Update README.md

README.md

@@ -1,10 +1,216 @@
 # NeuroGolf Solver
 
-Builds minimal ONNX networks for ARC-AGI tasks. Currently solves **127/400** on CPU (15s budget). With more time budget on faster hardware, expected **~140+**.
+Builds minimal ONNX networks for ARC-AGI tasks. Currently solves **294/400** on CPU (15s budget). With more time budget on faster hardware, expected .
 
 ## Repo
 https://huggingface.co/rogermt/neurogolf-solver
 
+Here’s the **clear, high‑signal overview** of the ARC‑AGI *NeuroGolf Championship* competition
+
+---
+
+# 🧠 **What the Competition Actually Is**
+The NeuroGolf Championship is a **model‑building competition** based on the ARC‑AGI benchmark.  
+Your job is to produce **400 ONNX models**, one per task, each mapping:
+
+```
+input:  [1, 10, 30, 30]  one‑hot grid
+output: [1, 10, 30, 30]  one‑hot grid
+```
+
+Each task is a small visual transformation puzzle (flip, rotate, color map, crop, tile, etc.).
+
+You are **not** training a single model.  
+You are **generating 400 tiny models**, one per puzzle.
+
+---
+
+# 📦 **Input / Output Format**
+Each ONNX model must:
+
+- Take a **fixed static shape**: `[1,10,30,30]`
+- Output the same shape
+- Use **only allowed ONNX opset 10 operators**
+- Be **fully deterministic**
+- Run on **CPU** in the official evaluator
+
+The input grid is encoded as **10 channels**, one per color (0–9).  
+The output must be the same encoding.
+
+---
+
+# 🚫 **Forbidden / Restricted Ops**
+The competition bans:
+
+- Dynamic shapes  
+- Control flow ops  
+- Non‑deterministic ops  
+- Most high‑level NN layers  
+- Anything outside opset 10  
+- Anything that breaks static shape inference  
+
+**OneHot is allowed**, but has no CUDA kernel — which is why you replaced it.
+
+---
+
+# 🧮 **Scoring System (the “Golf” part)**
+Lower score = better.
+
+Each model is scored by:
+
+### **1. MACs (Multiply‑Accumulate operations)**
+- Measures computational cost  
+- Conv kernels dominate this
+
+### **2. Memory footprint**
+- Size of intermediate tensors  
+- Larger spatial ops → higher memory
+
+### **3. Parameter count**
+- Number of learned weights  
+- Conv kernels dominate this too
+
+### **Total Score = MACs + Memory + Params**
+
+This is why your solver tries:
+
+- Analytical ops first (score ≈ 0)
+- Then tiny convs (score > 0)
+
+---
+
+# 🏌️ **Why It’s Called “NeuroGolf”**
+Because:
+
+- You “swing” at each task by generating a model  
+- The goal is the **lowest score**  
+- You can solve tasks with **zero‑parameter models** (identity, flip, rotate, gather)  
+- Conv models are the “heavy clubs” — used only when necessary
+
+---
+
+# 🧩 **Task Types**
+Most ARC tasks fall into:
+
+- Identity  
+- Color remapping  
+- Flips / rotations  
+- Cropping / padding  
+- Tiling / repetition  
+- Spatial copying  
+- Upscaling  
+- Pattern extraction  
+- Local convolutional rules  
+
+Your solver implements **all of these**.
+
+---
+
+# 🏗️ **Your Solver Architecture (high‑level)**
+Your solver tries:
+
+### **1. Analytical solvers (fast, zero‑cost)**
+- identity  
+- constant  
+- color_map  
+- transpose  
+- flip  
+- rotate  
+- tile  
+- upscale  
+- concat  
+- spatial_gather  
+
+### **2. Conv solvers**
+- fixed‑shape conv  
+- variable‑shape conv  
+- diff‑shape conv  
+
+Each produces a tiny ONNX graph.
+
+---
+
+# 🧪 **Validation**
+Each model must:
+
+- Load in ONNX Runtime  
+- Run on all train + test + arc‑gen examples  
+- Produce exact one‑hot output  
+- Use only allowed ops  
+
+Your `validate()` function enforces this.
+
+---
+
+# 📊 **Submission**
+You submit:
+
+```
+submission/
+    task001.onnx
+    task002.onnx
+    ...
+    task400.onnx
+```
+
+The evaluator:
+
+1. Loads each ONNX file  
+2. Computes MACs, memory, params  
+3. Sums them  
+4. Produces your final score  
+
+Lowest score wins.
+
+---
+
+# 🔥 **Strategic Insights**
+This is the part most competitors miss:
+
+### ✔ Analytical solvers are king  
+They give **zero‑cost** models.
+
+### ✔ Conv solvers must be tiny  
+Kernel size dominates MACs.
+
+### ✔ OneHot is expensive on GPU  
+You fixed this by replacing it with Equal+Cast.
+
+### ✔ Static shapes are mandatory  
+Dynamic ops break the evaluator.
+
+### ✔ Validation must be strict  
+Any mismatch → task marked unsolved → huge penalty.
+
+### ✔ WandB logging is essential  
+You now track:
+- solver type  
+- time  
+- model size  
+- MACs  
+- memory  
+- params  
+- total score  
+
+This lets you optimize solver ordering.
+
+---
+
+# 🎯 **In One Sentence**
+The NeuroGolf Championship is a puzzle‑to‑model generator competition where you must produce 400 tiny ONNX models that solve ARC tasks with the lowest possible computational cost, using only opset‑10 static graphs.
+
+---
+
+If you want, I can also give you:
+
+- A **strategy guide** for beating the leaderboard  
+- A **solver ordering optimization**  
+- A **cost‑minimizing conv kernel search**  
+- A **task taxonomy** for ARC  
+- A **visual diagram** of your solver pipeline  
+
+Just tell me what direction you want.
+
 ## Quick Start
 
 ```bash
@@ -79,7 +285,7 @@ Each .onnx file is a tiny network, typically:
 - **Different-shape tasks**: GatherElements-based pixel remapping
 - **Cost** = MACs + memory_bytes + params → **Score** = max(1, 25 - ln(cost))
 
-## What's NOT solved yet (273 tasks)
+## What's NOT solved yet (106 tasks)
 
 - Variable-shape tasks (input size differs across examples) — need dynamic ONNX
 - Tasks requiring multi-step reasoning (flood fill, gravity, object detection)
@@ -92,3 +298,456 @@ After running, please share the full terminal output — especially:
 1. The "Solved: X/400" line
 2. Any errors
 3. Total time taken
+
+this is run on GPU:
+/kaggle/working/neurogolf-solver
+Using providers: ['CUDAExecutionProvider', 'CPUExecutionProvider']
+Loaded 400 tasks, solving 400
+Conv budget: 30.0s per task
+======================================================================
+wandb: [wandb.login()] Loaded credentials for https://api.wandb.ai from WANDB_API_KEY.
+wandb: Currently logged in as: rogermt23 to https://api.wandb.ai. Use `wandb login --relogin` to force relogin
+wandb: ⢿ setting up run jfx0r5vj (0.0s)
+wandb: ⣻ setting up run jfx0r5vj (0.0s)
+wandb: Tracking run with wandb version 0.25.0
+wandb: Run data is saved locally in /kaggle/working/neurogolf-solver/wandb/run-20260424_053417-jfx0r5vj
+wandb: Run `wandb offline` to turn off syncing.
+wandb: Syncing run solver_run
+wandb: ⭐️ View project at https://wandb.ai/rogermt23/neurogolf
+wandb: 🚀 View run at https://wandb.ai/rogermt23/neurogolf/runs/jfx0r5vj
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+Task 236: spatial_gather        241742   0.049s  (  20,306 bytes)
+Task 237: spatial_gather        7485390   0.098s  (  32,860 bytes)
+Task 238: UNSOLVED    0.002s
+Task 239: UNSOLVED    0.001s
+Task 240: spatial_gather        30870190  17.815s  ( 336,971 bytes)
+Task 241: transpose             36000   0.026s  (     127 bytes)
+Task 242: spatial_gather        292586   0.041s  (   4,303 bytes)
+Task 243: spatial_gather        7485390   0.471s  (  32,860 bytes)
+Task 244: UNSOLVED    0.002s
+Task 245: spatial_gather        11105390   0.197s  (  48,860 bytes)
+Task 246: spatial_gather        26309390   1.377s  ( 116,060 bytes)
+Task 247: UNSOLVED    0.002s
+Task 248: UNSOLVED    1.096s
+Task 249: UNSOLVED    0.001s
+Task 250: spatial_gather        901462   0.119s  (  32,971 bytes)
+Task 251: spatial_gather        7485390   0.128s  (  32,860 bytes)
+Task 252: spatial_gather        11105390   0.152s  (  48,860 bytes)
+Task 253: spatial_gather        904082   0.030s  (  20,306 bytes)
+Task 254: spatial_gather        744750   0.095s  (  32,971 bytes)
+Task 255: UNSOLVED   81.152s
+Task 256: spatial_gather        7485390   0.094s  (  32,860 bytes)
+Task 257: spatial_gather        465842   0.039s  (  20,306 bytes)
+Task 258: spatial_gather        969390   0.025s  (   4,057 bytes)
+Task 259: UNSOLVED    0.001s
+Task 260: spatial_gather        901462   0.180s  (  32,971 bytes)
+Task 261: spatial_gather        969390   0.033s  (   4,057 bytes)
+Task 262: UNSOLVED    0.572s
+Task 263: UNSOLVED    0.001s
+Task 264: UNSOLVED    0.001s
+Task 265: spatial_gather        20646614   8.790s  ( 250,571 bytes)
+Task 266: spatial_gather        56382   0.022s  (   4,168 bytes)
+Task 267: spatial_gather        92014   0.023s  (   4,168 bytes)
+Task 268: spatial_gather        7485390   0.120s  (  32,860 bytes)
+Task 269: UNSOLVED    0.001s
+Task 270: spatial_gather        2852462   0.709s  (  48,971 bytes)
+Task 271: spatial_gather        258686   0.026s  (  10,703 bytes)
+Task 272: spatial_gather        969390   0.021s  (   4,057 bytes)
+Task 273: spatial_gather        2413462   0.386s  (  90,571 bytes)
+Task 274: UNSOLVED    0.001s
+Task 275: UNSOLVED    0.001s
+Task 276: color_map             126500   0.016s  (     549 bytes)
+Task 277: spatial_gather        1825462   0.340s  (  68,171 bytes)
+Task 278: spatial_gather        20517390   1.141s  (  90,460 bytes)
+Task 279: spatial_gather        26309390   1.984s  ( 116,060 bytes)
+Task 280: spatial_gather        56717390  13.654s  ( 250,460 bytes)
+Task 281: spatial_gather        11105390   0.463s  (  48,860 bytes)
+Task 282: spatial_gather        125550   0.041s  (   4,168 bytes)
+Task 283: spatial_gather        565462   0.068s  (  20,171 bytes)
+Task 284: spatial_gather        20517390   0.889s  (  90,460 bytes)
+Task 285: spatial_gather        15449390   2.575s  (  68,060 bytes)
+Task 286: spatial_gather        15449390   0.789s  (  68,060 bytes)
+Task 287: spatial_gather        2188150   0.566s  (  32,971 bytes)
+Task 288: spatial_gather        4589390   0.068s  (  20,060 bytes)
+Task 289: UNSOLVED    0.001s
+Task 290: UNSOLVED    0.001s
+Task 291: UNSOLVED    0.002s
+Task 292: spatial_gather        66129390   0.810s  ( 292,060 bytes)
+Task 293: spatial_gather        2417390   0.073s  (  10,457 bytes)
+Task 294: spatial_gather        145462   0.027s  (   4,168 bytes)
+Task 295: UNSOLVED    0.001s
+Task 296: spatial_gather        140006   0.043s  (  10,703 bytes)
+Task 297: spatial_gather        11105390   0.087s  (  48,860 bytes)
+Task 298: spatial_gather        969390   0.045s  (   4,057 bytes)
+Task 299: spatial_gather        242390   0.056s  (  20,171 bytes)
+Task 300: UNSOLVED    0.001s
+Task 301: spatial_gather        2417390   0.055s  (  10,457 bytes)
+Task 302: spatial_gather        2575574   0.549s  (  68,171 bytes)
+Task 303: spatial_gather        20517390   2.596s  (  90,460 bytes)
+Task 304: UNSOLVED    0.001s
+Task 305: spatial_gather        1352950   0.212s  (  20,171 bytes)
+Task 306: spatial_gather        40065390   5.174s  ( 176,860 bytes)
+Task 307: UNSOLVED    0.001s
+Task 308: UNSOLVED    0.002s
+Task 309: color_map             126500   0.030s  (     549 bytes)
+Task 310: UNSOLVED    0.004s
+Task 311: UNSOLVED    0.007s
+Task 312: spatial_gather        1860374   0.339s  (  48,971 bytes)
+Task 313: spatial_gather        15449390   0.577s  (  68,060 bytes)
+Task 314: spatial_gather        383734   0.071s  (  20,171 bytes)
+Task 315: UNSOLVED    0.001s
+Task 316: spatial_gather        307706   0.036s  (  10,703 bytes)
+Task 317: spatial_gather        125550   0.041s  (   4,168 bytes)
+Task 318: spatial_gather        143342   0.041s  (  10,703 bytes)
+Task 319: UNSOLVED    0.004s
+Task 320: spatial_gather        7485390   0.099s  (  32,860 bytes)
+Task 321: spatial_gather        341342   0.055s  (  20,306 bytes)
+Task 322: spatial_gather        50094   0.036s  (   4,168 bytes)
+Task 323: spatial_gather        3976174   0.677s  (  90,571 bytes)
+Task 324: spatial_gather        15449390   1.193s  (  68,060 bytes)
+Task 325: UNSOLVED    0.001s
+Task 326: UNSOLVED    0.001s
+Task 327: UNSOLVED    0.001s
+Task 328: spatial_gather        56717390   4.462s  ( 250,460 bytes)
+Task 329: spatial_gather        969390   0.023s  (   4,057 bytes)
+Task 330: spatial_gather        1825462   0.304s  (  68,171 bytes)
+Task 331: spatial_gather        145462   0.041s  (   4,168 bytes)
+Task 332: spatial_gather        32825390   0.288s  ( 144,860 bytes)
+Task 333: spatial_gather        565462   0.121s  (  20,171 bytes)
+Task 334: spatial_gather        114206   0.050s  (  10,703 bytes)
+Task 335: spatial_gather        15449390   0.478s  (  68,060 bytes)
+Task 336: spatial_gather        1321462   0.155s  (  48,971 bytes)
+Task 337: color_map             126500   0.017s  (     549 bytes)
+Task 338: spatial_gather        32825390   3.523s  ( 144,860 bytes)
+Task 339: UNSOLVED    0.000s
+Task 340: spatial_gather        7485390   0.357s  (  32,860 bytes)
+Task 341: spatial_gather        901462   0.197s  (  32,971 bytes)
+Task 342: spatial_gather        901462   0.178s  (  32,971 bytes)
+Task 343: spatial_gather        1847262   0.278s  (  90,571 bytes)
+Task 344: spatial_gather        2417390   0.047s  (  10,457 bytes)
+Task 345: spatial_gather        1321462   0.188s  (  48,971 bytes)
+Task 346: UNSOLVED    0.002s
+Task 347: spatial_gather        151346   0.046s  (  20,306 bytes)
+Task 348: spatial_gather        4589390   0.059s  (  20,060 bytes)
+Task 349: UNSOLVED   28.645s
+Task 350: spatial_gather        32825390   1.971s  ( 144,860 bytes)
+Task 351: spatial_gather        711914   0.037s  (  10,703 bytes)
+Task 352: spatial_gather        969390   0.025s  (   4,057 bytes)
+Task 353: spatial_gather        7485390   0.169s  (  32,860 bytes)
+Task 354: spatial_gather        901462   0.193s  (  32,971 bytes)
+Task 355: UNSOLVED    0.003s
+Task 356: spatial_gather        1321462   0.264s  (  48,971 bytes)
+Task 357: UNSOLVED    1.055s
+Task 358: spatial_gather        26309390   1.681s  ( 116,060 bytes)
+Task 359: spatial_gather        2417390   0.067s  (  10,457 bytes)
+Task 360: spatial_gather        285254   0.053s  (  10,703 bytes)
+Task 361: spatial_gather        313462   0.065s  (  10,568 bytes)
+Task 362: spatial_gather        565462   0.134s  (  20,171 bytes)
+Task 363: spatial_gather        901462   0.167s  (  32,971 bytes)
+Task 364: spatial_gather        20517390   1.368s  (  90,460 bytes)
+Task 365: UNSOLVED    0.001s
+Task 366: UNSOLVED    0.003s
+Task 367: spatial_gather        26309390   2.161s  ( 116,060 bytes)
+Task 368: spatial_gather        901462   0.133s  (  32,971 bytes)
+Task 369: spatial_gather        1321462   0.223s  (  48,971 bytes)
+Task 370: spatial_gather        11105390   0.705s  (  48,860 bytes)
+Task 371: spatial_gather        11105390   0.173s  (  48,860 bytes)
+Task 372: spatial_gather        669254   0.063s  (  20,306 bytes)
+Task 373: spatial_gather        121238   0.039s  (  20,171 bytes)
+Task 374: UNSOLVED   14.200s
+Task 375: spatial_gather        4589390   0.050s  (  20,060 bytes)
+Task 376: UNSOLVED    0.001s
+Task 377: UNSOLVED    0.003s
+Task 378: spatial_gather        11105390   0.303s  (  48,860 bytes)
+Task 379: spatial_gather        20517390   1.514s  (  90,460 bytes)
+Task 380: spatial_gather        50094   0.038s  (   4,168 bytes)
+Task 381: spatial_gather        1321462   0.212s  (  48,971 bytes)
+Task 382: spatial_gather        20517390   1.092s  (  90,460 bytes)
+Task 383: spatial_gather        15449390   1.503s  (  68,060 bytes)
+Task 384: UNSOLVED    0.001s
+Task 385: spatial_gather        586582   0.093s  (  48,971 bytes)
+Task 386: spatial_gather        201470   0.032s  (  20,306 bytes)
+Task 387: spatial_gather        15449390   1.712s  (  68,060 bytes)
+Task 388: UNSOLVED    0.001s
+Task 389: spatial_gather        969390   0.023s  (   4,057 bytes)
+Task 390: spatial_gather        3956462   0.939s  (  68,171 bytes)
+Task 391: UNSOLVED    0.002s
+Task 392: spatial_gather        901462   0.173s  (  32,971 bytes)
+Task 393: spatial_gather        420578   0.037s  (  10,703 bytes)
+Task 394: UNSOLVED    0.001s
+Task 395: spatial_gather        96146   0.027s  (  10,703 bytes)
+Task 396: UNSOLVED    0.002s
+Task 397: spatial_gather        565462   0.105s  (  20,171 bytes)
+Task 398: UNSOLVED    0.002s
+Task 399: UNSOLVED    0.002s
+Task 400: spatial_gather        2931914   0.042s  (  20,306 bytes)
+wandb: ⢿ updating run metadata (0.0s)
+wandb: ⣻ updating run metadata (0.0s)
+wandb: ⣽ updating run metadata (0.0s)
+wandb: 
+wandb: Run history:
+wandb:          macs ▁▁▁▃▁▁▂▂▂▁▂▁█▃▁▁▂▁▁▂▁▁▂▁▁▁▁▁▂▅▁▁▅▁▁▁▁▁▁▁
+wandb:        memory ▃▅▄▇█▃▆▂█▅▆▁▅▇▄▂▄▄▁▆▁▁▁▃▅▁▅▂▃▆▄▂▁▆▃▃▃▃▁▂
+wandb:    onnx_bytes ▂▂▁▁▁▁▂▂▁▁▁▄▁▁▂▁▁▁▁▂▁▁▁▁▂▁▁▁▂█▂▆▁▂▁▁▄▁▁▃
+wandb:        params ▃▃▃▃▃▁▁▁▃▁▁▁▂▃▃▁▁▁▁▁█▂▁▁▁▂▁▂▁▄▁▃▁▁▆▃▁▅▄▁
+wandb:         score █▁▁▁▁▁▄▃▁▂▃▂▁▁▁▁▁▁▁▁▂▁▂▂▄▂▁▁▁█▁▁▃▃▄▃▁▁▁▁
+wandb:       task_id ▁▁▁▁▂▂▂▂▂▂▂▂▃▃▃▃▄▄▄▄▄▄▄▅▅▅▅▅▅▆▆▆▇▇▇▇████
+wandb: task_time_sec ▁▁▁▁▁▁▁█▁▁▁▁▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
+wandb: 
+wandb: Run summary:
+wandb:          macs 2822650
+wandb:        memory 104338
+wandb:    onnx_bytes 20306
+wandb:        params 4926
+wandb:         score 2931914
+wandb:        solver spatial_gather
+wandb:       task_id 400
+wandb: task_time_sec 0.0423
+wandb: 
+wandb: 🚀 View run solver_run at: https://wandb.ai/rogermt23/neurogolf/runs/jfx0r5vj
+wandb: ⭐️ View project at: https://wandb.ai/rogermt23/neurogolf
+wandb: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
+wandb: Find logs at: ./wandb/run-20260424_053417-jfx0r5vj/logs
+
+======================================================================
+Solved: 294/400 in 578s
+  spatial_gather: 288
+  color_map: 4
+  transpose: 2
+
+306 ONNX files, total 15719.7 KB
+Created submission.zip