062904358], [32, 0.05827520415186882], [60, 0.05803295597434044]]}, {"ply": 13, "by": "random", "move": 32}, {"ply": 14, "by": "net", "move": 53, "top5": [[29, 0.1318829357624054], [21, 0.08929229527711868], [22, 0.08022450655698776], [20, 0.07139018177986145], [60, 0.058449070900678635]]}, {"ply": 15, "by": "random", "move": 22}, {"ply": 16, "by": "net", "move": 29, "top5": [[29, 0.1565467119216919], [20, 0.11017798632383347], [42, 0.07025279849767685], [60, 0.07025279849767685], [15, 0.04615946114063263]]}, {"ply": 17, "by": "random", "move": 12}, {"ply": 18, "by": "net", "move": 19, "top5": [[42, 0.09132496267557144], [60, 0.07992533594369888], [15, 0.06765499711036682], [20, 0.06224591284990311], [37, 0.06121686100959778]]}, {"ply": 19, "by": "random", "move": 38}, {"ply": 20, "by": "net", "move": 37, "top5": [[37, 0.9997312426567078], [42, 2.4909351850510575e-05], [40, 2.2092552171670832e-05], [11, 2.0394114471855573e-05], [60, 1.9078855984844267e-05]]}, {"ply": 21, "by": "random", "move": 31}, {"ply": 22, "by": "net", "move": 15, "top5": [[42, 0.11830966919660568], [15, 0.06825853139162064], [11, 0.06690714508295059], [60, 0.06602129340171814], [49, 0.05477868765592575]]}, {"ply": 23, "by": "random", "move": 60}, {"ply": 24, "by": "net", "move": 24, "top5": [[42, 0.21463792026042938], [58, 0.07362265884876251], [49, 0.06529726088047028], [11, 0.0621129609644413], [43, 0.05346103757619858]]}, {"ply": 25, "by": "random", "move": 13}, {"ply": 26, "by": "net", "move": 58, "top5": [[42, 0.3188425898551941], [11, 0.0834878608584404], [58, 0.057093847543001175], [43, 0.05596350133419037], [49, 0.050637561827898026]]}, {"ply": 27, "by": "random", "move": 0}, {"ply": 28, "by": "net", "move": 9, "top5": [[9, 0.9910458922386169], [42, 0.002911763731390238], [11, 0.0009789866162464023], [40, 0.0008770091226324439], [43, 0.0005110750789754093]]}, {"ply": 29, "by": "random", "move"
summary.json 1817
{
"ok": true,
"pass": 1,
"kind": "games",
"per_opponent": {
"random": {
"games": 32,
"score": 1.0,
"wins": 32,
"losses": 0,
"score_as_black": 1.0,
"score_as_white": 1.0,
"mean_margin": 76.65625,
"mean_length": 115.65625,
"stones_captured_per_game": 50.5,
"stones_lost_per_game": 0.4375,
"network_passes_per_game": 1.0,
"all_player_passes_per_game": 6.15625,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 19,
"end_repetition": 0,
"end_two_passes": 32,
"end_move_limit": 0
},
"weak": {
"games": 32,
"score": 0.96875,
"wins": 31,
"losses": 1,
"score_as_black": 0.9375,
"score_as_white": 1.0,
"mean_margin": 72.53125,
"mean_length": 121.34375,
"stones_captured_per_game": 52.875,
"stones_lost_per_game": 2.96875,
"network_passes_per_game": 1.59375,
"all_player_passes_per_game": 5.40625,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 8,
"end_repetition": 0,
"end_two_passes": 32,
"end_move_limit": 0
},
"strong": {
"games": 64,
"score": 0.421875,
"wins": 27,
"losses": 37,
"score_as_black": 0.3125,
"score_as_white": 0.53125,
"mean_margin": 25.578125,
"mean_length": 103.796875,
"stones_captured_per_game": 25.15625,
"stones_lost_per_game": 10.859375,
"network_passes_per_game": 1.671875,
"all_player_passes_per_game": 4.0,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 2,
"end_repetition": 7,
"end_two_passes": 57,
"end_move_limit": 0
}
},
"files": "/work/pass_1/"
}
```Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 3 of at most 120:
```
/work/pass_1 ['games.json', 'summary.json', 'boards.npy', 'README.txt', 'valid.npy']
games.json 1622759
[{"opponent": "random", "net_color": "black", "result": 1, "margin": 73.5, "end": "two_passes", "stones_captured": 54, "stones_lost": 0, "moves": [{"ply": 0, "by": "net", "move": 50, "top5": [[20, 0.06824281066656113], [24, 0.06824281066656113], [56, 0.06824281066656113], [60, 0.06824281066656113], [21, 0.043513670563697815]]}, {"ply": 1, "by": "random", "move": 7}, {"ply": 2, "by": "net", "move": 57, "top5": [[60, 0.08796501159667969], [24, 0.07571206986904144], [20, 0.058964621275663376], [56, 0.058964621275663376], [33, 0.05269087105989456]]}, {"ply": 3, "by": "random", "move": 46}, {"ply": 4, "by": "net", "move": 56, "top5": [[60, 0.09638267010450363], [24, 0.07357680052518845], [20, 0.05730167031288147], [33, 0.053161416202783585], [29, 0.05056854709982872]]}, {"ply": 5, "by": "random", "move": 5}, {"ply": 6, "by": "net", "move": 64, "top5": [[60, 0.07989044487476349], [24, 0.07830876857042313], [23, 0.06623201072216034], [38, 0.05249226093292236], [39, 0.05249185487627983]]}, {"ply": 7, "by": "random", "move": 81}, {"ply": 8, "by": "net", "move": 39, "top5": [[60, 0.07771416753530502], [24, 0.07617557793855667], [23, 0.06564691662788391], [38, 0.05458246171474457], [39, 0.05458204448223114]]}, {"ply": 9, "by": "random", "move": 25}, {"ply": 10, "by": "net", "move": 47, "top5": [[23, 0.10659720003604889], [60, 0.07012663781642914], [29, 0.06796906143426895], [32, 0.06425125151872635], [21, 0.060283444821834564]]}, {"ply": 11, "by": "random", "move": 4}, {"ply": 12, "by": "net", "move": 1, "top5": [[23, 0.1175970658659935], [29, 0.111861452460289], [21, 0.06650415062904358], [32, 0.05827520415186882], [60, 0.05803295597434044]]}, {"ply": 13, "by": "random", "move": 32}, {"ply": 14, "by": "net", "move": 53, "top5": [[29, 0.1318829357624054], [21, 0.08929229527711868], [22, 0.08022450655698776], [20, 0.07139018177986145], [60, 0.058449070900678635]]}, {"ply": 15, "by": "random", "move": 22}, {"ply": 16, "by": "net", "move": 29, "top5": [[29, 0.1565467119216919], [20, 0.11017798632383347], [42, 0.07025279849767685], [60, 0.07025279849767685], [15, 0.04615946114063263]]}, {"ply": 17, "by": "random", "move": 12}, {"ply": 18, "by": "net", "move": 19, "top5": [[42, 0.09132496267557144], [60, 0.07992533594369888], [15, 0.06765499711036682], [20, 0.06224591284990311], [37, 0.06121686100959778]]}, {"ply": 19, "by": "random", "move": 38}, {"ply": 20, "by": "net", "move": 37, "top5": [[37, 0.9997312426567078], [42, 2.4909351850510575e-05], [40, 2.2092552171670832e-05], [11, 2.0394114471855573e-05], [60, 1.9078855984844267e-05]]}, {"ply": 21, "by": "random", "move": 31}, {"ply": 22, "by": "net", "move": 15, "top5": [[42, 0.11830966919660568], [15, 0.06825853139162064], [11, 0.06690714508295059], [60, 0.06602129340171814], [49, 0.05477868765592575]]}, {"ply": 23, "by": "random", "move": 60}, {"ply": 24, "by": "net", "move": 24, "top5": [[42, 0.21463792026042938], [58, 0.07362265884876251], [49, 0.06529726088047028], [11, 0.0621129609644413], [43, 0.05346103757619858]]}, {"ply": 25, "by": "random", "move": 13}, {"ply": 26, "by": "net", "move": 58, "top5": [[42, 0.3188425898551941], [11, 0.0834878608584404], [58, 0.057093847543001175], [43, 0.05596350133419037], [49, 0.050637561827898026]]}, {"ply": 27, "by": "random", "move": 0}, {"ply": 28, "by": "net", "move": 9, "top5": [[9, 0.9910458922386169], [42, 0.002911763731390238], [11, 0.0009789866162464023], [40, 0.0008770091226324439], [43, 0.0005110750789754093]]}, {"ply": 29, "by": "random", "move"
summary.json 1817
{
"ok": true,
"pass": 1,
"kind": "games",
"per_opponent": {
"random": {
"games": 32,
"score": 1.0,
"wins": 32,
"losses": 0,
"score_as_black": 1.0,
"score_as_white": 1.0,
"mean_margin": 76.65625,
"mean_length": 115.65625,
"stones_captured_per_game": 50.5,
"stones_lost_per_game": 0.4375,
"network_passes_per_game": 1.0,
"all_player_passes_per_game": 6.15625,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 19,
"end_repetition": 0,
"end_two_passes": 32,
"end_move_limit": 0
},
"weak": {
"games": 32,
"score": 0.96875,
"wins": 31,
"losses": 1,
"score_as_black": 0.9375,
"score_as_white": 1.0,
"mean_margin": 72.53125,
"mean_length": 121.34375,
"stones_captured_per_game": 52.875,
"stones_lost_per_game": 2.96875,
"network_passes_per_game": 1.59375,
"all_player_passes_per_game": 5.40625,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 8,
"end_repetition": 0,
"end_two_passes": 32,
"end_move_limit": 0
},
"strong": {
"games": 64,
"score": 0.421875,
"wins": 27,
"losses": 37,
"score_as_black": 0.3125,
"score_as_white": 0.53125,
"mean_margin": 25.578125,
"mean_length": 103.796875,
"stones_captured_per_game": 25.15625,
"stones_lost_per_game": 10.859375,
"network_passes_per_game": 1.671875,
"all_player_passes_per_game": 4.0,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 2,
"end_repetition": 7,
"end_two_passes": 57,
"end_move_limit": 0
}
},
"files": "/work/pass_1/"
}
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import json, numpy as np
with open("/work/pass_1/games.json") as f:
games=json.load(f)
print(open("/work/pass_1/README.txt").read())
boards=np.load("/work/pass_1/boards.npy")
valid=np.load("/work/pass_1/valid.npy")
print("boards:",boards.shape,boards.dtype,"valid:",valid.shape, "values:",np.unique(boards))
for i,g in enumerate(games):
if g["opponent"]=="strong":
print(i,g["net_color"],g["result"],g["margin"],g["end"],
"captured/lost",g["stones_captured"],g["stones_lost"],
"length",len(g["moves"]), "last",g["moves"][-3:])
if i>=108: break
```
{
"request_sha256": "bb4b721b42f04be5d6f76a3d22d113d7c5a68770703965cf5e6d5c5a034d1719",
"request": {
"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import json, numpy as np\nwith open(\"/work/pass_1/games.json\") as f:\n games=json.load(f)\nprint(open(\"/work/pass_1/README.txt\").read())\nboards=np.load(\"/work/pass_1/boards.npy\")\nvalid=np.load(\"/work/pass_1/valid.npy\")\nprint(\"boards:\",boards.shape,boards.dtype,\"valid:\",valid.shape, \"values:\",np.unique(boards))\nfor i,g in enumerate(games):\n if g[\"opponent\"]==\"strong\":\n print(i,g[\"net_color\"],g[\"result\"],g[\"margin\"],g[\"end\"],\n \"captured/lost\",g[\"stones_captured\"],g[\"stones_lost\"],\n \"length\",len(g[\"moves\"]), \"last\",g[\"moves\"][-3:])\n if i>=108: break"
},
"result": {
"ok": true,
"out": "games.json: opponent, net_color, result +1/-1, area margin including komi, end reason, captured/lost stones, moves with ply/by/move and network top5 [move,probability]. boards.npy: (games,162,81), board AFTER each ply (Black1, White-1, empty0). valid.npy: (games,162), plies actually played.\n\nboards: (128, 162, 81) int8 valid: (128, 162) values: [-1 0 1]\n64 black 1 73.5 two_passes captured/lost 60 2 length 129 last [{'ply': 126, 'by': 'net', 'move': 8, 'top5': [[8, 1.0], [81, 5.439071502216786e-13], [9, 1.3688245160712218e-17], [45, 4.695150362335196e-18], [4, 4.164213319229766e-18]]}, {'ply': 127, 'by': 'strong', 'move': 81}, {'ply': 128, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999185800552368], [9, 2.5164463295368478e-05], [45, 8.63156219566008e-06], [4, 6.789841336285463e-06], [1, 6.655415745626669e-06]]}]\n65 white -1 -2.5 two_passes captured/lost 6 18 length 90 last [{'ply': 87, 'by': 'net', 'move': 71, 'top5': [[71, 0.790695071220398], [70, 0.17642655968666077], [81, 0.032230280339717865], [32, 0.0005844395491294563], [2, 4.129161243326962e-05]]}, {'ply': 88, 'by': 'strong', 'move': 81}, {'ply': 89, 'by': 'net', 'move': 81, 'top5': [[81, 0.9799486994743347], [32, 0.017769649624824524], [2, 0.0012554549612104893], [1, 0.0005930348997935653], [70, 0.0003455897676758468]]}]\n66 black -1 -22.5 two_passes captured/lost 2 23 length 99 last [{'ply': 96, 'by': 'net', 'move': 21, 'top5': [[81, 0.8825389742851257], [21, 0.04665631055831909], [43, 0.027461959049105644], [61, 0.024356691166758537], [37, 0.009419688954949379]]}, {'ply': 97, 'by': 'strong', 'move': 81}, {'ply': 98, 'by': 'net', 'move': 81, 'top5': [[81, 0.9315993785858154], [43, 0.028988569974899292], [61, 0.025710681453347206], [37, 0.009943329729139805], [36, 0.003657946363091469]]}]\n67 white -1 -4.5 two_passes captured/lost 3 14 length 85 last [{'ply': 82, 'by': 'strong', 'move': 61}, {'ply': 83, 'by': 'net', 'move': 81, 'top5': [[81, 0.9940990209579468], [52, 0.00410346919670701], [53, 0.001719163148663938], [3, 2.5269348043366335e-05], [9, 1.660317684581969e-05]]}, {'ply': 84, 'by': 'strong', 'move': 81}]\n68 black -1 -20.5 two_passes captured/lost 7 21 length 104 last [{'ply': 101, 'by': 'strong', 'move': 60}, {'ply': 102, 'by': 'net', 'move': 81, 'top5': [[81, 0.9049596190452576], [42, 0.05029425770044327], [51, 0.04243157431483269], [10, 0.0021337631624192], [0, 0.00017340814520139247]]}, {'ply': 103, 'by': 'strong', 'move': 81}]\n69 white -1 -2.5 two_passes captured/lost 5 18 length 96 last [{'ply': 93, 'by': 'net', 'move': 62, 'top5': [[62, 0.9343498349189758], [81, 0.06535577774047852], [0, 0.00022760209685657173], [9, 6.520908937091008e-05], [6, 4.482532744987111e-07]]}, {'ply': 94, 'by': 'strong', 'move': 81}, {'ply': 95, 'by': 'net', 'move': 81, 'top5': [[81, 0.9955177903175354], [0, 0.0034668997395783663], [9, 0.0009932833490893245], [6, 6.8279246079328004e-06], [26, 6.8279246079328004e-06]]}]\n70 black 1 73.5 two_passes captured/lost 59 2 length 123 last [{'ply': 120, 'by': 'net', 'move': 60, 'top5': [[60, 0.9999979734420776], [81, 1.9847861949529033e-06], [0, 1.0365014402324846e-10], [4, 6.675481695195273e-11], [2, 6.609045255512314e-11]]}, {'ply': 121, 'by': 'strong', 'move': 81}, {'ply': 122, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997805953025818], [0, 5.2210856665624306e-05], [4, 3.362586721777916e-05], [2, 3.329121682327241e-05], [18, 3.329121682327241e-05]]}]\n71 white 1 88.5 two_passes captured/lost 54 0 length 118 last [{'ply': 115, 'by': 'net', 'move': 64, 'top5': [[64, 0.9999833106994629], [81, 1.6701518688932993e-05], [57, 5.5326815129319584e-08], [72, 2.040622115728752e-09], [8, 9.932761280140312e-10]]}, {'ply': 116, 'by': 'strong', 'move': 81}, {'ply': 117, 'by': 'net', 'move': 81, 'top5': [[81, 0.999828577041626], [8, 5.946201417827979e-05], [72, 3.9462138374801725e-05], [71, 1.669887024036143e-05], [79, 1.481052822782658e-05]]}]\n72 black 1 73.5 two_passes captured/lost 61 7 length 131 last [{'ply': 128, 'by': 'net', 'move': 19, 'top5': [[19, 0.999993085861206], [81, 6.85860641169711e-06], [72, 6.860947920905858e-10], [35, 2.627010553535314e-10], [76, 2.627010553535314e-10]]}, {'ply': 129, 'by': 'strong', 'move': 81}, {'ply': 130, 'by': 'net', 'move': 81, 'top5': [[81, 0.9996083378791809], [72, 9.999495523516089e-05], [35, 3.8287391362246126e-05], [76, 3.8287391362246126e-05], [3, 3.7906342186033726e-05]]}]\n73 white -1 -4.5 two_passes captured/lost 9 23 length 99 last [{'ply': 96, 'by': 'strong', 'move': 58}, {'ply': 97, 'by': 'net', 'move': 81, 'top5': [[81, 0.9545677900314331], [51, 0.01646541990339756], [30, 0.011956262402236462], [12, 0.009691640734672546], [55, 0.0042684744112193584]]}, {'ply': 98, 'by': 'strong', 'move': 81}]\n74 black -1 -7.5 two_passes captured/lost 10 15 length 94 last [{'ply': 91, 'by': 'strong', 'move': 25}, {'ply': 92, 'by': 'net', 'move': 81, 'top5': [[81, 0.9933957457542419], [48, 0.006303618662059307], [0, 0.00019035425793845206], [72, 5.790967043139972e-05], [36, 3.8049434806453064e-05]]}, {'ply': 93, 'by': 'strong', 'move': 81}]\n75 white 1 88.5 two_passes captured/lost 63 3 length 130 last [{'ply': 127, 'by': 'net', 'move': 70, 'top5': [[70, 0.9999450445175171], [81, 5.489686009241268e-05], [8, 3.2648372894072963e-09], [75, 2.789336261965758e-10], [73, 2.7340918418161664e-10]]}, {'ply': 128, 'by': 'strong', 'move': 81}, {'ply': 129, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999041557312012], [8, 5.9466507082106546e-05], [75, 5.080561550130369e-06], [73, 4.9799382395576686e-06], [9, 4.461196112970356e-06]]}]\n76 black -1 -5.5 two_passes captured/lost 5 7 length 82 last [{'ply': 79, 'by': 'strong', 'move': 52}, {'ply': 80, 'by': 'net', 'move': 81, 'top5': [[81, 0.9725267291069031], [32, 0.02738211862742901], [0, 5.726301606046036e-05], [22, 1.8683713278733194e-05], [4, 7.3717824307095725e-06]]}, {'ply': 81, 'by': 'strong', 'move': 81}]\n77 white 1 88.5 two_passes captured/lost 57 0 length 118 last [{'ply': 115, 'by': 'net', 'move': 48, 'top5': [[48, 0.9999967813491821], [81, 3.239806574129034e-06], [8, 3.6908401335189467e-10], [72, 3.6908401335189467e-10], [27, 8.235377657594967e-11]]}, {'ply': 116, 'by': 'strong', 'move': 81}, {'ply': 117, 'by': 'net', 'move': 81, 'top5': [[81, 0.9996875524520874], [8, 0.00011388602433726192], [72, 0.00011388602433726192], [27, 2.5411403839825653e-05], [1, 1.6696514649083838e-05]]}]\n78 black -1 -6.5 two_passes captured/lost 4 6 length 86 last [{'ply': 83, 'by': 'strong', 'move': 54}, {'ply': 84, 'by': 'net', 'move': 81, 'top5': [[81, 0.9937422871589661], [25, 0.006180975120514631], [8, 3.409785495023243e-05], [35, 1.744819564919453e-05], [5, 9.292721188103314e-06]]}, {'ply': 85, 'by': 'strong', 'move': 81}]\n79 white -1 6.5 repetition captured/lost 4 8 length 84 last [{'ply': 81, 'by': 'net', 'move': 5, 'top5': [[5, 1.0], [19, 4.8473686869998645e-11], [7, 2.9108396248922475e-11], [81, 1.0736045299303276e-12], [29, 3.842764187368328e-14]]}, {'ply': 82, 'by': 'strong', 'move': 7}, {'ply': 83, 'by': 'net', 'move': 6, 'top5': [[6, 0.9999997615814209], [19, 2.686100515347789e-07], [81, 5.949226888901649e-09], [29, 2.1294130347904172e-10], [72, 1.9317570112975524e-11]]}]\n80 black -1 47.5 repetition captured/lost 51 9 length 127 last [{'ply': 124, 'by': 'net', 'move': 77, 'top5': [[77, 0.9999984502792358], [64, 1.6088388292700984e-06], [45, 3.948223525895855e-09], [38, 4.691975141746241e-10], [36, 2.1724366749964474e-10]]}, {'ply': 125, 'by': 'strong', 'move': 79}, {'ply': 126, 'by': 'net', 'move': 78, 'top5': [[78, 0.9913105964660645], [64, 0.008662731386721134], [45, 2.125906030414626e-05], [38, 2.5263761926908046e-06], [36, 1.1697402442223392e-06]]}]\n81 white 1 88.5 two_passes captured/lost 60 4 length 124 last [{'ply': 121, 'by': 'net', 'move': 64, 'top5': [[64, 1.0], [81, 2.4860231206957906e-08], [47, 7.377551347609312e-11], [0, 1.6670006304161933e-12], [24, 1.247364191103717e-12]]}, {'ply': 122, 'by': 'strong', 'move': 81}, {'ply': 123, 'by': 'net', 'move': 81, 'top5': [[81, 0.999729573726654], [0, 6.70367808197625e-05], [24, 5.016151408199221e-05], [18, 2.2765523681300692e-05], [6, 2.2765349058317952e-05]]}]\n82 black -1 -9.5 two_passes captured/lost 2 7 length 80 last [{'ply': 77, 'by': 'strong', 'move': 68}, {'ply': 78, 'by': 'net', 'move': 81, 'top5': [[81, 0.974189817905426], [30, 0.011841407977044582], [76, 0.0053207119926810265], [64, 0.0033926197793334723], [75, 0.002979052485898137]]}, {'ply': 79, 'by': 'strong', 'move': 81}]\n83 white -1 -1.5 two_passes captured/lost 4 14 length 89 last [{'ply': 86, 'by': 'strong', 'move': 51}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9982441663742065], [30, 0.0017263316549360752], [27, 2.2731697754352354e-05], [9, 3.720116865224554e-06], [2, 1.9615756627899827e-06]]}, {'ply': 88, 'by': 'strong', 'move': 81}]\n84 black 1 73.5 two_passes captured/lost 62 7 length 129 last [{'ply': 126, 'by': 'net', 'move': 30, 'top5': [[30, 0.999995231628418], [81, 4.785094461112749e-06], [41, 1.2720986930503386e-08], [0, 3.727907427197863e-10], [80, 2.498887208268741e-10]]}, {'ply': 127, 'by': 'strong', 'move': 81}, {'ply': 128, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997435212135315], [0, 7.788668153807521e-05], [80, 5.220892126089893e-05], [53, 3.012206798302941e-05], [63, 2.209282320109196e-05]]}]\n85 white -1 24.5 repetition captured/lost 11 4 length 74 last [{'ply': 71, 'by': 'net', 'move': 53, 'top5': [[53, 1.0], [6, 1.2011325267735629e-09], [75, 1.003269911592497e-09], [5, 9.169160430921863e-10], [74, 5.788346468804662e-10]]}, {'ply': 72, 'by': 'strong', 'move': 71}, {'ply': 73, 'by': 'net', 'move': 62, 'top5': [[62, 0.9999678134918213], [6, 6.997012405918213e-06], [75, 5.8443938542041e-06], [5, 5.341353244148195e-06], [74, 3.371911816429929e-06]]}]\n86 black -1 -10.5 repetition captured/lost 6 14 length 87 last [{'ply': 84, 'by': 'net', 'move': 78, 'top5': [[78, 1.0], [81, 4.441631090701392e-12], [55, 2.0009224854268537e-13], [65, 1.0341757289943077e-13], [0, 2.3075579668645554e-14]]}, {'ply': 85, 'by': 'strong', 'move': 77}, {'ply': 86, 'by': 'net', 'move': 69, 'top5': [[69, 0.9994966983795166], [81, 0.00045714687439613044], [55, 2.059413236565888e-05], [65, 9.44048588280566e-06], [68, 8.125426575134043e-06]]}]\n87 white 1 0.5 two_passes captured/lost 2 11 length 89 last [{'ply': 86, 'by': 'strong', 'move': 9}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999927282333374], [63, 5.030444299336523e-06], [55, 1.4557231224898715e-06], [65, 4.340930672697141e-07], [48, 3.0897334113433317e-07]]}, {'ply': 88, 'by': 'strong', 'move': 81}]\n88 black -1 1.5 repetition captured/lost 8 9 length 87 last [{'ply': 84, 'by': 'net', 'move': 18, 'top5': [[18, 1.0], [6, 3.273483151211565e-10], [5, 1.5462839342283985e-10], [0, 1.228570439826271e-10], [3, 4.172194534302065e-11]]}, {'ply': 85, 'by': 'strong', 'move': 0}, {'ply': 86, 'by': 'net', 'move': 9, 'top5': [[9, 0.9986767172813416], [3, 0.0013184096897020936], [6, 3.077704377574264e-06], [5, 1.4538045434164815e-06], [7, 3.211592627394566e-07]]}]\n89 white -1 -4.5 two_passes captured/lost 3 16 length 92 last [{'ply': 89, 'by': 'net', 'move': 47, 'top5': [[47, 0.9999997615814209], [29, 2.580794387085916e-07], [81, 2.2610960326296947e-10], [69, 6.3663232671706815e-12], [59, 3.2904304281267116e-12]]}, {'ply': 90, 'by': 'strong', 'move': 81}, {'ply': 91, 'by': 'net', 'move': 81, 'top5': [[81, 0.9570878744125366], [69, 0.02694767154753208], [59, 0.013927889056503773], [2, 0.0010875178268179297], [1, 0.00084695965051651]]}]\n90 black -1 -13.5 two_passes captured/lost 5 19 length 98 last [{'ply': 95, 'by': 'strong', 'move': 73}, {'ply': 96, 'by': 'net', 'move': 81, 'top5': [[81, 0.9891046285629272], [33, 0.010878604836761951], [35, 8.453302143607289e-06], [78, 3.68604969480657e-06], [25, 2.326927415197133e-06]]}, {'ply': 97, 'by': 'strong', 'move': 81}]\n91 white 1 6.5 two_passes captured/lost 20 20 length 117 last [{'ply': 114, 'by': 'strong', 'move': 61}, {'ply': 115, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999452829360962], [9, 1.670082019700203e-05], [1, 1.6534608221263625e-05], [3, 5.080770733911777e-06], [19, 3.5803093396680197e-06]]}, {'ply': 116, 'by': 'strong', 'move': 81}]\n92 black 1 73.5 two_passes captured/lost 61 7 length 129 last [{'ply': 126, 'by': 'net', 'move': 40, 'top5': [[40, 0.9999898672103882], [81, 9.929436600941699e-06], [21, 2.939044634331367e-07], [80, 9.93282567307574e-10], [8, 3.84144327458813e-10]]}, {'ply': 127, 'by': 'strong', 'move': 81}, {'ply': 128, 'by': 'net', 'move': 81, 'top5': [[81, 0.9996169805526733], [80, 9.999582107411698e-05], [8, 3.8672606024192646e-05], [45, 3.828772605629638e-05], [3, 3.790667324210517e-05]]}]\n93 white 1 88.5 two_passes captured/lost 58 0 length 124 last [{'ply': 121, 'by': 'net', 'move': 34, 'top5': [[34, 0.9999545812606812], [81, 4.539778092294e-05], [23, 3.563109984838775e-08], [80, 1.773968083540467e-09], [58, 5.13355524756065e-10]]}, {'ply': 122, 'by': 'strong', 'move': 81}, {'ply': 123, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999127388000488], [80, 3.907268910552375e-05], [58, 1.1306957276246976e-05], [76, 5.671371582138818e-06], [17, 5.080605205876054e-06]]}]\n94 black -1 -4.5 two_passes captured/lost 6 12 length 92 last [{'ply': 89, 'by': 'strong', 'move': 4}, {'ply': 90, 'by': 'net', 'move': 81, 'top5': [[81, 0.9719324707984924], [60, 0.020682498812675476], [68, 0.0053617036901414394], [65, 0.0019528298871591687], [72, 5.025180507800542e-05]]}, {'ply': 91, 'by': 'strong', 'move': 81}]\n95 white -1 -5.5 two_passes captured/lost 6 21 length 103 last [{'ply': 100, 'by': 'strong', 'move': 2}, {'ply': 101, 'by': 'net', 'move': 81, 'top5': [[81, 0.986890435218811], [15, 0.008976013399660587], [10, 0.0017066968139261007], [60, 0.0013696546666324139], [1, 0.0009846753673627973]]}, {'ply': 102, 'by': 'strong', 'move': 81}]\n96 black -1 -14.5 two_passes captured/lost 10 22 length 106 last [{'ply': 103, 'by': 'strong', 'move': 10}, {'ply': 104, 'by': 'net', 'move': 81, 'top5': [[81, 0.9788761138916016], [8, 0.005085548851639032], [49, 0.004886137321591377], [37, 0.004510464612394571], [53, 0.0032426989637315273]]}, {'ply': 105, 'by': 'strong', 'move': 81}]\n97 white 1 88.5 two_passes captured/lost 53 0 length 118 last [{'ply': 115, 'by': 'net', 'move': 71, 'top5': [[71, 0.9999972581863403], [81, 2.7332755507814e-06], [8, 1.6255392865094365e-10], [36, 6.947808300905578e-11], [18, 6.16218326365825e-11]]}, {'ply': 116, 'by': 'strong', 'move': 81}, {'ply': 117, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997962117195129], [8, 5.946008604951203e-05], [80, 5.326674727257341e-05], [36, 2.541416688472964e-05], [18, 2.2540454665431753e-05]]}]\n98 black -1 -1.5 two_passes captured/lost 2 5 length 77 last [{'ply': 74, 'by': 'net', 'move': 18, 'top5': [[18, 0.9999903440475464], [0, 9.635920832806733e-06], [81, 9.427153068591876e-13], [32, 7.994550219037316e-15], [64, 2.4321246649668463e-15]]}, {'ply': 75, 'by': 'strong', 'move': 81}, {'ply': 76, 'by': 'net', 'move': 81, 'top5': [[81, 0.9874961376190186], [32, 0.008374307304620743], [64, 0.002547655487433076], [73, 0.0014698648592457175], [7, 2.4604501959402114e-05]]}]\n99 white 1 88.5 two_passes captured/lost 65 6 length 134 last [{'ply': 131, 'by': 'net', 'move': 73, 'top5': [[73, 0.9999984502792358], [81, 1.5151365460042143e-06], [0, 1.0159734858961045e-10], [80, 5.251093310176813e-11], [8, 4.43013681294957e-11]]}, {'ply': 132, 'by': 'strong', 'move': 81}, {'ply': 133, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997754693031311], [0, 6.70398585498333e-05], [72, 4.19000098190736e-05], [80, 3.464977635303512e-05], [8, 2.9232627639430575e-05]]}]\n100 black -1 -9.5 two_passes captured/lost 3 9 length 83 last [{'ply': 80, 'by': 'net', 'move': 71, 'top5': [[71, 0.5514063239097595], [62, 0.4425133764743805], [81, 0.005826805252581835], [29, 0.00018683564849197865], [59, 4.045632158522494e-05]]}, {'ply': 81, 'by': 'strong', 'move': 81}, {'ply': 82, 'by': 'net', 'move': 81, 'top5': [[81, 0.9583132863044739], [29, 0.0307281743735075], [59, 0.006653703283518553], [28, 0.002065093256533146], [9, 0.0011109024053439498]]}]\n101 white 1 88.5 two_passes captured/lost 57 1 length 118 last [{'ply': 115, 'by': 'net', 'move': 11, 'top5': [[11, 0.9994322657585144], [2, 0.000563939509447664], [81, 3.837983967969194e-06], [8, 3.8778952271556477e-10], [0, 1.4848085261309762e-10]]}, {'ply': 116, 'by': 'strong', 'move': 81}, {'ply': 117, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997736811637878], [8, 0.00010101703082909808], [0, 5.2210598369129e-05], [75, 2.5413593903067522e-05], [57, 1.0027025382441934e-05]]}]\n102 black -1 -12.5 two_passes captured/lost 10 18 length 104 last [{'ply': 101, 'by': 'strong', 'move': 73}, {'ply': 102, 'by': 'net', 'move': 81, 'top5': [[81, 0.9872137308120728], [43, 0.008206164464354515], [25, 0.004503611009567976], [35, 6.488682993222028e-05], [6, 5.599291398539208e-06]]}, {'ply': 103, 'by': 'strong', 'move': 81}]\n103 white 1 88.5 two_passes captured/lost 57 2 length 120 last [{'ply': 117, 'by': 'net', 'move': 10, 'top5': [[10, 0.9999790191650391], [81, 2.102035068674013e-05], [77, 5.343235853771944e-10], [45, 4.739048597990347e-10], [47, 3.617676991307661e-10]]}, {'ply': 118, 'by': 'strong', 'move': 81}, {'ply': 119, 'by': 'net', 'move': 81, 'top5': [[81, 0.9998648166656494], [77, 2.541591129556764e-05], [45, 2.254200262541417e-05], [47, 1.720802902127616e-05], [67, 1.4088785974308848e-05]]}]\n104 black -1 -22.5 two_passes captured/lost 11 28 length 114 last [{'ply': 111, 'by': 'strong', 'move': 2}, {'ply': 112, 'by': 'net', 'move': 81, 'top5': [[81, 0.9349849224090576], [20, 0.04383939504623413], [41, 0.010283373296260834], [16, 0.0054223062470555305], [11, 0.005368383135646582]]}, {'ply': 113, 'by': 'strong', 'move': 81}]\n105 white 1 88.5 two_passes captured/lost 65 7 length 136 last [{'ply': 133, 'by': 'net', 'move': 65, 'top5': [[65, 0.9999266862869263], [81, 7.336439011851326e-05], [53, 1.883621258969015e-09], [5, 1.6706177552450185e-09], [33, 1.2753196276804601e-09]]}, {'ply': 134, 'by': 'strong', 'move': 81}, {'ply': 135, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999009370803833], [53, 2.5672328774817288e-05], [5, 2.2769250790588558e-05], [33, 1.7381637007929385e-05], [7, 4.9799223234003875e-06]]}]\n106 black -1 -6.5 two_passes captured/lost 5 12 length 88 last [{'ply': 85, 'by': 'strong', 'move': 63}, {'ply': 86, 'by': 'net', 'move': 81, 'top5': [[81, 0.9595587849617004], [23, 0.024202920496463776], [13, 0.0056772599928081036], [50, 0.005137004889547825], [64, 0.0024755795020610094]]}, {'ply': 87, 'by': 'strong', 'move': 81}]\n107 white 1 4.5 two_passes captured/lost 4 14 length 88 last [{'ply': 85, 'by': 'net', 'move': 5, 'top5': [[5, 0.9713945984840393], [81, 0.015010133385658264], [14, 0.013180283829569817], [41, 0.00025378126883879304], [43, 0.00016020932525862008]]}, {'ply': 86, 'by': 'strong', 'move': 81}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9730942845344543], [41, 0.016452426090836525], [43, 0.010386236011981964], [35, 2.4735421902732924e-05], [33, 2.150395630451385e-05]]}]\n108 black -1 -12.5 two_passes captured/lost 1 6 length 76 last [{'ply': 73, 'by': 'strong', 'move': 75}, {'ply': 74, 'by': 'net', 'move': 81, 'top5': [[81, 0.9805928468704224], [61, 0.01330519188195467], [72, 0.004518409259617329], [73, 0.0014595894608646631], [8, 3.793661016970873e-05]]}, {'ply': 75, 'by': 'strong', 'move': 81}]\n",
"stdout": "games.json: opponent, net_color, result +1/-1, area margin including komi, end reason, captured/lost stones, moves with ply/by/move and network top5 [move,probability]. boards.npy: (games,162,81), board AFTER each ply (Black1, White-1, empty0). valid.npy: (games,162), plies actually played.\n\nboards: (128, 162, 81) int8 valid: (128, 162) values: [-1 0 1]\n64 black 1 73.5 two_passes captured/lost 60 2 length 129 last [{'ply': 126, 'by': 'net', 'move': 8, 'top5': [[8, 1.0], [81, 5.439071502216786e-13], [9, 1.3688245160712218e-17], [45, 4.695150362335196e-18], [4, 4.164213319229766e-18]]}, {'ply': 127, 'by': 'strong', 'move': 81}, {'ply': 128, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999185800552368], [9, 2.5164463295368478e-05], [45, 8.63156219566008e-06], [4, 6.789841336285463e-06], [1, 6.655415745626669e-06]]}]\n65 white -1 -2.5 two_passes captured/lost 6 18 length 90 last [{'ply': 87, 'by': 'net', 'move': 71, 'top5': [[71, 0.790695071220398], [70, 0.17642655968666077], [81, 0.032230280339717865], [32, 0.0005844395491294563], [2, 4.129161243326962e-05]]}, {'ply': 88, 'by': 'strong', 'move': 81}, {'ply': 89, 'by': 'net', 'move': 81, 'top5': [[81, 0.9799486994743347], [32, 0.017769649624824524], [2, 0.0012554549612104893], [1, 0.0005930348997935653], [70, 0.0003455897676758468]]}]\n66 black -1 -22.5 two_passes captured/lost 2 23 length 99 last [{'ply': 96, 'by': 'net', 'move': 21, 'top5': [[81, 0.8825389742851257], [21, 0.04665631055831909], [43, 0.027461959049105644], [61, 0.024356691166758537], [37, 0.009419688954949379]]}, {'ply': 97, 'by': 'strong', 'move': 81}, {'ply': 98, 'by': 'net', 'move': 81, 'top5': [[81, 0.9315993785858154], [43, 0.028988569974899292], [61, 0.025710681453347206], [37, 0.009943329729139805], [36, 0.003657946363091469]]}]\n67 white -1 -4.5 two_passes captured/lost 3 14 length 85 last [{'ply': 82, 'by': 'strong', 'move': 61}, {'ply': 83, 'by': 'net', 'move': 81, 'top5': [[81, 0.9940990209579468], [52, 0.00410346919670701], [53, 0.001719163148663938], [3, 2.5269348043366335e-05], [9, 1.660317684581969e-05]]}, {'ply': 84, 'by': 'strong', 'move': 81}]\n68 black -1 -20.5 two_passes captured/lost 7 21 length 104 last [{'ply': 101, 'by': 'strong', 'move': 60}, {'ply': 102, 'by': 'net', 'move': 81, 'top5': [[81, 0.9049596190452576], [42, 0.05029425770044327], [51, 0.04243157431483269], [10, 0.0021337631624192], [0, 0.00017340814520139247]]}, {'ply': 103, 'by': 'strong', 'move': 81}]\n69 white -1 -2.5 two_passes captured/lost 5 18 length 96 last [{'ply': 93, 'by': 'net', 'move': 62, 'top5': [[62, 0.9343498349189758], [81, 0.06535577774047852], [0, 0.00022760209685657173], [9, 6.520908937091008e-05], [6, 4.482532744987111e-07]]}, {'ply': 94, 'by': 'strong', 'move': 81}, {'ply': 95, 'by': 'net', 'move': 81, 'top5': [[81, 0.9955177903175354], [0, 0.0034668997395783663], [9, 0.0009932833490893245], [6, 6.8279246079328004e-06], [26, 6.8279246079328004e-06]]}]\n70 black 1 73.5 two_passes captured/lost 59 2 length 123 last [{'ply': 120, 'by': 'net', 'move': 60, 'top5': [[60, 0.9999979734420776], [81, 1.9847861949529033e-06], [0, 1.0365014402324846e-10], [4, 6.675481695195273e-11], [2, 6.609045255512314e-11]]}, {'ply': 121, 'by': 'strong', 'move': 81}, {'ply': 122, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997805953025818], [0, 5.2210856665624306e-05], [4, 3.362586721777916e-05], [2, 3.329121682327241e-05], [18, 3.329121682327241e-05]]}]\n71 white 1 88.5 two_passes captured/lost 54 0 length 118 last [{'ply': 115, 'by': 'net', 'move': 64, 'top5': [[64, 0.9999833106994629], [81, 1.6701518688932993e-05], [57, 5.5326815129319584e-08], [72, 2.040622115728752e-09], [8, 9.932761280140312e-10]]}, {'ply': 116, 'by': 'strong', 'move': 81}, {'ply': 117, 'by': 'net', 'move': 81, 'top5': [[81, 0.999828577041626], [8, 5.946201417827979e-05], [72, 3.9462138374801725e-05], [71, 1.669887024036143e-05], [79, 1.481052822782658e-05]]}]\n72 black 1 73.5 two_passes captured/lost 61 7 length 131 last [{'ply': 128, 'by': 'net', 'move': 19, 'top5': [[19, 0.999993085861206], [81, 6.85860641169711e-06], [72, 6.860947920905858e-10], [35, 2.627010553535314e-10], [76, 2.627010553535314e-10]]}, {'ply': 129, 'by': 'strong', 'move': 81}, {'ply': 130, 'by': 'net', 'move': 81, 'top5': [[81, 0.9996083378791809], [72, 9.999495523516089e-05], [35, 3.8287391362246126e-05], [76, 3.8287391362246126e-05], [3, 3.7906342186033726e-05]]}]\n73 white -1 -4.5 two_passes captured/lost 9 23 length 99 last [{'ply': 96, 'by': 'strong', 'move': 58}, {'ply': 97, 'by': 'net', 'move': 81, 'top5': [[81, 0.9545677900314331], [51, 0.01646541990339756], [30, 0.011956262402236462], [12, 0.009691640734672546], [55, 0.0042684744112193584]]}, {'ply': 98, 'by': 'strong', 'move': 81}]\n74 black -1 -7.5 two_passes captured/lost 10 15 length 94 last [{'ply': 91, 'by': 'strong', 'move': 25}, {'ply': 92, 'by': 'net', 'move': 81, 'top5': [[81, 0.9933957457542419], [48, 0.006303618662059307], [0, 0.00019035425793845206], [72, 5.790967043139972e-05], [36, 3.8049434806453064e-05]]}, {'ply': 93, 'by': 'strong', 'move': 81}]\n75 white 1 88.5 two_passes captured/lost 63 3 length 130 last [{'ply': 127, 'by': 'net', 'move': 70, 'top5': [[70, 0.9999450445175171], [81, 5.489686009241268e-05], [8, 3.2648372894072963e-09], [75, 2.789336261965758e-10], [73, 2.7340918418161664e-10]]}, {'ply': 128, 'by': 'strong', 'move': 81}, {'ply': 129, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999041557312012], [8, 5.9466507082106546e-05], [75, 5.080561550130369e-06], [73, 4.9799382395576686e-06], [9, 4.461196112970356e-06]]}]\n76 black -1 -5.5 two_passes captured/lost 5 7 length 82 last [{'ply': 79, 'by': 'strong', 'move': 52}, {'ply': 80, 'by': 'net', 'move': 81, 'top5': [[81, 0.9725267291069031], [32, 0.02738211862742901], [0, 5.726301606046036e-05], [22, 1.8683713278733194e-05], [4, 7.3717824307095725e-06]]}, {'ply': 81, 'by': 'strong', 'move': 81}]\n77 white 1 88.5 two_passes captured/lost 57 0 length 118 last [{'ply': 115, 'by': 'net', 'move': 48, 'top5': [[48, 0.9999967813491821], [81, 3.239806574129034e-06], [8, 3.6908401335189467e-10], [72, 3.6908401335189467e-10], [27, 8.235377657594967e-11]]}, {'ply': 116, 'by': 'strong', 'move': 81}, {'ply': 117, 'by': 'net', 'move': 81, 'top5': [[81, 0.9996875524520874], [8, 0.00011388602433726192], [72, 0.00011388602433726192], [27, 2.5411403839825653e-05], [1, 1.6696514649083838e-05]]}]\n78 black -1 -6.5 two_passes captured/lost 4 6 length 86 last [{'ply': 83, 'by': 'strong', 'move': 54}, {'ply': 84, 'by': 'net', 'move': 81, 'top5': [[81, 0.9937422871589661], [25, 0.006180975120514631], [8, 3.409785495023243e-05], [35, 1.744819564919453e-05], [5, 9.292721188103314e-06]]}, {'ply': 85, 'by': 'strong', 'move': 81}]\n79 white -1 6.5 repetition captured/lost 4 8 length 84 last [{'ply': 81, 'by': 'net', 'move': 5, 'top5': [[5, 1.0], [19, 4.8473686869998645e-11], [7, 2.9108396248922475e-11], [81, 1.0736045299303276e-12], [29, 3.842764187368328e-14]]}, {'ply': 82, 'by': 'strong', 'move': 7}, {'ply': 83, 'by': 'net', 'move': 6, 'top5': [[6, 0.9999997615814209], [19, 2.686100515347789e-07], [81, 5.949226888901649e-09], [29, 2.1294130347904172e-10], [72, 1.9317570112975524e-11]]}]\n80 black -1 47.5 repetition captured/lost 51 9 length 127 last [{'ply': 124, 'by': 'net', 'move': 77, 'top5': [[77, 0.9999984502792358], [64, 1.6088388292700984e-06], [45, 3.948223525895855e-09], [38, 4.691975141746241e-10], [36, 2.1724366749964474e-10]]}, {'ply': 125, 'by': 'strong', 'move': 79}, {'ply': 126, 'by': 'net', 'move': 78, 'top5': [[78, 0.9913105964660645], [64, 0.008662731386721134], [45, 2.125906030414626e-05], [38, 2.5263761926908046e-06], [36, 1.1697402442223392e-06]]}]\n81 white 1 88.5 two_passes captured/lost 60 4 length 124 last [{'ply': 121, 'by': 'net', 'move': 64, 'top5': [[64, 1.0], [81, 2.4860231206957906e-08], [47, 7.377551347609312e-11], [0, 1.6670006304161933e-12], [24, 1.247364191103717e-12]]}, {'ply': 122, 'by': 'strong', 'move': 81}, {'ply': 123, 'by': 'net', 'move': 81, 'top5': [[81, 0.999729573726654], [0, 6.70367808197625e-05], [24, 5.016151408199221e-05], [18, 2.2765523681300692e-05], [6, 2.2765349058317952e-05]]}]\n82 black -1 -9.5 two_passes captured/lost 2 7 length 80 last [{'ply': 77, 'by': 'strong', 'move': 68}, {'ply': 78, 'by': 'net', 'move': 81, 'top5': [[81, 0.974189817905426], [30, 0.011841407977044582], [76, 0.0053207119926810265], [64, 0.0033926197793334723], [75, 0.002979052485898137]]}, {'ply': 79, 'by': 'strong', 'move': 81}]\n83 white -1 -1.5 two_passes captured/lost 4 14 length 89 last [{'ply': 86, 'by': 'strong', 'move': 51}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9982441663742065], [30, 0.0017263316549360752], [27, 2.2731697754352354e-05], [9, 3.720116865224554e-06], [2, 1.9615756627899827e-06]]}, {'ply': 88, 'by': 'strong', 'move': 81}]\n84 black 1 73.5 two_passes captured/lost 62 7 length 129 last [{'ply': 126, 'by': 'net', 'move': 30, 'top5': [[30, 0.999995231628418], [81, 4.785094461112749e-06], [41, 1.2720986930503386e-08], [0, 3.727907427197863e-10], [80, 2.498887208268741e-10]]}, {'ply': 127, 'by': 'strong', 'move': 81}, {'ply': 128, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997435212135315], [0, 7.788668153807521e-05], [80, 5.220892126089893e-05], [53, 3.012206798302941e-05], [63, 2.209282320109196e-05]]}]\n85 white -1 24.5 repetition captured/lost 11 4 length 74 last [{'ply': 71, 'by': 'net', 'move': 53, 'top5': [[53, 1.0], [6, 1.2011325267735629e-09], [75, 1.003269911592497e-09], [5, 9.169160430921863e-10], [74, 5.788346468804662e-10]]}, {'ply': 72, 'by': 'strong', 'move': 71}, {'ply': 73, 'by': 'net', 'move': 62, 'top5': [[62, 0.9999678134918213], [6, 6.997012405918213e-06], [75, 5.8443938542041e-06], [5, 5.341353244148195e-06], [74, 3.371911816429929e-06]]}]\n86 black -1 -10.5 repetition captured/lost 6 14 length 87 last [{'ply': 84, 'by': 'net', 'move': 78, 'top5': [[78, 1.0], [81, 4.441631090701392e-12], [55, 2.0009224854268537e-13], [65, 1.0341757289943077e-13], [0, 2.3075579668645554e-14]]}, {'ply': 85, 'by': 'strong', 'move': 77}, {'ply': 86, 'by': 'net', 'move': 69, 'top5': [[69, 0.9994966983795166], [81, 0.00045714687439613044], [55, 2.059413236565888e-05], [65, 9.44048588280566e-06], [68, 8.125426575134043e-06]]}]\n87 white 1 0.5 two_passes captured/lost 2 11 length 89 last [{'ply': 86, 'by': 'strong', 'move': 9}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999927282333374], [63, 5.030444299336523e-06], [55, 1.4557231224898715e-06], [65, 4.340930672697141e-07], [48, 3.0897334113433317e-07]]}, {'ply': 88, 'by': 'strong', 'move': 81}]\n88 black -1 1.5 repetition captured/lost 8 9 length 87 last [{'ply': 84, 'by': 'net', 'move': 18, 'top5': [[18, 1.0], [6, 3.273483151211565e-10], [5, 1.5462839342283985e-10], [0, 1.228570439826271e-10], [3, 4.172194534302065e-11]]}, {'ply': 85, 'by': 'strong', 'move': 0}, {'ply': 86, 'by': 'net', 'move': 9, 'top5': [[9, 0.9986767172813416], [3, 0.0013184096897020936], [6, 3.077704377574264e-06], [5, 1.4538045434164815e-06], [7, 3.211592627394566e-07]]}]\n89 white -1 -4.5 two_passes captured/lost 3 16 length 92 last [{'ply': 89, 'by': 'net', 'move': 47, 'top5': [[47, 0.9999997615814209], [29, 2.580794387085916e-07], [81, 2.2610960326296947e-10], [69, 6.3663232671706815e-12], [59, 3.2904304281267116e-12]]}, {'ply': 90, 'by': 'strong', 'move': 81}, {'ply': 91, 'by': 'net', 'move': 81, 'top5': [[81, 0.9570878744125366], [69, 0.02694767154753208], [59, 0.013927889056503773], [2, 0.0010875178268179297], [1, 0.00084695965051651]]}]\n90 black -1 -13.5 two_passes captured/lost 5 19 length 98 last [{'ply': 95, 'by': 'strong', 'move': 73}, {'ply': 96, 'by': 'net', 'move': 81, 'top5': [[81, 0.9891046285629272], [33, 0.010878604836761951], [35, 8.453302143607289e-06], [78, 3.68604969480657e-06], [25, 2.326927415197133e-06]]}, {'ply': 97, 'by': 'strong', 'move': 81}]\n91 white 1 6.5 two_passes captured/lost 20 20 length 117 last [{'ply': 114, 'by': 'strong', 'move': 61}, {'ply': 115, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999452829360962], [9, 1.670082019700203e-05], [1, 1.6534608221263625e-05], [3, 5.080770733911777e-06], [19, 3.5803093396680197e-06]]}, {'ply': 116, 'by': 'strong', 'move': 81}]\n92 black 1 73.5 two_passes captured/lost 61 7 length 129 last [{'ply': 126, 'by': 'net', 'move': 40, 'top5': [[40, 0.9999898672103882], [81, 9.929436600941699e-06], [21, 2.939044634331367e-07], [80, 9.93282567307574e-10], [8, 3.84144327458813e-10]]}, {'ply': 127, 'by': 'strong', 'move': 81}, {'ply': 128, 'by': 'net', 'move': 81, 'top5': [[81, 0.9996169805526733], [80, 9.999582107411698e-05], [8, 3.8672606024192646e-05], [45, 3.828772605629638e-05], [3, 3.790667324210517e-05]]}]\n93 white 1 88.5 two_passes captured/lost 58 0 length 124 last [{'ply': 121, 'by': 'net', 'move': 34, 'top5': [[34, 0.9999545812606812], [81, 4.539778092294e-05], [23, 3.563109984838775e-08], [80, 1.773968083540467e-09], [58, 5.13355524756065e-10]]}, {'ply': 122, 'by': 'strong', 'move': 81}, {'ply': 123, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999127388000488], [80, 3.907268910552375e-05], [58, 1.1306957276246976e-05], [76, 5.671371582138818e-06], [17, 5.080605205876054e-06]]}]\n94 black -1 -4.5 two_passes captured/lost 6 12 length 92 last [{'ply': 89, 'by': 'strong', 'move': 4}, {'ply': 90, 'by': 'net', 'move': 81, 'top5': [[81, 0.9719324707984924], [60, 0.020682498812675476], [68, 0.0053617036901414394], [65, 0.0019528298871591687], [72, 5.025180507800542e-05]]}, {'ply': 91, 'by': 'strong', 'move': 81}]\n95 white -1 -5.5 two_passes captured/lost 6 21 length 103 last [{'ply': 100, 'by': 'strong', 'move': 2}, {'ply': 101, 'by': 'net', 'move': 81, 'top5': [[81, 0.986890435218811], [15, 0.008976013399660587], [10, 0.0017066968139261007], [60, 0.0013696546666324139], [1, 0.0009846753673627973]]}, {'ply': 102, 'by': 'strong', 'move': 81}]\n96 black -1 -14.5 two_passes captured/lost 10 22 length 106 last [{'ply': 103, 'by': 'strong', 'move': 10}, {'ply': 104, 'by': 'net', 'move': 81, 'top5': [[81, 0.9788761138916016], [8, 0.005085548851639032], [49, 0.004886137321591377], [37, 0.004510464612394571], [53, 0.0032426989637315273]]}, {'ply': 105, 'by': 'strong', 'move': 81}]\n97 white 1 88.5 two_passes captured/lost 53 0 length 118 last [{'ply': 115, 'by': 'net', 'move': 71, 'top5': [[71, 0.9999972581863403], [81, 2.7332755507814e-06], [8, 1.6255392865094365e-10], [36, 6.947808300905578e-11], [18, 6.16218326365825e-11]]}, {'ply': 116, 'by': 'strong', 'move': 81}, {'ply': 117, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997962117195129], [8, 5.946008604951203e-05], [80, 5.326674727257341e-05], [36, 2.541416688472964e-05], [18, 2.2540454665431753e-05]]}]\n98 black -1 -1.5 two_passes captured/lost 2 5 length 77 last [{'ply': 74, 'by': 'net', 'move': 18, 'top5': [[18, 0.9999903440475464], [0, 9.635920832806733e-06], [81, 9.427153068591876e-13], [32, 7.994550219037316e-15], [64, 2.4321246649668463e-15]]}, {'ply': 75, 'by': 'strong', 'move': 81}, {'ply': 76, 'by': 'net', 'move': 81, 'top5': [[81, 0.9874961376190186], [32, 0.008374307304620743], [64, 0.002547655487433076], [73, 0.0014698648592457175], [7, 2.4604501959402114e-05]]}]\n99 white 1 88.5 two_passes captured/lost 65 6 length 134 last [{'ply': 131, 'by': 'net', 'move': 73, 'top5': [[73, 0.9999984502792358], [81, 1.5151365460042143e-06], [0, 1.0159734858961045e-10], [80, 5.251093310176813e-11], [8, 4.43013681294957e-11]]}, {'ply': 132, 'by': 'strong', 'move': 81}, {'ply': 133, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997754693031311], [0, 6.70398585498333e-05], [72, 4.19000098190736e-05], [80, 3.464977635303512e-05], [8, 2.9232627639430575e-05]]}]\n100 black -1 -9.5 two_passes captured/lost 3 9 length 83 last [{'ply': 80, 'by': 'net', 'move': 71, 'top5': [[71, 0.5514063239097595], [62, 0.4425133764743805], [81, 0.005826805252581835], [29, 0.00018683564849197865], [59, 4.045632158522494e-05]]}, {'ply': 81, 'by': 'strong', 'move': 81}, {'ply': 82, 'by': 'net', 'move': 81, 'top5': [[81, 0.9583132863044739], [29, 0.0307281743735075], [59, 0.006653703283518553], [28, 0.002065093256533146], [9, 0.0011109024053439498]]}]\n101 white 1 88.5 two_passes captured/lost 57 1 length 118 last [{'ply': 115, 'by': 'net', 'move': 11, 'top5': [[11, 0.9994322657585144], [2, 0.000563939509447664], [81, 3.837983967969194e-06], [8, 3.8778952271556477e-10], [0, 1.4848085261309762e-10]]}, {'ply': 116, 'by': 'strong', 'move': 81}, {'ply': 117, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997736811637878], [8, 0.00010101703082909808], [0, 5.2210598369129e-05], [75, 2.5413593903067522e-05], [57, 1.0027025382441934e-05]]}]\n102 black -1 -12.5 two_passes captured/lost 10 18 length 104 last [{'ply': 101, 'by': 'strong', 'move': 73}, {'ply': 102, 'by': 'net', 'move': 81, 'top5': [[81, 0.9872137308120728], [43, 0.008206164464354515], [25, 0.004503611009567976], [35, 6.488682993222028e-05], [6, 5.599291398539208e-06]]}, {'ply': 103, 'by': 'strong', 'move': 81}]\n103 white 1 88.5 two_passes captured/lost 57 2 length 120 last [{'ply': 117, 'by': 'net', 'move': 10, 'top5': [[10, 0.9999790191650391], [81, 2.102035068674013e-05], [77, 5.343235853771944e-10], [45, 4.739048597990347e-10], [47, 3.617676991307661e-10]]}, {'ply': 118, 'by': 'strong', 'move': 81}, {'ply': 119, 'by': 'net', 'move': 81, 'top5': [[81, 0.9998648166656494], [77, 2.541591129556764e-05], [45, 2.254200262541417e-05], [47, 1.720802902127616e-05], [67, 1.4088785974308848e-05]]}]\n104 black -1 -22.5 two_passes captured/lost 11 28 length 114 last [{'ply': 111, 'by': 'strong', 'move': 2}, {'ply': 112, 'by': 'net', 'move': 81, 'top5': [[81, 0.9349849224090576], [20, 0.04383939504623413], [41, 0.010283373296260834], [16, 0.0054223062470555305], [11, 0.005368383135646582]]}, {'ply': 113, 'by': 'strong', 'move': 81}]\n105 white 1 88.5 two_passes captured/lost 65 7 length 136 last [{'ply': 133, 'by': 'net', 'move': 65, 'top5': [[65, 0.9999266862869263], [81, 7.336439011851326e-05], [53, 1.883621258969015e-09], [5, 1.6706177552450185e-09], [33, 1.2753196276804601e-09]]}, {'ply': 134, 'by': 'strong', 'move': 81}, {'ply': 135, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999009370803833], [53, 2.5672328774817288e-05], [5, 2.2769250790588558e-05], [33, 1.7381637007929385e-05], [7, 4.9799223234003875e-06]]}]\n106 black -1 -6.5 two_passes captured/lost 5 12 length 88 last [{'ply': 85, 'by': 'strong', 'move': 63}, {'ply': 86, 'by': 'net', 'move': 81, 'top5': [[81, 0.9595587849617004], [23, 0.024202920496463776], [13, 0.0056772599928081036], [50, 0.005137004889547825], [64, 0.0024755795020610094]]}, {'ply': 87, 'by': 'strong', 'move': 81}]\n107 white 1 4.5 two_passes captured/lost 4 14 length 88 last [{'ply': 85, 'by': 'net', 'move': 5, 'top5': [[5, 0.9713945984840393], [81, 0.015010133385658264], [14, 0.013180283829569817], [41, 0.00025378126883879304], [43, 0.00016020932525862008]]}, {'ply': 86, 'by': 'strong', 'move': 81}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9730942845344543], [41, 0.016452426090836525], [43, 0.010386236011981964], [35, 2.4735421902732924e-05], [33, 2.150395630451385e-05]]}]\n108 black -1 -12.5 two_passes captured/lost 1 6 length 76 last [{'ply': 73, 'by': 'strong', 'move': 75}, {'ply': 74, 'by': 'net', 'move': 81, 'top5': [[81, 0.9805928468704224], [61, 0.01330519188195467], [72, 0.004518409259617329], [73, 0.0014595894608646631], [8, 3.793661016970873e-05]]}, {'ply': 75, 'by': 'strong', 'move': 81}]\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.3120530559681356,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-494ad8f99e2c40e0a908184c8f0cc86c",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
"-i",
"HOME=/tmp",
"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
"MKL_NUM_THREADS=8",
"CUDA_VISIBLE_DEVICES=",
"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 4 of at most 120:
```
games.json: opponent, net_color, result +1/-1, area margin including komi, end reason, captured/lost stones, moves with ply/by/move and network top5 [move,probability]. boards.npy: (games,162,81), board AFTER each ply (Black1, White-1, empty0). valid.npy: (games,162), plies actually played.
boards: (128, 162, 81) int8 valid: (128, 162) values: [-1 0 1]
64 black 1 73.5 two_passes captured/lost 60 2 length 129 last [{'ply': 126, 'by': 'net', 'move': 8, 'top5': [[8, 1.0], [81, 5.439071502216786e-13], [9, 1.3688245160712218e-17], [45, 4.695150362335196e-18], [4, 4.164213319229766e-18]]}, {'ply': 127, 'by': 'strong', 'move': 81}, {'ply': 128, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999185800552368], [9, 2.5164463295368478e-05], [45, 8.63156219566008e-06], [4, 6.789841336285463e-06], [1, 6.655415745626669e-06]]}]
65 white -1 -2.5 two_passes captured/lost 6 18 length 90 last [{'ply': 87, 'by': 'net', 'move': 71, 'top5': [[71, 0.790695071220398], [70, 0.17642655968666077], [81, 0.032230280339717865], [32, 0.0005844395491294563], [2, 4.129161243326962e-05]]}, {'ply': 88, 'by': 'strong', 'move': 81}, {'ply': 89, 'by': 'net', 'move': 81, 'top5': [[81, 0.9799486994743347], [32, 0.017769649624824524], [2, 0.0012554549612104893], [1, 0.0005930348997935653], [70, 0.0003455897676758468]]}]
66 black -1 -22.5 two_passes captured/lost 2 23 length 99 last [{'ply': 96, 'by': 'net', 'move': 21, 'top5': [[81, 0.8825389742851257], [21, 0.04665631055831909], [43, 0.027461959049105644], [61, 0.024356691166758537], [37, 0.009419688954949379]]}, {'ply': 97, 'by': 'strong', 'move': 81}, {'ply': 98, 'by': 'net', 'move': 81, 'top5': [[81, 0.9315993785858154], [43, 0.028988569974899292], [61, 0.025710681453347206], [37, 0.009943329729139805], [36, 0.003657946363091469]]}]
67 white -1 -4.5 two_passes captured/lost 3 14 length 85 last [{'ply': 82, 'by': 'strong', 'move': 61}, {'ply': 83, 'by': 'net', 'move': 81, 'top5': [[81, 0.9940990209579468], [52, 0.00410346919670701], [53, 0.001719163148663938], [3, 2.5269348043366335e-05], [9, 1.660317684581969e-05]]}, {'ply': 84, 'by': 'strong', 'move': 81}]
68 black -1 -20.5 two_passes captured/lost 7 21 length 104 last [{'ply': 101, 'by': 'strong', 'move': 60}, {'ply': 102, 'by': 'net', 'move': 81, 'top5': [[81, 0.9049596190452576], [42, 0.05029425770044327], [51, 0.04243157431483269], [10, 0.0021337631624192], [0, 0.00017340814520139247]]}, {'ply': 103, 'by': 'strong', 'move': 81}]
69 white -1 -2.5 two_passes captured/lost 5 18 length 96 last [{'ply': 93, 'by': 'net', 'move': 62, 'top5': [[62, 0.9343498349189758], [81, 0.06535577774047852], [0, 0.00022760209685657173], [9, 6.520908937091008e-05], [6, 4.482532744987111e-07]]}, {'ply': 94, 'by': 'strong', 'move': 81}, {'ply': 95, 'by': 'net', 'move': 81, 'top5': [[81, 0.9955177903175354], [0, 0.0034668997395783663], [9, 0.0009932833490893245], [6, 6.8279246079328004e-06], [26, 6.8279246079328004e-06]]}]
70 black 1 73.5 two_passes captured/lost 59 2 length 123 last [{'ply': 120, 'by': 'net', 'move': 60, 'top5': [[60, 0.9999979734420776], [81, 1.9847861949529033e-06], [0, 1.0365014402324846e-10], [4, 6.675481695195273e-11], [2, 6.609045255512314e-11]]}, {'ply': 121, 'by': 'strong', 'move': 81}, {'ply': 122, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997805953025818], [0, 5.2210856665624306e-05], [4, 3.362586721777916e-05], [2, 3.329121682327241e-05], [18, 3.329121682327241e-05]]}]
71 white 1 88.5 two_passes captured/lost 54 0 length 118 last [{'ply': 115, 'by': 'net', 'move': 64, 'top5': [[64, 0.9999833106994629], [81, 1.6701518688932993e-05], [57, 5.5326815129319584e-08], [72, 2.040622115728752e-09], [8, 9.932761280140312e-10]]}, {'ply': 116, 'by': 'strong', 'move': 81}, {'ply': 117, 'by': 'net', 'move': 81, 'top5': [[81, 0.999828577041626], [8, 5.946201417827979e-05], [72, 3.9462138374801725e-05], [71, 1.669887024036143e-05], [79, 1.481052822782658e-05]]}]
72 black 1 73.5 two_passes captured/lost 61 7 length 131 last [{'ply': 128, 'by': 'net', 'move': 19, 'top5': [[19, 0.999993085861206], [81, 6.85860641169711e-06], [72, 6.860947920905858e-10], [35, 2.627010553535314e-10], [76, 2.627010553535314e-10]]}, {'ply': 129, 'by': 'strong', 'move': 81}, {'ply': 130, 'by': 'net', 'move': 81, 'top5': [[81, 0.9996083378791809], [72, 9.999495523516089e-05], [35, 3.8287391362246126e-05], [76, 3.8287391362246126e-05], [3, 3.7906342186033726e-05]]}]
73 white -1 -4.5 two_passes captured/lost 9 23 length 99 last [{'ply': 96, 'by': 'strong', 'move': 58}, {'ply': 97, 'by': 'net', 'move': 81, 'top5': [[81, 0.9545677900314331], [51, 0.01646541990339756], [30, 0.011956262402236462], [12, 0.009691640734672546], [55, 0.0042684744112193584]]}, {'ply': 98, 'by': 'strong', 'move': 81}]
74 black -1 -7.5 two_passes captured/lost 10 15 length 94 last [{'ply': 91, 'by': 'strong', 'move': 25}, {'ply': 92, 'by': 'net', 'move': 81, 'top5': [[81, 0.9933957457542419], [48, 0.006303618662059307], [0, 0.00019035425793845206], [72, 5.790967043139972e-05], [36, 3.8049434806453064e-05]]}, {'ply': 93, 'by': 'strong', 'move': 81}]
75 white 1 88.5 two_passes captured/lost 63 3 length 130 last [{'ply': 127, 'by': 'net', 'move': 70, 'top5': [[70, 0.9999450445175171], [81, 5.489686009241268e-05], [8, 3.2648372894072963e-09], [75, 2.789336261965758e-10], [73, 2.7340918418161664e-10]]}, {'ply': 128, 'by': 'strong', 'move': 81}, {'ply': 129, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999041557312012], [8, 5.9466507082106546e-05], [75, 5.080561550130369e-06], [73, 4.9799382395576686e-06], [9, 4.461196112970356e-06]]}]
76 black -1 -5.5 two_passes captured/lost 5 7 length 82 last [{'ply': 79, 'by': 'strong', 'move': 52}, {'ply': 80, 'by': 'net', 'move': 81, 'top5': [[81, 0.9725267291069031], [32, 0.02738211862742901], [0, 5.726301606046036e-05], [22, 1.8683713278733194e-05], [4, 7.3717824307095725e-06]]}, {'ply': 81, 'by': 'strong', 'move': 81}]
77 white 1 88.5 two_passes captured/lost 57 0 length 118 last [{'ply': 115, 'by': 'net', 'move': 48, 'top5': [[48, 0.9999967813491821], [81, 3.239806574129034e-06], [8, 3.6908401335189467e-10], [72, 3.6908401335189467e-10], [27, 8.235377657594967e-11]]}, {'ply': 116, 'by': 'strong', 'move': 81}, {'ply': 117, 'by': 'net', 'move': 81, 'top5': [[81, 0.9996875524520874], [8, 0.00011388602433726192], [72, 0.00011388602433726192], [27, 2.5411403839825653e-05], [1, 1.6696514649083838e-05]]}]
78 black -1 -6.5 two_passes captured/lost 4 6 length 86 last [{'ply': 83, 'by': 'strong', 'move': 54}, {'ply': 84, 'by': 'net', 'move': 81, 'top5': [[81, 0.9937422871589661], [25, 0.006180975120514631], [8, 3.409785495023243e-05], [35, 1.744819564919453e-05], [5, 9.292721188103314e-06]]}, {'ply': 85, 'by': 'strong', 'move': 81}]
79 white -1 6.5 repetition captured/lost 4 8 length 84 last [{'ply': 81, 'by': 'net', 'move': 5, 'top5': [[5, 1.0], [19, 4.8473686869998645e-11], [7, 2.9108396248922475e-11], [81, 1.0736045299303276e-12], [29, 3.842764187368328e-14]]}, {'ply': 82, 'by': 'strong', 'move': 7}, {'ply': 83, 'by': 'net', 'move': 6, 'top5': [[6, 0.9999997615814209], [19, 2.686100515347789e-07], [81, 5.949226888901649e-09], [29, 2.1294130347904172e-10], [72, 1.9317570112975524e-11]]}]
80 black -1 47.5 repetition captured/lost 51 9 length 127 last [{'ply': 124, 'by': 'net', 'move': 77, 'top5': [[77, 0.9999984502792358], [64, 1.6088388292700984e-06], [45, 3.948223525895855e-09], [38, 4.691975141746241e-10], [36, 2.1724366749964474e-10]]}, {'ply': 125, 'by': 'strong', 'move': 79}, {'ply': 126, 'by': 'net', 'move': 78, 'top5': [[78, 0.9913105964660645], [64, 0.008662731386721134], [45, 2.125906030414626e-05], [38, 2.5263761926908046e-06], [36, 1.1697402442223392e-06]]}]
81 white 1 88.5 two_passes captured/lost 60 4 length 124 last [{'ply': 121, 'by': 'net', 'move': 64, 'top5': [[64, 1.0], [81, 2.4860231206957906e-08], [47, 7.377551347609312e-11], [0, 1.6670006304161933e-12], [24, 1.247364191103717e-12]]}, {'ply': 122, 'by': 'strong', 'move': 81}, {'ply': 123, 'by': 'net', 'move': 81, 'top5': [[81, 0.999729573726654], [0, 6.70367808197625e-05], [24, 5.016151408199221e-05], [18, 2.2765523681300692e-05], [6, 2.2765349058317952e-05]]}]
82 black -1 -9.5 two_passes captured/lost 2 7 length 80 last [{'ply': 77, 'by': 'strong', 'move': 68}, {'ply': 78, 'by': 'net', 'move': 81, 'top5': [[81, 0.974189817905426], [30, 0.011841407977044582], [76, 0.0053207119926810265], [64, 0.0033926197793334723], [75, 0.002979052485898137]]}, {'ply': 79, 'by': 'strong', 'move': 81}]
83 white -1 -1.5 two_passes captured/lost 4 14 length 89 last [{'ply': 86, 'by': 'strong', 'move': 51}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9982441663742065], [30, 0.0017263316549360752], [27, 2.2731697754352354e-05], [9, 3.720116865224554e-06], [2, 1.9615756627899827e-06]]}, {'ply': 88, 'by': 'strong', 'move': 81}]
84 black 1 73.5 two_passes captured/lost 62 7 length 129 last [{'ply': 126, 'by': 'net', 'move': 30, 'top5': [[30, 0.999995231628418], [81, 4.785094461112749e-06], [41, 1.2720986930503386e-08], [0, 3.727907427197863e-10], [80, 2.498887208268741e-10]]}, {'ply': 127, 'by': 'strong', 'move': 81}, {'ply': 128, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997435212135315], [0, 7.788668153807521e-05], [80, 5.220892126089893e-05], [53, 3.012206798302941e-05], [63, 2.209282320109196e-05]]}]
85 white -1 24.5 repetition captured/lost 11 4 length 74 last [{'ply': 71, 'by': 'net', 'move': 53, 'top5': [[53, 1.0], [6, 1.2011325267735629e-09], [75, 1.003269911592497e-09], [5, 9.169160430921863e-10], [74, 5.788346468804662e-10]]}, {'ply': 72, 'by': 'strong', 'move': 71}, {'ply': 73, 'by': 'net', 'move': 62, 'top5': [[62, 0.9999678134918213], [6, 6.997012405918213e-06], [75, 5.8443938542041e-06], [5, 5.341353244148195e-06], [74, 3.371911816429929e-06]]}]
86 black -1 -10.5 repetition captured/lost 6 14 length 87 last [{'ply': 84, 'by': 'net', 'move': 78, 'top5': [[78, 1.0], [81, 4.441631090701392e-12], [55, 2.0009224854268537e-13], [65, 1.0341757289943077e-13], [0, 2.3075579668645554e-14]]}, {'ply': 85, 'by': 'strong', 'move': 77}, {'ply': 86, 'by': 'net', 'move': 69, 'top5': [[69, 0.9994966983795166], [81, 0.00045714687439613044], [55, 2.059413236565888e-05], [65, 9.44048588280566e-06], [68, 8.125426575134043e-06]]}]
87 white 1 0.5 two_passes captured/lost 2 11 length 89 last [{'ply': 86, 'by': 'strong', 'move': 9}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999927282333374], [63, 5.030444299336523e-06], [55, 1.4557231224898715e-06], [65, 4.340930672697141e-07], [48, 3.0897334113433317e-07]]}, {'ply': 88, 'by': 'strong', 'move': 81}]
88 black -1 1.5 repetition captured/lost 8 9 length 87 last [{'ply': 84, 'by': 'net', 'move': 18, 'top5': [[18, 1.0], [6, 3.273483151211565e-10], [5, 1.5462839342283985e-10], [0, 1.228570439826271e-10], [3, 4.172194534302065e-11]]}, {'ply': 85, 'by': 'strong', 'move': 0}, {'ply': 86, 'by': 'net', 'move': 9, 'top5': [[9, 0.9986767172813416], [3, 0.0013184096897020936], [6, 3.077704377574264e-06], [5, 1.4538045434164815e-06], [7, 3.211592627394566e-07]]}]
89 white -1 -4.5 two_passes captured/lost 3 16 length 92 last [{'ply': 89, 'by': 'net', 'move': 47, 'top5': [[47, 0.9999997615814209], [29, 2.580794387085916e-07], [81, 2.2610960326296947e-10], [69, 6.3663232671706815e-12], [59, 3.2904304281267116e-12]]}, {'ply': 90, 'by': 'strong', 'move': 81}, {'ply': 91, 'by': 'net', 'move': 81, 'top5': [[81, 0.9570878744125366], [69, 0.02694767154753208], [59, 0.013927889056503773], [2, 0.0010875178268179297], [1, 0.00084695965051651]]}]
90 black -1 -13.5 two_passes captured/lost 5 19 length 98 last [{'ply': 95, 'by': 'strong', 'move': 73}, {'ply': 96, 'by': 'net', 'move': 81, 'top5': [[81, 0.9891046285629272], [33, 0.010878604836761951], [35, 8.453302143607289e-06], [78, 3.68604969480657e-06], [25, 2.326927415197133e-06]]}, {'ply': 97, 'by': 'strong', 'move': 81}]
91 white 1 6.5 two_passes captured/lost 20 20 length 117 last [{'ply': 114, 'by': 'strong', 'move': 61}, {'ply': 115, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999452829360962], [9, 1.670082019700203e-05], [1, 1.6534608221263625e-05], [3, 5.080770733911777e-06], [19, 3.5803093396680197e-06]]}, {'ply': 116, 'by': 'strong', 'move': 81}]
92 black 1 73.5 two_passes captured/lost 61 7 length 129 last [{'ply': 126, 'by': 'net', 'move': 40, 'top5': [[40, 0.9999898672103882], [81, 9.929436600941699e-06], [21, 2.939044634331367e-07], [80, 9.93282567307574e-10], [8, 3.84144327458813e-10]]}, {'ply': 127, 'by': 'strong', 'move': 81}, {'ply': 128, 'by': 'net', 'move': 81, 'top5': [[81, 0.9996169805526733], [80, 9.999582107411698e-05], [8, 3.8672606024192646e-05], [45, 3.828772605629638e-05], [3, 3.790667324210517e-05]]}]
93 white 1 88.5 two_passes captured/lost 58 0 length 124 last [{'ply': 121, 'by': 'net', 'move': 34, 'top5': [[34, 0.9999545812606812], [81, 4.539778092294e-05], [23, 3.563109984838775e-08], [80, 1.773968083540467e-09], [58, 5.13355524756065e-10]]}, {'ply': 122, 'by': 'strong', 'move': 81}, {'ply': 123, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999127388000488], [80, 3.907268910552375e-05], [58, 1.1306957276246976e-05], [76, 5.671371582138818e-06], [17, 5.080605205876054e-06]]}]
94 black -1 -4.5 two_passes captured/lost 6 12 length 92 last [{'ply': 89, 'by': 'strong', 'move': 4}, {'ply': 90, 'by': 'net', 'move': 81, 'top5': [[81, 0.9719324707984924], [60, 0.020682498812675476], [68, 0.0053617036901414394], [65, 0.0019528298871591687], [72, 5.025180507800542e-05]]}, {'ply': 91, 'by': 'strong', 'move': 81}]
95 white -1 -5.5 two_passes captured/lost 6 21 length 103 last [{'ply': 100, 'by': 'strong', 'move': 2}, {'ply': 101, 'by': 'net', 'move': 81, 'top5': [[81, 0.986890435218811], [15, 0.008976013399660587], [10, 0.0017066968139261007], [60, 0.0013696546666324139], [1, 0.0009846753673627973]]}, {'ply': 102, 'by': 'strong', 'move': 81}]
96 black -1 -14.5 two_passes captured/lost 10 22 length 106 last [{'ply': 103, 'by': 'strong', 'move': 10}, {'ply': 104, 'by': 'net', 'move': 81, 'top5': [[81, 0.9788761138916016], [8, 0.005085548851639032], [49, 0.004886137321591377], [37, 0.004510464612394571], [53, 0.0032426989637315273]]}, {'ply': 105, 'by': 'strong', 'move': 81}]
97 white 1 88.5 two_passes captured/lost 53 0 length 118 last [{'ply': 115, 'by': 'net', 'move': 71, 'top5': [[71, 0.9999972581863403], [81, 2.7332755507814e-06], [8, 1.6255392865094365e-10], [36, 6.947808300905578e-11], [18, 6.16218326365825e-11]]}, {'ply': 116, 'by': 'strong', 'move': 81}, {'ply': 117, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997962117195129], [8, 5.946008604951203e-05], [80, 5.326674727257341e-05], [36, 2.541416688472964e-05], [18, 2.2540454665431753e-05]]}]
98 black -1 -1.5 two_passes captured/lost 2 5 length 77 last [{'ply': 74, 'by': 'net', 'move': 18, 'top5': [[18, 0.9999903440475464], [0, 9.635920832806733e-06], [81, 9.427153068591876e-13], [32, 7.994550219037316e-15], [64, 2.4321246649668463e-15]]}, {'ply': 75, 'by': 'strong', 'move': 81}, {'ply': 76, 'by': 'net', 'move': 81, 'top5': [[81, 0.9874961376190186], [32, 0.008374307304620743], [64, 0.002547655487433076], [73, 0.0014698648592457175], [7, 2.4604501959402114e-05]]}]
99 white 1 88.5 two_passes captured/lost 65 6 length 134 last [{'ply': 131, 'by': 'net', 'move': 73, 'top5': [[73, 0.9999984502792358], [81, 1.5151365460042143e-06], [0, 1.0159734858961045e-10], [80, 5.251093310176813e-11], [8, 4.43013681294957e-11]]}, {'ply': 132, 'by': 'strong', 'move': 81}, {'ply': 133, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997754693031311], [0, 6.70398585498333e-05], [72, 4.19000098190736e-05], [80, 3.464977635303512e-05], [8, 2.9232627639430575e-05]]}]
100 black -1 -9.5 two_passes captured/lost 3 9 length 83 last [{'ply': 80, 'by': 'net', 'move': 71, 'top5': [[71, 0.5514063239097595], [62, 0.4425133764743805], [81, 0.005826805252581835], [29, 0.00018683564849197865], [59, 4.045632158522494e-05]]}, {'ply': 81, 'by': 'strong', 'move': 81}, {'ply': 82, 'by': 'net', 'move': 81, 'top5': [[81, 0.9583132863044739], [29, 0.0307281743735075], [59, 0.006653703283518553], [28, 0.002065093256533146], [9, 0.0011109024053439498]]}]
101 white 1 88.5 two_passes captured/lost 57 1 length 118 last [{'ply': 115, 'by': 'net', 'move': 11, 'top5': [[11, 0.9994322657585144], [2, 0.000563939509447664], [81, 3.837983967969194e-06], [8, 3.8778952271556477e-10], [0, 1.4848085261309762e-10]]}, {'ply': 116, 'by': 'strong', 'move': 81}, {'ply': 117, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997736811637878], [8, 0.00010101703082909808], [0, 5.2210598369129e-05], [75, 2.5413593903067522e-05], [57, 1.0027025382441934e-05]]}]
102 black -1 -12.5 two_passes captured/lost 10 18 length 104 last [{'ply': 101, 'by': 'strong', 'move': 73}, {'ply': 102, 'by': 'net', 'move': 81, 'top5': [[81, 0.9872137308120728], [43, 0.008206164464354515], [25, 0.004503611009567976], [35, 6.488682993222028e-05], [6, 5.599291398539208e-06]]}, {'ply': 103, 'by': 'strong', 'move': 81}]
103 white 1 88.5 two_passes captured/lost 57 2 length 120 last [{'ply': 117, 'by': 'net', 'move': 10, 'top5': [[10, 0.9999790191650391], [81, 2.102035068674013e-05], [77, 5.343235853771944e-10], [45, 4.739048597990347e-10], [47, 3.617676991307661e-10]]}, {'ply': 118, 'by': 'strong', 'move': 81}, {'ply': 119, 'by': 'net', 'move': 81, 'top5': [[81, 0.9998648166656494], [77, 2.541591129556764e-05], [45, 2.254200262541417e-05], [47, 1.720802902127616e-05], [67, 1.4088785974308848e-05]]}]
104 black -1 -22.5 two_passes captured/lost 11 28 length 114 last [{'ply': 111, 'by': 'strong', 'move': 2}, {'ply': 112, 'by': 'net', 'move': 81, 'top5': [[81, 0.9349849224090576], [20, 0.04383939504623413], [41, 0.010283373296260834], [16, 0.0054223062470555305], [11, 0.005368383135646582]]}, {'ply': 113, 'by': 'strong', 'move': 81}]
105 white 1 88.5 two_passes captured/lost 65 7 length 136 last [{'ply': 133, 'by': 'net', 'move': 65, 'top5': [[65, 0.9999266862869263], [81, 7.336439011851326e-05], [53, 1.883621258969015e-09], [5, 1.6706177552450185e-09], [33, 1.2753196276804601e-09]]}, {'ply': 134, 'by': 'strong', 'move': 81}, {'ply': 135, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999009370803833], [53, 2.5672328774817288e-05], [5, 2.2769250790588558e-05], [33, 1.7381637007929385e-05], [7, 4.9799223234003875e-06]]}]
106 black -1 -6.5 two_passes captured/lost 5 12 length 88 last [{'ply': 85, 'by': 'strong', 'move': 63}, {'ply': 86, 'by': 'net', 'move': 81, 'top5': [[81, 0.9595587849617004], [23, 0.024202920496463776], [13, 0.0056772599928081036], [50, 0.005137004889547825], [64, 0.0024755795020610094]]}, {'ply': 87, 'by': 'strong', 'move': 81}]
107 white 1 4.5 two_passes captured/lost 4 14 length 88 last [{'ply': 85, 'by': 'net', 'move': 5, 'top5': [[5, 0.9713945984840393], [81, 0.015010133385658264], [14, 0.013180283829569817], [41, 0.00025378126883879304], [43, 0.00016020932525862008]]}, {'ply': 86, 'by': 'strong', 'move': 81}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9730942845344543], [41, 0.016452426090836525], [43, 0.010386236011981964], [35, 2.4735421902732924e-05], [33, 2.150395630451385e-05]]}]
108 black -1 -12.5 two_passes captured/lost 1 6 length 76 last [{'ply': 73, 'by': 'strong', 'move': 75}, {'ply': 74, 'by': 'net', 'move': 81, 'top5': [[81, 0.9805928468704224], [61, 0.01330519188195467], [72, 0.004518409259617329], [73, 0.0014595894608646631], [8, 3.793661016970873e-05]]}, {'ply': 75, 'by': 'strong', 'move': 81}]
```Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 4 of at most 120:
```
games.json: opponent, net_color, result +1/-1, area margin including komi, end reason, captured/lost stones, moves with ply/by/move and network top5 [move,probability]. boards.npy: (games,162,81), board AFTER each ply (Black1, White-1, empty0). valid.npy: (games,162), plies actually played.
boards: (128, 162, 81) int8 valid: (128, 162) values: [-1 0 1]
64 black 1 73.5 two_passes captured/lost 60 2 length 129 last [{'ply': 126, 'by': 'net', 'move': 8, 'top5': [[8, 1.0], [81, 5.439071502216786e-13], [9, 1.3688245160712218e-17], [45, 4.695150362335196e-18], [4, 4.164213319229766e-18]]}, {'ply': 127, 'by': 'strong', 'move': 81}, {'ply': 128, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999185800552368], [9, 2.5164463295368478e-05], [45, 8.63156219566008e-06], [4, 6.789841336285463e-06], [1, 6.655415745626669e-06]]}]
65 white -1 -2.5 two_passes captured/lost 6 18 length 90 last [{'ply': 87, 'by': 'net', 'move': 71, 'top5': [[71, 0.790695071220398], [70, 0.17642655968666077], [81, 0.032230280339717865], [32, 0.0005844395491294563], [2, 4.129161243326962e-05]]}, {'ply': 88, 'by': 'strong', 'move': 81}, {'ply': 89, 'by': 'net', 'move': 81, 'top5': [[81, 0.9799486994743347], [32, 0.017769649624824524], [2, 0.0012554549612104893], [1, 0.0005930348997935653], [70, 0.0003455897676758468]]}]
66 black -1 -22.5 two_passes captured/lost 2 23 length 99 last [{'ply': 96, 'by': 'net', 'move': 21, 'top5': [[81, 0.8825389742851257], [21, 0.04665631055831909], [43, 0.027461959049105644], [61, 0.024356691166758537], [37, 0.009419688954949379]]}, {'ply': 97, 'by': 'strong', 'move': 81}, {'ply': 98, 'by': 'net', 'move': 81, 'top5': [[81, 0.9315993785858154], [43, 0.028988569974899292], [61, 0.025710681453347206], [37, 0.009943329729139805], [36, 0.003657946363091469]]}]
67 white -1 -4.5 two_passes captured/lost 3 14 length 85 last [{'ply': 82, 'by': 'strong', 'move': 61}, {'ply': 83, 'by': 'net', 'move': 81, 'top5': [[81, 0.9940990209579468], [52, 0.00410346919670701], [53, 0.001719163148663938], [3, 2.5269348043366335e-05], [9, 1.660317684581969e-05]]}, {'ply': 84, 'by': 'strong', 'move': 81}]
68 black -1 -20.5 two_passes captured/lost 7 21 length 104 last [{'ply': 101, 'by': 'strong', 'move': 60}, {'ply': 102, 'by': 'net', 'move': 81, 'top5': [[81, 0.9049596190452576], [42, 0.05029425770044327], [51, 0.04243157431483269], [10, 0.0021337631624192], [0, 0.00017340814520139247]]}, {'ply': 103, 'by': 'strong', 'move': 81}]
69 white -1 -2.5 two_passes captured/lost 5 18 length 96 last [{'ply': 93, 'by': 'net', 'move': 62, 'top5': [[62, 0.9343498349189758], [81, 0.06535577774047852], [0, 0.00022760209685657173], [9, 6.520908937091008e-05], [6, 4.482532744987111e-07]]}, {'ply': 94, 'by': 'strong', 'move': 81}, {'ply': 95, 'by': 'net', 'move': 81, 'top5': [[81, 0.9955177903175354], [0, 0.0034668997395783663], [9, 0.0009932833490893245], [6, 6.8279246079328004e-06], [26, 6.8279246079328004e-06]]}]
70 black 1 73.5 two_passes captured/lost 59 2 length 123 last [{'ply': 120, 'by': 'net', 'move': 60, 'top5': [[60, 0.9999979734420776], [81, 1.9847861949529033e-06], [0, 1.0365014402324846e-10], [4, 6.675481695195273e-11], [2, 6.609045255512314e-11]]}, {'ply': 121, 'by': 'strong', 'move': 81}, {'ply': 122, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997805953025818], [0, 5.2210856665624306e-05], [4, 3.362586721777916e-05], [2, 3.329121682327241e-05], [18, 3.329121682327241e-05]]}]
71 white 1 88.5 two_passes captured/lost 54 0 length 118 last [{'ply': 115, 'by': 'net', 'move': 64, 'top5': [[64, 0.9999833106994629], [81, 1.6701518688932993e-05], [57, 5.5326815129319584e-08], [72, 2.040622115728752e-09], [8, 9.932761280140312e-10]]}, {'ply': 116, 'by': 'strong', 'move': 81}, {'ply': 117, 'by': 'net', 'move': 81, 'top5': [[81, 0.999828577041626], [8, 5.946201417827979e-05], [72, 3.9462138374801725e-05], [71, 1.669887024036143e-05], [79, 1.481052822782658e-05]]}]
72 black 1 73.5 two_passes captured/lost 61 7 length 131 last [{'ply': 128, 'by': 'net', 'move': 19, 'top5': [[19, 0.999993085861206], [81, 6.85860641169711e-06], [72, 6.860947920905858e-10], [35, 2.627010553535314e-10], [76, 2.627010553535314e-10]]}, {'ply': 129, 'by': 'strong', 'move': 81}, {'ply': 130, 'by': 'net', 'move': 81, 'top5': [[81, 0.9996083378791809], [72, 9.999495523516089e-05], [35, 3.8287391362246126e-05], [76, 3.8287391362246126e-05], [3, 3.7906342186033726e-05]]}]
73 white -1 -4.5 two_passes captured/lost 9 23 length 99 last [{'ply': 96, 'by': 'strong', 'move': 58}, {'ply': 97, 'by': 'net', 'move': 81, 'top5': [[81, 0.9545677900314331], [51, 0.01646541990339756], [30, 0.011956262402236462], [12, 0.009691640734672546], [55, 0.0042684744112193584]]}, {'ply': 98, 'by': 'strong', 'move': 81}]
74 black -1 -7.5 two_passes captured/lost 10 15 length 94 last [{'ply': 91, 'by': 'strong', 'move': 25}, {'ply': 92, 'by': 'net', 'move': 81, 'top5': [[81, 0.9933957457542419], [48, 0.006303618662059307], [0, 0.00019035425793845206], [72, 5.790967043139972e-05], [36, 3.8049434806453064e-05]]}, {'ply': 93, 'by': 'strong', 'move': 81}]
75 white 1 88.5 two_passes captured/lost 63 3 length 130 last [{'ply': 127, 'by': 'net', 'move': 70, 'top5': [[70, 0.9999450445175171], [81, 5.489686009241268e-05], [8, 3.2648372894072963e-09], [75, 2.789336261965758e-10], [73, 2.7340918418161664e-10]]}, {'ply': 128, 'by': 'strong', 'move': 81}, {'ply': 129, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999041557312012], [8, 5.9466507082106546e-05], [75, 5.080561550130369e-06], [73, 4.9799382395576686e-06], [9, 4.461196112970356e-06]]}]
76 black -1 -5.5 two_passes captured/lost 5 7 length 82 last [{'ply': 79, 'by': 'strong', 'move': 52}, {'ply': 80, 'by': 'net', 'move': 81, 'top5': [[81, 0.9725267291069031], [32, 0.02738211862742901], [0, 5.726301606046036e-05], [22, 1.8683713278733194e-05], [4, 7.3717824307095725e-06]]}, {'ply': 81, 'by': 'strong', 'move': 81}]
77 white 1 88.5 two_passes captured/lost 57 0 length 118 last [{'ply': 115, 'by': 'net', 'move': 48, 'top5': [[48, 0.9999967813491821], [81, 3.239806574129034e-06], [8, 3.6908401335189467e-10], [72, 3.6908401335189467e-10], [27, 8.235377657594967e-11]]}, {'ply': 116, 'by': 'strong', 'move': 81}, {'ply': 117, 'by': 'net', 'move': 81, 'top5': [[81, 0.9996875524520874], [8, 0.00011388602433726192], [72, 0.00011388602433726192], [27, 2.5411403839825653e-05], [1, 1.6696514649083838e-05]]}]
78 black -1 -6.5 two_passes captured/lost 4 6 length 86 last [{'ply': 83, 'by': 'strong', 'move': 54}, {'ply': 84, 'by': 'net', 'move': 81, 'top5': [[81, 0.9937422871589661], [25, 0.006180975120514631], [8, 3.409785495023243e-05], [35, 1.744819564919453e-05], [5, 9.292721188103314e-06]]}, {'ply': 85, 'by': 'strong', 'move': 81}]
79 white -1 6.5 repetition captured/lost 4 8 length 84 last [{'ply': 81, 'by': 'net', 'move': 5, 'top5': [[5, 1.0], [19, 4.8473686869998645e-11], [7, 2.9108396248922475e-11], [81, 1.0736045299303276e-12], [29, 3.842764187368328e-14]]}, {'ply': 82, 'by': 'strong', 'move': 7}, {'ply': 83, 'by': 'net', 'move': 6, 'top5': [[6, 0.9999997615814209], [19, 2.686100515347789e-07], [81, 5.949226888901649e-09], [29, 2.1294130347904172e-10], [72, 1.9317570112975524e-11]]}]
80 black -1 47.5 repetition captured/lost 51 9 length 127 last [{'ply': 124, 'by': 'net', 'move': 77, 'top5': [[77, 0.9999984502792358], [64, 1.6088388292700984e-06], [45, 3.948223525895855e-09], [38, 4.691975141746241e-10], [36, 2.1724366749964474e-10]]}, {'ply': 125, 'by': 'strong', 'move': 79}, {'ply': 126, 'by': 'net', 'move': 78, 'top5': [[78, 0.9913105964660645], [64, 0.008662731386721134], [45, 2.125906030414626e-05], [38, 2.5263761926908046e-06], [36, 1.1697402442223392e-06]]}]
81 white 1 88.5 two_passes captured/lost 60 4 length 124 last [{'ply': 121, 'by': 'net', 'move': 64, 'top5': [[64, 1.0], [81, 2.4860231206957906e-08], [47, 7.377551347609312e-11], [0, 1.6670006304161933e-12], [24, 1.247364191103717e-12]]}, {'ply': 122, 'by': 'strong', 'move': 81}, {'ply': 123, 'by': 'net', 'move': 81, 'top5': [[81, 0.999729573726654], [0, 6.70367808197625e-05], [24, 5.016151408199221e-05], [18, 2.2765523681300692e-05], [6, 2.2765349058317952e-05]]}]
82 black -1 -9.5 two_passes captured/lost 2 7 length 80 last [{'ply': 77, 'by': 'strong', 'move': 68}, {'ply': 78, 'by': 'net', 'move': 81, 'top5': [[81, 0.974189817905426], [30, 0.011841407977044582], [76, 0.0053207119926810265], [64, 0.0033926197793334723], [75, 0.002979052485898137]]}, {'ply': 79, 'by': 'strong', 'move': 81}]
83 white -1 -1.5 two_passes captured/lost 4 14 length 89 last [{'ply': 86, 'by': 'strong', 'move': 51}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9982441663742065], [30, 0.0017263316549360752], [27, 2.2731697754352354e-05], [9, 3.720116865224554e-06], [2, 1.9615756627899827e-06]]}, {'ply': 88, 'by': 'strong', 'move': 81}]
84 black 1 73.5 two_passes captured/lost 62 7 length 129 last [{'ply': 126, 'by': 'net', 'move': 30, 'top5': [[30, 0.999995231628418], [81, 4.785094461112749e-06], [41, 1.2720986930503386e-08], [0, 3.727907427197863e-10], [80, 2.498887208268741e-10]]}, {'ply': 127, 'by': 'strong', 'move': 81}, {'ply': 128, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997435212135315], [0, 7.788668153807521e-05], [80, 5.220892126089893e-05], [53, 3.012206798302941e-05], [63, 2.209282320109196e-05]]}]
85 white -1 24.5 repetition captured/lost 11 4 length 74 last [{'ply': 71, 'by': 'net', 'move': 53, 'top5': [[53, 1.0], [6, 1.2011325267735629e-09], [75, 1.003269911592497e-09], [5, 9.169160430921863e-10], [74, 5.788346468804662e-10]]}, {'ply': 72, 'by': 'strong', 'move': 71}, {'ply': 73, 'by': 'net', 'move': 62, 'top5': [[62, 0.9999678134918213], [6, 6.997012405918213e-06], [75, 5.8443938542041e-06], [5, 5.341353244148195e-06], [74, 3.371911816429929e-06]]}]
86 black -1 -10.5 repetition captured/lost 6 14 length 87 last [{'ply': 84, 'by': 'net', 'move': 78, 'top5': [[78, 1.0], [81, 4.441631090701392e-12], [55, 2.0009224854268537e-13], [65, 1.0341757289943077e-13], [0, 2.3075579668645554e-14]]}, {'ply': 85, 'by': 'strong', 'move': 77}, {'ply': 86, 'by': 'net', 'move': 69, 'top5': [[69, 0.9994966983795166], [81, 0.00045714687439613044], [55, 2.059413236565888e-05], [65, 9.44048588280566e-06], [68, 8.125426575134043e-06]]}]
87 white 1 0.5 two_passes captured/lost 2 11 length 89 last [{'ply': 86, 'by': 'strong', 'move': 9}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999927282333374], [63, 5.030444299336523e-06], [55, 1.4557231224898715e-06], [65, 4.340930672697141e-07], [48, 3.0897334113433317e-07]]}, {'ply': 88, 'by': 'strong', 'move': 81}]
88 black -1 1.5 repetition captured/lost 8 9 length 87 last [{'ply': 84, 'by': 'net', 'move': 18, 'top5': [[18, 1.0], [6, 3.273483151211565e-10], [5, 1.5462839342283985e-10], [0, 1.228570439826271e-10], [3, 4.172194534302065e-11]]}, {'ply': 85, 'by': 'strong', 'move': 0}, {'ply': 86, 'by': 'net', 'move': 9, 'top5': [[9, 0.9986767172813416], [3, 0.0013184096897020936], [6, 3.077704377574264e-06], [5, 1.4538045434164815e-06], [7, 3.211592627394566e-07]]}]
89 white -1 -4.5 two_passes captured/lost 3 16 length 92 last [{'ply': 89, 'by': 'net', 'move': 47, 'top5': [[47, 0.9999997615814209], [29, 2.580794387085916e-07], [81, 2.2610960326296947e-10], [69, 6.3663232671706815e-12], [59, 3.2904304281267116e-12]]}, {'ply': 90, 'by': 'strong', 'move': 81}, {'ply': 91, 'by': 'net', 'move': 81, 'top5': [[81, 0.9570878744125366], [69, 0.02694767154753208], [59, 0.013927889056503773], [2, 0.0010875178268179297], [1, 0.00084695965051651]]}]
90 black -1 -13.5 two_passes captured/lost 5 19 length 98 last [{'ply': 95, 'by': 'strong', 'move': 73}, {'ply': 96, 'by': 'net', 'move': 81, 'top5': [[81, 0.9891046285629272], [33, 0.010878604836761951], [35, 8.453302143607289e-06], [78, 3.68604969480657e-06], [25, 2.326927415197133e-06]]}, {'ply': 97, 'by': 'strong', 'move': 81}]
91 white 1 6.5 two_passes captured/lost 20 20 length 117 last [{'ply': 114, 'by': 'strong', 'move': 61}, {'ply': 115, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999452829360962], [9, 1.670082019700203e-05], [1, 1.6534608221263625e-05], [3, 5.080770733911777e-06], [19, 3.5803093396680197e-06]]}, {'ply': 116, 'by': 'strong', 'move': 81}]
92 black 1 73.5 two_passes captured/lost 61 7 length 129 last [{'ply': 126, 'by': 'net', 'move': 40, 'top5': [[40, 0.9999898672103882], [81, 9.929436600941699e-06], [21, 2.939044634331367e-07], [80, 9.93282567307574e-10], [8, 3.84144327458813e-10]]}, {'ply': 127, 'by': 'strong', 'move': 81}, {'ply': 128, 'by': 'net', 'move': 81, 'top5': [[81, 0.9996169805526733], [80, 9.999582107411698e-05], [8, 3.8672606024192646e-05], [45, 3.828772605629638e-05], [3, 3.790667324210517e-05]]}]
93 white 1 88.5 two_passes captured/lost 58 0 length 124 last [{'ply': 121, 'by': 'net', 'move': 34, 'top5': [[34, 0.9999545812606812], [81, 4.539778092294e-05], [23, 3.563109984838775e-08], [80, 1.773968083540467e-09], [58, 5.13355524756065e-10]]}, {'ply': 122, 'by': 'strong', 'move': 81}, {'ply': 123, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999127388000488], [80, 3.907268910552375e-05], [58, 1.1306957276246976e-05], [76, 5.671371582138818e-06], [17, 5.080605205876054e-06]]}]
94 black -1 -4.5 two_passes captured/lost 6 12 length 92 last [{'ply': 89, 'by': 'strong', 'move': 4}, {'ply': 90, 'by': 'net', 'move': 81, 'top5': [[81, 0.9719324707984924], [60, 0.020682498812675476], [68, 0.0053617036901414394], [65, 0.0019528298871591687], [72, 5.025180507800542e-05]]}, {'ply': 91, 'by': 'strong', 'move': 81}]
95 white -1 -5.5 two_passes captured/lost 6 21 length 103 last [{'ply': 100, 'by': 'strong', 'move': 2}, {'ply': 101, 'by': 'net', 'move': 81, 'top5': [[81, 0.986890435218811], [15, 0.008976013399660587], [10, 0.0017066968139261007], [60, 0.0013696546666324139], [1, 0.0009846753673627973]]}, {'ply': 102, 'by': 'strong', 'move': 81}]
96 black -1 -14.5 two_passes captured/lost 10 22 length 106 last [{'ply': 103, 'by': 'strong', 'move': 10}, {'ply': 104, 'by': 'net', 'move': 81, 'top5': [[81, 0.9788761138916016], [8, 0.005085548851639032], [49, 0.004886137321591377], [37, 0.004510464612394571], [53, 0.0032426989637315273]]}, {'ply': 105, 'by': 'strong', 'move': 81}]
97 white 1 88.5 two_passes captured/lost 53 0 length 118 last [{'ply': 115, 'by': 'net', 'move': 71, 'top5': [[71, 0.9999972581863403], [81, 2.7332755507814e-06], [8, 1.6255392865094365e-10], [36, 6.947808300905578e-11], [18, 6.16218326365825e-11]]}, {'ply': 116, 'by': 'strong', 'move': 81}, {'ply': 117, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997962117195129], [8, 5.946008604951203e-05], [80, 5.326674727257341e-05], [36, 2.541416688472964e-05], [18, 2.2540454665431753e-05]]}]
98 black -1 -1.5 two_passes captured/lost 2 5 length 77 last [{'ply': 74, 'by': 'net', 'move': 18, 'top5': [[18, 0.9999903440475464], [0, 9.635920832806733e-06], [81, 9.427153068591876e-13], [32, 7.994550219037316e-15], [64, 2.4321246649668463e-15]]}, {'ply': 75, 'by': 'strong', 'move': 81}, {'ply': 76, 'by': 'net', 'move': 81, 'top5': [[81, 0.9874961376190186], [32, 0.008374307304620743], [64, 0.002547655487433076], [73, 0.0014698648592457175], [7, 2.4604501959402114e-05]]}]
99 white 1 88.5 two_passes captured/lost 65 6 length 134 last [{'ply': 131, 'by': 'net', 'move': 73, 'top5': [[73, 0.9999984502792358], [81, 1.5151365460042143e-06], [0, 1.0159734858961045e-10], [80, 5.251093310176813e-11], [8, 4.43013681294957e-11]]}, {'ply': 132, 'by': 'strong', 'move': 81}, {'ply': 133, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997754693031311], [0, 6.70398585498333e-05], [72, 4.19000098190736e-05], [80, 3.464977635303512e-05], [8, 2.9232627639430575e-05]]}]
100 black -1 -9.5 two_passes captured/lost 3 9 length 83 last [{'ply': 80, 'by': 'net', 'move': 71, 'top5': [[71, 0.5514063239097595], [62, 0.4425133764743805], [81, 0.005826805252581835], [29, 0.00018683564849197865], [59, 4.045632158522494e-05]]}, {'ply': 81, 'by': 'strong', 'move': 81}, {'ply': 82, 'by': 'net', 'move': 81, 'top5': [[81, 0.9583132863044739], [29, 0.0307281743735075], [59, 0.006653703283518553], [28, 0.002065093256533146], [9, 0.0011109024053439498]]}]
101 white 1 88.5 two_passes captured/lost 57 1 length 118 last [{'ply': 115, 'by': 'net', 'move': 11, 'top5': [[11, 0.9994322657585144], [2, 0.000563939509447664], [81, 3.837983967969194e-06], [8, 3.8778952271556477e-10], [0, 1.4848085261309762e-10]]}, {'ply': 116, 'by': 'strong', 'move': 81}, {'ply': 117, 'by': 'net', 'move': 81, 'top5': [[81, 0.9997736811637878], [8, 0.00010101703082909808], [0, 5.2210598369129e-05], [75, 2.5413593903067522e-05], [57, 1.0027025382441934e-05]]}]
102 black -1 -12.5 two_passes captured/lost 10 18 length 104 last [{'ply': 101, 'by': 'strong', 'move': 73}, {'ply': 102, 'by': 'net', 'move': 81, 'top5': [[81, 0.9872137308120728], [43, 0.008206164464354515], [25, 0.004503611009567976], [35, 6.488682993222028e-05], [6, 5.599291398539208e-06]]}, {'ply': 103, 'by': 'strong', 'move': 81}]
103 white 1 88.5 two_passes captured/lost 57 2 length 120 last [{'ply': 117, 'by': 'net', 'move': 10, 'top5': [[10, 0.9999790191650391], [81, 2.102035068674013e-05], [77, 5.343235853771944e-10], [45, 4.739048597990347e-10], [47, 3.617676991307661e-10]]}, {'ply': 118, 'by': 'strong', 'move': 81}, {'ply': 119, 'by': 'net', 'move': 81, 'top5': [[81, 0.9998648166656494], [77, 2.541591129556764e-05], [45, 2.254200262541417e-05], [47, 1.720802902127616e-05], [67, 1.4088785974308848e-05]]}]
104 black -1 -22.5 two_passes captured/lost 11 28 length 114 last [{'ply': 111, 'by': 'strong', 'move': 2}, {'ply': 112, 'by': 'net', 'move': 81, 'top5': [[81, 0.9349849224090576], [20, 0.04383939504623413], [41, 0.010283373296260834], [16, 0.0054223062470555305], [11, 0.005368383135646582]]}, {'ply': 113, 'by': 'strong', 'move': 81}]
105 white 1 88.5 two_passes captured/lost 65 7 length 136 last [{'ply': 133, 'by': 'net', 'move': 65, 'top5': [[65, 0.9999266862869263], [81, 7.336439011851326e-05], [53, 1.883621258969015e-09], [5, 1.6706177552450185e-09], [33, 1.2753196276804601e-09]]}, {'ply': 134, 'by': 'strong', 'move': 81}, {'ply': 135, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999009370803833], [53, 2.5672328774817288e-05], [5, 2.2769250790588558e-05], [33, 1.7381637007929385e-05], [7, 4.9799223234003875e-06]]}]
106 black -1 -6.5 two_passes captured/lost 5 12 length 88 last [{'ply': 85, 'by': 'strong', 'move': 63}, {'ply': 86, 'by': 'net', 'move': 81, 'top5': [[81, 0.9595587849617004], [23, 0.024202920496463776], [13, 0.0056772599928081036], [50, 0.005137004889547825], [64, 0.0024755795020610094]]}, {'ply': 87, 'by': 'strong', 'move': 81}]
107 white 1 4.5 two_passes captured/lost 4 14 length 88 last [{'ply': 85, 'by': 'net', 'move': 5, 'top5': [[5, 0.9713945984840393], [81, 0.015010133385658264], [14, 0.013180283829569817], [41, 0.00025378126883879304], [43, 0.00016020932525862008]]}, {'ply': 86, 'by': 'strong', 'move': 81}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9730942845344543], [41, 0.016452426090836525], [43, 0.010386236011981964], [35, 2.4735421902732924e-05], [33, 2.150395630451385e-05]]}]
108 black -1 -12.5 two_passes captured/lost 1 6 length 76 last [{'ply': 73, 'by': 'strong', 'move': 75}, {'ply': 74, 'by': 'net', 'move': 81, 'top5': [[81, 0.9805928468704224], [61, 0.01330519188195467], [72, 0.004518409259617329], [73, 0.0014595894608646631], [8, 3.793661016970873e-05]]}, {'ply': 75, 'by': 'strong', 'move': 81}]
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import numpy as np, json
games=json.load(open("/work/pass_1/games.json"))
boards=np.load("/work/pass_1/boards.npy")
def show(b):
for row in np.asarray(b).reshape(9,9):
print("".join({1:"X",-1:"O",0:"."}[int(v)] for v in row))
for gi in [65,66,79,85]:
g=games[gi]
print("\nGAME",gi, g["net_color"],g["margin"],g["end"])
if g["end"]=="repetition":
plies=range(max(0,len(g["moves"])-7),len(g["moves"]))
else:
our=1 if g["net_color"]=="black" else -1
plies=[t for t in range(1,len(g["moves"]))
if g["moves"][t]["by"]!="net"
and np.sum((boards[gi,t-1]==our)&(boards[gi,t]!=our))>=2][:3]
for t in plies:
print("PLY",t,g["moves"][t])
if g["end"]!="repetition":
print("Two plies before:")
show(boards[gi,max(0,t-2)])
print("Network preceding move:",g["moves"][t-1])
show(boards[gi,t])
```
{
"request_sha256": "d8ffb6bf9c03f0b6bf69dc8103660adf7f3f6d5dc0660c5aa2b59fc84ad569a0",
"request": {
"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import numpy as np, json\ngames=json.load(open(\"/work/pass_1/games.json\"))\nboards=np.load(\"/work/pass_1/boards.npy\")\ndef show(b):\n for row in np.asarray(b).reshape(9,9):\n print(\"\".join({1:\"X\",-1:\"O\",0:\".\"}[int(v)] for v in row))\nfor gi in [65,66,79,85]:\n g=games[gi]\n print(\"\\nGAME\",gi, g[\"net_color\"],g[\"margin\"],g[\"end\"])\n if g[\"end\"]==\"repetition\":\n plies=range(max(0,len(g[\"moves\"])-7),len(g[\"moves\"]))\n else:\n our=1 if g[\"net_color\"]==\"black\" else -1\n plies=[t for t in range(1,len(g[\"moves\"]))\n if g[\"moves\"][t][\"by\"]!=\"net\"\n and np.sum((boards[gi,t-1]==our)&(boards[gi,t]!=our))>=2][:3]\n for t in plies:\n print(\"PLY\",t,g[\"moves\"][t])\n if g[\"end\"]!=\"repetition\":\n print(\"Two plies before:\")\n show(boards[gi,max(0,t-2)])\n print(\"Network preceding move:\",g[\"moves\"][t-1])\n show(boards[gi,t])"
},
"result": {
"ok": true,
"out": "\nGAME 65 white -2.5 two_passes\nPLY 50 {'ply': 50, 'by': 'strong', 'move': 0}\nTwo plies before:\n.O.X.O.O.\n.XOXX.O..\nOXOXOO.O.\n.XXXO.O..\nX.X.XO.O.\nXXOX.XO..\nOOOOXXX..\n.XXXXXO..\n.XOO.....\nNetwork preceding move: {'ply': 49, 'by': 'net', 'move': 2, 'top5': [[2, 0.9746227264404297], [61, 0.012330153025686741], [77, 0.001977920066565275], [70, 0.0017896989593282342], [62, 0.0010640163673087955]]}\nX..X.O.O.\n.X.XX.O..\nOX.XOO.O.\n.XXXO.O..\nX.X.XO.O.\nXXOX.XO..\nOOOOXXX..\n.XXXXXO..\n.XOO.....\nPLY 52 {'ply': 52, 'by': 'strong', 'move': 63}\nTwo plies before:\nX..X.O.O.\n.X.XX.O..\nOX.XOO.O.\n.XXXO.O..\nX.X.XO.O.\nXXOX.XO..\nOOOOXXX..\n.XXXXXO..\n.XOO.....\nNetwork preceding move: {'ply': 51, 'by': 'net', 'move': 44, 'top5': [[61, 0.48729991912841797], [77, 0.07816938310861588], [70, 0.07073068618774414], [62, 0.042050983756780624], [52, 0.04000001400709152]]}\nX..X.O.O.\n.X.XX.O..\nOX.XOO.O.\n.XXXO.O..\nX.X.XO.OO\nXX.X.XO..\n....XXX..\nXXXXXXO..\n.XOO.....\nPLY 60 {'ply': 60, 'by': 'strong', 'move': 76}\nTwo plies before:\nX..X.O.O.\n.X.XX.O..\nOX.XOO.O.\n.XXXO.O..\nX.X.XO.OO\nXX.X.XOXX\n..O.XXX..\nXXXXXXOX.\n.XOO.OO..\nNetwork preceding move: {'ply': 59, 'by': 'net', 'move': 42, 'top5': [[76, 0.8328378796577454], [42, 0.16481834650039673], [17, 0.00029371128766797483], [80, 0.00028503115754574537], [62, 0.00026576139498502016]]}\nX..X.O.O.\n.X.XX.O..\nOX.XOO.O.\n.XXXO.O..\nX.X.XOOOO\nXX.X.XOXX\n..O.XXX..\nXXXXXXOX.\n.X..XOO..\n\nGAME 66 black -22.5 two_passes\nPLY 53 {'ply': 53, 'by': 'strong', 'move': 4}\nTwo plies before:\n..OX.X...\nXOOXXOX..\nOOOXOOXX.\nXOOOOOOX.\nXXXOO.X..\nXOOO.X.X.\nXXXOX.X..\n.OOOOX...\n........X\nNetwork preceding move: {'ply': 52, 'by': 'net', 'move': 1, 'top5': [[1, 0.9998565912246704], [4, 0.00014336139429360628], [70, 3.3977807234464308e-09], [49, 2.61985855232183e-09], [41, 1.5115222407047213e-09]]}\n.XO.OX...\nXOO..OX..\nOOO.OOXX.\nXOOOOOOX.\nXXXOO.X..\nXOOO.X.X.\nXXXOX.X..\n.OOOOX...\n........X\nPLY 65 {'ply': 65, 'by': 'strong', 'move': 0}\nTwo plies before:\n.XOOOXX..\nXOOX.OX..\nOOO.OOXX.\nXOOOOOOX.\nXXXOOXX..\nXOOOOX.X.\nXXXOXXX..\n.OOOOX.X.\n...O.OO.X\nNetwork preceding move: {'ply': 64, 'by': 'net', 'move': 21, 'top5': [[21, 0.8544570207595825], [13, 0.14554159343242645], [62, 2.38884553027674e-07], [44, 2.1615203138480865e-07], [17, 2.0560953828407946e-07]]}\nO.OOOXX..\n.OOX.OX..\nOOOXOOXX.\nXOOOOOOX.\nXXXOOXX..\nXOOOOX.X.\nXXXOXXX..\n.OOOOX.X.\n...O.OO.X\nPLY 67 {'ply': 67, 'by': 'strong', 'move': 13}\nTwo plies before:\nO.OOOXX..\n.OOX.OX..\nOOOXOOXX.\nXOOOOOOX.\nXXXOOXX..\nXOOOOX.X.\nXXXOXXX..\n.OOOOX.X.\n...O.OO.X\nNetwork preceding move: {'ply': 66, 'by': 'net', 'move': 62, 'top5': [[62, 0.17392563819885254], [44, 0.15737466514110565], [17, 0.14969895780086517], [72, 0.11314017325639725], [7, 0.07972865551710129]]}\nO.OOOXX..\n.OO.OOX..\nOOO.OOXX.\nXOOOOOOX.\nXXXOOXX..\nXOOOOX.X.\nXXXOXXX.X\n.OOOOX.X.\n...O.OO.X\n\nGAME 79 white 6.5 repetition\nPLY 77 {'ply': 77, 'by': 'net', 'move': 6, 'top5': [[6, 0.9999865293502808], [5, 1.1421526323829312e-05], [77, 9.85599967862072e-07], [75, 5.04340846418927e-07], [19, 4.6556442612200044e-07]]}\nOOXX..O.O\n.OXXXXXO.\nO.OOOXOOO\nXO.OXXXXO\nXXOOOXXXO\nXOOXOOXXO\nXOXXOOOXO\nXXXXXXXXO\n..X.O.X.O\nPLY 78 {'ply': 78, 'by': 'strong', 'move': 77}\nOOXX..O.O\n.OXXXXXO.\nO.OOOXOOO\nXO.OXXXXO\nXXOOOXXXO\nXOOXOOXXO\nXOXXOOOXO\nXXXXXXXXO\n..X.OXX.O\nPLY 79 {'ply': 79, 'by': 'net', 'move': 79, 'top5': [[79, 1.0], [5, 3.5029515095888475e-13], [19, 2.354165785380634e-14], [7, 1.253812812173358e-14], [81, 5.214061125776391e-16]]}\nOOXX..O.O\n.OXXXXXO.\nO.OOOXOOO\nXO.OXXXXO\nXXOOOXXXO\nXOOXOOXXO\nXOXXOOOXO\nXXXXXXXXO\n..X.OXXOO\nPLY 80 {'ply': 80, 'by': 'strong', 'move': 4}\nOOXXX.O.O\n.OXXXXXO.\nO.OOOXOOO\nXO.OXXXXO\nXXOOOXXXO\nXOOXOOXXO\nXOXXOOOXO\nXXXXXXXXO\n..X.OXXOO\nPLY 81 {'ply': 81, 'by': 'net', 'move': 5, 'top5': [[5, 1.0], [19, 4.8473686869998645e-11], [7, 2.9108396248922475e-11], [81, 1.0736045299303276e-12], [29, 3.842764187368328e-14]]}\nOOXXXOO.O\n.OXXXXXO.\nO.OOOXOOO\nXO.OXXXXO\nXXOOOXXXO\nXOOXOOXXO\nXOXXOOOXO\nXXXXXXXXO\n..X.OXXOO\nPLY 82 {'ply': 82, 'by': 'strong', 'move': 7}\nOOXXX..XO\n.OXXXXXO.\nO.OOOXOOO\nXO.OXXXXO\nXXOOOXXXO\nXOOXOOXXO\nXOXXOOOXO\nXXXXXXXXO\n..X.OXXOO\nPLY 83 {'ply': 83, 'by': 'net', 'move': 6, 'top5': [[6, 0.9999997615814209], [19, 2.686100515347789e-07], [81, 5.949226888901649e-09], [29, 2.1294130347904172e-10], [72, 1.9317570112975524e-11]]}\nOOXXX.O.O\n.OXXXXXO.\nO.OOOXOOO\nXO.OXXXXO\nXXOOOXXXO\nXOOXOOXXO\nXOXXOOOXO\nXXXXXXXXO\n..X.OXXOO\n\nGAME 85 white 24.5 repetition\nPLY 67 {'ply': 67, 'by': 'net', 'move': 62, 'top5': [[62, 1.0], [6, 6.7077672305515534e-09], [75, 6.509530692255794e-09], [74, 3.75566111543435e-09], [5, 3.4324283415543277e-09]]}\n..O.O....\nOOOOO.OOO\nO.O.OOXXX\n..O..OOOX\nOOOOOOXXX\nXXXXOXXXO\n.XOOOXXXO\nOXXXXXOO.\n.....XX.O\nPLY 68 {'ply': 68, 'by': 'strong', 'move': 71}\n..O.O....\nOOOOO.OOO\nO.O.OOXXX\n..O..OOOX\nOOOOOOXXX\nXXXXOXXX.\n.XOOOXXX.\nOXXXXXOOX\n.....XX.O\nPLY 69 {'ply': 69, 'by': 'net', 'move': 62, 'top5': [[62, 0.9999681711196899], [6, 6.022376965120202e-06], [75, 5.844396127940854e-06], [74, 3.371912953298306e-06], [5, 3.0817079732514685e-06]]}\n..O.O....\nOOOOO.OOO\nO.O.OOXXX\n..O..OOOX\nOOOOOOXXX\nXXXXOXXX.\n.XOOOXXXO\nOXXXXXOO.\n.....XX.O\nPLY 70 {'ply': 70, 'by': 'strong', 'move': 7}\n..O.O..X.\nOOOOO.OOO\nO.O.OOXXX\n..O..OOOX\nOOOOOOXXX\nXXXXOXXX.\n.XOOOXXXO\nOXXXXXOO.\n.....XX.O\nPLY 71 {'ply': 71, 'by': 'net', 'move': 53, 'top5': [[53, 1.0], [6, 1.2011325267735629e-09], [75, 1.003269911592497e-09], [5, 9.169160430921863e-10], [74, 5.788346468804662e-10]]}\n..O.O..X.\nOOOOO.OOO\nO.O.OOXXX\n..O..OOOX\nOOOOOOXXX\nXXXXOXXXO\n.XOOOXXXO\nOXXXXXOO.\n.....XX.O\nPLY 72 {'ply': 72, 'by': 'strong', 'move': 71}\n..O.O..X.\nOOOOO.OOO\nO.O.OOXXX\n..O..OOOX\nOOOOOOXXX\nXXXXOXXX.\n.XOOOXXX.\nOXXXXXOOX\n.....XX.O\nPLY 73 {'ply': 73, 'by': 'net', 'move': 62, 'top5': [[62, 0.9999678134918213], [6, 6.997012405918213e-06], [75, 5.8443938542041e-06], [5, 5.341353244148195e-06], [74, 3.371911816429929e-06]]}\n..O.O..X.\nOOOOO.OOO\nO.O.OOXXX\n..O..OOOX\nOOOOOOXXX\nXXXXOXXX.\n.XOOOXXXO\nOXXXXXOO.\n.....XX.O\n",
"stdout": "\nGAME 65 white -2.5 two_passes\nPLY 50 {'ply': 50, 'by': 'strong', 'move': 0}\nTwo plies before:\n.O.X.O.O.\n.XOXX.O..\nOXOXOO.O.\n.XXXO.O..\nX.X.XO.O.\nXXOX.XO..\nOOOOXXX..\n.XXXXXO..\n.XOO.....\nNetwork preceding move: {'ply': 49, 'by': 'net', 'move': 2, 'top5': [[2, 0.9746227264404297], [61, 0.012330153025686741], [77, 0.001977920066565275], [70, 0.0017896989593282342], [62, 0.0010640163673087955]]}\nX..X.O.O.\n.X.XX.O..\nOX.XOO.O.\n.XXXO.O..\nX.X.XO.O.\nXXOX.XO..\nOOOOXXX..\n.XXXXXO..\n.XOO.....\nPLY 52 {'ply': 52, 'by': 'strong', 'move': 63}\nTwo plies before:\nX..X.O.O.\n.X.XX.O..\nOX.XOO.O.\n.XXXO.O..\nX.X.XO.O.\nXXOX.XO..\nOOOOXXX..\n.XXXXXO..\n.XOO.....\nNetwork preceding move: {'ply': 51, 'by': 'net', 'move': 44, 'top5': [[61, 0.48729991912841797], [77, 0.07816938310861588], [70, 0.07073068618774414], [62, 0.042050983756780624], [52, 0.04000001400709152]]}\nX..X.O.O.\n.X.XX.O..\nOX.XOO.O.\n.XXXO.O..\nX.X.XO.OO\nXX.X.XO..\n....XXX..\nXXXXXXO..\n.XOO.....\nPLY 60 {'ply': 60, 'by': 'strong', 'move': 76}\nTwo plies before:\nX..X.O.O.\n.X.XX.O..\nOX.XOO.O.\n.XXXO.O..\nX.X.XO.OO\nXX.X.XOXX\n..O.XXX..\nXXXXXXOX.\n.XOO.OO..\nNetwork preceding move: {'ply': 59, 'by': 'net', 'move': 42, 'top5': [[76, 0.8328378796577454], [42, 0.16481834650039673], [17, 0.00029371128766797483], [80, 0.00028503115754574537], [62, 0.00026576139498502016]]}\nX..X.O.O.\n.X.XX.O..\nOX.XOO.O.\n.XXXO.O..\nX.X.XOOOO\nXX.X.XOXX\n..O.XXX..\nXXXXXXOX.\n.X..XOO..\n\nGAME 66 black -22.5 two_passes\nPLY 53 {'ply': 53, 'by': 'strong', 'move': 4}\nTwo plies before:\n..OX.X...\nXOOXXOX..\nOOOXOOXX.\nXOOOOOOX.\nXXXOO.X..\nXOOO.X.X.\nXXXOX.X..\n.OOOOX...\n........X\nNetwork preceding move: {'ply': 52, 'by': 'net', 'move': 1, 'top5': [[1, 0.9998565912246704], [4, 0.00014336139429360628], [70, 3.3977807234464308e-09], [49, 2.61985855232183e-09], [41, 1.5115222407047213e-09]]}\n.XO.OX...\nXOO..OX..\nOOO.OOXX.\nXOOOOOOX.\nXXXOO.X..\nXOOO.X.X.\nXXXOX.X..\n.OOOOX...\n........X\nPLY 65 {'ply': 65, 'by': 'strong', 'move': 0}\nTwo plies before:\n.XOOOXX..\nXOOX.OX..\nOOO.OOXX.\nXOOOOOOX.\nXXXOOXX..\nXOOOOX.X.\nXXXOXXX..\n.OOOOX.X.\n...O.OO.X\nNetwork preceding move: {'ply': 64, 'by': 'net', 'move': 21, 'top5': [[21, 0.8544570207595825], [13, 0.14554159343242645], [62, 2.38884553027674e-07], [44, 2.1615203138480865e-07], [17, 2.0560953828407946e-07]]}\nO.OOOXX..\n.OOX.OX..\nOOOXOOXX.\nXOOOOOOX.\nXXXOOXX..\nXOOOOX.X.\nXXXOXXX..\n.OOOOX.X.\n...O.OO.X\nPLY 67 {'ply': 67, 'by': 'strong', 'move': 13}\nTwo plies before:\nO.OOOXX..\n.OOX.OX..\nOOOXOOXX.\nXOOOOOOX.\nXXXOOXX..\nXOOOOX.X.\nXXXOXXX..\n.OOOOX.X.\n...O.OO.X\nNetwork preceding move: {'ply': 66, 'by': 'net', 'move': 62, 'top5': [[62, 0.17392563819885254], [44, 0.15737466514110565], [17, 0.14969895780086517], [72, 0.11314017325639725], [7, 0.07972865551710129]]}\nO.OOOXX..\n.OO.OOX..\nOOO.OOXX.\nXOOOOOOX.\nXXXOOXX..\nXOOOOX.X.\nXXXOXXX.X\n.OOOOX.X.\n...O.OO.X\n\nGAME 79 white 6.5 repetition\nPLY 77 {'ply': 77, 'by': 'net', 'move': 6, 'top5': [[6, 0.9999865293502808], [5, 1.1421526323829312e-05], [77, 9.85599967862072e-07], [75, 5.04340846418927e-07], [19, 4.6556442612200044e-07]]}\nOOXX..O.O\n.OXXXXXO.\nO.OOOXOOO\nXO.OXXXXO\nXXOOOXXXO\nXOOXOOXXO\nXOXXOOOXO\nXXXXXXXXO\n..X.O.X.O\nPLY 78 {'ply': 78, 'by': 'strong', 'move': 77}\nOOXX..O.O\n.OXXXXXO.\nO.OOOXOOO\nXO.OXXXXO\nXXOOOXXXO\nXOOXOOXXO\nXOXXOOOXO\nXXXXXXXXO\n..X.OXX.O\nPLY 79 {'ply': 79, 'by': 'net', 'move': 79, 'top5': [[79, 1.0], [5, 3.5029515095888475e-13], [19, 2.354165785380634e-14], [7, 1.253812812173358e-14], [81, 5.214061125776391e-16]]}\nOOXX..O.O\n.OXXXXXO.\nO.OOOXOOO\nXO.OXXXXO\nXXOOOXXXO\nXOOXOOXXO\nXOXXOOOXO\nXXXXXXXXO\n..X.OXXOO\nPLY 80 {'ply': 80, 'by': 'strong', 'move': 4}\nOOXXX.O.O\n.OXXXXXO.\nO.OOOXOOO\nXO.OXXXXO\nXXOOOXXXO\nXOOXOOXXO\nXOXXOOOXO\nXXXXXXXXO\n..X.OXXOO\nPLY 81 {'ply': 81, 'by': 'net', 'move': 5, 'top5': [[5, 1.0], [19, 4.8473686869998645e-11], [7, 2.9108396248922475e-11], [81, 1.0736045299303276e-12], [29, 3.842764187368328e-14]]}\nOOXXXOO.O\n.OXXXXXO.\nO.OOOXOOO\nXO.OXXXXO\nXXOOOXXXO\nXOOXOOXXO\nXOXXOOOXO\nXXXXXXXXO\n..X.OXXOO\nPLY 82 {'ply': 82, 'by': 'strong', 'move': 7}\nOOXXX..XO\n.OXXXXXO.\nO.OOOXOOO\nXO.OXXXXO\nXXOOOXXXO\nXOOXOOXXO\nXOXXOOOXO\nXXXXXXXXO\n..X.OXXOO\nPLY 83 {'ply': 83, 'by': 'net', 'move': 6, 'top5': [[6, 0.9999997615814209], [19, 2.686100515347789e-07], [81, 5.949226888901649e-09], [29, 2.1294130347904172e-10], [72, 1.9317570112975524e-11]]}\nOOXXX.O.O\n.OXXXXXO.\nO.OOOXOOO\nXO.OXXXXO\nXXOOOXXXO\nXOOXOOXXO\nXOXXOOOXO\nXXXXXXXXO\n..X.OXXOO\n\nGAME 85 white 24.5 repetition\nPLY 67 {'ply': 67, 'by': 'net', 'move': 62, 'top5': [[62, 1.0], [6, 6.7077672305515534e-09], [75, 6.509530692255794e-09], [74, 3.75566111543435e-09], [5, 3.4324283415543277e-09]]}\n..O.O....\nOOOOO.OOO\nO.O.OOXXX\n..O..OOOX\nOOOOOOXXX\nXXXXOXXXO\n.XOOOXXXO\nOXXXXXOO.\n.....XX.O\nPLY 68 {'ply': 68, 'by': 'strong', 'move': 71}\n..O.O....\nOOOOO.OOO\nO.O.OOXXX\n..O..OOOX\nOOOOOOXXX\nXXXXOXXX.\n.XOOOXXX.\nOXXXXXOOX\n.....XX.O\nPLY 69 {'ply': 69, 'by': 'net', 'move': 62, 'top5': [[62, 0.9999681711196899], [6, 6.022376965120202e-06], [75, 5.844396127940854e-06], [74, 3.371912953298306e-06], [5, 3.0817079732514685e-06]]}\n..O.O....\nOOOOO.OOO\nO.O.OOXXX\n..O..OOOX\nOOOOOOXXX\nXXXXOXXX.\n.XOOOXXXO\nOXXXXXOO.\n.....XX.O\nPLY 70 {'ply': 70, 'by': 'strong', 'move': 7}\n..O.O..X.\nOOOOO.OOO\nO.O.OOXXX\n..O..OOOX\nOOOOOOXXX\nXXXXOXXX.\n.XOOOXXXO\nOXXXXXOO.\n.....XX.O\nPLY 71 {'ply': 71, 'by': 'net', 'move': 53, 'top5': [[53, 1.0], [6, 1.2011325267735629e-09], [75, 1.003269911592497e-09], [5, 9.169160430921863e-10], [74, 5.788346468804662e-10]]}\n..O.O..X.\nOOOOO.OOO\nO.O.OOXXX\n..O..OOOX\nOOOOOOXXX\nXXXXOXXXO\n.XOOOXXXO\nOXXXXXOO.\n.....XX.O\nPLY 72 {'ply': 72, 'by': 'strong', 'move': 71}\n..O.O..X.\nOOOOO.OOO\nO.O.OOXXX\n..O..OOOX\nOOOOOOXXX\nXXXXOXXX.\n.XOOOXXX.\nOXXXXXOOX\n.....XX.O\nPLY 73 {'ply': 73, 'by': 'net', 'move': 62, 'top5': [[62, 0.9999678134918213], [6, 6.997012405918213e-06], [75, 5.8443938542041e-06], [5, 5.341353244148195e-06], [74, 3.371911816429929e-06]]}\n..O.O..X.\nOOOOO.OOO\nO.O.OOXXX\n..O..OOOX\nOOOOOOXXX\nXXXXOXXX.\n.XOOOXXXO\nOXXXXXOO.\n.....XX.O\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.2849713861942291,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-dc0afe1e6f9949bb9b172c85bbb39300",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
"-i",
"HOME=/tmp",
"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
"MKL_NUM_THREADS=8",
"CUDA_VISIBLE_DEVICES=",
"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 5 of at most 120:
```
GAME 65 white -2.5 two_passes
PLY 50 {'ply': 50, 'by': 'strong', 'move': 0}
Two plies before:
.O.X.O.O.
.XOXX.O..
OXOXOO.O.
.XXXO.O..
X.X.XO.O.
XXOX.XO..
OOOOXXX..
.XXXXXO..
.XOO.....
Network preceding move: {'ply': 49, 'by': 'net', 'move': 2, 'top5': [[2, 0.9746227264404297], [61, 0.012330153025686741], [77, 0.001977920066565275], [70, 0.0017896989593282342], [62, 0.0010640163673087955]]}
X..X.O.O.
.X.XX.O..
OX.XOO.O.
.XXXO.O..
X.X.XO.O.
XXOX.XO..
OOOOXXX..
.XXXXXO..
.XOO.....
PLY 52 {'ply': 52, 'by': 'strong', 'move': 63}
Two plies before:
X..X.O.O.
.X.XX.O..
OX.XOO.O.
.XXXO.O..
X.X.XO.O.
XXOX.XO..
OOOOXXX..
.XXXXXO..
.XOO.....
Network preceding move: {'ply': 51, 'by': 'net', 'move': 44, 'top5': [[61, 0.48729991912841797], [77, 0.07816938310861588], [70, 0.07073068618774414], [62, 0.042050983756780624], [52, 0.04000001400709152]]}
X..X.O.O.
.X.XX.O..
OX.XOO.O.
.XXXO.O..
X.X.XO.OO
XX.X.XO..
....XXX..
XXXXXXO..
.XOO.....
PLY 60 {'ply': 60, 'by': 'strong', 'move': 76}
Two plies before:
X..X.O.O.
.X.XX.O..
OX.XOO.O.
.XXXO.O..
X.X.XO.OO
XX.X.XOXX
..O.XXX..
XXXXXXOX.
.XOO.OO..
Network preceding move: {'ply': 59, 'by': 'net', 'move': 42, 'top5': [[76, 0.8328378796577454], [42, 0.16481834650039673], [17, 0.00029371128766797483], [80, 0.00028503115754574537], [62, 0.00026576139498502016]]}
X..X.O.O.
.X.XX.O..
OX.XOO.O.
.XXXO.O..
X.X.XOOOO
XX.X.XOXX
..O.XXX..
XXXXXXOX.
.X..XOO..
GAME 66 black -22.5 two_passes
PLY 53 {'ply': 53, 'by': 'strong', 'move': 4}
Two plies before:
..OX.X...
XOOXXOX..
OOOXOOXX.
XOOOOOOX.
XXXOO.X..
XOOO.X.X.
XXXOX.X..
.OOOOX...
........X
Network preceding move: {'ply': 52, 'by': 'net', 'move': 1, 'top5': [[1, 0.9998565912246704], [4, 0.00014336139429360628], [70, 3.3977807234464308e-09], [49, 2.61985855232183e-09], [41, 1.5115222407047213e-09]]}
.XO.OX...
XOO..OX..
OOO.OOXX.
XOOOOOOX.
XXXOO.X..
XOOO.X.X.
XXXOX.X..
.OOOOX...
........X
PLY 65 {'ply': 65, 'by': 'strong', 'move': 0}
Two plies before:
.XOOOXX..
XOOX.OX..
OOO.OOXX.
XOOOOOOX.
XXXOOXX..
XOOOOX.X.
XXXOXXX..
.OOOOX.X.
...O.OO.X
Network preceding move: {'ply': 64, 'by': 'net', 'move': 21, 'top5': [[21, 0.8544570207595825], [13, 0.14554159343242645], [62, 2.38884553027674e-07], [44, 2.1615203138480865e-07], [17, 2.0560953828407946e-07]]}
O.OOOXX..
.OOX.OX..
OOOXOOXX.
XOOOOOOX.
XXXOOXX..
XOOOOX.X.
XXXOXXX..
.OOOOX.X.
...O.OO.X
PLY 67 {'ply': 67, 'by': 'strong', 'move': 13}
Two plies before:
O.OOOXX..
.OOX.OX..
OOOXOOXX.
XOOOOOOX.
XXXOOXX..
XOOOOX.X.
XXXOXXX..
.OOOOX.X.
...O.OO.X
Network preceding move: {'ply': 66, 'by': 'net', 'move': 62, 'top5': [[62, 0.17392563819885254], [44, 0.15737466514110565], [17, 0.14969895780086517], [72, 0.11314017325639725], [7, 0.07972865551710129]]}
O.OOOXX..
.OO.OOX..
OOO.OOXX.
XOOOOOOX.
XXXOOXX..
XOOOOX.X.
XXXOXXX.X
.OOOOX.X.
...O.OO.X
GAME 79 white 6.5 repetition
PLY 77 {'ply': 77, 'by': 'net', 'move': 6, 'top5': [[6, 0.9999865293502808], [5, 1.1421526323829312e-05], [77, 9.85599967862072e-07], [75, 5.04340846418927e-07], [19, 4.6556442612200044e-07]]}
OOXX..O.O
.OXXXXXO.
O.OOOXOOO
XO.OXXXXO
XXOOOXXXO
XOOXOOXXO
XOXXOOOXO
XXXXXXXXO
..X.O.X.O
PLY 78 {'ply': 78, 'by': 'strong', 'move': 77}
OOXX..O.O
.OXXXXXO.
O.OOOXOOO
XO.OXXXXO
XXOOOXXXO
XOOXOOXXO
XOXXOOOXO
XXXXXXXXO
..X.OXX.O
PLY 79 {'ply': 79, 'by': 'net', 'move': 79, 'top5': [[79, 1.0], [5, 3.5029515095888475e-13], [19, 2.354165785380634e-14], [7, 1.253812812173358e-14], [81, 5.214061125776391e-16]]}
OOXX..O.O
.OXXXXXO.
O.OOOXOOO
XO.OXXXXO
XXOOOXXXO
XOOXOOXXO
XOXXOOOXO
XXXXXXXXO
..X.OXXOO
PLY 80 {'ply': 80, 'by': 'strong', 'move': 4}
OOXXX.O.O
.OXXXXXO.
O.OOOXOOO
XO.OXXXXO
XXOOOXXXO
XOOXOOXXO
XOXXOOOXO
XXXXXXXXO
..X.OXXOO
PLY 81 {'ply': 81, 'by': 'net', 'move': 5, 'top5': [[5, 1.0], [19, 4.8473686869998645e-11], [7, 2.9108396248922475e-11], [81, 1.0736045299303276e-12], [29, 3.842764187368328e-14]]}
OOXXXOO.O
.OXXXXXO.
O.OOOXOOO
XO.OXXXXO
XXOOOXXXO
XOOXOOXXO
XOXXOOOXO
XXXXXXXXO
..X.OXXOO
PLY 82 {'ply': 82, 'by': 'strong', 'move': 7}
OOXXX..XO
.OXXXXXO.
O.OOOXOOO
XO.OXXXXO
XXOOOXXXO
XOOXOOXXO
XOXXOOOXO
XXXXXXXXO
..X.OXXOO
PLY 83 {'ply': 83, 'by': 'net', 'move': 6, 'top5': [[6, 0.9999997615814209], [19, 2.686100515347789e-07], [81, 5.949226888901649e-09], [29, 2.1294130347904172e-10], [72, 1.9317570112975524e-11]]}
OOXXX.O.O
.OXXXXXO.
O.OOOXOOO
XO.OXXXXO
XXOOOXXXO
XOOXOOXXO
XOXXOOOXO
XXXXXXXXO
..X.OXXOO
GAME 85 white 24.5 repetition
PLY 67 {'ply': 67, 'by': 'net', 'move': 62, 'top5': [[62, 1.0], [6, 6.7077672305515534e-09], [75, 6.509530692255794e-09], [74, 3.75566111543435e-09], [5, 3.4324283415543277e-09]]}
..O.O....
OOOOO.OOO
O.O.OOXXX
..O..OOOX
OOOOOOXXX
XXXXOXXXO
.XOOOXXXO
OXXXXXOO.
.....XX.O
PLY 68 {'ply': 68, 'by': 'strong', 'move': 71}
..O.O....
OOOOO.OOO
O.O.OOXXX
..O..OOOX
OOOOOOXXX
XXXXOXXX.
.XOOOXXX.
OXXXXXOOX
.....XX.O
PLY 69 {'ply': 69, 'by': 'net', 'move': 62, 'top5': [[62, 0.9999681711196899], [6, 6.022376965120202e-06], [75, 5.844396127940854e-06], [74, 3.371912953298306e-06], [5, 3.0817079732514685e-06]]}
..O.O....
OOOOO.OOO
O.O.OOXXX
..O..OOOX
OOOOOOXXX
XXXXOXXX.
.XOOOXXXO
OXXXXXOO.
.....XX.O
PLY 70 {'ply': 70, 'by': 'strong', 'move': 7}
..O.O..X.
OOOOO.OOO
O.O.OOXXX
..O..OOOX
OOOOOOXXX
XXXXOXXX.
.XOOOXXXO
OXXXXXOO.
.....XX.O
PLY 71 {'ply': 71, 'by': 'net', 'move': 53, 'top5': [[53, 1.0], [6, 1.2011325267735629e-09], [75, 1.003269911592497e-09], [5, 9.169160430921863e-10], [74, 5.788346468804662e-10]]}
..O.O..X.
OOOOO.OOO
O.O.OOXXX
..O..OOOX
OOOOOOXXX
XXXXOXXXO
.XOOOXXXO
OXXXXXOO.
.....XX.O
PLY 72 {'ply': 72, 'by': 'strong', 'move': 71}
..O.O..X.
OOOOO.OOO
O.O.OOXXX
..O..OOOX
OOOOOOXXX
XXXXOXXX.
.XOOOXXX.
OXXXXXOOX
.....XX.O
PLY 73 {'ply': 73, 'by': 'net', 'move': 62, 'top5': [[62, 0.9999678134918213], [6, 6.997012405918213e-06], [75, 5.8443938542041e-06], [5, 5.341353244148195e-06], [74, 3.371911816429929e-06]]}
..O.O..X.
OOOOO.OOO
O.O.OOXXX
..O..OOOX
OOOOOOXXX
XXXXOXXX.
.XOOOXXXO
OXXXXXOO.
.....XX.O
```Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 5 of at most 120:
```
GAME 65 white -2.5 two_passes
PLY 50 {'ply': 50, 'by': 'strong', 'move': 0}
Two plies before:
.O.X.O.O.
.XOXX.O..
OXOXOO.O.
.XXXO.O..
X.X.XO.O.
XXOX.XO..
OOOOXXX..
.XXXXXO..
.XOO.....
Network preceding move: {'ply': 49, 'by': 'net', 'move': 2, 'top5': [[2, 0.9746227264404297], [61, 0.012330153025686741], [77, 0.001977920066565275], [70, 0.0017896989593282342], [62, 0.0010640163673087955]]}
X..X.O.O.
.X.XX.O..
OX.XOO.O.
.XXXO.O..
X.X.XO.O.
XXOX.XO..
OOOOXXX..
.XXXXXO..
.XOO.....
PLY 52 {'ply': 52, 'by': 'strong', 'move': 63}
Two plies before:
X..X.O.O.
.X.XX.O..
OX.XOO.O.
.XXXO.O..
X.X.XO.O.
XXOX.XO..
OOOOXXX..
.XXXXXO..
.XOO.....
Network preceding move: {'ply': 51, 'by': 'net', 'move': 44, 'top5': [[61, 0.48729991912841797], [77, 0.07816938310861588], [70, 0.07073068618774414], [62, 0.042050983756780624], [52, 0.04000001400709152]]}
X..X.O.O.
.X.XX.O..
OX.XOO.O.
.XXXO.O..
X.X.XO.OO
XX.X.XO..
....XXX..
XXXXXXO..
.XOO.....
PLY 60 {'ply': 60, 'by': 'strong', 'move': 76}
Two plies before:
X..X.O.O.
.X.XX.O..
OX.XOO.O.
.XXXO.O..
X.X.XO.OO
XX.X.XOXX
..O.XXX..
XXXXXXOX.
.XOO.OO..
Network preceding move: {'ply': 59, 'by': 'net', 'move': 42, 'top5': [[76, 0.8328378796577454], [42, 0.16481834650039673], [17, 0.00029371128766797483], [80, 0.00028503115754574537], [62, 0.00026576139498502016]]}
X..X.O.O.
.X.XX.O..
OX.XOO.O.
.XXXO.O..
X.X.XOOOO
XX.X.XOXX
..O.XXX..
XXXXXXOX.
.X..XOO..
GAME 66 black -22.5 two_passes
PLY 53 {'ply': 53, 'by': 'strong', 'move': 4}
Two plies before:
..OX.X...
XOOXXOX..
OOOXOOXX.
XOOOOOOX.
XXXOO.X..
XOOO.X.X.
XXXOX.X..
.OOOOX...
........X
Network preceding move: {'ply': 52, 'by': 'net', 'move': 1, 'top5': [[1, 0.9998565912246704], [4, 0.00014336139429360628], [70, 3.3977807234464308e-09], [49, 2.61985855232183e-09], [41, 1.5115222407047213e-09]]}
.XO.OX...
XOO..OX..
OOO.OOXX.
XOOOOOOX.
XXXOO.X..
XOOO.X.X.
XXXOX.X..
.OOOOX...
........X
PLY 65 {'ply': 65, 'by': 'strong', 'move': 0}
Two plies before:
.XOOOXX..
XOOX.OX..
OOO.OOXX.
XOOOOOOX.
XXXOOXX..
XOOOOX.X.
XXXOXXX..
.OOOOX.X.
...O.OO.X
Network preceding move: {'ply': 64, 'by': 'net', 'move': 21, 'top5': [[21, 0.8544570207595825], [13, 0.14554159343242645], [62, 2.38884553027674e-07], [44, 2.1615203138480865e-07], [17, 2.0560953828407946e-07]]}
O.OOOXX..
.OOX.OX..
OOOXOOXX.
XOOOOOOX.
XXXOOXX..
XOOOOX.X.
XXXOXXX..
.OOOOX.X.
...O.OO.X
PLY 67 {'ply': 67, 'by': 'strong', 'move': 13}
Two plies before:
O.OOOXX..
.OOX.OX..
OOOXOOXX.
XOOOOOOX.
XXXOOXX..
XOOOOX.X.
XXXOXXX..
.OOOOX.X.
...O.OO.X
Network preceding move: {'ply': 66, 'by': 'net', 'move': 62, 'top5': [[62, 0.17392563819885254], [44, 0.15737466514110565], [17, 0.14969895780086517], [72, 0.11314017325639725], [7, 0.07972865551710129]]}
O.OOOXX..
.OO.OOX..
OOO.OOXX.
XOOOOOOX.
XXXOOXX..
XOOOOX.X.
XXXOXXX.X
.OOOOX.X.
...O.OO.X
GAME 79 white 6.5 repetition
PLY 77 {'ply': 77, 'by': 'net', 'move': 6, 'top5': [[6, 0.9999865293502808], [5, 1.1421526323829312e-05], [77, 9.85599967862072e-07], [75, 5.04340846418927e-07], [19, 4.6556442612200044e-07]]}
OOXX..O.O
.OXXXXXO.
O.OOOXOOO
XO.OXXXXO
XXOOOXXXO
XOOXOOXXO
XOXXOOOXO
XXXXXXXXO
..X.O.X.O
PLY 78 {'ply': 78, 'by': 'strong', 'move': 77}
OOXX..O.O
.OXXXXXO.
O.OOOXOOO
XO.OXXXXO
XXOOOXXXO
XOOXOOXXO
XOXXOOOXO
XXXXXXXXO
..X.OXX.O
PLY 79 {'ply': 79, 'by': 'net', 'move': 79, 'top5': [[79, 1.0], [5, 3.5029515095888475e-13], [19, 2.354165785380634e-14], [7, 1.253812812173358e-14], [81, 5.214061125776391e-16]]}
OOXX..O.O
.OXXXXXO.
O.OOOXOOO
XO.OXXXXO
XXOOOXXXO
XOOXOOXXO
XOXXOOOXO
XXXXXXXXO
..X.OXXOO
PLY 80 {'ply': 80, 'by': 'strong', 'move': 4}
OOXXX.O.O
.OXXXXXO.
O.OOOXOOO
XO.OXXXXO
XXOOOXXXO
XOOXOOXXO
XOXXOOOXO
XXXXXXXXO
..X.OXXOO
PLY 81 {'ply': 81, 'by': 'net', 'move': 5, 'top5': [[5, 1.0], [19, 4.8473686869998645e-11], [7, 2.9108396248922475e-11], [81, 1.0736045299303276e-12], [29, 3.842764187368328e-14]]}
OOXXXOO.O
.OXXXXXO.
O.OOOXOOO
XO.OXXXXO
XXOOOXXXO
XOOXOOXXO
XOXXOOOXO
XXXXXXXXO
..X.OXXOO
PLY 82 {'ply': 82, 'by': 'strong', 'move': 7}
OOXXX..XO
.OXXXXXO.
O.OOOXOOO
XO.OXXXXO
XXOOOXXXO
XOOXOOXXO
XOXXOOOXO
XXXXXXXXO
..X.OXXOO
PLY 83 {'ply': 83, 'by': 'net', 'move': 6, 'top5': [[6, 0.9999997615814209], [19, 2.686100515347789e-07], [81, 5.949226888901649e-09], [29, 2.1294130347904172e-10], [72, 1.9317570112975524e-11]]}
OOXXX.O.O
.OXXXXXO.
O.OOOXOOO
XO.OXXXXO
XXOOOXXXO
XOOXOOXXO
XOXXOOOXO
XXXXXXXXO
..X.OXXOO
GAME 85 white 24.5 repetition
PLY 67 {'ply': 67, 'by': 'net', 'move': 62, 'top5': [[62, 1.0], [6, 6.7077672305515534e-09], [75, 6.509530692255794e-09], [74, 3.75566111543435e-09], [5, 3.4324283415543277e-09]]}
..O.O....
OOOOO.OOO
O.O.OOXXX
..O..OOOX
OOOOOOXXX
XXXXOXXXO
.XOOOXXXO
OXXXXXOO.
.....XX.O
PLY 68 {'ply': 68, 'by': 'strong', 'move': 71}
..O.O....
OOOOO.OOO
O.O.OOXXX
..O..OOOX
OOOOOOXXX
XXXXOXXX.
.XOOOXXX.
OXXXXXOOX
.....XX.O
PLY 69 {'ply': 69, 'by': 'net', 'move': 62, 'top5': [[62, 0.9999681711196899], [6, 6.022376965120202e-06], [75, 5.844396127940854e-06], [74, 3.371912953298306e-06], [5, 3.0817079732514685e-06]]}
..O.O....
OOOOO.OOO
O.O.OOXXX
..O..OOOX
OOOOOOXXX
XXXXOXXX.
.XOOOXXXO
OXXXXXOO.
.....XX.O
PLY 70 {'ply': 70, 'by': 'strong', 'move': 7}
..O.O..X.
OOOOO.OOO
O.O.OOXXX
..O..OOOX
OOOOOOXXX
XXXXOXXX.
.XOOOXXXO
OXXXXXOO.
.....XX.O
PLY 71 {'ply': 71, 'by': 'net', 'move': 53, 'top5': [[53, 1.0], [6, 1.2011325267735629e-09], [75, 1.003269911592497e-09], [5, 9.169160430921863e-10], [74, 5.788346468804662e-10]]}
..O.O..X.
OOOOO.OOO
O.O.OOXXX
..O..OOOX
OOOOOOXXX
XXXXOXXXO
.XOOOXXXO
OXXXXXOO.
.....XX.O
PLY 72 {'ply': 72, 'by': 'strong', 'move': 71}
..O.O..X.
OOOOO.OOO
O.O.OOXXX
..O..OOOX
OOOOOOXXX
XXXXOXXX.
.XOOOXXX.
OXXXXXOOX
.....XX.O
PLY 73 {'ply': 73, 'by': 'net', 'move': 62, 'top5': [[62, 0.9999678134918213], [6, 6.997012405918213e-06], [75, 5.8443938542041e-06], [5, 5.341353244148195e-06], [74, 3.371911816429929e-06]]}
..O.O..X.
OOOOO.OOO
O.O.OOXXX
..O..OOOX
OOOOOOXXX
XXXXOXXX.
.XOOOXXXO
OXXXXXOO.
.....XX.O
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import numpy as np
np.savez("/work/policy_v1.npz", **{name:load(name) for name in NAMES})
design2 = r'''
import numpy as np
def build_policy_v2():
A = {name:np.zeros(shape,np.float32) for name,shape in SHAPES.items()}
def u(ch,p): return 81*ch+p
def add(k,i,j,w): A[f"L{k}.W"][i,j] += w
def bias(k,j,b): A[f"L{k}.b"][j] += b
def copy(k,a,b):
for p in range(81): add(k,u(a,p),u(b,p),1)
def neighbors(p,offsets):
r,c=divmod(p,9)
return [(r+dr)*9+c+dc for dr,dc in offsets
if 0<=r+dr<9 and 0<=c+dc<9]
n=[neighbors(p,[(-1,0),(1,0),(0,-1),(0,1)]) for p in range(81)]
dg=[neighbors(p,[(-1,-1),(-1,1),(1,-1),(1,1)]) for p in range(81)]
a2=[neighbors(p,[(-2,0),(2,0),(0,-2),(0,2)]) for p in range(81)]
kn=[neighbors(p,[(r,c) for r in range(-2,3) for c in range(-2,3)
if abs(r)*abs(c)==2]) for p in range(81)]
a3=[neighbors(p,[(-3,0),(3,0),(0,-3),(0,3)]) for p in range(81)]
# Integer identifiers are only algebraic liberty fingerprints.
# No examples, labels, fitting, or network evaluation are used.
codes=np.random.default_rng(90173).choice(np.arange(1,1010),81,replace=False)
for p in range(81):
d=len(n[p])
add(1,3*p,u(0,p),1)
add(1,3*p+1,u(1,p),1)
for color,ch in [(0,2),(1,3)]:
add(1,3*p+color,u(ch,p),d)
for q in n[p]:
add(1,3*q,u(ch,p),-1)
add(1,3*q+1,u(ch,p),-1)
add(1,3*p+1,u(4,p),sum(codes[q] for q in n[p]))
for q in n[p]:
add(1,3*q,u(4,p),-codes[q])
add(1,3*q+1,u(4,p),-codes[q])
bias(1,u(5,p),-2*d)
add(1,3*p,u(5,p),d+1)
for q in n[p]:
add(1,3*q,u(5,p),1)
add(1,3*q+1,u(5,p),1)
add(1,2,486,1)
bias(1,489,24)
for p in range(81):
add(1,3*p,489,-1)
add(1,3*p+1,489,-1)
for k in range(2,7):
add(k,486,486,1)
add(k,489,489,1)
# Three rounds of same-colour message propagation. If an enemy
# component has only liberty q, code_sum == codes[q]*liberty_count,
# regardless of the number of propagation paths reaching it.
for k in (2,3,4):
copy(k,0,0)
copy(k,1,1)
for p in range(81):
for ch in (3,4):
gate={2:10000,3:50000,4:250000}[k] if ch==3 else {
2:100000,3:500000,4:2500000}[k]
bias(k,u(ch,p),-gate)
add(k,u(1,p),u(ch,p),gate)
for q in [p]+n[p]:
add(k,u(ch,q),u(ch,p),1)
if k in (2,3):
copy(k,2,2)
if k==2:
for p in range(81):
bias(k,u(5,p),-21)
add(k,u(0,p),u(5,p),20)
add(k,u(5,p),u(5,p),-1)
for q in [p]+n[p]:
add(k,u(2,q),u(5,p),1)
else:
for p in range(81):
gate=128 if k==3 else 1024
bias(k,u(5,p),-gate)
add(k,u(0,p),u(5,p),gate)
for q in [p]+n[p]:
add(k,u(5,q),u(5,p),1)
if k==4:
add(k,u(0,p),u(2,p),2)
add(k,u(2,p),u(2,p),-1)
for q in [p]+n[p]:
add(k,u(5,q),u(2,p),-2)
for p in range(81):
d=len(n[p])
# Positive and negative deviations from "p is the only liberty".
for ch,sign in [(0,1),(1,-1)]:
bias(5,u(ch,p),1)
for q in n[p]:
add(5,u(4,q),u(ch,p),8*sign)
add(5,u(3,q),u(ch,p),-8*sign*codes[p])
add(5,u(1,q),u(ch,p),-1)
bias(5,u(2,p),100)
for qs,wo,we in [(n[p],-1.9,-0.8),(dg[p],-0.15,0.35),
(a2[p],0.55,0.55),(kn[p],0.2,0.2),
(a3[p],0.1,0.1)]:
for q in qs:
add(5,u(0,q),u(2,p),wo)
add(5,u(1,q),u(2,p),we)
bias(5,u(3,p),2-d)
for q in n[p]:
add(5,u(0,q),u(3,p),1)
add(5,u(1,q),u(3,p),1)
add(5,u(5,q),u(3,p),-2)
bias(5,u(4,p),1-d)
for q in n[p]:
add(5,u(0,q),u(4,p),1)
for q in dg[p]:
add(5,u(1,q),u(4,p),-0.5 if d==4 else -1)
for q in n[p]:
add(5,u(2,q),u(5,p),1)
# Final maps: base, capture, rescue, self-atari, capture relief, eye.
add(6,u(2,p),u(0,p),1)
bias(6,u(1,p),1)
add(6,u(0,p),u(1,p),-1)
add(6,u(1,p),u(1,p),-1)
add(6,u(5,p),u(2,p),1)
add(6,u(3,p),u(2,p),-8)
add(6,u(4,p),u(2,p),-2)
add(6,u(3,p),u(3,p),1)
add(6,u(3,p),u(4,p),1)
add(6,u(0,p),u(4,p),-2)
add(6,u(1,p),u(4,p),-2)
add(6,u(4,p),u(5,p),1)
r,c=divmod(p,9)
edge=min(r,c,8-r,8-c)
rr,cc=min(r,8-r),min(c,8-c)
opening=1.6 if (rr,cc)==(2,2) else (
1.15 if (rr,cc) in [(2,3),(3,2)] else (
0.5 if (rr,cc)==(3,3) else 0))
A["out.b"][p]=[-1.6,-0.15,0.65,0.45,0.25][edge]-100
A["out.W"][489,p]=opening/24
for ch,w in [(0,1),(1,11),(2,8),(3,-11),(4,11),(5,-14)]:
A["out.W"][u(ch,p),p]=w
A["out.b"][81]=-7
A["out.W"][486,81]=0.4
return A
weights=build_policy_v2()
for name in NAMES: save(name,weights[name])
print("Saved liberty-fingerprint policy:",sum(np.count_nonzero(a) for a in weights.values()),
"nonzero parameters.")
'''
open("/work/design_v2.py","w").write(design2)
exec(design2)
```
{
"request_sha256": "2ede74eb12f252d5dc601b806a6bddec96e3ad14d764a7938c3f18babc3324c4",
"request": {
"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import numpy as np\n\nnp.savez(\"/work/policy_v1.npz\", **{name:load(name) for name in NAMES})\n\ndesign2 = r'''\nimport numpy as np\n\ndef build_policy_v2():\n A = {name:np.zeros(shape,np.float32) for name,shape in SHAPES.items()}\n def u(ch,p): return 81*ch+p\n def add(k,i,j,w): A[f\"L{k}.W\"][i,j] += w\n def bias(k,j,b): A[f\"L{k}.b\"][j] += b\n def copy(k,a,b):\n for p in range(81): add(k,u(a,p),u(b,p),1)\n def neighbors(p,offsets):\n r,c=divmod(p,9)\n return [(r+dr)*9+c+dc for dr,dc in offsets\n if 0<=r+dr<9 and 0<=c+dc<9]\n n=[neighbors(p,[(-1,0),(1,0),(0,-1),(0,1)]) for p in range(81)]\n dg=[neighbors(p,[(-1,-1),(-1,1),(1,-1),(1,1)]) for p in range(81)]\n a2=[neighbors(p,[(-2,0),(2,0),(0,-2),(0,2)]) for p in range(81)]\n kn=[neighbors(p,[(r,c) for r in range(-2,3) for c in range(-2,3)\n if abs(r)*abs(c)==2]) for p in range(81)]\n a3=[neighbors(p,[(-3,0),(3,0),(0,-3),(0,3)]) for p in range(81)]\n\n # Integer identifiers are only algebraic liberty fingerprints.\n # No examples, labels, fitting, or network evaluation are used.\n codes=np.random.default_rng(90173).choice(np.arange(1,1010),81,replace=False)\n for p in range(81):\n d=len(n[p])\n add(1,3*p,u(0,p),1)\n add(1,3*p+1,u(1,p),1)\n for color,ch in [(0,2),(1,3)]:\n add(1,3*p+color,u(ch,p),d)\n for q in n[p]:\n add(1,3*q,u(ch,p),-1)\n add(1,3*q+1,u(ch,p),-1)\n add(1,3*p+1,u(4,p),sum(codes[q] for q in n[p]))\n for q in n[p]:\n add(1,3*q,u(4,p),-codes[q])\n add(1,3*q+1,u(4,p),-codes[q])\n bias(1,u(5,p),-2*d)\n add(1,3*p,u(5,p),d+1)\n for q in n[p]:\n add(1,3*q,u(5,p),1)\n add(1,3*q+1,u(5,p),1)\n\n add(1,2,486,1)\n bias(1,489,24)\n for p in range(81):\n add(1,3*p,489,-1)\n add(1,3*p+1,489,-1)\n for k in range(2,7):\n add(k,486,486,1)\n add(k,489,489,1)\n\n # Three rounds of same-colour message propagation. If an enemy\n # component has only liberty q, code_sum == codes[q]*liberty_count,\n # regardless of the number of propagation paths reaching it.\n for k in (2,3,4):\n copy(k,0,0)\n copy(k,1,1)\n for p in range(81):\n for ch in (3,4):\n gate={2:10000,3:50000,4:250000}[k] if ch==3 else {\n 2:100000,3:500000,4:2500000}[k]\n bias(k,u(ch,p),-gate)\n add(k,u(1,p),u(ch,p),gate)\n for q in [p]+n[p]:\n add(k,u(ch,q),u(ch,p),1)\n\n if k in (2,3):\n copy(k,2,2)\n if k==2:\n for p in range(81):\n bias(k,u(5,p),-21)\n add(k,u(0,p),u(5,p),20)\n add(k,u(5,p),u(5,p),-1)\n for q in [p]+n[p]:\n add(k,u(2,q),u(5,p),1)\n else:\n for p in range(81):\n gate=128 if k==3 else 1024\n bias(k,u(5,p),-gate)\n add(k,u(0,p),u(5,p),gate)\n for q in [p]+n[p]:\n add(k,u(5,q),u(5,p),1)\n if k==4:\n add(k,u(0,p),u(2,p),2)\n add(k,u(2,p),u(2,p),-1)\n for q in [p]+n[p]:\n add(k,u(5,q),u(2,p),-2)\n\n for p in range(81):\n d=len(n[p])\n # Positive and negative deviations from \"p is the only liberty\".\n for ch,sign in [(0,1),(1,-1)]:\n bias(5,u(ch,p),1)\n for q in n[p]:\n add(5,u(4,q),u(ch,p),8*sign)\n add(5,u(3,q),u(ch,p),-8*sign*codes[p])\n add(5,u(1,q),u(ch,p),-1)\n\n bias(5,u(2,p),100)\n for qs,wo,we in [(n[p],-1.9,-0.8),(dg[p],-0.15,0.35),\n (a2[p],0.55,0.55),(kn[p],0.2,0.2),\n (a3[p],0.1,0.1)]:\n for q in qs:\n add(5,u(0,q),u(2,p),wo)\n add(5,u(1,q),u(2,p),we)\n\n bias(5,u(3,p),2-d)\n for q in n[p]:\n add(5,u(0,q),u(3,p),1)\n add(5,u(1,q),u(3,p),1)\n add(5,u(5,q),u(3,p),-2)\n\n bias(5,u(4,p),1-d)\n for q in n[p]:\n add(5,u(0,q),u(4,p),1)\n for q in dg[p]:\n add(5,u(1,q),u(4,p),-0.5 if d==4 else -1)\n\n for q in n[p]:\n add(5,u(2,q),u(5,p),1)\n\n # Final maps: base, capture, rescue, self-atari, capture relief, eye.\n add(6,u(2,p),u(0,p),1)\n bias(6,u(1,p),1)\n add(6,u(0,p),u(1,p),-1)\n add(6,u(1,p),u(1,p),-1)\n add(6,u(5,p),u(2,p),1)\n add(6,u(3,p),u(2,p),-8)\n add(6,u(4,p),u(2,p),-2)\n add(6,u(3,p),u(3,p),1)\n add(6,u(3,p),u(4,p),1)\n add(6,u(0,p),u(4,p),-2)\n add(6,u(1,p),u(4,p),-2)\n add(6,u(4,p),u(5,p),1)\n\n r,c=divmod(p,9)\n edge=min(r,c,8-r,8-c)\n rr,cc=min(r,8-r),min(c,8-c)\n opening=1.6 if (rr,cc)==(2,2) else (\n 1.15 if (rr,cc) in [(2,3),(3,2)] else (\n 0.5 if (rr,cc)==(3,3) else 0))\n A[\"out.b\"][p]=[-1.6,-0.15,0.65,0.45,0.25][edge]-100\n A[\"out.W\"][489,p]=opening/24\n for ch,w in [(0,1),(1,11),(2,8),(3,-11),(4,11),(5,-14)]:\n A[\"out.W\"][u(ch,p),p]=w\n A[\"out.b\"][81]=-7\n A[\"out.W\"][486,81]=0.4\n return A\n\nweights=build_policy_v2()\nfor name in NAMES: save(name,weights[name])\nprint(\"Saved liberty-fingerprint policy:\",sum(np.count_nonzero(a) for a in weights.values()),\n \"nonzero parameters.\")\n'''\nopen(\"/work/design_v2.py\",\"w\").write(design2)\nexec(design2)"
},
"result": {
"ok": true,
"out": "Saved liberty-fingerprint policy: 17386 nonzero parameters.\n",
"stdout": "Saved liberty-fingerprint policy: 17386 nonzero parameters.\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.2813103897497058,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-2914abcf8712441293325470ecd1fa29",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
"-i",
"HOME=/tmp",
"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
"MKL_NUM_THREADS=8",
"CUDA_VISIBLE_DEVICES=",
"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 6 of at most 120: ``` Saved liberty-fingerprint policy: 17386 nonzero parameters. ```
Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 6 of at most 120: ``` Saved liberty-fingerprint policy: 17386 nonzero parameters. ```
Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```games
{"games":{"strong":96,"weak":16,"random":16}}
```{
"request_sha256": "84da2a07b90954a011625933cc8fdedc8298795786461a3cc8599667ee417066",
"request": {
"kind": "games",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"pass": 2,
"request": {
"games": {
"strong": 96,
"weak": 16,
"random": 16
}
}
},
"result": {
"ok": true,
"pass": 2,
"kind": "games",
"per_opponent": {
"random": {
"games": 16,
"score": 1.0,
"wins": 16,
"losses": 0,
"score_as_black": 1.0,
"score_as_white": 1.0,
"mean_margin": 71.375,
"mean_length": 121.0625,
"stones_captured_per_game": 51.0625,
"stones_lost_per_game": 3.25,
"network_passes_per_game": 1.1875,
"all_player_passes_per_game": 6.1875,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 10,
"end_repetition": 0,
"end_two_passes": 16,
"end_move_limit": 0
},
"weak": {
"games": 16,
"score": 0.6875,
"wins": 11,
"losses": 5,
"score_as_black": 0.5,
"score_as_white": 0.875,
"mean_margin": 43.1875,
"mean_length": 117.0,
"stones_captured_per_game": 37.9375,
"stones_lost_per_game": 10.0625,
"network_passes_per_game": 1.375,
"all_player_passes_per_game": 4.8125,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 5,
"end_repetition": 0,
"end_two_passes": 16,
"end_move_limit": 0
},
"strong": {
"games": 96,
"score": 0.20833333333333334,
"wins": 20,
"losses": 76,
"score_as_black": 0.14583333333333334,
"score_as_white": 0.2708333333333333,
"mean_margin": -3.1354166666666665,
"mean_length": 101.32291666666667,
"stones_captured_per_game": 10.760416666666666,
"stones_lost_per_game": 17.697916666666668,
"network_passes_per_game": 2.3020833333333335,
"all_player_passes_per_game": 4.1875,
"games_with_network_pass_before_move_60": 1,
"games_with_any_pass_before_move_60": 1,
"end_repetition": 0,
"end_two_passes": 96,
"end_move_limit": 0
}
},
"files": "/work/pass_2/"
}
}Games pass 2 of 10 done.
```
{"ok": true, "pass": 2, "kind": "games", "per_opponent": {"random": {"games": 16, "score": 1.0, "wins": 16, "losses": 0, "score_as_black": 1.0, "score_as_white": 1.0, "mean_margin": 71.375, "mean_length": 121.0625, "stones_captured_per_game": 51.0625, "stones_lost_per_game": 3.25, "network_passes_per_game": 1.1875, "all_player_passes_per_game": 6.1875, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 10, "end_repetition": 0, "end_two_passes": 16, "end_move_limit": 0}, "weak": {"games": 16, "score": 0.6875, "wins": 11, "losses": 5, "score_as_black": 0.5, "score_as_white": 0.875, "mean_margin": 43.1875, "mean_length": 117.0, "stones_captured_per_game": 37.9375, "stones_lost_per_game": 10.0625, "network_passes_per_game": 1.375, "all_player_passes_per_game": 4.8125, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 5, "end_repetition": 0, "end_two_passes": 16, "end_move_limit": 0}, "strong": {"games": 96, "score": 0.20833333333333334, "wins": 20, "losses": 76, "score_as_black": 0.14583333333333334, "score_as_white": 0.2708333333333333, "mean_margin": -3.1354166666666665, "mean_length": 101.32291666666667, "stones_captured_per_game": 10.760416666666666, "stones_lost_per_game": 17.697916666666668, "network_passes_per_game": 2.3020833333333335, "all_player_passes_per_game": 4.1875, "games_with_network_pass_before_move_60": 1, "games_with_any_pass_before_move_60": 1, "end_repetition": 0, "end_two_passes": 96, "end_move_limit": 0}}, "files": "/work/pass_2/"}
```Exact prompt · Raw CLI events · Settings and audit
Games pass 2 of 10 done.
```
{"ok": true, "pass": 2, "kind": "games", "per_opponent": {"random": {"games": 16, "score": 1.0, "wins": 16, "losses": 0, "score_as_black": 1.0, "score_as_white": 1.0, "mean_margin": 71.375, "mean_length": 121.0625, "stones_captured_per_game": 51.0625, "stones_lost_per_game": 3.25, "network_passes_per_game": 1.1875, "all_player_passes_per_game": 6.1875, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 10, "end_repetition": 0, "end_two_passes": 16, "end_move_limit": 0}, "weak": {"games": 16, "score": 0.6875, "wins": 11, "losses": 5, "score_as_black": 0.5, "score_as_white": 0.875, "mean_margin": 43.1875, "mean_length": 117.0, "stones_captured_per_game": 37.9375, "stones_lost_per_game": 10.0625, "network_passes_per_game": 1.375, "all_player_passes_per_game": 4.8125, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 5, "end_repetition": 0, "end_two_passes": 16, "end_move_limit": 0}, "strong": {"games": 96, "score": 0.20833333333333334, "wins": 20, "losses": 76, "score_as_black": 0.14583333333333334, "score_as_white": 0.2708333333333333, "mean_margin": -3.1354166666666665, "mean_length": 101.32291666666667, "stones_captured_per_game": 10.760416666666666, "stones_lost_per_game": 17.697916666666668, "network_passes_per_game": 2.3020833333333335, "all_player_passes_per_game": 4.1875, "games_with_network_pass_before_move_60": 1, "games_with_any_pass_before_move_60": 1, "end_repetition": 0, "end_two_passes": 96, "end_move_limit": 0}}, "files": "/work/pass_2/"}
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import numpy as np
np.savez("/work/policy_v2.npz", **{name:load(name) for name in NAMES})
# Rebuild the first policy, then revise its internal rule circuit.
exec(open("/work/design.py").read())
A=build_policy()
def u(ch,p): return 81*ch+p
def neigh(p, offsets):
r,c=divmod(p,9)
return [(r+dr)*9+c+dc for dr,dc in offsets
if 0<=r+dr<9 and 0<=c+dc<9]
N=[neigh(p,[(-1,0),(1,0),(0,-1),(0,1)]) for p in range(81)]
D=[neigh(p,[(-1,-1),(-1,1),(1,-1),(1,1)]) for p in range(81)]
# L2-L3 now propagate separate certificates for two and three liberties.
# Direct liberty counts need not be retained: a stone adjacent to a legal
# candidate point necessarily has at least that one liberty.
oldbase=A["L4.W"][:,405:486].copy()
oldbasebias=A["L4.b"][405:486].copy()
for k in (2,3,4):
A[f"L{k}.W"][:,:486]=0
A[f"L{k}.b"][:486]=0
for k in (2,3,4):
for p in range(81):
for ch in (0,1):
A[f"L{k}.W"][u(ch,p),u(ch,p)]=1
for p in range(81):
for color,ch in [(0,2),(1,3)]:
A["L2.b"][u(ch,p)]=-21
A["L2.W"][u(color,p),u(ch,p)]=20
A["L2.W"][u(4+color,p),u(ch,p)]=-1
for q in [p]+N[p]:
A["L2.W"][u(2+color,q),u(ch,p)]+=1
A["L2.b"][u(4,p)]=-44
A["L2.W"][u(0,p),u(4,p)]=40
A["L2.W"][u(2,p),u(4,p)]=2
for q in N[p]:
A["L2.W"][u(2,q),u(4,p)]+=1
A["L2.W"][:,405:486]=oldbase
A["L2.b"][405:486]=oldbasebias
for p in range(81):
for ch,color in [(2,0),(3,1),(4,0)]:
A["L3.b"][u(ch,p)]=-256
A["L3.W"][u(color,p),u(ch,p)]=256
for q in [p]+N[p]:
A["L3.W"][u(ch,q),u(ch,p)]+=1
A["L3.W"][u(5,p),u(5,p)]=1
A["L4.W"][u(5,p),u(5,p)]=1
A["L4.b"][u(2,p)]=-2048
A["L4.W"][u(0,p),u(2,p)]=2048
for q in [p]+N[p]:
A["L4.W"][u(4,q),u(2,p)]+=1
for color,src,dst in [(0,2,4),(1,3,3)]:
A["L4.W"][u(color,p),u(dst,p)]=1
for q in [p]+N[p]:
A["L4.W"][u(src,q),u(dst,p)]-=2
# Friendly connections with two liberties suffice when the new move has
# an empty neighbour; a three-liberty certificate also protects tight moves.
for p in range(81):
for q in N[p]:
A["L5.W"][u(0,q),u(1,p)]-=1
A["L5.W"][u(4,q),u(1,p)]+=1
# Reward connecting nearby stones without rewarding an already filled-in
# triangle. Saturate the attack bonus instead of counting a chain repeatedly.
for ch in (3,4):
A["L5.W"][:,ch*81:(ch+1)*81]=0
A["L5.b"][ch*81:(ch+1)*81]=0
for p in range(81):
A["L5.b"][u(3,p)]=-1
for q in N[p]:
A["L5.W"][u(0,q),u(3,p)]=1
for q in D[p]:
A["L5.W"][u(0,q),u(3,p)]=-0.7
A["L5.b"][u(4,p)]=-1
for q in N[p]:
A["L5.W"][u(3,q),u(4,p)]=1
A["out.W"][u(3,p),p]=2.5
A["out.W"][u(4,p),p]=-9
# Unsupported contact is discouraged in the linear positional component.
for p in range(81):
for q in N[p]:
A["L2.W"][u(1,q),u(5,p)]-=0.85
for name in NAMES: save(name,A[name])
np.savez("/work/policy_v3.npz", **A)
print("Saved revised connection and distinct-liberty rule circuit.")
```
{
"request_sha256": "b24677ef783c8d3898b794a2f5ae2b5fcd7d88488085ff7413cc2e76fa236912",
"request": {
"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import numpy as np\nnp.savez(\"/work/policy_v2.npz\", **{name:load(name) for name in NAMES})\n\n# Rebuild the first policy, then revise its internal rule circuit.\nexec(open(\"/work/design.py\").read())\nA=build_policy()\n\ndef u(ch,p): return 81*ch+p\ndef neigh(p, offsets):\n r,c=divmod(p,9)\n return [(r+dr)*9+c+dc for dr,dc in offsets\n if 0<=r+dr<9 and 0<=c+dc<9]\nN=[neigh(p,[(-1,0),(1,0),(0,-1),(0,1)]) for p in range(81)]\nD=[neigh(p,[(-1,-1),(-1,1),(1,-1),(1,1)]) for p in range(81)]\n\n# L2-L3 now propagate separate certificates for two and three liberties.\n# Direct liberty counts need not be retained: a stone adjacent to a legal\n# candidate point necessarily has at least that one liberty.\noldbase=A[\"L4.W\"][:,405:486].copy()\noldbasebias=A[\"L4.b\"][405:486].copy()\nfor k in (2,3,4):\n A[f\"L{k}.W\"][:,:486]=0\n A[f\"L{k}.b\"][:486]=0\nfor k in (2,3,4):\n for p in range(81):\n for ch in (0,1):\n A[f\"L{k}.W\"][u(ch,p),u(ch,p)]=1\n\nfor p in range(81):\n for color,ch in [(0,2),(1,3)]:\n A[\"L2.b\"][u(ch,p)]=-21\n A[\"L2.W\"][u(color,p),u(ch,p)]=20\n A[\"L2.W\"][u(4+color,p),u(ch,p)]=-1\n for q in [p]+N[p]:\n A[\"L2.W\"][u(2+color,q),u(ch,p)]+=1\n A[\"L2.b\"][u(4,p)]=-44\n A[\"L2.W\"][u(0,p),u(4,p)]=40\n A[\"L2.W\"][u(2,p),u(4,p)]=2\n for q in N[p]:\n A[\"L2.W\"][u(2,q),u(4,p)]+=1\n\nA[\"L2.W\"][:,405:486]=oldbase\nA[\"L2.b\"][405:486]=oldbasebias\n\nfor p in range(81):\n for ch,color in [(2,0),(3,1),(4,0)]:\n A[\"L3.b\"][u(ch,p)]=-256\n A[\"L3.W\"][u(color,p),u(ch,p)]=256\n for q in [p]+N[p]:\n A[\"L3.W\"][u(ch,q),u(ch,p)]+=1\n A[\"L3.W\"][u(5,p),u(5,p)]=1\n A[\"L4.W\"][u(5,p),u(5,p)]=1\n\n A[\"L4.b\"][u(2,p)]=-2048\n A[\"L4.W\"][u(0,p),u(2,p)]=2048\n for q in [p]+N[p]:\n A[\"L4.W\"][u(4,q),u(2,p)]+=1\n for color,src,dst in [(0,2,4),(1,3,3)]:\n A[\"L4.W\"][u(color,p),u(dst,p)]=1\n for q in [p]+N[p]:\n A[\"L4.W\"][u(src,q),u(dst,p)]-=2\n\n# Friendly connections with two liberties suffice when the new move has\n# an empty neighbour; a three-liberty certificate also protects tight moves.\nfor p in range(81):\n for q in N[p]:\n A[\"L5.W\"][u(0,q),u(1,p)]-=1\n A[\"L5.W\"][u(4,q),u(1,p)]+=1\n\n# Reward connecting nearby stones without rewarding an already filled-in\n# triangle. Saturate the attack bonus instead of counting a chain repeatedly.\nfor ch in (3,4):\n A[\"L5.W\"][:,ch*81:(ch+1)*81]=0\n A[\"L5.b\"][ch*81:(ch+1)*81]=0\nfor p in range(81):\n A[\"L5.b\"][u(3,p)]=-1\n for q in N[p]:\n A[\"L5.W\"][u(0,q),u(3,p)]=1\n for q in D[p]:\n A[\"L5.W\"][u(0,q),u(3,p)]=-0.7\n A[\"L5.b\"][u(4,p)]=-1\n for q in N[p]:\n A[\"L5.W\"][u(3,q),u(4,p)]=1\n A[\"out.W\"][u(3,p),p]=2.5\n A[\"out.W\"][u(4,p),p]=-9\n\n# Unsupported contact is discouraged in the linear positional component.\nfor p in range(81):\n for q in N[p]:\n A[\"L2.W\"][u(1,q),u(5,p)]-=0.85\n\nfor name in NAMES: save(name,A[name])\nnp.savez(\"/work/policy_v3.npz\", **A)\nprint(\"Saved revised connection and distinct-liberty rule circuit.\")"
},
"result": {
"ok": true,
"out": "Saved all tensors; nonzero parameters: 16981\nDesign: connected-liberty signals, captures, safe escapes, eye protection, shape, opening placement, and passing.\nSaved revised connection and distinct-liberty rule circuit.\n",
"stdout": "Saved all tensors; nonzero parameters: 16981\nDesign: connected-liberty signals, captures, safe escapes, eye protection, shape, opening placement, and passing.\nSaved revised connection and distinct-liberty rule circuit.\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.4164086449891329,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-0a3c648f89654c6a89a2797118a84161",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
"-i",
"HOME=/tmp",
"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
"MKL_NUM_THREADS=8",
"CUDA_VISIBLE_DEVICES=",
"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 7 of at most 120: ``` Saved all tensors; nonzero parameters: 16981 Design: connected-liberty signals, captures, safe escapes, eye protection, shape, opening placement, and passing. Saved revised connection and distinct-liberty rule circuit. ```
Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 7 of at most 120: ``` Saved all tensors; nonzero parameters: 16981 Design: connected-liberty signals, captures, safe escapes, eye protection, shape, opening placement, and passing. Saved revised connection and distinct-liberty rule circuit. ```
Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```games
{"games":{"strong":96,"weak":16,"random":16}}
```{
"request_sha256": "782267659807ddaded180be86ce2bc8fac40df672b5407b2c110aa84c95735e8",
"request": {
"kind": "games",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"pass": 3,
"request": {
"games": {
"strong": 96,
"weak": 16,
"random": 16
}
}
},
"result": {
"ok": true,
"pass": 3,
"kind": "games",
"per_opponent": {
"random": {
"games": 16,
"score": 1.0,
"wins": 16,
"losses": 0,
"score_as_black": 1.0,
"score_as_white": 1.0,
"mean_margin": 81.0,
"mean_length": 129.125,
"stones_captured_per_game": 58.25,
"stones_lost_per_game": 0.625,
"network_passes_per_game": 1.0625,
"all_player_passes_per_game": 7.125,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 8,
"end_repetition": 0,
"end_two_passes": 16,
"end_move_limit": 0
},
"weak": {
"games": 16,
"score": 0.875,
"wins": 14,
"losses": 2,
"score_as_black": 0.75,
"score_as_white": 1.0,
"mean_margin": 58.4375,
"mean_length": 124.5625,
"stones_captured_per_game": 47.8125,
"stones_lost_per_game": 5.4375,
"network_passes_per_game": 1.75,
"all_player_passes_per_game": 5.4375,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 4,
"end_repetition": 0,
"end_two_passes": 15,
"end_move_limit": 1
},
"strong": {
"games": 96,
"score": 0.19791666666666666,
"wins": 19,
"losses": 77,
"score_as_black": 0.125,
"score_as_white": 0.2708333333333333,
"mean_margin": 2.3541666666666665,
"mean_length": 97.27083333333333,
"stones_captured_per_game": 11.90625,
"stones_lost_per_game": 12.322916666666666,
"network_passes_per_game": 2.2291666666666665,
"all_player_passes_per_game": 4.177083333333333,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 0,
"end_repetition": 4,
"end_two_passes": 92,
"end_move_limit": 0
}
},
"files": "/work/pass_3/"
}
}Games pass 3 of 10 done.
```
{"ok": true, "pass": 3, "kind": "games", "per_opponent": {"random": {"games": 16, "score": 1.0, "wins": 16, "losses": 0, "score_as_black": 1.0, "score_as_white": 1.0, "mean_margin": 81.0, "mean_length": 129.125, "stones_captured_per_game": 58.25, "stones_lost_per_game": 0.625, "network_passes_per_game": 1.0625, "all_player_passes_per_game": 7.125, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 8, "end_repetition": 0, "end_two_passes": 16, "end_move_limit": 0}, "weak": {"games": 16, "score": 0.875, "wins": 14, "losses": 2, "score_as_black": 0.75, "score_as_white": 1.0, "mean_margin": 58.4375, "mean_length": 124.5625, "stones_captured_per_game": 47.8125, "stones_lost_per_game": 5.4375, "network_passes_per_game": 1.75, "all_player_passes_per_game": 5.4375, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 4, "end_repetition": 0, "end_two_passes": 15, "end_move_limit": 1}, "strong": {"games": 96, "score": 0.19791666666666666, "wins": 19, "losses": 77, "score_as_black": 0.125, "score_as_white": 0.2708333333333333, "mean_margin": 2.3541666666666665, "mean_length": 97.27083333333333, "stones_captured_per_game": 11.90625, "stones_lost_per_game": 12.322916666666666, "network_passes_per_game": 2.2291666666666665, "all_player_passes_per_game": 4.177083333333333, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 0, "end_repetition": 4, "end_two_passes": 92, "end_move_limit": 0}}, "files": "/work/pass_3/"}
```Exact prompt · Raw CLI events · Settings and audit
Games pass 3 of 10 done.
```
{"ok": true, "pass": 3, "kind": "games", "per_opponent": {"random": {"games": 16, "score": 1.0, "wins": 16, "losses": 0, "score_as_black": 1.0, "score_as_white": 1.0, "mean_margin": 81.0, "mean_length": 129.125, "stones_captured_per_game": 58.25, "stones_lost_per_game": 0.625, "network_passes_per_game": 1.0625, "all_player_passes_per_game": 7.125, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 8, "end_repetition": 0, "end_two_passes": 16, "end_move_limit": 0}, "weak": {"games": 16, "score": 0.875, "wins": 14, "losses": 2, "score_as_black": 0.75, "score_as_white": 1.0, "mean_margin": 58.4375, "mean_length": 124.5625, "stones_captured_per_game": 47.8125, "stones_lost_per_game": 5.4375, "network_passes_per_game": 1.75, "all_player_passes_per_game": 5.4375, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 4, "end_repetition": 0, "end_two_passes": 15, "end_move_limit": 1}, "strong": {"games": 96, "score": 0.19791666666666666, "wins": 19, "losses": 77, "score_as_black": 0.125, "score_as_white": 0.2708333333333333, "mean_margin": 2.3541666666666665, "mean_length": 97.27083333333333, "stones_captured_per_game": 11.90625, "stones_lost_per_game": 12.322916666666666, "network_passes_per_game": 2.2291666666666665, "all_player_passes_per_game": 4.177083333333333, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 0, "end_repetition": 4, "end_two_passes": 92, "end_move_limit": 0}}, "files": "/work/pass_3/"}
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import numpy as np
V1=dict(np.load("/work/policy_v1.npz"))
V3=dict(np.load("/work/policy_v3.npz"))
A={n:V1[n].copy() for n in NAMES}
for k in (2,3,4):
A[f"L{k}.W"]=V3[f"L{k}.W"].copy()
A[f"L{k}.b"]=V3[f"L{k}.b"].copy()
# Restore the original spacious, contact-aware positional policy.
A["L2.W"][:,405:486]=V1["L4.W"][:,405:486]
A["L2.b"][405:486]=V1["L4.b"][405:486]
A["L5.W"][:,81:162]=V3["L5.W"][:,81:162]
A["L5.b"][81:162]=V3["L5.b"][81:162]
def u(ch,p): return 81*ch+p
def neighbors(p):
r,c=divmod(p,9)
return [(r+dr)*9+c+dc for dr,dc in [(-1,0),(1,0),(0,-1),(0,1)]
if 0<=r+dr<9 and 0<=c+dc<9]
# Edge connection traps: consuming a group's penultimate liberty without
# making any new liberty can initiate a losing capture/repetition cycle.
edge_points=[r*9+c for r in range(9) for c in range(9)
if ((r in (0,8) and c in (1,2,3,5,6,7))
or (c in (0,8) and r in (1,2,3,5,6,7)))]
slots=[487,488]+list(range(490,512))
for j,p in zip(slots,edge_points):
A["L5.W"][:,j]=0
A["L5.b"][j]=-4*len(neighbors(p))
for q in neighbors(p):
A["L5.W"][u(0,q),j]+=5
A["L5.W"][u(1,q),j]+=4
A["L5.W"][u(4,q),j]-=1
A["L5.W"][u(2,q),j]-=4
A["L6.W"][:,j]=0
A["L6.W"][j,j]=1
A["L6.b"][j]=0
A["out.W"][j,:]=0
A["out.W"][j,p]=-24
for p in range(81):
A["out.W"][u(5,p),p]=12
for name in NAMES: save(name,A[name])
np.savez("/work/policy_v4.npz",**A)
print("Saved original shape policy with separate three-liberty safety,",
"edge self-atari protection, and priority for saving threatened stones.")
```
{
"request_sha256": "c5fec0c36de48d3baa6699b4a66925aecd59c665cd4d068aeb7cfca0e0fe5815",
"request": {
"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import numpy as np\nV1=dict(np.load(\"/work/policy_v1.npz\"))\nV3=dict(np.load(\"/work/policy_v3.npz\"))\nA={n:V1[n].copy() for n in NAMES}\nfor k in (2,3,4):\n A[f\"L{k}.W\"]=V3[f\"L{k}.W\"].copy()\n A[f\"L{k}.b\"]=V3[f\"L{k}.b\"].copy()\n\n# Restore the original spacious, contact-aware positional policy.\nA[\"L2.W\"][:,405:486]=V1[\"L4.W\"][:,405:486]\nA[\"L2.b\"][405:486]=V1[\"L4.b\"][405:486]\nA[\"L5.W\"][:,81:162]=V3[\"L5.W\"][:,81:162]\nA[\"L5.b\"][81:162]=V3[\"L5.b\"][81:162]\n\ndef u(ch,p): return 81*ch+p\ndef neighbors(p):\n r,c=divmod(p,9)\n return [(r+dr)*9+c+dc for dr,dc in [(-1,0),(1,0),(0,-1),(0,1)]\n if 0<=r+dr<9 and 0<=c+dc<9]\n# Edge connection traps: consuming a group's penultimate liberty without\n# making any new liberty can initiate a losing capture/repetition cycle.\nedge_points=[r*9+c for r in range(9) for c in range(9)\n if ((r in (0,8) and c in (1,2,3,5,6,7))\n or (c in (0,8) and r in (1,2,3,5,6,7)))]\nslots=[487,488]+list(range(490,512))\nfor j,p in zip(slots,edge_points):\n A[\"L5.W\"][:,j]=0\n A[\"L5.b\"][j]=-4*len(neighbors(p))\n for q in neighbors(p):\n A[\"L5.W\"][u(0,q),j]+=5\n A[\"L5.W\"][u(1,q),j]+=4\n A[\"L5.W\"][u(4,q),j]-=1\n A[\"L5.W\"][u(2,q),j]-=4\n A[\"L6.W\"][:,j]=0\n A[\"L6.W\"][j,j]=1\n A[\"L6.b\"][j]=0\n A[\"out.W\"][j,:]=0\n A[\"out.W\"][j,p]=-24\n\nfor p in range(81):\n A[\"out.W\"][u(5,p),p]=12\n\nfor name in NAMES: save(name,A[name])\nnp.savez(\"/work/policy_v4.npz\",**A)\nprint(\"Saved original shape policy with separate three-liberty safety,\",\n \"edge self-atari protection, and priority for saving threatened stones.\")"
},
"result": {
"ok": true,
"out": "Saved original shape policy with separate three-liberty safety, edge self-atari protection, and priority for saving threatened stones.\n",
"stdout": "Saved original shape policy with separate three-liberty safety, edge self-atari protection, and priority for saving threatened stones.\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.4287754390388727,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-13652326112141fbba4e2600d972bfea",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
"-i",
"HOME=/tmp",
"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
"MKL_NUM_THREADS=8",
"CUDA_VISIBLE_DEVICES=",
"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 8 of at most 120: ``` Saved original shape policy with separate three-liberty safety, edge self-atari protection, and priority for saving threatened stones. ```
Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 8 of at most 120: ``` Saved original shape policy with separate three-liberty safety, edge self-atari protection, and priority for saving threatened stones. ```
Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```games
{"games":{"strong":128}}
```{
"request_sha256": "5084fdb422f091250c68137ece2e5b402aa827bb1e4dd4cf1a42bb4b5c057f7f",
"request": {
"kind": "games",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"pass": 4,
"request": {
"games": {
"strong": 128
}
}
},
"result": {
"ok": true,
"pass": 4,
"kind": "games",
"per_opponent": {
"strong": {
"games": 128,
"score": 0.359375,
"wins": 46,
"losses": 82,
"score_as_black": 0.28125,
"score_as_white": 0.4375,
"mean_margin": 15.0390625,
"mean_length": 102.125,
"stones_captured_per_game": 19.875,
"stones_lost_per_game": 12.0,
"network_passes_per_game": 2.609375,
"all_player_passes_per_game": 4.5390625,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 0,
"end_repetition": 6,
"end_two_passes": 122,
"end_move_limit": 0
}
},
"files": "/work/pass_4/"
}
}Games pass 4 of 10 done.
```
{"ok": true, "pass": 4, "kind": "games", "per_opponent": {"strong": {"games": 128, "score": 0.359375, "wins": 46, "losses": 82, "score_as_black": 0.28125, "score_as_white": 0.4375, "mean_margin": 15.0390625, "mean_length": 102.125, "stones_captured_per_game": 19.875, "stones_lost_per_game": 12.0, "network_passes_per_game": 2.609375, "all_player_passes_per_game": 4.5390625, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 0, "end_repetition": 6, "end_two_passes": 122, "end_move_limit": 0}}, "files": "/work/pass_4/"}
```Exact prompt · Raw CLI events · Settings and audit
Games pass 4 of 10 done.
```
{"ok": true, "pass": 4, "kind": "games", "per_opponent": {"strong": {"games": 128, "score": 0.359375, "wins": 46, "losses": 82, "score_as_black": 0.28125, "score_as_white": 0.4375, "mean_margin": 15.0390625, "mean_length": 102.125, "stones_captured_per_game": 19.875, "stones_lost_per_game": 12.0, "network_passes_per_game": 2.609375, "all_player_passes_per_game": 4.5390625, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 0, "end_repetition": 6, "end_two_passes": 122, "end_move_limit": 0}}, "files": "/work/pass_4/"}
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import numpy as np
A={n:a.copy() for n,a in dict(np.load("/work/policy_v4.npz")).items()}
for p in range(81):
A["out.W"][405+p,p]=8
# Reduce accidental low-quality moves under the mandated temperature-one
# sampling, without changing the ordering of any position's logits.
A["out.W"]*=1.8
A["out.b"]*=1.8
for name in NAMES: save(name,A[name])
np.savez("/work/policy_v5.npz",**A)
print("Saved sharper policy; all output logits are analytically scaled by 1.8.")
```
{
"request_sha256": "42cf07472d7eed8f960ac21c80ffdce75d944d9500ac35f1c5a4e402a180f08f",
"request": {
"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import numpy as np\nA={n:a.copy() for n,a in dict(np.load(\"/work/policy_v4.npz\")).items()}\nfor p in range(81):\n A[\"out.W\"][405+p,p]=8\n# Reduce accidental low-quality moves under the mandated temperature-one\n# sampling, without changing the ordering of any position's logits.\nA[\"out.W\"]*=1.8\nA[\"out.b\"]*=1.8\nfor name in NAMES: save(name,A[name])\nnp.savez(\"/work/policy_v5.npz\",**A)\nprint(\"Saved sharper policy; all output logits are analytically scaled by 1.8.\")"
},
"result": {
"ok": true,
"out": "Saved sharper policy; all output logits are analytically scaled by 1.8.\n",
"stdout": "Saved sharper policy; all output logits are analytically scaled by 1.8.\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.38249651063233614,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-f0a6e5eedf53470b8de6d21a8178d5ac",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
"-i",
"HOME=/tmp",
"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
"MKL_NUM_THREADS=8",
"CUDA_VISIBLE_DEVICES=",
"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 9 of at most 120: ``` Saved sharper policy; all output logits are analytically scaled by 1.8. ```
Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 9 of at most 120: ``` Saved sharper policy; all output logits are analytically scaled by 1.8. ```
Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```games
{"games":{"strong":128}}
```{
"request_sha256": "ab603493e960dc6280c3335f92624b88840b071379ef1542158033e73e612d46",
"request": {
"kind": "games",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"pass": 5,
"request": {
"games": {
"strong": 128
}
}
},
"result": {
"ok": true,
"pass": 5,
"kind": "games",
"per_opponent": {
"strong": {
"games": 128,
"score": 0.3828125,
"wins": 49,
"losses": 79,
"score_as_black": 0.3125,
"score_as_white": 0.453125,
"mean_margin": 13.703125,
"mean_length": 98.453125,
"stones_captured_per_game": 18.0546875,
"stones_lost_per_game": 12.78125,
"network_passes_per_game": 2.1796875,
"all_player_passes_per_game": 4.078125,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 0,
"end_repetition": 16,
"end_two_passes": 111,
"end_move_limit": 1
}
},
"files": "/work/pass_5/"
}
}Games pass 5 of 10 done.
```
{"ok": true, "pass": 5, "kind": "games", "per_opponent": {"strong": {"games": 128, "score": 0.3828125, "wins": 49, "losses": 79, "score_as_black": 0.3125, "score_as_white": 0.453125, "mean_margin": 13.703125, "mean_length": 98.453125, "stones_captured_per_game": 18.0546875, "stones_lost_per_game": 12.78125, "network_passes_per_game": 2.1796875, "all_player_passes_per_game": 4.078125, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 0, "end_repetition": 16, "end_two_passes": 111, "end_move_limit": 1}}, "files": "/work/pass_5/"}
```Exact prompt · Raw CLI events · Settings and audit
Games pass 5 of 10 done.
```
{"ok": true, "pass": 5, "kind": "games", "per_opponent": {"strong": {"games": 128, "score": 0.3828125, "wins": 49, "losses": 79, "score_as_black": 0.3125, "score_as_white": 0.453125, "mean_margin": 13.703125, "mean_length": 98.453125, "stones_captured_per_game": 18.0546875, "stones_lost_per_game": 12.78125, "network_passes_per_game": 2.1796875, "all_player_passes_per_game": 4.078125, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 0, "end_repetition": 16, "end_two_passes": 111, "end_move_limit": 1}}, "files": "/work/pass_5/"}
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import json, numpy as np
gs=json.load(open("/work/pass_5/games.json"))
bs=np.load("/work/pass_5/boards.npy")
def show(b):
print("\n".join("".join(".XO"[{0:0,1:1,-1:2}[int(x)]] for x in row)
for row in b.reshape(9,9)))
for i,g in enumerate(gs):
if g["end"]=="repetition":
print("\nGAME",i,g["net_color"],g["margin"],"last moves",
[(m["by"],m["move"]) for m in g["moves"][-7:]])
print("Before final three moves:")
show(bs[i,len(g["moves"])-4])
print("Final:")
show(bs[i,len(g["moves"])-1])
if i>=40: break
```
{
"request_sha256": "594cc06997e0bbc2c57ddaf9df82dbd8d5d99571f1e6407bc9ac7e9015ecc4ae",
"request": {
"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import json, numpy as np\ngs=json.load(open(\"/work/pass_5/games.json\"))\nbs=np.load(\"/work/pass_5/boards.npy\")\ndef show(b):\n print(\"\\n\".join(\"\".join(\".XO\"[{0:0,1:1,-1:2}[int(x)]] for x in row)\n for row in b.reshape(9,9)))\nfor i,g in enumerate(gs):\n if g[\"end\"]==\"repetition\":\n print(\"\\nGAME\",i,g[\"net_color\"],g[\"margin\"],\"last moves\",\n [(m[\"by\"],m[\"move\"]) for m in g[\"moves\"][-7:]])\n print(\"Before final three moves:\")\n show(bs[i,len(g[\"moves\"])-4])\n print(\"Final:\")\n show(bs[i,len(g[\"moves\"])-1])\n if i>=40: break"
},
"result": {
"ok": true,
"out": "\nGAME 2 black -8.5 last moves [('net', 36), ('strong', 6), ('net', 78), ('strong', 45), ('net', 72), ('strong', 74), ('net', 73)]\nBefore final three moves:\nO.OOOOOO.\n.O.XXO.O.\nOO.OXOOOO\n.OOOOOXOO\nXOOXXXXOX\nOOXXX.XXX\nOOOX.X.X.\nOOX.X.XX.\n.X.X.XX.X\nFinal:\nO.OOOOOO.\n.O.XXO.O.\nOO.OXOOOO\n.OOOOOXOO\nXOOXXXXOX\nOOXXX.XXX\nOOOX.X.X.\nOOX.X.XX.\n.X.X.XX.X\n\nGAME 5 white 27.5 last moves [('strong', 5), ('net', 4), ('strong', 75), ('net', 6), ('strong', 73), ('net', 74), ('strong', 72)]\nBefore final three moves:\nO.XOO.O.O\nXXXOOOOO.\nOXXXOOO.O\nOXXXOOO..\nOOOXO.OO.\n.OXXOOOXO\nOOOXXOXX.\nOOXXXXXXX\nX.OXXO.O.\nFinal:\nO.XOO.O.O\nXXXOOOOO.\nOXXXOOO.O\nOXXXOOO..\nOOOXO.OO.\n.OXXOOOXO\nOOOXXOXX.\nOOXXXXXXX\nX.OXXO.O.\n\nGAME 6 black 13.5 last moves [('net', 7), ('strong', 25), ('net', 26), ('strong', 3), ('net', 0), ('strong', 18), ('net', 9)]\nBefore final three moves:\n.OOO.OXX.\nXOOOOOOX.\n.XXXOOX.X\nXXXOOX.X.\n.XOOOXX..\nXXOOXX.X.\nOXXOX.X..\nOOOOOX.X.\nXX.O..X..\nFinal:\n.OOO.OXX.\nXOOOOOOX.\n.XXXOOX.X\nXXXOOX.X.\n.XOOOXX..\nXXOOXX.X.\nOXXOX.X..\nOOOOOX.X.\nXX.O..X..\n\nGAME 10 black -15.5 last moves [('net', 22), ('strong', 54), ('net', 63), ('strong', 11), ('net', 72), ('strong', 54), ('net', 63)]\nBefore final three moves:\nX.O.OOO..\nOOOXXO..O\nOOOOXOOOO\nXXOOOOOOO\nX.XOOOXOX\nXXXOXXXXX\n.XXOOOXXX\nXOOOOX.X.\n.OOOXXX.X\nFinal:\nX.O.OOO..\nOOOXXO..O\nOOOOXOOOO\nXXOOOOOOO\nX.XOOOXOX\nXXXOXXXXX\n.XXOOOXXX\nXOOOOX.X.\n.OOOXXX.X\n\nGAME 31 white 21.5 last moves [('net', 73), ('strong', 18), ('net', 9), ('strong', 74), ('net', 0), ('strong', 18), ('net', 9)]\nBefore final three moves:\n.XXXO.O..\nOXXXOOOO.\n.OOXXO.O.\nOOOXXOO.O\n.OXXXOOO.\nOOXXOXOXO\nOX.XOXXX.\nOXXXOOXX.\n.OXO.X...\nFinal:\n.XXXO.O..\nOXXXOOOO.\n.OOXXO.O.\nOOOXXOO.O\n.OXXXOOO.\nOOXXOXOXO\nOX.XOXXX.\nOXXXOOXX.\n.OXO.X...\n\nGAME 43 white -3.5 last moves [('strong', 45), ('net', 79), ('strong', 78), ('net', 37), ('strong', 54), ('net', 63), ('strong', 45)]\nBefore final three moves:\n.O.OOOXOX\nO.O.OXX.X\nOO.OOXXXX\n.OOXXXXXX\nOOOOXOOXX\nXOXXXOOXX\n.OOXX.XXX\nOXXXXXXXX\nXXXXXXXO.\nFinal:\n.O.OOOXOX\nO.O.OXX.X\nOO.OOXXXX\n.OOXXXXXX\nOOOOXOOXX\nXOXXXOOXX\n.OOXX.XXX\nOXXXXXXXX\nXXXXXXXO.\n",
"stdout": "\nGAME 2 black -8.5 last moves [('net', 36), ('strong', 6), ('net', 78), ('strong', 45), ('net', 72), ('strong', 74), ('net', 73)]\nBefore final three moves:\nO.OOOOOO.\n.O.XXO.O.\nOO.OXOOOO\n.OOOOOXOO\nXOOXXXXOX\nOOXXX.XXX\nOOOX.X.X.\nOOX.X.XX.\n.X.X.XX.X\nFinal:\nO.OOOOOO.\n.O.XXO.O.\nOO.OXOOOO\n.OOOOOXOO\nXOOXXXXOX\nOOXXX.XXX\nOOOX.X.X.\nOOX.X.XX.\n.X.X.XX.X\n\nGAME 5 white 27.5 last moves [('strong', 5), ('net', 4), ('strong', 75), ('net', 6), ('strong', 73), ('net', 74), ('strong', 72)]\nBefore final three moves:\nO.XOO.O.O\nXXXOOOOO.\nOXXXOOO.O\nOXXXOOO..\nOOOXO.OO.\n.OXXOOOXO\nOOOXXOXX.\nOOXXXXXXX\nX.OXXO.O.\nFinal:\nO.XOO.O.O\nXXXOOOOO.\nOXXXOOO.O\nOXXXOOO..\nOOOXO.OO.\n.OXXOOOXO\nOOOXXOXX.\nOOXXXXXXX\nX.OXXO.O.\n\nGAME 6 black 13.5 last moves [('net', 7), ('strong', 25), ('net', 26), ('strong', 3), ('net', 0), ('strong', 18), ('net', 9)]\nBefore final three moves:\n.OOO.OXX.\nXOOOOOOX.\n.XXXOOX.X\nXXXOOX.X.\n.XOOOXX..\nXXOOXX.X.\nOXXOX.X..\nOOOOOX.X.\nXX.O..X..\nFinal:\n.OOO.OXX.\nXOOOOOOX.\n.XXXOOX.X\nXXXOOX.X.\n.XOOOXX..\nXXOOXX.X.\nOXXOX.X..\nOOOOOX.X.\nXX.O..X..\n\nGAME 10 black -15.5 last moves [('net', 22), ('strong', 54), ('net', 63), ('strong', 11), ('net', 72), ('strong', 54), ('net', 63)]\nBefore final three moves:\nX.O.OOO..\nOOOXXO..O\nOOOOXOOOO\nXXOOOOOOO\nX.XOOOXOX\nXXXOXXXXX\n.XXOOOXXX\nXOOOOX.X.\n.OOOXXX.X\nFinal:\nX.O.OOO..\nOOOXXO..O\nOOOOXOOOO\nXXOOOOOOO\nX.XOOOXOX\nXXXOXXXXX\n.XXOOOXXX\nXOOOOX.X.\n.OOOXXX.X\n\nGAME 31 white 21.5 last moves [('net', 73), ('strong', 18), ('net', 9), ('strong', 74), ('net', 0), ('strong', 18), ('net', 9)]\nBefore final three moves:\n.XXXO.O..\nOXXXOOOO.\n.OOXXO.O.\nOOOXXOO.O\n.OXXXOOO.\nOOXXOXOXO\nOX.XOXXX.\nOXXXOOXX.\n.OXO.X...\nFinal:\n.XXXO.O..\nOXXXOOOO.\n.OOXXO.O.\nOOOXXOO.O\n.OXXXOOO.\nOOXXOXOXO\nOX.XOXXX.\nOXXXOOXX.\n.OXO.X...\n\nGAME 43 white -3.5 last moves [('strong', 45), ('net', 79), ('strong', 78), ('net', 37), ('strong', 54), ('net', 63), ('strong', 45)]\nBefore final three moves:\n.O.OOOXOX\nO.O.OXX.X\nOO.OOXXXX\n.OOXXXXXX\nOOOOXOOXX\nXOXXXOOXX\n.OOXX.XXX\nOXXXXXXXX\nXXXXXXXO.\nFinal:\n.O.OOOXOX\nO.O.OXX.X\nOO.OOXXXX\n.OOXXXXXX\nOOOOXOOXX\nXOXXXOOXX\n.OOXX.XXX\nOXXXXXXXX\nXXXXXXXO.\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.41429450595751405,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-413c30e60d994b58b4142a2322ac3877",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
"-i",
"HOME=/tmp",
"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
"MKL_NUM_THREADS=8",
"CUDA_VISIBLE_DEVICES=",
"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 10 of at most 120:
```
GAME 2 black -8.5 last moves [('net', 36), ('strong', 6), ('net', 78), ('strong', 45), ('net', 72), ('strong', 74), ('net', 73)]
Before final three moves:
O.OOOOOO.
.O.XXO.O.
OO.OXOOOO
.OOOOOXOO
XOOXXXXOX
OOXXX.XXX
OOOX.X.X.
OOX.X.XX.
.X.X.XX.X
Final:
O.OOOOOO.
.O.XXO.O.
OO.OXOOOO
.OOOOOXOO
XOOXXXXOX
OOXXX.XXX
OOOX.X.X.
OOX.X.XX.
.X.X.XX.X
GAME 5 white 27.5 last moves [('strong', 5), ('net', 4), ('strong', 75), ('net', 6), ('strong', 73), ('net', 74), ('strong', 72)]
Before final three moves:
O.XOO.O.O
XXXOOOOO.
OXXXOOO.O
OXXXOOO..
OOOXO.OO.
.OXXOOOXO
OOOXXOXX.
OOXXXXXXX
X.OXXO.O.
Final:
O.XOO.O.O
XXXOOOOO.
OXXXOOO.O
OXXXOOO..
OOOXO.OO.
.OXXOOOXO
OOOXXOXX.
OOXXXXXXX
X.OXXO.O.
GAME 6 black 13.5 last moves [('net', 7), ('strong', 25), ('net', 26), ('strong', 3), ('net', 0), ('strong', 18), ('net', 9)]
Before final three moves:
.OOO.OXX.
XOOOOOOX.
.XXXOOX.X
XXXOOX.X.
.XOOOXX..
XXOOXX.X.
OXXOX.X..
OOOOOX.X.
XX.O..X..
Final:
.OOO.OXX.
XOOOOOOX.
.XXXOOX.X
XXXOOX.X.
.XOOOXX..
XXOOXX.X.
OXXOX.X..
OOOOOX.X.
XX.O..X..
GAME 10 black -15.5 last moves [('net', 22), ('strong', 54), ('net', 63), ('strong', 11), ('net', 72), ('strong', 54), ('net', 63)]
Before final three moves:
X.O.OOO..
OOOXXO..O
OOOOXOOOO
XXOOOOOOO
X.XOOOXOX
XXXOXXXXX
.XXOOOXXX
XOOOOX.X.
.OOOXXX.X
Final:
X.O.OOO..
OOOXXO..O
OOOOXOOOO
XXOOOOOOO
X.XOOOXOX
XXXOXXXXX
.XXOOOXXX
XOOOOX.X.
.OOOXXX.X
GAME 31 white 21.5 last moves [('net', 73), ('strong', 18), ('net', 9), ('strong', 74), ('net', 0), ('strong', 18), ('net', 9)]
Before final three moves:
.XXXO.O..
OXXXOOOO.
.OOXXO.O.
OOOXXOO.O
.OXXXOOO.
OOXXOXOXO
OX.XOXXX.
OXXXOOXX.
.OXO.X...
Final:
.XXXO.O..
OXXXOOOO.
.OOXXO.O.
OOOXXOO.O
.OXXXOOO.
OOXXOXOXO
OX.XOXXX.
OXXXOOXX.
.OXO.X...
GAME 43 white -3.5 last moves [('strong', 45), ('net', 79), ('strong', 78), ('net', 37), ('strong', 54), ('net', 63), ('strong', 45)]
Before final three moves:
.O.OOOXOX
O.O.OXX.X
OO.OOXXXX
.OOXXXXXX
OOOOXOOXX
XOXXXOOXX
.OOXX.XXX
OXXXXXXXX
XXXXXXXO.
Final:
.O.OOOXOX
O.O.OXX.X
OO.OOXXXX
.OOXXXXXX
OOOOXOOXX
XOXXXOOXX
.OOXX.XXX
OXXXXXXXX
XXXXXXXO.
```Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 10 of at most 120:
```
GAME 2 black -8.5 last moves [('net', 36), ('strong', 6), ('net', 78), ('strong', 45), ('net', 72), ('strong', 74), ('net', 73)]
Before final three moves:
O.OOOOOO.
.O.XXO.O.
OO.OXOOOO
.OOOOOXOO
XOOXXXXOX
OOXXX.XXX
OOOX.X.X.
OOX.X.XX.
.X.X.XX.X
Final:
O.OOOOOO.
.O.XXO.O.
OO.OXOOOO
.OOOOOXOO
XOOXXXXOX
OOXXX.XXX
OOOX.X.X.
OOX.X.XX.
.X.X.XX.X
GAME 5 white 27.5 last moves [('strong', 5), ('net', 4), ('strong', 75), ('net', 6), ('strong', 73), ('net', 74), ('strong', 72)]
Before final three moves:
O.XOO.O.O
XXXOOOOO.
OXXXOOO.O
OXXXOOO..
OOOXO.OO.
.OXXOOOXO
OOOXXOXX.
OOXXXXXXX
X.OXXO.O.
Final:
O.XOO.O.O
XXXOOOOO.
OXXXOOO.O
OXXXOOO..
OOOXO.OO.
.OXXOOOXO
OOOXXOXX.
OOXXXXXXX
X.OXXO.O.
GAME 6 black 13.5 last moves [('net', 7), ('strong', 25), ('net', 26), ('strong', 3), ('net', 0), ('strong', 18), ('net', 9)]
Before final three moves:
.OOO.OXX.
XOOOOOOX.
.XXXOOX.X
XXXOOX.X.
.XOOOXX..
XXOOXX.X.
OXXOX.X..
OOOOOX.X.
XX.O..X..
Final:
.OOO.OXX.
XOOOOOOX.
.XXXOOX.X
XXXOOX.X.
.XOOOXX..
XXOOXX.X.
OXXOX.X..
OOOOOX.X.
XX.O..X..
GAME 10 black -15.5 last moves [('net', 22), ('strong', 54), ('net', 63), ('strong', 11), ('net', 72), ('strong', 54), ('net', 63)]
Before final three moves:
X.O.OOO..
OOOXXO..O
OOOOXOOOO
XXOOOOOOO
X.XOOOXOX
XXXOXXXXX
.XXOOOXXX
XOOOOX.X.
.OOOXXX.X
Final:
X.O.OOO..
OOOXXO..O
OOOOXOOOO
XXOOOOOOO
X.XOOOXOX
XXXOXXXXX
.XXOOOXXX
XOOOOX.X.
.OOOXXX.X
GAME 31 white 21.5 last moves [('net', 73), ('strong', 18), ('net', 9), ('strong', 74), ('net', 0), ('strong', 18), ('net', 9)]
Before final three moves:
.XXXO.O..
OXXXOOOO.
.OOXXO.O.
OOOXXOO.O
.OXXXOOO.
OOXXOXOXO
OX.XOXXX.
OXXXOOXX.
.OXO.X...
Final:
.XXXO.O..
OXXXOOOO.
.OOXXO.O.
OOOXXOO.O
.OXXXOOO.
OOXXOXOXO
OX.XOXXX.
OXXXOOXX.
.OXO.X...
GAME 43 white -3.5 last moves [('strong', 45), ('net', 79), ('strong', 78), ('net', 37), ('strong', 54), ('net', 63), ('strong', 45)]
Before final three moves:
.O.OOOXOX
O.O.OXX.X
OO.OOXXXX
.OOXXXXXX
OOOOXOOXX
XOXXXOOXX
.OOXX.XXX
OXXXXXXXX
XXXXXXXO.
Final:
.O.OOOXOX
O.O.OXX.X
OO.OOXXXX
.OOXXXXXX
OOOOXOOXX
XOXXXOOXX
.OOXX.XXX
OXXXXXXXX
XXXXXXXO.
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import numpy as np
A={n:a.copy() for n,a in dict(np.load("/work/policy_v5.npz")).items()}
def ns(p):
r,c=divmod(p,9)
return [(r+dr)*9+c+dc for dr,dc in [(-1,0),(1,0),(0,-1),(0,1)]
if 0<=r+dr<9 and 0<=c+dc<9]
def u(ch,p): return ch*81+p
# Complete the edge-trap rule at corners and side midpoints. At these
# eight points it replaces the less important unsupported-contact feature.
for p in [0,4,8,36,44,72,76,80]:
j=u(4,p)
A["L5.W"][:,j]=0
A["L5.b"][j]=-4*len(ns(p))
for q in ns(p):
A["L5.W"][u(0,q),j]+=5
A["L5.W"][u(1,q),j]+=4
A["L5.W"][u(4,q),j]-=1
A["L5.W"][u(2,q),j]-=4
A["out.W"][j,p]=-24*1.8
# Opening: avoid overconcentration. As the board fills, permit the close
# connections required for contact fighting and endgame boundaries.
for p in range(81):
A["L5.b"][u(3,p)]=-2.5
A["L5.W"][487,u(3,p)]=-0.025
A["L5.W"][488,u(3,p)]=-0.025
for name in NAMES: save(name,A[name])
np.savez("/work/policy_v6.npz",**A)
print("Saved complete edge trap protection and phase-aware shape rule.")
```
{
"request_sha256": "fa04e3e387499113a8631bb2e63fb061e18309beb136ad0f5f4bcd8dbf264ca8",
"request": {
"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import numpy as np\nA={n:a.copy() for n,a in dict(np.load(\"/work/policy_v5.npz\")).items()}\ndef ns(p):\n r,c=divmod(p,9)\n return [(r+dr)*9+c+dc for dr,dc in [(-1,0),(1,0),(0,-1),(0,1)]\n if 0<=r+dr<9 and 0<=c+dc<9]\ndef u(ch,p): return ch*81+p\n\n# Complete the edge-trap rule at corners and side midpoints. At these\n# eight points it replaces the less important unsupported-contact feature.\nfor p in [0,4,8,36,44,72,76,80]:\n j=u(4,p)\n A[\"L5.W\"][:,j]=0\n A[\"L5.b\"][j]=-4*len(ns(p))\n for q in ns(p):\n A[\"L5.W\"][u(0,q),j]+=5\n A[\"L5.W\"][u(1,q),j]+=4\n A[\"L5.W\"][u(4,q),j]-=1\n A[\"L5.W\"][u(2,q),j]-=4\n A[\"out.W\"][j,p]=-24*1.8\n\n# Opening: avoid overconcentration. As the board fills, permit the close\n# connections required for contact fighting and endgame boundaries.\nfor p in range(81):\n A[\"L5.b\"][u(3,p)]=-2.5\n A[\"L5.W\"][487,u(3,p)]=-0.025\n A[\"L5.W\"][488,u(3,p)]=-0.025\n\nfor name in NAMES: save(name,A[name])\nnp.savez(\"/work/policy_v6.npz\",**A)\nprint(\"Saved complete edge trap protection and phase-aware shape rule.\")"
},
"result": {
"ok": true,
"out": "Saved complete edge trap protection and phase-aware shape rule.\n",
"stdout": "Saved complete edge trap protection and phase-aware shape rule.\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.3913903129287064,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-9b4c5d72921642aea71b4b2dc6f6f95f",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
"-i",
"HOME=/tmp",
"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
"MKL_NUM_THREADS=8",
"CUDA_VISIBLE_DEVICES=",
"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 11 of at most 120: ``` Saved complete edge trap protection and phase-aware shape rule. ```
Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 11 of at most 120: ``` Saved complete edge trap protection and phase-aware shape rule. ```
Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```games
{"games":{"strong":128}}
```{
"request_sha256": "ac2e277a1f70fc9ccd78a5143f01c41448583c23dfd1060781a6abe25a533a44",
"request": {
"kind": "games",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"pass": 6,
"request": {
"games": {
"strong": 128
}
}
},
"result": {
"ok": true,
"pass": 6,
"kind": "games",
"per_opponent": {
"strong": {
"games": 128,
"score": 0.4140625,
"wins": 53,
"losses": 75,
"score_as_black": 0.390625,
"score_as_white": 0.4375,
"mean_margin": 14.46875,
"mean_length": 97.34375,
"stones_captured_per_game": 17.46875,
"stones_lost_per_game": 11.640625,
"network_passes_per_game": 2.53125,
"all_player_passes_per_game": 4.3984375,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 2,
"end_repetition": 5,
"end_two_passes": 123,
"end_move_limit": 0
}
},
"files": "/work/pass_6/"
}
}Games pass 6 of 10 done.
```
{"ok": true, "pass": 6, "kind": "games", "per_opponent": {"strong": {"games": 128, "score": 0.4140625, "wins": 53, "losses": 75, "score_as_black": 0.390625, "score_as_white": 0.4375, "mean_margin": 14.46875, "mean_length": 97.34375, "stones_captured_per_game": 17.46875, "stones_lost_per_game": 11.640625, "network_passes_per_game": 2.53125, "all_player_passes_per_game": 4.3984375, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 2, "end_repetition": 5, "end_two_passes": 123, "end_move_limit": 0}}, "files": "/work/pass_6/"}
```Exact prompt · Raw CLI events · Settings and audit
Games pass 6 of 10 done.
```
{"ok": true, "pass": 6, "kind": "games", "per_opponent": {"strong": {"games": 128, "score": 0.4140625, "wins": 53, "losses": 75, "score_as_black": 0.390625, "score_as_white": 0.4375, "mean_margin": 14.46875, "mean_length": 97.34375, "stones_captured_per_game": 17.46875, "stones_lost_per_game": 11.640625, "network_passes_per_game": 2.53125, "all_player_passes_per_game": 4.3984375, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 2, "end_repetition": 5, "end_two_passes": 123, "end_move_limit": 0}}, "files": "/work/pass_6/"}
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import numpy as np
A={n:a.copy() for n,a in dict(np.load("/work/policy_v6.npz")).items()}
def u(ch,p): return 81*ch+p
def ns(p):
r,c=divmod(p,9)
return [(r+dr)*9+c+dc for dr,dc in [(-1,0),(1,0),(0,-1),(0,1)]
if 0<=r+dr<9 and 0<=c+dc<9]
# Propagate the Boolean absence of a liberty certificate. Once complemented,
# Boolean AND over connected neighbours requires only one ReLU.
for ch,color in [(2,0),(3,1),(4,0)]:
A["L3.W"][:,81*ch:81*(ch+1)]=0
A["L3.b"][81*ch:81*(ch+1)]=0
for p in range(81):
A["L3.W"][u(color,p),u(ch,p)]=1
for q in [p]+ns(p):
A["L3.W"][u(ch,q),u(ch,p)]-=1
for dst,src,color in [(4,2,0),(3,3,1),(2,4,0)]:
A["L4.W"][:,81*dst:81*(dst+1)]=0
A["L4.b"][81*dst:81*(dst+1)]=0
for p in range(81):
for q in [p]+ns(p):
A["L4.W"][u(src,q),u(dst,p)]+=1
for q in ns(p):
A["L4.W"][u(color,q),u(dst,p)]-=1
# Channel 2 now means "friendly stone without a three-liberty certificate".
# Rewrite consumers using known_safe = own_stone - weak_stone.
w=A["L5.W"][162:243,:].copy()
A["L5.W"][0:81,:]+=w
A["L5.W"][162:243,:]=-w
# Protect two-liberty groups proactively, while retaining full urgency for
# actual atari. This is a rule-based intermediate tactical priority.
for p in range(81):
for q in ns(p):
A["L5.W"][u(4,q),u(5,p)]=0.65
A["L5.W"][u(2,q),u(5,p)]+=0.35
for name in NAMES: save(name,A[name])
np.savez("/work/policy_v7.npz",**A)
print("Saved bounded Boolean connectivity and proactive weak-group protection.")
```
{
"request_sha256": "4b9067cd5f950c6ddbe14077ac456b5339ba0981e0c1ff6be19854b8dbc0d3f4",
"request": {
"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import numpy as np\nA={n:a.copy() for n,a in dict(np.load(\"/work/policy_v6.npz\")).items()}\ndef u(ch,p): return 81*ch+p\ndef ns(p):\n r,c=divmod(p,9)\n return [(r+dr)*9+c+dc for dr,dc in [(-1,0),(1,0),(0,-1),(0,1)]\n if 0<=r+dr<9 and 0<=c+dc<9]\n\n# Propagate the Boolean absence of a liberty certificate. Once complemented,\n# Boolean AND over connected neighbours requires only one ReLU.\nfor ch,color in [(2,0),(3,1),(4,0)]:\n A[\"L3.W\"][:,81*ch:81*(ch+1)]=0\n A[\"L3.b\"][81*ch:81*(ch+1)]=0\n for p in range(81):\n A[\"L3.W\"][u(color,p),u(ch,p)]=1\n for q in [p]+ns(p):\n A[\"L3.W\"][u(ch,q),u(ch,p)]-=1\n\nfor dst,src,color in [(4,2,0),(3,3,1),(2,4,0)]:\n A[\"L4.W\"][:,81*dst:81*(dst+1)]=0\n A[\"L4.b\"][81*dst:81*(dst+1)]=0\n for p in range(81):\n for q in [p]+ns(p):\n A[\"L4.W\"][u(src,q),u(dst,p)]+=1\n for q in ns(p):\n A[\"L4.W\"][u(color,q),u(dst,p)]-=1\n\n# Channel 2 now means \"friendly stone without a three-liberty certificate\".\n# Rewrite consumers using known_safe = own_stone - weak_stone.\nw=A[\"L5.W\"][162:243,:].copy()\nA[\"L5.W\"][0:81,:]+=w\nA[\"L5.W\"][162:243,:]=-w\n\n# Protect two-liberty groups proactively, while retaining full urgency for\n# actual atari. This is a rule-based intermediate tactical priority.\nfor p in range(81):\n for q in ns(p):\n A[\"L5.W\"][u(4,q),u(5,p)]=0.65\n A[\"L5.W\"][u(2,q),u(5,p)]+=0.35\n\nfor name in NAMES: save(name,A[name])\nnp.savez(\"/work/policy_v7.npz\",**A)\nprint(\"Saved bounded Boolean connectivity and proactive weak-group protection.\")"
},
"result": {
"ok": true,
"out": "Saved bounded Boolean connectivity and proactive weak-group protection.\n",
"stdout": "Saved bounded Boolean connectivity and proactive weak-group protection.\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.39796743588522077,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-6a5cd1acd54f4df485240b3894e181a3",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
"-i",
"HOME=/tmp",
"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
"MKL_NUM_THREADS=8",
"CUDA_VISIBLE_DEVICES=",
"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 12 of at most 120: ``` Saved bounded Boolean connectivity and proactive weak-group protection. ```
Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 12 of at most 120: ``` Saved bounded Boolean connectivity and proactive weak-group protection. ```
Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```games
{"games":{"strong":128}}
```{
"request_sha256": "b48f8acb94f6a3f326ea22dce6206d94e6c997b7dc9feca04b09781b6a43bc17",
"request": {
"kind": "games",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"pass": 7,
"request": {
"games": {
"strong": 128
}
}
},
"result": {
"ok": true,
"pass": 7,
"kind": "games",
"per_opponent": {
"strong": {
"games": 128,
"score": 0.4609375,
"wins": 59,
"losses": 69,
"score_as_black": 0.5,
"score_as_white": 0.421875,
"mean_margin": 21.3828125,
"mean_length": 105.8671875,
"stones_captured_per_game": 23.984375,
"stones_lost_per_game": 11.8203125,
"network_passes_per_game": 2.171875,
"all_player_passes_per_game": 4.5078125,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 2,
"end_repetition": 1,
"end_two_passes": 126,
"end_move_limit": 1
}
},
"files": "/work/pass_7/"
}
}Games pass 7 of 10 done.
```
{"ok": true, "pass": 7, "kind": "games", "per_opponent": {"strong": {"games": 128, "score": 0.4609375, "wins": 59, "losses": 69, "score_as_black": 0.5, "score_as_white": 0.421875, "mean_margin": 21.3828125, "mean_length": 105.8671875, "stones_captured_per_game": 23.984375, "stones_lost_per_game": 11.8203125, "network_passes_per_game": 2.171875, "all_player_passes_per_game": 4.5078125, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 2, "end_repetition": 1, "end_two_passes": 126, "end_move_limit": 1}}, "files": "/work/pass_7/"}
```Exact prompt · Raw CLI events · Settings and audit
Games pass 7 of 10 done.
```
{"ok": true, "pass": 7, "kind": "games", "per_opponent": {"strong": {"games": 128, "score": 0.4609375, "wins": 59, "losses": 69, "score_as_black": 0.5, "score_as_white": 0.421875, "mean_margin": 21.3828125, "mean_length": 105.8671875, "stones_captured_per_game": 23.984375, "stones_lost_per_game": 11.8203125, "network_passes_per_game": 2.171875, "all_player_passes_per_game": 4.5078125, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 2, "end_repetition": 1, "end_two_passes": 126, "end_move_limit": 1}}, "files": "/work/pass_7/"}
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import numpy as np
A={n:a.copy() for n,a in dict(np.load("/work/policy_v7.npz")).items()}
V1=dict(np.load("/work/policy_v1.npz"))
def u(ch,p): return 81*ch+p
def ns(p):
r,c=divmod(p,9)
return [(r+dr)*9+c+dc for dr,dc in [(-1,0),(1,0),(0,-1),(0,1)]
if 0<=r+dr<9 and 0<=c+dc<9]
# Compute positional influence later, directly from the retained stones.
# This frees one spatial map for an opponent three-liberty certificate.
A["L5.W"][:,:81]=V1["L4.W"][:,405:486]
A["L5.b"][:81]=V1["L4.b"][405:486]
for p in range(81):
for q in ns(p):
A["L5.W"][u(3,q),u(0,p)]+=7.5
A["L5.W"][u(5,q),u(0,p)]+=2.5
for k in (2,3,4):
A[f"L{k}.W"][:,405:486]=0
A[f"L{k}.b"][405:486]=0
for p in range(81):
A["L2.b"][u(5,p)]=-44
A["L2.W"][u(1,p),u(5,p)]=40
A["L2.W"][u(3,p),u(5,p)]=2
for q in ns(p):
A["L2.W"][u(3,q),u(5,p)]+=1
A["L3.W"][u(1,p),u(5,p)]=1
for q in [p]+ns(p):
A["L3.W"][u(5,q),u(5,p)]-=1
A["L4.W"][u(5,q),u(5,p)]+=1
for q in ns(p):
A["L4.W"][u(1,q),u(5,p)]-=1
for name in NAMES: save(name,A[name])
np.savez("/work/policy_v8.npz",**A)
print("Saved symmetric two-/three-liberty certificates and proactive attacks.")
```
{
"request_sha256": "d03f59ff22488cb14b5cf2547276754a0c3bb7520eb062ea9ba4265a94dcbc20",
"request": {
"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import numpy as np\nA={n:a.copy() for n,a in dict(np.load(\"/work/policy_v7.npz\")).items()}\nV1=dict(np.load(\"/work/policy_v1.npz\"))\ndef u(ch,p): return 81*ch+p\ndef ns(p):\n r,c=divmod(p,9)\n return [(r+dr)*9+c+dc for dr,dc in [(-1,0),(1,0),(0,-1),(0,1)]\n if 0<=r+dr<9 and 0<=c+dc<9]\n\n# Compute positional influence later, directly from the retained stones.\n# This frees one spatial map for an opponent three-liberty certificate.\nA[\"L5.W\"][:,:81]=V1[\"L4.W\"][:,405:486]\nA[\"L5.b\"][:81]=V1[\"L4.b\"][405:486]\nfor p in range(81):\n for q in ns(p):\n A[\"L5.W\"][u(3,q),u(0,p)]+=7.5\n A[\"L5.W\"][u(5,q),u(0,p)]+=2.5\n\nfor k in (2,3,4):\n A[f\"L{k}.W\"][:,405:486]=0\n A[f\"L{k}.b\"][405:486]=0\nfor p in range(81):\n A[\"L2.b\"][u(5,p)]=-44\n A[\"L2.W\"][u(1,p),u(5,p)]=40\n A[\"L2.W\"][u(3,p),u(5,p)]=2\n for q in ns(p):\n A[\"L2.W\"][u(3,q),u(5,p)]+=1\n\n A[\"L3.W\"][u(1,p),u(5,p)]=1\n for q in [p]+ns(p):\n A[\"L3.W\"][u(5,q),u(5,p)]-=1\n A[\"L4.W\"][u(5,q),u(5,p)]+=1\n for q in ns(p):\n A[\"L4.W\"][u(1,q),u(5,p)]-=1\n\nfor name in NAMES: save(name,A[name])\nnp.savez(\"/work/policy_v8.npz\",**A)\nprint(\"Saved symmetric two-/three-liberty certificates and proactive attacks.\")"
},
"result": {
"ok": true,
"out": "Saved symmetric two-/three-liberty certificates and proactive attacks.\n",
"stdout": "Saved symmetric two-/three-liberty certificates and proactive attacks.\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.41326375771313906,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-898385c8b02e498ab6637876b1d667c7",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
"-i",
"HOME=/tmp",
"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
"MKL_NUM_THREADS=8",
"CUDA_VISIBLE_DEVICES=",
"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 13 of at most 120: ``` Saved symmetric two-/three-liberty certificates and proactive attacks. ```
Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 13 of at most 120: ``` Saved symmetric two-/three-liberty certificates and proactive attacks. ```
Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```games
{"games":{"strong":128}}
```{
"request_sha256": "8dbe8b7b15c0df02d26d1f81c8521337f712ccfa0d0ac6203e91eded93999086",
"request": {
"kind": "games",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"pass": 8,
"request": {
"games": {
"strong": 128
}
}
},
"result": {
"ok": true,
"pass": 8,
"kind": "games",
"per_opponent": {
"strong": {
"games": 128,
"score": 0.5859375,
"wins": 75,
"losses": 53,
"score_as_black": 0.59375,
"score_as_white": 0.578125,
"mean_margin": 29.34375,
"mean_length": 106.7109375,
"stones_captured_per_game": 28.203125,
"stones_lost_per_game": 10.8984375,
"network_passes_per_game": 1.890625,
"all_player_passes_per_game": 4.265625,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 1,
"end_repetition": 5,
"end_two_passes": 122,
"end_move_limit": 1
}
},
"files": "/work/pass_8/"
}
}Games pass 8 of 10 done.
```
{"ok": true, "pass": 8, "kind": "games", "per_opponent": {"strong": {"games": 128, "score": 0.5859375, "wins": 75, "losses": 53, "score_as_black": 0.59375, "score_as_white": 0.578125, "mean_margin": 29.34375, "mean_length": 106.7109375, "stones_captured_per_game": 28.203125, "stones_lost_per_game": 10.8984375, "network_passes_per_game": 1.890625, "all_player_passes_per_game": 4.265625, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 1, "end_repetition": 5, "end_two_passes": 122, "end_move_limit": 1}}, "files": "/work/pass_8/"}
```Exact prompt · Raw CLI events · Settings and audit
Games pass 8 of 10 done.
```
{"ok": true, "pass": 8, "kind": "games", "per_opponent": {"strong": {"games": 128, "score": 0.5859375, "wins": 75, "losses": 53, "score_as_black": 0.59375, "score_as_white": 0.578125, "mean_margin": 29.34375, "mean_length": 106.7109375, "stones_captured_per_game": 28.203125, "stones_lost_per_game": 10.8984375, "network_passes_per_game": 1.890625, "all_player_passes_per_game": 4.265625, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 1, "end_repetition": 5, "end_two_passes": 122, "end_move_limit": 1}}, "files": "/work/pass_8/"}
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import json, numpy as np, collections
gs=json.load(open("/work/pass_8/games.json"))
bs=np.load("/work/pass_8/boards.npy")
def show(b):
print("\n".join("".join({0:".",1:"X",-1:"O"}[int(x)] for x in row)
for row in b.reshape(9,9)))
print("Loss endings:",collections.Counter(g["end"] for g in gs if g["result"]<0))
print("Loss margin distribution:",collections.Counter(
"near" if g["margin"]>-10 else "medium" if g["margin"]>-30 else "large"
for g in gs if g["result"]<0))
for i,g in enumerate(gs):
if g["end"]=="repetition":
print("\nRepetition",i,"result",g["result"],g["net_color"],g["margin"],
[(m["by"],m["move"]) for m in g["moves"][-6:]])
show(bs[i,len(g["moves"])-4])
for i,g in enumerate(gs):
if g["result"]<0 and g["end"]=="two_passes" and g["margin"]>-6:
print("\nClose loss",i,g["net_color"],g["margin"],
"captured",g["stones_captured"],"lost",g["stones_lost"])
show(bs[i,len(g["moves"])-1])
print("Last moves:",g["moves"][-4:])
if i>25: break
```
{
"request_sha256": "4343210c788d63e31c2eb1c73e0d96b44b2fd38f075ed2320a96b7ca1f5451d4",
"request": {
"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import json, numpy as np, collections\ngs=json.load(open(\"/work/pass_8/games.json\"))\nbs=np.load(\"/work/pass_8/boards.npy\")\ndef show(b):\n print(\"\\n\".join(\"\".join({0:\".\",1:\"X\",-1:\"O\"}[int(x)] for x in row)\n for row in b.reshape(9,9)))\nprint(\"Loss endings:\",collections.Counter(g[\"end\"] for g in gs if g[\"result\"]<0))\nprint(\"Loss margin distribution:\",collections.Counter(\n \"near\" if g[\"margin\"]>-10 else \"medium\" if g[\"margin\"]>-30 else \"large\"\n for g in gs if g[\"result\"]<0))\nfor i,g in enumerate(gs):\n if g[\"end\"]==\"repetition\":\n print(\"\\nRepetition\",i,\"result\",g[\"result\"],g[\"net_color\"],g[\"margin\"],\n [(m[\"by\"],m[\"move\"]) for m in g[\"moves\"][-6:]])\n show(bs[i,len(g[\"moves\"])-4])\nfor i,g in enumerate(gs):\n if g[\"result\"]<0 and g[\"end\"]==\"two_passes\" and g[\"margin\"]>-6:\n print(\"\\nClose loss\",i,g[\"net_color\"],g[\"margin\"],\n \"captured\",g[\"stones_captured\"],\"lost\",g[\"stones_lost\"])\n show(bs[i,len(g[\"moves\"])-1])\n print(\"Last moves:\",g[\"moves\"][-4:])\n if i>25: break"
},
"result": {
"ok": true,
"out": "Loss endings: Counter({'two_passes': 50, 'repetition': 3})\nLoss margin distribution: Counter({'near': 34, 'medium': 19})\n\nRepetition 37 result -1 white 8.5 [('strong', 70), ('net', 37), ('strong', 10), ('net', 56), ('strong', 74), ('net', 65)]\n...X.....\n.XXOO....\n..XXO.O..\n.OXXO.O..\n.OXXOO.O.\n.OXXO.O..\n.X.XXXXX.\n.XOXXXOX.\n.O.OOOO..\n\nRepetition 89 result -1 white 14.5 [('strong', 34), ('net', 17), ('strong', 0), ('net', 81), ('strong', 8), ('net', 9)]\nXOOOO.OO.\n.XOOOOOXO\nXXOXOOOXX\nXXOXOOXXX\nOXXXXXX.X\nOOXXOOXX.\nOOOXOOOX.\n.O.OOOXXX\nO.OO.OXX.\n\nRepetition 94 result 1 black -8.5 [('net', 40), ('strong', 80), ('net', 38), ('strong', 35), ('net', 53), ('strong', 44)]\n.........\n...X..OO.\n.X.XOOOXX\n..X.XXOX.\n..XOXXXXO\n...XXOXO.\n..XO.OOOO\n....OOXO.\n...O..XXO\n\nRepetition 101 result 1 white 7.5 [('net', 52), ('strong', 59), ('net', 41), ('strong', 51), ('net', 33), ('strong', 42)]\n.........\nO.O......\n...OX.XX.\nO.O..X.XX\n.O.O.OXO.\nOXXXXO.O.\nOOOXXXO..\n.XX......\n.........\n\nRepetition 118 result -1 black 4.5 [('strong', 64), ('net', 74), ('strong', 49), ('net', 39), ('strong', 21), ('net', 30)]\n.........\n.OXX.X...\n.OX.XXX.X\n..OXOXOX.\n..O.OOOOX\n.OOOOOOX.\n..XOXOX.X\n.OXOXOXX.\n..XX.X...\n\nClose loss 0 black -2.5 captured 10 lost 12\n.OOOXX.X.\nOOOOX.X.X\nOOOXXXXXX\nOOOOOXXX.\nOOOOOOXXX\nOOXOXXXXX\nOO.OOOX.X\nOOOOOOXXX\nX.OXXXXXX\nLast moves: [{'ply': 96, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999985694885254], [61, 1.2529567356978077e-06], [6, 9.049274751760095e-08], [8, 5.0869612522319585e-08], [35, 2.804584564586321e-09]]}, {'ply': 97, 'by': 'strong', 'move': 28}, {'ply': 98, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999985694885254], [61, 1.346504973298579e-06], [6, 9.049274751760095e-08], [8, 5.0869612522319585e-08], [35, 3.013980620636403e-09]]}, {'ply': 99, 'by': 'strong', 'move': 81}]\n\nClose loss 5 white -0.5 captured 8 lost 18\n.OOO.OOX.\nOO.OO.OXX\n.OOOOOOXX\nOOXXXXXXX\nOOOXXXXOX\nOOOX.XX.X\nOXXXXXXXX\nOOXXXXXXX\n.OOXXXX.X\nLast moves: [{'ply': 95, 'by': 'net', 'move': 37, 'top5': [[37, 0.8139641880989075], [81, 0.1860358566045761], [0, 6.844517397297523e-09], [4, 2.5432491668198054e-09], [18, 1.236198365894836e-10]]}, {'ply': 96, 'by': 'strong', 'move': 78}, {'ply': 97, 'by': 'net', 'move': 81, 'top5': [[81, 1.0], [0, 3.679139126688824e-08], [4, 1.4691434735425446e-08], [18, 1.2254046666271279e-09], [14, 4.472043013681315e-10]]}, {'ply': 98, 'by': 'strong', 'move': 81}]\n\nClose loss 13 white -1.5 captured 2 lost 14\n.O.O.OXXX\nO.O.OOXXO\nOO.OOOXX.\n.OOOOXXXX\nOOOXOOOXX\nXXOXOXXOX\nXXOXOXX.X\nXXXXXXXXX\nX.XXXXX.X\nLast moves: [{'ply': 85, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999998807907104], [4, 5.5660194675510866e-08], [0, 2.4760947070490147e-08], [12, 7.824498382547063e-09], [20, 4.900182926093066e-09]]}, {'ply': 86, 'by': 'strong', 'move': 72}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999998807907104], [4, 5.5660194675510866e-08], [0, 2.4760947070490147e-08], [12, 7.824498382547063e-09], [20, 4.900182926093066e-09]]}, {'ply': 88, 'by': 'strong', 'move': 81}]\n\nClose loss 16 black -3.5 captured 7 lost 10\n.XXXXX.X.\nXOOXX.X.X\nOOXX.X.X.\nOOOXXXXXX\nOOXXOOOX.\nOOOOOXXXX\nOO.OOOOOO\nXOO.OOOO.\nX.OO.OX.X\nLast moves: [{'ply': 81, 'by': 'strong', 'move': 54}, {'ply': 82, 'by': 'net', 'move': 3, 'top5': [[3, 0.999994158744812], [81, 5.786420388176339e-06], [24, 1.7782489077165092e-13], [16, 1.5122461388596825e-13], [6, 1.3094591329223387e-13]]}, {'ply': 83, 'by': 'strong', 'move': 81}, {'ply': 84, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999998807907104], [24, 3.3025347789816806e-08], [6, 2.8086045489317257e-08], [16, 2.8085617387318962e-08], [44, 2.1057957155790064e-08]]}]\n\nClose loss 19 white -2.5 captured 2 lost 14\nO.O.OO.O.\n.O.OO.OOO\nOOOXOOO.O\nOXXXXO.OO\nOXXXXOOXX\nXXXXXXXXX\nXX.OXXX.X\n.XXXXXXXX\nXXXXXXX.X\nLast moves: [{'ply': 85, 'by': 'net', 'move': 81, 'top5': [[81, 0.9820897579193115], [33, 0.01259971410036087], [11, 0.005310445558279753], [8, 3.613244814459904e-08], [3, 2.4317476032820196e-08]]}, {'ply': 86, 'by': 'strong', 'move': 72}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9820897579193115], [33, 0.01259971410036087], [11, 0.005310445558279753], [8, 3.613244814459904e-08], [3, 2.4317476032820196e-08]]}, {'ply': 88, 'by': 'strong', 'move': 81}]\n\nClose loss 22 black -5.5 captured 9 lost 15\nOOOOOOXX.\n.XOOOOX.X\nOOOOXX.X.\nOOOOOXXXX\nOOOXXX.XX\nO.OOXXX.X\nOOOOXX.X.\nOOOOOOX.X\n..OXXXXX.\nLast moves: [{'ply': 91, 'by': 'strong', 'move': 18}, {'ply': 92, 'by': 'net', 'move': 10, 'top5': [[10, 0.913257896900177], [81, 0.05711330100893974], [72, 0.014541899785399437], [73, 0.0074711511842906475], [9, 0.003769822884351015]]}, {'ply': 93, 'by': 'strong', 'move': 81}, {'ply': 94, 'by': 'net', 'move': 81, 'top5': [[81, 0.6859683394432068], [72, 0.17465779185295105], [73, 0.08973343670368195], [60, 0.045278746634721756], [24, 0.004361544270068407]]}]\n\nClose loss 23 white -1.5 captured 7 lost 23\n.XXXXXO.O\nXXXXXXOO.\nXXXX.XO.O\nXOOOXXXO.\nXXO.XXOOO\nXXXXXO.O.\nXXXXXOO.O\nXXXXXOOO.\n.X.OXO.OO\nLast moves: [{'ply': 98, 'by': 'strong', 'move': 81}, {'ply': 99, 'by': 'net', 'move': 75, 'top5': [[81, 0.7301363945007324], [75, 0.2146967649459839], [74, 0.03679030388593674], [51, 0.014957912266254425], [25, 0.003418534528464079]]}, {'ply': 100, 'by': 'strong', 'move': 81}, {'ply': 101, 'by': 'net', 'move': 81, 'top5': [[81, 0.9736648797988892], [51, 0.021435903385281563], [25, 0.00489911250770092], [35, 2.8348731362370927e-08], [7, 1.2165319418500076e-08]]}]\n\nClose loss 33 white -3.5 captured 2 lost 13\n.O.O.OXXX\nO.O.OOX.X\n.OOOOOXX.\nOOOXXXXXX\nOOOOOOOXX\nOXXXXXOOX\nXXXXOOOOX\nXX.XXXXXX\n.XXXXXXXX\nLast moves: [{'ply': 86, 'by': 'strong', 'move': 7}, {'ply': 87, 'by': 'net', 'move': 20, 'top5': [[81, 0.9616538882255554], [20, 0.03834594413638115], [4, 5.352585219497996e-08], [12, 1.8177106042571722e-08], [18, 1.7534448559786142e-08]]}, {'ply': 88, 'by': 'strong', 'move': 81}, {'ply': 89, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999998807907104], [4, 5.981589623615946e-08], [18, 1.9951006180463082e-08], [2, 1.367095503468363e-08], [0, 9.53789669466687e-09]]}]\n",
"stdout": "Loss endings: Counter({'two_passes': 50, 'repetition': 3})\nLoss margin distribution: Counter({'near': 34, 'medium': 19})\n\nRepetition 37 result -1 white 8.5 [('strong', 70), ('net', 37), ('strong', 10), ('net', 56), ('strong', 74), ('net', 65)]\n...X.....\n.XXOO....\n..XXO.O..\n.OXXO.O..\n.OXXOO.O.\n.OXXO.O..\n.X.XXXXX.\n.XOXXXOX.\n.O.OOOO..\n\nRepetition 89 result -1 white 14.5 [('strong', 34), ('net', 17), ('strong', 0), ('net', 81), ('strong', 8), ('net', 9)]\nXOOOO.OO.\n.XOOOOOXO\nXXOXOOOXX\nXXOXOOXXX\nOXXXXXX.X\nOOXXOOXX.\nOOOXOOOX.\n.O.OOOXXX\nO.OO.OXX.\n\nRepetition 94 result 1 black -8.5 [('net', 40), ('strong', 80), ('net', 38), ('strong', 35), ('net', 53), ('strong', 44)]\n.........\n...X..OO.\n.X.XOOOXX\n..X.XXOX.\n..XOXXXXO\n...XXOXO.\n..XO.OOOO\n....OOXO.\n...O..XXO\n\nRepetition 101 result 1 white 7.5 [('net', 52), ('strong', 59), ('net', 41), ('strong', 51), ('net', 33), ('strong', 42)]\n.........\nO.O......\n...OX.XX.\nO.O..X.XX\n.O.O.OXO.\nOXXXXO.O.\nOOOXXXO..\n.XX......\n.........\n\nRepetition 118 result -1 black 4.5 [('strong', 64), ('net', 74), ('strong', 49), ('net', 39), ('strong', 21), ('net', 30)]\n.........\n.OXX.X...\n.OX.XXX.X\n..OXOXOX.\n..O.OOOOX\n.OOOOOOX.\n..XOXOX.X\n.OXOXOXX.\n..XX.X...\n\nClose loss 0 black -2.5 captured 10 lost 12\n.OOOXX.X.\nOOOOX.X.X\nOOOXXXXXX\nOOOOOXXX.\nOOOOOOXXX\nOOXOXXXXX\nOO.OOOX.X\nOOOOOOXXX\nX.OXXXXXX\nLast moves: [{'ply': 96, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999985694885254], [61, 1.2529567356978077e-06], [6, 9.049274751760095e-08], [8, 5.0869612522319585e-08], [35, 2.804584564586321e-09]]}, {'ply': 97, 'by': 'strong', 'move': 28}, {'ply': 98, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999985694885254], [61, 1.346504973298579e-06], [6, 9.049274751760095e-08], [8, 5.0869612522319585e-08], [35, 3.013980620636403e-09]]}, {'ply': 99, 'by': 'strong', 'move': 81}]\n\nClose loss 5 white -0.5 captured 8 lost 18\n.OOO.OOX.\nOO.OO.OXX\n.OOOOOOXX\nOOXXXXXXX\nOOOXXXXOX\nOOOX.XX.X\nOXXXXXXXX\nOOXXXXXXX\n.OOXXXX.X\nLast moves: [{'ply': 95, 'by': 'net', 'move': 37, 'top5': [[37, 0.8139641880989075], [81, 0.1860358566045761], [0, 6.844517397297523e-09], [4, 2.5432491668198054e-09], [18, 1.236198365894836e-10]]}, {'ply': 96, 'by': 'strong', 'move': 78}, {'ply': 97, 'by': 'net', 'move': 81, 'top5': [[81, 1.0], [0, 3.679139126688824e-08], [4, 1.4691434735425446e-08], [18, 1.2254046666271279e-09], [14, 4.472043013681315e-10]]}, {'ply': 98, 'by': 'strong', 'move': 81}]\n\nClose loss 13 white -1.5 captured 2 lost 14\n.O.O.OXXX\nO.O.OOXXO\nOO.OOOXX.\n.OOOOXXXX\nOOOXOOOXX\nXXOXOXXOX\nXXOXOXX.X\nXXXXXXXXX\nX.XXXXX.X\nLast moves: [{'ply': 85, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999998807907104], [4, 5.5660194675510866e-08], [0, 2.4760947070490147e-08], [12, 7.824498382547063e-09], [20, 4.900182926093066e-09]]}, {'ply': 86, 'by': 'strong', 'move': 72}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999998807907104], [4, 5.5660194675510866e-08], [0, 2.4760947070490147e-08], [12, 7.824498382547063e-09], [20, 4.900182926093066e-09]]}, {'ply': 88, 'by': 'strong', 'move': 81}]\n\nClose loss 16 black -3.5 captured 7 lost 10\n.XXXXX.X.\nXOOXX.X.X\nOOXX.X.X.\nOOOXXXXXX\nOOXXOOOX.\nOOOOOXXXX\nOO.OOOOOO\nXOO.OOOO.\nX.OO.OX.X\nLast moves: [{'ply': 81, 'by': 'strong', 'move': 54}, {'ply': 82, 'by': 'net', 'move': 3, 'top5': [[3, 0.999994158744812], [81, 5.786420388176339e-06], [24, 1.7782489077165092e-13], [16, 1.5122461388596825e-13], [6, 1.3094591329223387e-13]]}, {'ply': 83, 'by': 'strong', 'move': 81}, {'ply': 84, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999998807907104], [24, 3.3025347789816806e-08], [6, 2.8086045489317257e-08], [16, 2.8085617387318962e-08], [44, 2.1057957155790064e-08]]}]\n\nClose loss 19 white -2.5 captured 2 lost 14\nO.O.OO.O.\n.O.OO.OOO\nOOOXOOO.O\nOXXXXO.OO\nOXXXXOOXX\nXXXXXXXXX\nXX.OXXX.X\n.XXXXXXXX\nXXXXXXX.X\nLast moves: [{'ply': 85, 'by': 'net', 'move': 81, 'top5': [[81, 0.9820897579193115], [33, 0.01259971410036087], [11, 0.005310445558279753], [8, 3.613244814459904e-08], [3, 2.4317476032820196e-08]]}, {'ply': 86, 'by': 'strong', 'move': 72}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9820897579193115], [33, 0.01259971410036087], [11, 0.005310445558279753], [8, 3.613244814459904e-08], [3, 2.4317476032820196e-08]]}, {'ply': 88, 'by': 'strong', 'move': 81}]\n\nClose loss 22 black -5.5 captured 9 lost 15\nOOOOOOXX.\n.XOOOOX.X\nOOOOXX.X.\nOOOOOXXXX\nOOOXXX.XX\nO.OOXXX.X\nOOOOXX.X.\nOOOOOOX.X\n..OXXXXX.\nLast moves: [{'ply': 91, 'by': 'strong', 'move': 18}, {'ply': 92, 'by': 'net', 'move': 10, 'top5': [[10, 0.913257896900177], [81, 0.05711330100893974], [72, 0.014541899785399437], [73, 0.0074711511842906475], [9, 0.003769822884351015]]}, {'ply': 93, 'by': 'strong', 'move': 81}, {'ply': 94, 'by': 'net', 'move': 81, 'top5': [[81, 0.6859683394432068], [72, 0.17465779185295105], [73, 0.08973343670368195], [60, 0.045278746634721756], [24, 0.004361544270068407]]}]\n\nClose loss 23 white -1.5 captured 7 lost 23\n.XXXXXO.O\nXXXXXXOO.\nXXXX.XO.O\nXOOOXXXO.\nXXO.XXOOO\nXXXXXO.O.\nXXXXXOO.O\nXXXXXOOO.\n.X.OXO.OO\nLast moves: [{'ply': 98, 'by': 'strong', 'move': 81}, {'ply': 99, 'by': 'net', 'move': 75, 'top5': [[81, 0.7301363945007324], [75, 0.2146967649459839], [74, 0.03679030388593674], [51, 0.014957912266254425], [25, 0.003418534528464079]]}, {'ply': 100, 'by': 'strong', 'move': 81}, {'ply': 101, 'by': 'net', 'move': 81, 'top5': [[81, 0.9736648797988892], [51, 0.021435903385281563], [25, 0.00489911250770092], [35, 2.8348731362370927e-08], [7, 1.2165319418500076e-08]]}]\n\nClose loss 33 white -3.5 captured 2 lost 13\n.O.O.OXXX\nO.O.OOX.X\n.OOOOOXX.\nOOOXXXXXX\nOOOOOOOXX\nOXXXXXOOX\nXXXXOOOOX\nXX.XXXXXX\n.XXXXXXXX\nLast moves: [{'ply': 86, 'by': 'strong', 'move': 7}, {'ply': 87, 'by': 'net', 'move': 20, 'top5': [[81, 0.9616538882255554], [20, 0.03834594413638115], [4, 5.352585219497996e-08], [12, 1.8177106042571722e-08], [18, 1.7534448559786142e-08]]}, {'ply': 88, 'by': 'strong', 'move': 81}, {'ply': 89, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999998807907104], [4, 5.981589623615946e-08], [18, 1.9951006180463082e-08], [2, 1.367095503468363e-08], [0, 9.53789669466687e-09]]}]\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.3962149848230183,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-5363e92ac4264a70a941a9a2ba7a6738",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
"-i",
"HOME=/tmp",
"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
"MKL_NUM_THREADS=8",
"CUDA_VISIBLE_DEVICES=",
"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 14 of at most 120:
```
Loss endings: Counter({'two_passes': 50, 'repetition': 3})
Loss margin distribution: Counter({'near': 34, 'medium': 19})
Repetition 37 result -1 white 8.5 [('strong', 70), ('net', 37), ('strong', 10), ('net', 56), ('strong', 74), ('net', 65)]
...X.....
.XXOO....
..XXO.O..
.OXXO.O..
.OXXOO.O.
.OXXO.O..
.X.XXXXX.
.XOXXXOX.
.O.OOOO..
Repetition 89 result -1 white 14.5 [('strong', 34), ('net', 17), ('strong', 0), ('net', 81), ('strong', 8), ('net', 9)]
XOOOO.OO.
.XOOOOOXO
XXOXOOOXX
XXOXOOXXX
OXXXXXX.X
OOXXOOXX.
OOOXOOOX.
.O.OOOXXX
O.OO.OXX.
Repetition 94 result 1 black -8.5 [('net', 40), ('strong', 80), ('net', 38), ('strong', 35), ('net', 53), ('strong', 44)]
.........
...X..OO.
.X.XOOOXX
..X.XXOX.
..XOXXXXO
...XXOXO.
..XO.OOOO
....OOXO.
...O..XXO
Repetition 101 result 1 white 7.5 [('net', 52), ('strong', 59), ('net', 41), ('strong', 51), ('net', 33), ('strong', 42)]
.........
O.O......
...OX.XX.
O.O..X.XX
.O.O.OXO.
OXXXXO.O.
OOOXXXO..
.XX......
.........
Repetition 118 result -1 black 4.5 [('strong', 64), ('net', 74), ('strong', 49), ('net', 39), ('strong', 21), ('net', 30)]
.........
.OXX.X...
.OX.XXX.X
..OXOXOX.
..O.OOOOX
.OOOOOOX.
..XOXOX.X
.OXOXOXX.
..XX.X...
Close loss 0 black -2.5 captured 10 lost 12
.OOOXX.X.
OOOOX.X.X
OOOXXXXXX
OOOOOXXX.
OOOOOOXXX
OOXOXXXXX
OO.OOOX.X
OOOOOOXXX
X.OXXXXXX
Last moves: [{'ply': 96, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999985694885254], [61, 1.2529567356978077e-06], [6, 9.049274751760095e-08], [8, 5.0869612522319585e-08], [35, 2.804584564586321e-09]]}, {'ply': 97, 'by': 'strong', 'move': 28}, {'ply': 98, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999985694885254], [61, 1.346504973298579e-06], [6, 9.049274751760095e-08], [8, 5.0869612522319585e-08], [35, 3.013980620636403e-09]]}, {'ply': 99, 'by': 'strong', 'move': 81}]
Close loss 5 white -0.5 captured 8 lost 18
.OOO.OOX.
OO.OO.OXX
.OOOOOOXX
OOXXXXXXX
OOOXXXXOX
OOOX.XX.X
OXXXXXXXX
OOXXXXXXX
.OOXXXX.X
Last moves: [{'ply': 95, 'by': 'net', 'move': 37, 'top5': [[37, 0.8139641880989075], [81, 0.1860358566045761], [0, 6.844517397297523e-09], [4, 2.5432491668198054e-09], [18, 1.236198365894836e-10]]}, {'ply': 96, 'by': 'strong', 'move': 78}, {'ply': 97, 'by': 'net', 'move': 81, 'top5': [[81, 1.0], [0, 3.679139126688824e-08], [4, 1.4691434735425446e-08], [18, 1.2254046666271279e-09], [14, 4.472043013681315e-10]]}, {'ply': 98, 'by': 'strong', 'move': 81}]
Close loss 13 white -1.5 captured 2 lost 14
.O.O.OXXX
O.O.OOXXO
OO.OOOXX.
.OOOOXXXX
OOOXOOOXX
XXOXOXXOX
XXOXOXX.X
XXXXXXXXX
X.XXXXX.X
Last moves: [{'ply': 85, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999998807907104], [4, 5.5660194675510866e-08], [0, 2.4760947070490147e-08], [12, 7.824498382547063e-09], [20, 4.900182926093066e-09]]}, {'ply': 86, 'by': 'strong', 'move': 72}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999998807907104], [4, 5.5660194675510866e-08], [0, 2.4760947070490147e-08], [12, 7.824498382547063e-09], [20, 4.900182926093066e-09]]}, {'ply': 88, 'by': 'strong', 'move': 81}]
Close loss 16 black -3.5 captured 7 lost 10
.XXXXX.X.
XOOXX.X.X
OOXX.X.X.
OOOXXXXXX
OOXXOOOX.
OOOOOXXXX
OO.OOOOOO
XOO.OOOO.
X.OO.OX.X
Last moves: [{'ply': 81, 'by': 'strong', 'move': 54}, {'ply': 82, 'by': 'net', 'move': 3, 'top5': [[3, 0.999994158744812], [81, 5.786420388176339e-06], [24, 1.7782489077165092e-13], [16, 1.5122461388596825e-13], [6, 1.3094591329223387e-13]]}, {'ply': 83, 'by': 'strong', 'move': 81}, {'ply': 84, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999998807907104], [24, 3.3025347789816806e-08], [6, 2.8086045489317257e-08], [16, 2.8085617387318962e-08], [44, 2.1057957155790064e-08]]}]
Close loss 19 white -2.5 captured 2 lost 14
O.O.OO.O.
.O.OO.OOO
OOOXOOO.O
OXXXXO.OO
OXXXXOOXX
XXXXXXXXX
XX.OXXX.X
.XXXXXXXX
XXXXXXX.X
Last moves: [{'ply': 85, 'by': 'net', 'move': 81, 'top5': [[81, 0.9820897579193115], [33, 0.01259971410036087], [11, 0.005310445558279753], [8, 3.613244814459904e-08], [3, 2.4317476032820196e-08]]}, {'ply': 86, 'by': 'strong', 'move': 72}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9820897579193115], [33, 0.01259971410036087], [11, 0.005310445558279753], [8, 3.613244814459904e-08], [3, 2.4317476032820196e-08]]}, {'ply': 88, 'by': 'strong', 'move': 81}]
Close loss 22 black -5.5 captured 9 lost 15
OOOOOOXX.
.XOOOOX.X
OOOOXX.X.
OOOOOXXXX
OOOXXX.XX
O.OOXXX.X
OOOOXX.X.
OOOOOOX.X
..OXXXXX.
Last moves: [{'ply': 91, 'by': 'strong', 'move': 18}, {'ply': 92, 'by': 'net', 'move': 10, 'top5': [[10, 0.913257896900177], [81, 0.05711330100893974], [72, 0.014541899785399437], [73, 0.0074711511842906475], [9, 0.003769822884351015]]}, {'ply': 93, 'by': 'strong', 'move': 81}, {'ply': 94, 'by': 'net', 'move': 81, 'top5': [[81, 0.6859683394432068], [72, 0.17465779185295105], [73, 0.08973343670368195], [60, 0.045278746634721756], [24, 0.004361544270068407]]}]
Close loss 23 white -1.5 captured 7 lost 23
.XXXXXO.O
XXXXXXOO.
XXXX.XO.O
XOOOXXXO.
XXO.XXOOO
XXXXXO.O.
XXXXXOO.O
XXXXXOOO.
.X.OXO.OO
Last moves: [{'ply': 98, 'by': 'strong', 'move': 81}, {'ply': 99, 'by': 'net', 'move': 75, 'top5': [[81, 0.7301363945007324], [75, 0.2146967649459839], [74, 0.03679030388593674], [51, 0.014957912266254425], [25, 0.003418534528464079]]}, {'ply': 100, 'by': 'strong', 'move': 81}, {'ply': 101, 'by': 'net', 'move': 81, 'top5': [[81, 0.9736648797988892], [51, 0.021435903385281563], [25, 0.00489911250770092], [35, 2.8348731362370927e-08], [7, 1.2165319418500076e-08]]}]
Close loss 33 white -3.5 captured 2 lost 13
.O.O.OXXX
O.O.OOX.X
.OOOOOXX.
OOOXXXXXX
OOOOOOOXX
OXXXXXOOX
XXXXOOOOX
XX.XXXXXX
.XXXXXXXX
Last moves: [{'ply': 86, 'by': 'strong', 'move': 7}, {'ply': 87, 'by': 'net', 'move': 20, 'top5': [[81, 0.9616538882255554], [20, 0.03834594413638115], [4, 5.352585219497996e-08], [12, 1.8177106042571722e-08], [18, 1.7534448559786142e-08]]}, {'ply': 88, 'by': 'strong', 'move': 81}, {'ply': 89, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999998807907104], [4, 5.981589623615946e-08], [18, 1.9951006180463082e-08], [2, 1.367095503468363e-08], [0, 9.53789669466687e-09]]}]
```Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 14 of at most 120:
```
Loss endings: Counter({'two_passes': 50, 'repetition': 3})
Loss margin distribution: Counter({'near': 34, 'medium': 19})
Repetition 37 result -1 white 8.5 [('strong', 70), ('net', 37), ('strong', 10), ('net', 56), ('strong', 74), ('net', 65)]
...X.....
.XXOO....
..XXO.O..
.OXXO.O..
.OXXOO.O.
.OXXO.O..
.X.XXXXX.
.XOXXXOX.
.O.OOOO..
Repetition 89 result -1 white 14.5 [('strong', 34), ('net', 17), ('strong', 0), ('net', 81), ('strong', 8), ('net', 9)]
XOOOO.OO.
.XOOOOOXO
XXOXOOOXX
XXOXOOXXX
OXXXXXX.X
OOXXOOXX.
OOOXOOOX.
.O.OOOXXX
O.OO.OXX.
Repetition 94 result 1 black -8.5 [('net', 40), ('strong', 80), ('net', 38), ('strong', 35), ('net', 53), ('strong', 44)]
.........
...X..OO.
.X.XOOOXX
..X.XXOX.
..XOXXXXO
...XXOXO.
..XO.OOOO
....OOXO.
...O..XXO
Repetition 101 result 1 white 7.5 [('net', 52), ('strong', 59), ('net', 41), ('strong', 51), ('net', 33), ('strong', 42)]
.........
O.O......
...OX.XX.
O.O..X.XX
.O.O.OXO.
OXXXXO.O.
OOOXXXO..
.XX......
.........
Repetition 118 result -1 black 4.5 [('strong', 64), ('net', 74), ('strong', 49), ('net', 39), ('strong', 21), ('net', 30)]
.........
.OXX.X...
.OX.XXX.X
..OXOXOX.
..O.OOOOX
.OOOOOOX.
..XOXOX.X
.OXOXOXX.
..XX.X...
Close loss 0 black -2.5 captured 10 lost 12
.OOOXX.X.
OOOOX.X.X
OOOXXXXXX
OOOOOXXX.
OOOOOOXXX
OOXOXXXXX
OO.OOOX.X
OOOOOOXXX
X.OXXXXXX
Last moves: [{'ply': 96, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999985694885254], [61, 1.2529567356978077e-06], [6, 9.049274751760095e-08], [8, 5.0869612522319585e-08], [35, 2.804584564586321e-09]]}, {'ply': 97, 'by': 'strong', 'move': 28}, {'ply': 98, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999985694885254], [61, 1.346504973298579e-06], [6, 9.049274751760095e-08], [8, 5.0869612522319585e-08], [35, 3.013980620636403e-09]]}, {'ply': 99, 'by': 'strong', 'move': 81}]
Close loss 5 white -0.5 captured 8 lost 18
.OOO.OOX.
OO.OO.OXX
.OOOOOOXX
OOXXXXXXX
OOOXXXXOX
OOOX.XX.X
OXXXXXXXX
OOXXXXXXX
.OOXXXX.X
Last moves: [{'ply': 95, 'by': 'net', 'move': 37, 'top5': [[37, 0.8139641880989075], [81, 0.1860358566045761], [0, 6.844517397297523e-09], [4, 2.5432491668198054e-09], [18, 1.236198365894836e-10]]}, {'ply': 96, 'by': 'strong', 'move': 78}, {'ply': 97, 'by': 'net', 'move': 81, 'top5': [[81, 1.0], [0, 3.679139126688824e-08], [4, 1.4691434735425446e-08], [18, 1.2254046666271279e-09], [14, 4.472043013681315e-10]]}, {'ply': 98, 'by': 'strong', 'move': 81}]
Close loss 13 white -1.5 captured 2 lost 14
.O.O.OXXX
O.O.OOXXO
OO.OOOXX.
.OOOOXXXX
OOOXOOOXX
XXOXOXXOX
XXOXOXX.X
XXXXXXXXX
X.XXXXX.X
Last moves: [{'ply': 85, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999998807907104], [4, 5.5660194675510866e-08], [0, 2.4760947070490147e-08], [12, 7.824498382547063e-09], [20, 4.900182926093066e-09]]}, {'ply': 86, 'by': 'strong', 'move': 72}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999998807907104], [4, 5.5660194675510866e-08], [0, 2.4760947070490147e-08], [12, 7.824498382547063e-09], [20, 4.900182926093066e-09]]}, {'ply': 88, 'by': 'strong', 'move': 81}]
Close loss 16 black -3.5 captured 7 lost 10
.XXXXX.X.
XOOXX.X.X
OOXX.X.X.
OOOXXXXXX
OOXXOOOX.
OOOOOXXXX
OO.OOOOOO
XOO.OOOO.
X.OO.OX.X
Last moves: [{'ply': 81, 'by': 'strong', 'move': 54}, {'ply': 82, 'by': 'net', 'move': 3, 'top5': [[3, 0.999994158744812], [81, 5.786420388176339e-06], [24, 1.7782489077165092e-13], [16, 1.5122461388596825e-13], [6, 1.3094591329223387e-13]]}, {'ply': 83, 'by': 'strong', 'move': 81}, {'ply': 84, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999998807907104], [24, 3.3025347789816806e-08], [6, 2.8086045489317257e-08], [16, 2.8085617387318962e-08], [44, 2.1057957155790064e-08]]}]
Close loss 19 white -2.5 captured 2 lost 14
O.O.OO.O.
.O.OO.OOO
OOOXOOO.O
OXXXXO.OO
OXXXXOOXX
XXXXXXXXX
XX.OXXX.X
.XXXXXXXX
XXXXXXX.X
Last moves: [{'ply': 85, 'by': 'net', 'move': 81, 'top5': [[81, 0.9820897579193115], [33, 0.01259971410036087], [11, 0.005310445558279753], [8, 3.613244814459904e-08], [3, 2.4317476032820196e-08]]}, {'ply': 86, 'by': 'strong', 'move': 72}, {'ply': 87, 'by': 'net', 'move': 81, 'top5': [[81, 0.9820897579193115], [33, 0.01259971410036087], [11, 0.005310445558279753], [8, 3.613244814459904e-08], [3, 2.4317476032820196e-08]]}, {'ply': 88, 'by': 'strong', 'move': 81}]
Close loss 22 black -5.5 captured 9 lost 15
OOOOOOXX.
.XOOOOX.X
OOOOXX.X.
OOOOOXXXX
OOOXXX.XX
O.OOXXX.X
OOOOXX.X.
OOOOOOX.X
..OXXXXX.
Last moves: [{'ply': 91, 'by': 'strong', 'move': 18}, {'ply': 92, 'by': 'net', 'move': 10, 'top5': [[10, 0.913257896900177], [81, 0.05711330100893974], [72, 0.014541899785399437], [73, 0.0074711511842906475], [9, 0.003769822884351015]]}, {'ply': 93, 'by': 'strong', 'move': 81}, {'ply': 94, 'by': 'net', 'move': 81, 'top5': [[81, 0.6859683394432068], [72, 0.17465779185295105], [73, 0.08973343670368195], [60, 0.045278746634721756], [24, 0.004361544270068407]]}]
Close loss 23 white -1.5 captured 7 lost 23
.XXXXXO.O
XXXXXXOO.
XXXX.XO.O
XOOOXXXO.
XXO.XXOOO
XXXXXO.O.
XXXXXOO.O
XXXXXOOO.
.X.OXO.OO
Last moves: [{'ply': 98, 'by': 'strong', 'move': 81}, {'ply': 99, 'by': 'net', 'move': 75, 'top5': [[81, 0.7301363945007324], [75, 0.2146967649459839], [74, 0.03679030388593674], [51, 0.014957912266254425], [25, 0.003418534528464079]]}, {'ply': 100, 'by': 'strong', 'move': 81}, {'ply': 101, 'by': 'net', 'move': 81, 'top5': [[81, 0.9736648797988892], [51, 0.021435903385281563], [25, 0.00489911250770092], [35, 2.8348731362370927e-08], [7, 1.2165319418500076e-08]]}]
Close loss 33 white -3.5 captured 2 lost 13
.O.O.OXXX
O.O.OOX.X
.OOOOOXX.
OOOXXXXXX
OOOOOOOXX
OXXXXXOOX
XXXXOOOOX
XX.XXXXXX
.XXXXXXXX
Last moves: [{'ply': 86, 'by': 'strong', 'move': 7}, {'ply': 87, 'by': 'net', 'move': 20, 'top5': [[81, 0.9616538882255554], [20, 0.03834594413638115], [4, 5.352585219497996e-08], [12, 1.8177106042571722e-08], [18, 1.7534448559786142e-08]]}, {'ply': 88, 'by': 'strong', 'move': 81}, {'ply': 89, 'by': 'net', 'move': 81, 'top5': [[81, 0.9999998807907104], [4, 5.981589623615946e-08], [18, 1.9951006180463082e-08], [2, 1.367095503468363e-08], [0, 9.53789669466687e-09]]}]
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import json, collections
gs=json.load(open("/work/pass_8/games.json"))
for who in ["net","strong"]:
c=collections.Counter()
for g in gs:
first=next(m for m in g["moves"] if m["by"]==who)
c[first["move"]]+=1
print(who,"first-move counts:",c.most_common(20))
print("First 12 plies of selected close losses:")
for i in [0,5,13,16]:
print(i,gs[i]["net_color"],
[(m["by"],divmod(m["move"],9) if m["move"]<81 else "pass")
for m in gs[i]["moves"][:12]])
```
{
"request_sha256": "d88d288bc4dd44a3cac970fa26148d4263641bf7d5f9f7931d78a7a60146e2dc",
"request": {
"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import json, collections\ngs=json.load(open(\"/work/pass_8/games.json\"))\nfor who in [\"net\",\"strong\"]:\n c=collections.Counter()\n for g in gs:\n first=next(m for m in g[\"moves\"] if m[\"by\"]==who)\n c[first[\"move\"]]+=1\n print(who,\"first-move counts:\",c.most_common(20))\nprint(\"First 12 plies of selected close losses:\")\nfor i in [0,5,13,16]:\n print(i,gs[i][\"net_color\"],\n [(m[\"by\"],divmod(m[\"move\"],9) if m[\"move\"]<81 else \"pass\")\n for m in gs[i][\"moves\"][:12]])"
},
"result": {
"ok": true,
"out": "net first-move counts: [(56, 19), (60, 19), (24, 16), (20, 15), (51, 10), (23, 8), (59, 8), (21, 7), (29, 7), (33, 4), (47, 3), (58, 3), (57, 2), (50, 2), (27, 1), (61, 1), (3, 1), (43, 1), (46, 1)]\nstrong first-move counts: [(48, 83), (40, 14), (30, 10), (41, 6), (50, 3), (32, 2), (39, 1), (49, 1), (5, 1), (24, 1), (60, 1), (34, 1), (47, 1), (22, 1), (17, 1), (57, 1)]\nFirst 12 plies of selected close losses:\n0 black [('net', (6, 2)), ('strong', (4, 4)), ('net', (5, 2)), ('strong', (3, 3)), ('net', (3, 2)), ('strong', (7, 4)), ('net', (6, 6)), ('strong', (1, 5)), ('net', (3, 5)), ('strong', (3, 4)), ('net', (2, 6)), ('strong', (4, 5))]\n5 white [('strong', (5, 3)), ('net', (2, 3)), ('strong', (3, 3)), ('net', (4, 2)), ('strong', (3, 4)), ('net', (4, 5)), ('strong', (3, 5)), ('net', (2, 6)), ('strong', (4, 6)), ('net', (4, 4)), ('strong', (4, 3)), ('net', (5, 5))]\n13 white [('strong', (5, 3)), ('net', (6, 6)), ('strong', (3, 5)), ('net', (2, 5)), ('strong', (3, 6)), ('net', (2, 1)), ('strong', (2, 6)), ('net', (2, 4)), ('strong', (7, 3)), ('net', (3, 2)), ('strong', (1, 6)), ('net', (6, 2))]\n16 black [('net', (2, 2)), ('strong', (4, 5)), ('net', (3, 3)), ('strong', (4, 4)), ('net', (5, 6)), ('strong', (6, 6)), ('net', (2, 5)), ('strong', (5, 3)), ('net', (1, 4)), ('strong', (5, 2)), ('net', (6, 4)), ('strong', (5, 4))]\n",
"stdout": "net first-move counts: [(56, 19), (60, 19), (24, 16), (20, 15), (51, 10), (23, 8), (59, 8), (21, 7), (29, 7), (33, 4), (47, 3), (58, 3), (57, 2), (50, 2), (27, 1), (61, 1), (3, 1), (43, 1), (46, 1)]\nstrong first-move counts: [(48, 83), (40, 14), (30, 10), (41, 6), (50, 3), (32, 2), (39, 1), (49, 1), (5, 1), (24, 1), (60, 1), (34, 1), (47, 1), (22, 1), (17, 1), (57, 1)]\nFirst 12 plies of selected close losses:\n0 black [('net', (6, 2)), ('strong', (4, 4)), ('net', (5, 2)), ('strong', (3, 3)), ('net', (3, 2)), ('strong', (7, 4)), ('net', (6, 6)), ('strong', (1, 5)), ('net', (3, 5)), ('strong', (3, 4)), ('net', (2, 6)), ('strong', (4, 5))]\n5 white [('strong', (5, 3)), ('net', (2, 3)), ('strong', (3, 3)), ('net', (4, 2)), ('strong', (3, 4)), ('net', (4, 5)), ('strong', (3, 5)), ('net', (2, 6)), ('strong', (4, 6)), ('net', (4, 4)), ('strong', (4, 3)), ('net', (5, 5))]\n13 white [('strong', (5, 3)), ('net', (6, 6)), ('strong', (3, 5)), ('net', (2, 5)), ('strong', (3, 6)), ('net', (2, 1)), ('strong', (2, 6)), ('net', (2, 4)), ('strong', (7, 3)), ('net', (3, 2)), ('strong', (1, 6)), ('net', (6, 2))]\n16 black [('net', (2, 2)), ('strong', (4, 5)), ('net', (3, 3)), ('strong', (4, 4)), ('net', (5, 6)), ('strong', (6, 6)), ('net', (2, 5)), ('strong', (5, 3)), ('net', (1, 4)), ('strong', (5, 2)), ('net', (6, 4)), ('strong', (5, 4))]\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.37446895288303494,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-6bb40c0d5bc94c60a3a18bd680c3b02d",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
"-i",
"HOME=/tmp",
"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
"MKL_NUM_THREADS=8",
"CUDA_VISIBLE_DEVICES=",
"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 15 of at most 120:
```
net first-move counts: [(56, 19), (60, 19), (24, 16), (20, 15), (51, 10), (23, 8), (59, 8), (21, 7), (29, 7), (33, 4), (47, 3), (58, 3), (57, 2), (50, 2), (27, 1), (61, 1), (3, 1), (43, 1), (46, 1)]
strong first-move counts: [(48, 83), (40, 14), (30, 10), (41, 6), (50, 3), (32, 2), (39, 1), (49, 1), (5, 1), (24, 1), (60, 1), (34, 1), (47, 1), (22, 1), (17, 1), (57, 1)]
First 12 plies of selected close losses:
0 black [('net', (6, 2)), ('strong', (4, 4)), ('net', (5, 2)), ('strong', (3, 3)), ('net', (3, 2)), ('strong', (7, 4)), ('net', (6, 6)), ('strong', (1, 5)), ('net', (3, 5)), ('strong', (3, 4)), ('net', (2, 6)), ('strong', (4, 5))]
5 white [('strong', (5, 3)), ('net', (2, 3)), ('strong', (3, 3)), ('net', (4, 2)), ('strong', (3, 4)), ('net', (4, 5)), ('strong', (3, 5)), ('net', (2, 6)), ('strong', (4, 6)), ('net', (4, 4)), ('strong', (4, 3)), ('net', (5, 5))]
13 white [('strong', (5, 3)), ('net', (6, 6)), ('strong', (3, 5)), ('net', (2, 5)), ('strong', (3, 6)), ('net', (2, 1)), ('strong', (2, 6)), ('net', (2, 4)), ('strong', (7, 3)), ('net', (3, 2)), ('strong', (1, 6)), ('net', (6, 2))]
16 black [('net', (2, 2)), ('strong', (4, 5)), ('net', (3, 3)), ('strong', (4, 4)), ('net', (5, 6)), ('strong', (6, 6)), ('net', (2, 5)), ('strong', (5, 3)), ('net', (1, 4)), ('strong', (5, 2)), ('net', (6, 4)), ('strong', (5, 4))]
```Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 15 of at most 120:
```
net first-move counts: [(56, 19), (60, 19), (24, 16), (20, 15), (51, 10), (23, 8), (59, 8), (21, 7), (29, 7), (33, 4), (47, 3), (58, 3), (57, 2), (50, 2), (27, 1), (61, 1), (3, 1), (43, 1), (46, 1)]
strong first-move counts: [(48, 83), (40, 14), (30, 10), (41, 6), (50, 3), (32, 2), (39, 1), (49, 1), (5, 1), (24, 1), (60, 1), (34, 1), (47, 1), (22, 1), (17, 1), (57, 1)]
First 12 plies of selected close losses:
0 black [('net', (6, 2)), ('strong', (4, 4)), ('net', (5, 2)), ('strong', (3, 3)), ('net', (3, 2)), ('strong', (7, 4)), ('net', (6, 6)), ('strong', (1, 5)), ('net', (3, 5)), ('strong', (3, 4)), ('net', (2, 6)), ('strong', (4, 5))]
5 white [('strong', (5, 3)), ('net', (2, 3)), ('strong', (3, 3)), ('net', (4, 2)), ('strong', (3, 4)), ('net', (4, 5)), ('strong', (3, 5)), ('net', (2, 6)), ('strong', (4, 6)), ('net', (4, 4)), ('strong', (4, 3)), ('net', (5, 5))]
13 white [('strong', (5, 3)), ('net', (6, 6)), ('strong', (3, 5)), ('net', (2, 5)), ('strong', (3, 6)), ('net', (2, 1)), ('strong', (2, 6)), ('net', (2, 4)), ('strong', (7, 3)), ('net', (3, 2)), ('strong', (1, 6)), ('net', (6, 2))]
16 black [('net', (2, 2)), ('strong', (4, 5)), ('net', (3, 3)), ('strong', (4, 4)), ('net', (5, 6)), ('strong', (6, 6)), ('net', (2, 5)), ('strong', (5, 3)), ('net', (1, 4)), ('strong', (5, 2)), ('net', (6, 4)), ('strong', (5, 4))]
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import numpy as np
A={n:a.copy() for n,a in dict(np.load("/work/policy_v8.npz")).items()}
# On a nine-line board the centre is strategically close to every side.
# Use a symmetric centre/fourth-line opening prior, decaying to zero as
# 24 stones accumulate; keep all tactical and later-game rules unchanged.
for p in range(81):
r,c=divmod(p,9)
rr,cc=min(r,8-r),min(c,8-c)
if (rr,cc)==(4,4):
opening=2.0
elif (rr,cc)==(3,3):
opening=1.5
elif (rr,cc) in [(3,4),(4,3)]:
opening=1.1
elif (rr,cc) in [(2,3),(3,2)]:
opening=0.5
else:
opening=0.0
A["out.W"][489,p]=1.8*opening/24
for name in NAMES: save(name,A[name])
np.savez("/work/policy_v9.npz",**A)
print("Saved symmetric nine-line centre-control opening prior.")
```
{
"request_sha256": "9fdfc582160bacf3ca242367cad1b7a14871e4b1549f5d22b709880242b07048",
"request": {
"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import numpy as np\nA={n:a.copy() for n,a in dict(np.load(\"/work/policy_v8.npz\")).items()}\n\n# On a nine-line board the centre is strategically close to every side.\n# Use a symmetric centre/fourth-line opening prior, decaying to zero as\n# 24 stones accumulate; keep all tactical and later-game rules unchanged.\nfor p in range(81):\n r,c=divmod(p,9)\n rr,cc=min(r,8-r),min(c,8-c)\n if (rr,cc)==(4,4):\n opening=2.0\n elif (rr,cc)==(3,3):\n opening=1.5\n elif (rr,cc) in [(3,4),(4,3)]:\n opening=1.1\n elif (rr,cc) in [(2,3),(3,2)]:\n opening=0.5\n else:\n opening=0.0\n A[\"out.W\"][489,p]=1.8*opening/24\n\nfor name in NAMES: save(name,A[name])\nnp.savez(\"/work/policy_v9.npz\",**A)\nprint(\"Saved symmetric nine-line centre-control opening prior.\")"
},
"result": {
"ok": true,
"out": "Saved symmetric nine-line centre-control opening prior.\n",
"stdout": "Saved symmetric nine-line centre-control opening prior.\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.41103787207975984,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-5b8c1117631145b4a67faaa1a332ca24",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
"-i",
"HOME=/tmp",
"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
"MKL_NUM_THREADS=8",
"CUDA_VISIBLE_DEVICES=",
"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 16 of at most 120: ``` Saved symmetric nine-line centre-control opening prior. ```
Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 16 of at most 120: ``` Saved symmetric nine-line centre-control opening prior. ```
Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```games
{"games":{"strong":128}}
```{
"request_sha256": "df5eb55a8ae664637b618dd85fee3187947a2bbd472011b5d80e73a677afa7b9",
"request": {
"kind": "games",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"pass": 9,
"request": {
"games": {
"strong": 128
}
}
},
"result": {
"ok": true,
"pass": 9,
"kind": "games",
"per_opponent": {
"strong": {
"games": 128,
"score": 0.5078125,
"wins": 65,
"losses": 63,
"score_as_black": 0.375,
"score_as_white": 0.640625,
"mean_margin": 24.9765625,
"mean_length": 106.4453125,
"stones_captured_per_game": 25.46875,
"stones_lost_per_game": 11.984375,
"network_passes_per_game": 1.8046875,
"all_player_passes_per_game": 4.484375,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 2,
"end_repetition": 4,
"end_two_passes": 124,
"end_move_limit": 0
}
},
"files": "/work/pass_9/"
}
}Games pass 9 of 10 done.
```
{"ok": true, "pass": 9, "kind": "games", "per_opponent": {"strong": {"games": 128, "score": 0.5078125, "wins": 65, "losses": 63, "score_as_black": 0.375, "score_as_white": 0.640625, "mean_margin": 24.9765625, "mean_length": 106.4453125, "stones_captured_per_game": 25.46875, "stones_lost_per_game": 11.984375, "network_passes_per_game": 1.8046875, "all_player_passes_per_game": 4.484375, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 2, "end_repetition": 4, "end_two_passes": 124, "end_move_limit": 0}}, "files": "/work/pass_9/"}
```Exact prompt · Raw CLI events · Settings and audit
Games pass 9 of 10 done.
```
{"ok": true, "pass": 9, "kind": "games", "per_opponent": {"strong": {"games": 128, "score": 0.5078125, "wins": 65, "losses": 63, "score_as_black": 0.375, "score_as_white": 0.640625, "mean_margin": 24.9765625, "mean_length": 106.4453125, "stones_captured_per_game": 25.46875, "stones_lost_per_game": 11.984375, "network_passes_per_game": 1.8046875, "all_player_passes_per_game": 4.484375, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 2, "end_repetition": 4, "end_two_passes": 124, "end_move_limit": 0}}, "files": "/work/pass_9/"}
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```python
import numpy as np, json
A={n:a.copy() for n,a in dict(np.load("/work/policy_v8.npz")).items()}
C=dict(np.load("/work/policy_v9.npz"))
# Black establishes third-line territory with the initiative. White uses
# the centre-oriented response prior. Both priors disappear after 24 stones.
# This is a direct ReLU gate, not a fitted model or a separate evaluator.
j=490
A["L1.W"][:,j]=0
A["L1.b"][j]=0
A["L1.W"][2,j]=24
for p in range(81):
A["L1.W"][3*p,j]=-1
A["L1.W"][3*p+1,j]=-1
for k in (2,3,4):
A[f"L{k}.W"][:,j]=0
A[f"L{k}.b"][j]=0
A[f"L{k}.W"][j,j]=1
# The positional score is computed in L5; this feature's slot can then be
# reused by the existing edge-protection circuit without increasing width.
for p in range(81):
A["L5.W"][j,p] += (C["out.W"][489,p]-A["out.W"][489,p])/1.8
for name in NAMES:
assert A[name].shape==tuple(SHAPES[name])
assert A[name].dtype==np.float32
assert np.isfinite(A[name]).all()
save(name,A[name])
np.savez("/work/final_policy.npz",**A)
print("All tensors saved:",len(saved()),"of",len(NAMES))
print("Total parameters:",sum(a.size for a in A.values()))
print("Nonzero parameters:",sum(np.count_nonzero(a) for a in A.values()))
print("Final design: bounded connected-liberty certificates for both colours;",
"capture and rescue priorities; two-liberty attack/defence;",
"eye, self-atari and edge-cycle protection; phase-aware shape;",
"colour-aware symmetric opening priors; selective passing.")
```
{
"request_sha256": "4504ffec56dbfa11c33a55fb77e468f556664512a97f2669f9957ce688ece8fc",
"request": {
"kind": "python",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"code": "import numpy as np, json\n\nA={n:a.copy() for n,a in dict(np.load(\"/work/policy_v8.npz\")).items()}\nC=dict(np.load(\"/work/policy_v9.npz\"))\n\n# Black establishes third-line territory with the initiative. White uses\n# the centre-oriented response prior. Both priors disappear after 24 stones.\n# This is a direct ReLU gate, not a fitted model or a separate evaluator.\nj=490\nA[\"L1.W\"][:,j]=0\nA[\"L1.b\"][j]=0\nA[\"L1.W\"][2,j]=24\nfor p in range(81):\n A[\"L1.W\"][3*p,j]=-1\n A[\"L1.W\"][3*p+1,j]=-1\nfor k in (2,3,4):\n A[f\"L{k}.W\"][:,j]=0\n A[f\"L{k}.b\"][j]=0\n A[f\"L{k}.W\"][j,j]=1\n\n# The positional score is computed in L5; this feature's slot can then be\n# reused by the existing edge-protection circuit without increasing width.\nfor p in range(81):\n A[\"L5.W\"][j,p] += (C[\"out.W\"][489,p]-A[\"out.W\"][489,p])/1.8\n\nfor name in NAMES:\n assert A[name].shape==tuple(SHAPES[name])\n assert A[name].dtype==np.float32\n assert np.isfinite(A[name]).all()\n save(name,A[name])\nnp.savez(\"/work/final_policy.npz\",**A)\n\nprint(\"All tensors saved:\",len(saved()),\"of\",len(NAMES))\nprint(\"Total parameters:\",sum(a.size for a in A.values()))\nprint(\"Nonzero parameters:\",sum(np.count_nonzero(a) for a in A.values()))\nprint(\"Final design: bounded connected-liberty certificates for both colours;\",\n \"capture and rescue priorities; two-liberty attack/defence;\",\n \"eye, self-atari and edge-cycle protection; phase-aware shape;\",\n \"colour-aware symmetric opening priors; selective passing.\")"
},
"result": {
"ok": true,
"out": "All tensors saved: 14 of 14\nTotal parameters: 1480274\nNonzero parameters: 20976\nFinal design: bounded connected-liberty certificates for both colours; capture and rescue priorities; two-liberty attack/defence; eye, self-atari and edge-cycle protection; phase-aware shape; colour-aware symmetric opening priors; selective passing.\n",
"stdout": "All tensors saved: 14 of 14\nTotal parameters: 1480274\nNonzero parameters: 20976\nFinal design: bounded connected-liberty certificates for both colours; capture and rescue priorities; two-liberty attack/defence; eye, self-atari and edge-cycle protection; phase-aware shape; colour-aware symmetric opening priors; selective passing.\n",
"stderr": "",
"rc": 0,
"timed_out": false,
"truncated": false,
"seconds": 0.4281170070171356,
"sandbox_command": [
"docker",
"run",
"--rm",
"-i",
"--name",
"lm-exp6-6922efa9c9374a348f7795ab560b22b6",
"--network",
"none",
"--cap-drop",
"ALL",
"--security-opt",
"no-new-privileges",
"--read-only",
"--user",
"1000:1000",
"--cpus",
"8",
"--memory",
"103079215104",
"--pids-limit",
"256",
"--tmpfs",
"/tmp:rw,nosuid,mode=1777,size=536870912",
"--mount",
"type=bind,src=/usr,dst=/usr,readonly",
"--mount",
"type=bind,src=<gpu-project>/.venv,dst=/env,readonly",
"--mount",
"type=bind,src=<gpu-project>/reconstructed/exp6/work/e549c4a0b7ab4aba89b6039f2708c842,dst=/work",
"--workdir",
"/work",
"--entrypoint",
"/usr/bin/env",
"sha256:5b8c0c14690ed170da4e663fe0bae0d58efe59661e791296ffab28ed2113b650",
"-i",
"HOME=/tmp",
"PATH=/usr/bin",
"OMP_NUM_THREADS=8",
"OPENBLAS_NUM_THREADS=8",
"MKL_NUM_THREADS=8",
"CUDA_VISIBLE_DEVICES=",
"/env/bin/python",
"-I",
"-"
],
"prelude_sha256": "6c02f33e84d0631bbb88b06f0f5d138176c4888240a0db7828733f8d5883835b"
}
}OUTPUT of Python run 17 of at most 120: ``` All tensors saved: 14 of 14 Total parameters: 1480274 Nonzero parameters: 20976 Final design: bounded connected-liberty certificates for both colours; capture and rescue priorities; two-liberty attack/defence; eye, self-atari and edge-cycle protection; phase-aware shape; colour-aware symmetric opening priors; selective passing. ```
Exact prompt · Raw CLI events · Settings and audit
OUTPUT of Python run 17 of at most 120: ``` All tensors saved: 14 of 14 Total parameters: 1480274 Nonzero parameters: 20976 Final design: bounded connected-liberty certificates for both colours; capture and rescue priorities; two-liberty attack/defence; eye, self-atari and edge-cycle protection; phase-aware shape; colour-aware symmetric opening priors; selective passing. ```
Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
```games
{"games":{"strong":96,"weak":16,"random":16}}
```{
"request_sha256": "536dc2183566a6a5c4f55f9e6abe89dbd967f429561bd1d21dba2fe0dd494c86",
"request": {
"kind": "games",
"case_id": "e549c4a0b7ab4aba89b6039f2708c842",
"pass": 10,
"request": {
"games": {
"strong": 96,
"weak": 16,
"random": 16
}
}
},
"result": {
"ok": true,
"pass": 10,
"kind": "games",
"per_opponent": {
"random": {
"games": 16,
"score": 1.0,
"wins": 16,
"losses": 0,
"score_as_black": 1.0,
"score_as_white": 1.0,
"mean_margin": 80.6875,
"mean_length": 112.75,
"stones_captured_per_game": 51.625,
"stones_lost_per_game": 0.0,
"network_passes_per_game": 1.0,
"all_player_passes_per_game": 5.375,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 9,
"end_repetition": 0,
"end_two_passes": 16,
"end_move_limit": 0
},
"weak": {
"games": 16,
"score": 1.0,
"wins": 16,
"losses": 0,
"score_as_black": 1.0,
"score_as_white": 1.0,
"mean_margin": 78.875,
"mean_length": 118.1875,
"stones_captured_per_game": 53.9375,
"stones_lost_per_game": 0.3125,
"network_passes_per_game": 1.25,
"all_player_passes_per_game": 5.375,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 3,
"end_repetition": 0,
"end_two_passes": 16,
"end_move_limit": 0
},
"strong": {
"games": 96,
"score": 0.5416666666666666,
"wins": 52,
"losses": 44,
"score_as_black": 0.625,
"score_as_white": 0.4583333333333333,
"mean_margin": 27.697916666666668,
"mean_length": 106.79166666666667,
"stones_captured_per_game": 26.885416666666668,
"stones_lost_per_game": 11.364583333333334,
"network_passes_per_game": 1.9895833333333333,
"all_player_passes_per_game": 4.40625,
"games_with_network_pass_before_move_60": 0,
"games_with_any_pass_before_move_60": 0,
"end_repetition": 3,
"end_two_passes": 92,
"end_move_limit": 1
}
},
"files": "/work/pass_10/"
}
}Games pass 10 of 10 done.
```
{"ok": true, "pass": 10, "kind": "games", "per_opponent": {"random": {"games": 16, "score": 1.0, "wins": 16, "losses": 0, "score_as_black": 1.0, "score_as_white": 1.0, "mean_margin": 80.6875, "mean_length": 112.75, "stones_captured_per_game": 51.625, "stones_lost_per_game": 0.0, "network_passes_per_game": 1.0, "all_player_passes_per_game": 5.375, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 9, "end_repetition": 0, "end_two_passes": 16, "end_move_limit": 0}, "weak": {"games": 16, "score": 1.0, "wins": 16, "losses": 0, "score_as_black": 1.0, "score_as_white": 1.0, "mean_margin": 78.875, "mean_length": 118.1875, "stones_captured_per_game": 53.9375, "stones_lost_per_game": 0.3125, "network_passes_per_game": 1.25, "all_player_passes_per_game": 5.375, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 3, "end_repetition": 0, "end_two_passes": 16, "end_move_limit": 0}, "strong": {"games": 96, "score": 0.5416666666666666, "wins": 52, "losses": 44, "score_as_black": 0.625, "score_as_white": 0.4583333333333333, "mean_margin": 27.697916666666668, "mean_length": 106.79166666666667, "stones_captured_per_game": 26.885416666666668, "stones_lost_per_game": 11.364583333333334, "network_passes_per_game": 1.9895833333333333, "all_player_passes_per_game": 4.40625, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 0, "end_repetition": 3, "end_two_passes": 92, "end_move_limit": 1}}, "files": "/work/pass_10/"}
```Exact prompt · Raw CLI events · Settings and audit
Games pass 10 of 10 done.
```
{"ok": true, "pass": 10, "kind": "games", "per_opponent": {"random": {"games": 16, "score": 1.0, "wins": 16, "losses": 0, "score_as_black": 1.0, "score_as_white": 1.0, "mean_margin": 80.6875, "mean_length": 112.75, "stones_captured_per_game": 51.625, "stones_lost_per_game": 0.0, "network_passes_per_game": 1.0, "all_player_passes_per_game": 5.375, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 9, "end_repetition": 0, "end_two_passes": 16, "end_move_limit": 0}, "weak": {"games": 16, "score": 1.0, "wins": 16, "losses": 0, "score_as_black": 1.0, "score_as_white": 1.0, "mean_margin": 78.875, "mean_length": 118.1875, "stones_captured_per_game": 53.9375, "stones_lost_per_game": 0.3125, "network_passes_per_game": 1.25, "all_player_passes_per_game": 5.375, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 3, "end_repetition": 0, "end_two_passes": 16, "end_move_limit": 0}, "strong": {"games": 96, "score": 0.5416666666666666, "wins": 52, "losses": 44, "score_as_black": 0.625, "score_as_white": 0.4583333333333333, "mean_margin": 27.697916666666668, "mean_length": 106.79166666666667, "stones_captured_per_game": 26.885416666666668, "stones_lost_per_game": 11.364583333333334, "network_passes_per_game": 1.9895833333333333, "all_player_passes_per_game": 4.40625, "games_with_network_pass_before_move_60": 0, "games_with_any_pass_before_move_60": 0, "end_repetition": 3, "end_two_passes": 92, "end_move_limit": 1}}, "files": "/work/pass_10/"}
```Failed to read global AGENTS.md instructions from `<local-home>/.codex/AGENTS.md`: Operation not permitted (os error 1)
Code Mode is unavailable because code-mode host is disabled. Code mode will fail closed; enable `features.code_mode_host` and install `codex-code-mode-host`.
All 14 tensors are saved. The network implements handcrafted Go heuristics: approximate connected-group liberty detection, captures, urgent rescues, proactive attacks, eye preservation, self-atari avoidance, edge-trap protection, and opening/endgame priorities. No training or search was used. Final practice results: - **Strong:** 52/96 wins (54.2%) - **Weak:** 16/16 - **Random:** 16/16 Its strength comes from exploiting vulnerable groups while protecting its own. Performance against the two unseen evaluation networks remains unmeasured.
All 14 tensors are saved. The network implements handcrafted Go heuristics: approximate connected-group liberty detection, captures, urgent rescues, proactive attacks, eye preservation, self-atari avoidance, edge-trap protection, and opening/endgame priorities. No training or search was used. Final practice results: - **Strong:** 52/96 wins (54.2%) - **Weak:** 16/16 - **Random:** 16/16 Its strength comes from exploiting vulnerable groups while protecting its own. Performance against the two unseen evaluation networks remains unmeasured.