{ "version": 1, "recordedAt": "2026-09-04T08:28:14.094Z", "base": "https://www.neurarch.com", "task": { "id": "mnist-digits", "prompt": "classify handwritten digit images", "said": "I want to recognise handwritten digits.", "dataset": "mnist", "inputShape": [ 1, 28, 28 ], "numClasses": 10, "goal": "image" }, "honesty": { "recording": "Everything below is one run against the production API, replayed. No number on this page was typed by hand.", "notAutoML": "This is not a claim that the system designs a better model. Between two designs that both run, we do not know which trains better: our own selection benchmark expresses a preference on 8.3% of pairs and lands at 51.4% pairwise accuracy, which is a coin flip. The ordering here is legality first, then cost, and cost is our money, not a judgement about the design.", "candidateSource": "The candidates are generated deterministically from the task by the seeded generator (src/utils/architectureSeed.ts). No language model was called to produce them." }, "candidates": [ { "id": "CNN-S-CV-1", "family": "CNN", "scale": "S", "origin": "seeded generator, retargeted to 1x28x28 and a 10-way head", "legal": true, "model": { "id": "rl-root", "name": "CNN-S-CV", "components": [ { "id": "n-rl0", "type": "input", "name": "input", "position": { "x": 220, "y": 120 }, "params": { "shape": [ 1, 28, 28 ] }, "inputs": [], "outputs": [ "n-rl1" ] }, { "id": "n-rl1", "type": "conv2d", "name": "conv1", "position": { "x": 220, "y": 260 }, "params": { "outChannels": 64, "kernelSize": 3, "stride": 1, "padding": 1 }, "inputs": [ "n-rl0" ], "outputs": [ "n-rl2" ] }, { "id": "n-rl2", "type": "batchNorm", "name": "bn1", "position": { "x": 220, "y": 400 }, "params": { "numFeatures": 64 }, "inputs": [ "n-rl1" ], "outputs": [ "n-rl3" ] }, { "id": "n-rl3", "type": "gelu", "name": "gelu1", "position": { "x": 220, "y": 540 }, "params": {}, "inputs": [ "n-rl2" ], "outputs": [ "n-rl4" ] }, { "id": "n-rl4", "type": "conv2d", "name": "conv2", "position": { "x": 220, "y": 680 }, "params": { "outChannels": 64, "kernelSize": 3, "stride": 1, "padding": 1 }, "inputs": [ "n-rl3" ], "outputs": [ "n-rl5" ] }, { "id": "n-rl5", "type": "batchNorm", "name": "bn2", "position": { "x": 220, "y": 820 }, "params": { "numFeatures": 64 }, "inputs": [ "n-rl4" ], "outputs": [ "n-rl6" ] }, { "id": "n-rl6", "type": "gelu", "name": "gelu2", "position": { "x": 220, "y": 960 }, "params": {}, "inputs": [ "n-rl5" ], "outputs": [ "n-rl7" ] }, { "id": "n-rl7", "type": "conv2d", "name": "conv3", "position": { "x": 220, "y": 1100 }, "params": { "outChannels": 64, "kernelSize": 3, "stride": 1, "padding": 1 }, "inputs": [ "n-rl6" ], "outputs": [ "n-rl8" ] }, { "id": "n-rl8", "type": "batchNorm", "name": "bn3", "position": { "x": 220, "y": 1240 }, "params": { "numFeatures": 64 }, "inputs": [ "n-rl7" ], "outputs": [ "n-rl9" ] }, { "id": "n-rl9", "type": "gelu", "name": "gelu3", "position": { "x": 220, "y": 1380 }, "params": {}, "inputs": [ "n-rl8" ], "outputs": [ "n-rl10" ] }, { "id": "n-rl10", "type": "globalAvgPool2d", "name": "gap", "position": { "x": 220, "y": 1520 }, "params": {}, "inputs": [ "n-rl9" ], "outputs": [ "n-rl11" ] }, { "id": "n-rl11", "type": "flatten", "name": "flatten", "position": { "x": 220, "y": 1660 }, "params": {}, "inputs": [ "n-rl10" ], "outputs": [ "n-rl12" ] }, { "id": "n-rl12", "type": "linear", "name": "head", "position": { "x": 220, "y": 1800 }, "params": { "outFeatures": 10 }, "inputs": [ "n-rl11" ], "outputs": [ "n-rl13" ] }, { "id": "n-rl13", "type": "output", "name": "output", "position": { "x": 220, "y": 1940 }, "params": {}, "inputs": [ "n-rl12" ], "outputs": [] } ], "connections": [ { "id": "c-rl14", "from": "n-rl0", "to": "n-rl1", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl15", "from": "n-rl1", "to": "n-rl2", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl16", "from": "n-rl2", "to": "n-rl3", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl17", "from": "n-rl3", "to": "n-rl4", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl18", "from": "n-rl4", "to": "n-rl5", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl19", "from": "n-rl5", "to": "n-rl6", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl20", "from": "n-rl6", "to": "n-rl7", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl21", "from": "n-rl7", "to": "n-rl8", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl22", "from": "n-rl8", "to": "n-rl9", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl23", "from": "n-rl9", "to": "n-rl10", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl24", "from": "n-rl10", "to": "n-rl11", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl25", "from": "n-rl11", "to": "n-rl12", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl26", "from": "n-rl12", "to": "n-rl13", "fromPort": "bottom", "toPort": "top" } ] }, "summary": "CNN-S-CV: 12 layers, 75.5K params, will run, fits a T4, about $0.04 to train", "params": 75530, "layers": 12, "inputShape": [ 1, 28, 28 ], "outputShape": [ 10 ], "fingerprint": "4f78dfe7", "cost": { "estCostUsd": 0.0444266753026351, "estTrainSec": 145.39639189953306, "fitsGpu": "A10G (24GB)", "gpuFits": { "T4": true, "A100_40": true, "H100_80": true }, "assumptions": "Cost is a roofline estimate on the priced GPU for 10 epochs at batch 32 over 50,000 samples (assumed; no dataset attached). GPU fit is fp32 weights plus gradients plus two Adam moments (16 bytes per parameter) with 1.3x headroom; activations are not included and grow with batch size." }, "blockers": [], "warnings": [], "text": "Plan: CNN-S-CV 12 layers · 75.5K params · fingerprint 4f78dfe7\n shape [1,28,28] -> [10]\n will run yes (0 blockers, 0 warnings)\n fits T4 16GB yes · A100 40GB yes · H100 80GB yes\n train ~$0.04 / 3m on A10G (24GB) (10 epochs, batch 32, 50k samples assumed)\n policy all lines pass\n history Last time this structure trained here: valAcc 0.9683, 10 epochs, $0.03, 3m, 2026-09-04 (+2 earlier)" }, { "id": "CNN-S-CV-0", "family": "CNN", "scale": "S", "origin": "seeded generator, retargeted to 1x28x28 and a 10-way head", "legal": true, "model": { "id": "rl-root", "name": "CNN-S-CV", "components": [ { "id": "n-rl0", "type": "input", "name": "input", "position": { "x": 220, "y": 120 }, "params": { "shape": [ 1, 28, 28 ] }, "inputs": [], "outputs": [ "n-rl1" ] }, { "id": "n-rl1", "type": "conv2d", "name": "conv1", "position": { "x": 220, "y": 260 }, "params": { "outChannels": 64, "kernelSize": 3, "stride": 2, "padding": 1 }, "inputs": [ "n-rl0" ], "outputs": [ "n-rl2" ] }, { "id": "n-rl2", "type": "batchNorm", "name": "bn1", "position": { "x": 220, "y": 400 }, "params": { "numFeatures": 64 }, "inputs": [ "n-rl1" ], "outputs": [ "n-rl3" ] }, { "id": "n-rl3", "type": "gelu", "name": "gelu1", "position": { "x": 220, "y": 540 }, "params": {}, "inputs": [ "n-rl2" ], "outputs": [ "n-rl4" ] }, { "id": "n-rl4", "type": "conv2d", "name": "conv2", "position": { "x": 220, "y": 680 }, "params": { "outChannels": 64, "kernelSize": 3, "stride": 2, "padding": 1 }, "inputs": [ "n-rl3" ], "outputs": [ "n-rl5" ] }, { "id": "n-rl5", "type": "batchNorm", "name": "bn2", "position": { "x": 220, "y": 820 }, "params": { "numFeatures": 64 }, "inputs": [ "n-rl4" ], "outputs": [ "n-rl6" ] }, { "id": "n-rl6", "type": "gelu", "name": "gelu2", "position": { "x": 220, "y": 960 }, "params": {}, "inputs": [ "n-rl5" ], "outputs": [ "n-rl7" ] }, { "id": "n-rl7", "type": "conv2d", "name": "conv3", "position": { "x": 220, "y": 1100 }, "params": { "outChannels": 128, "kernelSize": 3, "stride": 1, "padding": 1 }, "inputs": [ "n-rl6" ], "outputs": [ "n-rl8" ] }, { "id": "n-rl8", "type": "batchNorm", "name": "bn3", "position": { "x": 220, "y": 1240 }, "params": { "numFeatures": 128 }, "inputs": [ "n-rl7" ], "outputs": [ "n-rl9" ] }, { "id": "n-rl9", "type": "gelu", "name": "gelu3", "position": { "x": 220, "y": 1380 }, "params": {}, "inputs": [ "n-rl8" ], "outputs": [ "n-rl10" ] }, { "id": "n-rl10", "type": "globalAvgPool2d", "name": "gap", "position": { "x": 220, "y": 1520 }, "params": {}, "inputs": [ "n-rl9" ], "outputs": [ "n-rl11" ] }, { "id": "n-rl11", "type": "flatten", "name": "flatten", "position": { "x": 220, "y": 1660 }, "params": {}, "inputs": [ "n-rl10" ], "outputs": [ "n-rl12" ] }, { "id": "n-rl12", "type": "linear", "name": "head", "position": { "x": 220, "y": 1800 }, "params": { "outFeatures": 10 }, "inputs": [ "n-rl11" ], "outputs": [ "n-rl13" ] }, { "id": "n-rl13", "type": "output", "name": "output", "position": { "x": 220, "y": 1940 }, "params": {}, "inputs": [ "n-rl12" ], "outputs": [] } ], "connections": [ { "id": "c-rl14", "from": "n-rl0", "to": "n-rl1", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl15", "from": "n-rl1", "to": "n-rl2", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl16", "from": "n-rl2", "to": "n-rl3", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl17", "from": "n-rl3", "to": "n-rl4", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl18", "from": "n-rl4", "to": "n-rl5", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl19", "from": "n-rl5", "to": "n-rl6", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl20", "from": "n-rl6", "to": "n-rl7", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl21", "from": "n-rl7", "to": "n-rl8", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl22", "from": "n-rl8", "to": "n-rl9", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl23", "from": "n-rl9", "to": "n-rl10", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl24", "from": "n-rl10", "to": "n-rl11", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl25", "from": "n-rl11", "to": "n-rl12", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl26", "from": "n-rl12", "to": "n-rl13", "fromPort": "bottom", "toPort": "top" } ] }, "summary": "CNN-S-CV: 12 layers, 113.2K params, will run, fits a T4, about $0.04 to train", "params": 113226, "layers": 12, "inputShape": [ 1, 28, 28 ], "outputShape": [ 10 ], "fingerprint": "4f78dfe7", "cost": { "estCostUsd": 0.042424553250298785, "estTrainSec": 138.84399245552328, "fitsGpu": "A10G (24GB)", "gpuFits": { "T4": true, "A100_40": true, "H100_80": true }, "assumptions": "Cost is a roofline estimate on the priced GPU for 10 epochs at batch 32 over 50,000 samples (assumed; no dataset attached). GPU fit is fp32 weights plus gradients plus two Adam moments (16 bytes per parameter) with 1.3x headroom; activations are not included and grow with batch size." }, "blockers": [], "warnings": [], "text": "Plan: CNN-S-CV 12 layers · 113.2K params · fingerprint 4f78dfe7\n shape [1,28,28] -> [10]\n will run yes (0 blockers, 0 warnings)\n fits T4 16GB yes · A100 40GB yes · H100 80GB yes\n train ~$0.04 / 3m on A10G (24GB) (10 epochs, batch 32, 50k samples assumed)\n policy all lines pass\n history Last time this structure trained here: valAcc 0.9683, 10 epochs, $0.03, 3m, 2026-09-04 (+2 earlier)" }, { "id": "CNN-M-CV-0", "family": "CNN", "scale": "M", "origin": "seeded generator, retargeted to 1x28x28 and a 10-way head", "legal": false, "model": { "id": "rl-root", "name": "CNN-M-CV", "components": [ { "id": "n-rl0", "type": "input", "name": "input", "position": { "x": 220, "y": 120 }, "params": { "shape": [ 1, 28, 28 ] }, "inputs": [], "outputs": [ "n-rl1" ] }, { "id": "n-rl1", "type": "conv2d", "name": "conv1", "position": { "x": 220, "y": 260 }, "params": { "outChannels": 128, "kernelSize": 3, "stride": 1, "padding": 1 }, "inputs": [ "n-rl0" ], "outputs": [ "n-rl2" ] }, { "id": "n-rl2", "type": "batchNorm", "name": "bn1", "position": { "x": 220, "y": 400 }, "params": { "numFeatures": 128 }, "inputs": [ "n-rl1" ], "outputs": [ "n-rl3" ] }, { "id": "n-rl3", "type": "gelu", "name": "gelu1", "position": { "x": 220, "y": 540 }, "params": {}, "inputs": [ "n-rl2" ], "outputs": [ "n-rl4" ] }, { "id": "n-rl4", "type": "conv2d", "name": "conv2", "position": { "x": 220, "y": 680 }, "params": { "outChannels": 256, "kernelSize": 3, "stride": 1, "padding": 1 }, "inputs": [ "n-rl3" ], "outputs": [ "n-rl5" ] }, { "id": "n-rl5", "type": "batchNorm", "name": "bn2", "position": { "x": 220, "y": 820 }, "params": { "numFeatures": 256 }, "inputs": [ "n-rl4" ], "outputs": [ "n-rl6" ] }, { "id": "n-rl6", "type": "gelu", "name": "gelu2", "position": { "x": 220, "y": 960 }, "params": {}, "inputs": [ "n-rl5" ], "outputs": [ "n-rl7" ] }, { "id": "n-rl7", "type": "conv2d", "name": "conv3", "position": { "x": 220, "y": 1100 }, "params": { "outChannels": 256, "kernelSize": 3, "stride": 1, "padding": 1 }, "inputs": [ "n-rl6" ], "outputs": [ "n-rl8" ] }, { "id": "n-rl8", "type": "batchNorm", "name": "bn3", "position": { "x": 220, "y": 1240 }, "params": { "numFeatures": 256 }, "inputs": [ "n-rl7" ], "outputs": [ "n-rl9" ] }, { "id": "n-rl9", "type": "gelu", "name": "gelu3", "position": { "x": 220, "y": 1380 }, "params": {}, "inputs": [ "n-rl8" ], "outputs": [ "n-rl10" ] }, { "id": "n-rl10", "type": "conv2d", "name": "conv4", "position": { "x": 220, "y": 1520 }, "params": { "outChannels": 256, "kernelSize": 3, "stride": 2, "padding": 1 }, "inputs": [ "n-rl9" ], "outputs": [ "n-rl11" ] }, { "id": "n-rl11", "type": "batchNorm", "name": "bn4", "position": { "x": 220, "y": 1660 }, "params": { "numFeatures": 256 }, "inputs": [ "n-rl10" ], "outputs": [ "n-rl12" ] }, { "id": "n-rl12", "type": "gelu", "name": "gelu4", "position": { "x": 220, "y": 1800 }, "params": {}, "inputs": [ "n-rl11" ], "outputs": [ "n-rl13" ] }, { "id": "n-rl13", "type": "conv2d", "name": "conv5", "position": { "x": 220, "y": 1940 }, "params": { "outChannels": 256, "kernelSize": 3, "stride": 1, "padding": 1 }, "inputs": [ "n-rl12" ], "outputs": [ "n-rl14" ] }, { "id": "n-rl14", "type": "batchNorm", "name": "bn5", "position": { "x": 220, "y": 2080 }, "params": { "numFeatures": 256 }, "inputs": [ "n-rl13" ], "outputs": [ "n-rl15" ] }, { "id": "n-rl15", "type": "gelu", "name": "gelu5", "position": { "x": 220, "y": 2220 }, "params": {}, "inputs": [ "n-rl14" ], "outputs": [ "n-rl16" ] }, { "id": "n-rl16", "type": "globalAvgPool2d", "name": "gap", "position": { "x": 220, "y": 2360 }, "params": {}, "inputs": [ "n-rl15" ], "outputs": [ "n-rl17" ] }, { "id": "n-rl17", "type": "flatten", "name": "flatten", "position": { "x": 220, "y": 2500 }, "params": {}, "inputs": [ "n-rl16" ], "outputs": [ "n-rl18" ] }, { "id": "n-rl18", "type": "linear", "name": "head", "position": { "x": 220, "y": 2640 }, "params": { "outFeatures": 10 }, "inputs": [ "n-rl17" ], "outputs": [ "n-rl19" ] }, { "id": "n-rl19", "type": "output", "name": "output", "position": { "x": 220, "y": 2780 }, "params": {}, "inputs": [ "n-rl18" ], "outputs": [] } ], "connections": [ { "id": "c-rl20", "from": "n-rl0", "to": "n-rl1", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl21", "from": "n-rl1", "to": "n-rl2", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl22", "from": "n-rl2", "to": "n-rl3", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl23", "from": "n-rl3", "to": "n-rl4", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl24", "from": "n-rl4", "to": "n-rl5", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl25", "from": "n-rl5", "to": "n-rl6", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl26", "from": "n-rl6", "to": "n-rl7", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl27", "from": "n-rl7", "to": "n-rl8", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl28", "from": "n-rl8", "to": "n-rl9", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl29", "from": "n-rl9", "to": "n-rl10", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl30", "from": "n-rl10", "to": "n-rl11", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl31", "from": "n-rl11", "to": "n-rl12", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl32", "from": "n-rl12", "to": "n-rl13", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl33", "from": "n-rl13", "to": "n-rl14", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl34", "from": "n-rl14", "to": "n-rl15", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl35", "from": "n-rl15", "to": "n-rl16", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl36", "from": "n-rl16", "to": "n-rl17", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl37", "from": "n-rl17", "to": "n-rl18", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl38", "from": "n-rl18", "to": "n-rl19", "fromPort": "bottom", "toPort": "top" } ] }, "summary": "CNN-M-CV: 18 layers, 2.1M params, will not run (1 blocker: policy: max_params 1M exceeded (2.1M))", "params": 2071562, "layers": 18, "inputShape": [ 1, 28, 28 ], "outputShape": [ 10 ], "fingerprint": "466b3a77", "cost": { "estCostUsd": 0.07699582498087185, "estTrainSec": 251.9863363010351, "fitsGpu": "A10G (24GB)", "gpuFits": { "T4": true, "A100_40": true, "H100_80": true }, "assumptions": "Cost is a roofline estimate on the priced GPU for 10 epochs at batch 32 over 50,000 samples (assumed; no dataset attached). GPU fit is fp32 weights plus gradients plus two Adam moments (16 bytes per parameter) with 1.3x headroom; activations are not included and grow with batch size." }, "blockers": [ { "title": "policy: max_params 1M exceeded (2.1M)", "detail": "max_params: 1M", "fix": "Reduce the model by 1.1M parameters or raise max_params.", "stage": "policy", "componentIds": [] } ], "warnings": [], "text": "Plan: CNN-M-CV 18 layers · 2.1M params · fingerprint 466b3a77\n shape [1,28,28] -> [10]\n will run NO (1 blocker)\n fits T4 16GB yes · A100 40GB yes · H100 80GB yes\n train ~$0.08 / 5m on A10G (24GB) (10 epochs, batch 32, 50k samples assumed)\n blockers\n ! policy: max_params 1M exceeded (2.1M)\n policy 1 line violated (listed above)" }, { "id": "CNN-M-CV-1", "family": "CNN", "scale": "M", "origin": "seeded generator, retargeted to 1x28x28 and a 10-way head", "legal": false, "model": { "id": "rl-root", "name": "CNN-M-CV", "components": [ { "id": "n-rl0", "type": "input", "name": "input", "position": { "x": 220, "y": 120 }, "params": { "shape": [ 1, 28, 28 ] }, "inputs": [], "outputs": [ "n-rl1" ] }, { "id": "n-rl1", "type": "conv2d", "name": "conv1", "position": { "x": 220, "y": 260 }, "params": { "outChannels": 128, "kernelSize": 3, "stride": 2, "padding": 1 }, "inputs": [ "n-rl0" ], "outputs": [ "n-rl2" ] }, { "id": "n-rl2", "type": "batchNorm", "name": "bn1", "position": { "x": 220, "y": 400 }, "params": { "numFeatures": 128 }, "inputs": [ "n-rl1" ], "outputs": [ "n-rl3" ] }, { "id": "n-rl3", "type": "gelu", "name": "gelu1", "position": { "x": 220, "y": 540 }, "params": {}, "inputs": [ "n-rl2" ], "outputs": [ "n-rl4" ] }, { "id": "n-rl4", "type": "conv2d", "name": "conv2", "position": { "x": 220, "y": 680 }, "params": { "outChannels": 128, "kernelSize": 3, "stride": 2, "padding": 1 }, "inputs": [ "n-rl3" ], "outputs": [ "n-rl5" ] }, { "id": "n-rl5", "type": "batchNorm", "name": "bn2", "position": { "x": 220, "y": 820 }, "params": { "numFeatures": 128 }, "inputs": [ "n-rl4" ], "outputs": [ "n-rl6" ] }, { "id": "n-rl6", "type": "gelu", "name": "gelu2", "position": { "x": 220, "y": 960 }, "params": {}, "inputs": [ "n-rl5" ], "outputs": [ "n-rl7" ] }, { "id": "n-rl7", "type": "conv2d", "name": "conv3", "position": { "x": 220, "y": 1100 }, "params": { "outChannels": 256, "kernelSize": 3, "stride": 1, "padding": 1 }, "inputs": [ "n-rl6" ], "outputs": [ "n-rl8" ] }, { "id": "n-rl8", "type": "batchNorm", "name": "bn3", "position": { "x": 220, "y": 1240 }, "params": { "numFeatures": 256 }, "inputs": [ "n-rl7" ], "outputs": [ "n-rl9" ] }, { "id": "n-rl9", "type": "gelu", "name": "gelu3", "position": { "x": 220, "y": 1380 }, "params": {}, "inputs": [ "n-rl8" ], "outputs": [ "n-rl10" ] }, { "id": "n-rl10", "type": "conv2d", "name": "conv4", "position": { "x": 220, "y": 1520 }, "params": { "outChannels": 256, "kernelSize": 3, "stride": 1, "padding": 1 }, "inputs": [ "n-rl9" ], "outputs": [ "n-rl11" ] }, { "id": "n-rl11", "type": "batchNorm", "name": "bn4", "position": { "x": 220, "y": 1660 }, "params": { "numFeatures": 256 }, "inputs": [ "n-rl10" ], "outputs": [ "n-rl12" ] }, { "id": "n-rl12", "type": "gelu", "name": "gelu4", "position": { "x": 220, "y": 1800 }, "params": {}, "inputs": [ "n-rl11" ], "outputs": [ "n-rl13" ] }, { "id": "n-rl13", "type": "conv2d", "name": "conv5", "position": { "x": 220, "y": 1940 }, "params": { "outChannels": 512, "kernelSize": 3, "stride": 1, "padding": 1 }, "inputs": [ "n-rl12" ], "outputs": [ "n-rl14" ] }, { "id": "n-rl14", "type": "batchNorm", "name": "bn5", "position": { "x": 220, "y": 2080 }, "params": { "numFeatures": 512 }, "inputs": [ "n-rl13" ], "outputs": [ "n-rl15" ] }, { "id": "n-rl15", "type": "gelu", "name": "gelu5", "position": { "x": 220, "y": 2220 }, "params": {}, "inputs": [ "n-rl14" ], "outputs": [ "n-rl16" ] }, { "id": "n-rl16", "type": "globalAvgPool2d", "name": "gap", "position": { "x": 220, "y": 2360 }, "params": {}, "inputs": [ "n-rl15" ], "outputs": [ "n-rl17" ] }, { "id": "n-rl17", "type": "flatten", "name": "flatten", "position": { "x": 220, "y": 2500 }, "params": {}, "inputs": [ "n-rl16" ], "outputs": [ "n-rl18" ] }, { "id": "n-rl18", "type": "linear", "name": "head", "position": { "x": 220, "y": 2640 }, "params": { "outFeatures": 10 }, "inputs": [ "n-rl17" ], "outputs": [ "n-rl19" ] }, { "id": "n-rl19", "type": "output", "name": "output", "position": { "x": 220, "y": 2780 }, "params": {}, "inputs": [ "n-rl18" ], "outputs": [] } ], "connections": [ { "id": "c-rl20", "from": "n-rl0", "to": "n-rl1", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl21", "from": "n-rl1", "to": "n-rl2", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl22", "from": "n-rl2", "to": "n-rl3", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl23", "from": "n-rl3", "to": "n-rl4", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl24", "from": "n-rl4", "to": "n-rl5", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl25", "from": "n-rl5", "to": "n-rl6", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl26", "from": "n-rl6", "to": "n-rl7", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl27", "from": "n-rl7", "to": "n-rl8", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl28", "from": "n-rl8", "to": "n-rl9", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl29", "from": "n-rl9", "to": "n-rl10", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl30", "from": "n-rl10", "to": "n-rl11", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl31", "from": "n-rl11", "to": "n-rl12", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl32", "from": "n-rl12", "to": "n-rl13", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl33", "from": "n-rl13", "to": "n-rl14", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl34", "from": "n-rl14", "to": "n-rl15", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl35", "from": "n-rl15", "to": "n-rl16", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl36", "from": "n-rl16", "to": "n-rl17", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl37", "from": "n-rl17", "to": "n-rl18", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl38", "from": "n-rl18", "to": "n-rl19", "fromPort": "bottom", "toPort": "top" } ] }, "summary": "CNN-M-CV: 18 layers, 2.2M params, will not run (1 blocker: policy: max_params 1M exceeded (2.2M))", "params": 2221962, "layers": 18, "inputShape": [ 1, 28, 28 ], "outputShape": [ 10 ], "fingerprint": "466b3a77", "cost": { "estCostUsd": 0.0462959239375151, "estTrainSec": 151.51393288641304, "fitsGpu": "A10G (24GB)", "gpuFits": { "T4": true, "A100_40": true, "H100_80": true }, "assumptions": "Cost is a roofline estimate on the priced GPU for 10 epochs at batch 32 over 50,000 samples (assumed; no dataset attached). GPU fit is fp32 weights plus gradients plus two Adam moments (16 bytes per parameter) with 1.3x headroom; activations are not included and grow with batch size." }, "blockers": [ { "title": "policy: max_params 1M exceeded (2.2M)", "detail": "max_params: 1M", "fix": "Reduce the model by 1.2M parameters or raise max_params.", "stage": "policy", "componentIds": [] } ], "warnings": [], "text": "Plan: CNN-M-CV 18 layers · 2.2M params · fingerprint 466b3a77\n shape [1,28,28] -> [10]\n will run NO (1 blocker)\n fits T4 16GB yes · A100 40GB yes · H100 80GB yes\n train ~$0.05 / 3m on A10G (24GB) (10 epochs, batch 32, 50k samples assumed)\n blockers\n ! policy: max_params 1M exceeded (2.2M)\n policy 1 line violated (listed above)" }, { "id": "HYB-S-CV-0", "family": "HYB", "scale": "S", "origin": "seeded generator, retargeted to 1x28x28 and a 10-way head", "legal": false, "model": { "id": "rl-root", "name": "HYB-S-CV", "components": [ { "id": "n-rl0", "type": "input", "name": "input", "position": { "x": 220, "y": 120 }, "params": { "shape": [ 1, 28, 28 ] }, "inputs": [], "outputs": [ "n-rl1" ] }, { "id": "n-rl1", "type": "conv2d", "name": "stem_c1", "position": { "x": 220, "y": 260 }, "params": { "outChannels": 64, "kernelSize": 7, "stride": 2, "padding": 3 }, "inputs": [ "n-rl0" ], "outputs": [ "n-rl2" ] }, { "id": "n-rl2", "type": "batchNorm", "name": "stem_bn", "position": { "x": 220, "y": 400 }, "params": { "numFeatures": 64 }, "inputs": [ "n-rl1" ], "outputs": [ "n-rl3" ] }, { "id": "n-rl3", "type": "relu", "name": "stem_act", "position": { "x": 220, "y": 540 }, "params": {}, "inputs": [ "n-rl2" ], "outputs": [ "n-rl4" ] }, { "id": "n-rl4", "type": "maxpool2d", "name": "stem_pool", "position": { "x": 220, "y": 680 }, "params": { "kernelSize": 3, "stride": 2 }, "inputs": [ "n-rl3" ], "outputs": [ "n-rl5" ] }, { "id": "n-rl5", "type": "patchEmbed", "name": "patch_proj", "position": { "x": 220, "y": 820 }, "params": { "embedDim": 256, "patchSize": 1, "inChans": 64 }, "inputs": [ "n-rl4" ], "outputs": [ "n-rl6" ] }, { "id": "n-rl6", "type": "positionalEncoding", "name": "pos_enc", "position": { "x": 220, "y": 960 }, "params": {}, "inputs": [ "n-rl5" ], "outputs": [ "n-rl7" ] }, { "id": "n-rl7", "type": "transformerBlock", "name": "block_1", "position": { "x": 220, "y": 1100 }, "params": { "embedDim": 256, "numHeads": 8, "ffDim": 1024 }, "inputs": [ "n-rl6" ], "outputs": [ "n-rl8" ] }, { "id": "n-rl8", "type": "layerNorm", "name": "ln_out", "position": { "x": 220, "y": 1240 }, "params": { "normalizedShape": 256 }, "inputs": [ "n-rl7" ], "outputs": [ "n-rl9" ] }, { "id": "n-rl9", "type": "linear", "name": "head", "position": { "x": 220, "y": 1380 }, "params": { "outFeatures": 10 }, "inputs": [ "n-rl8" ], "outputs": [ "n-rl10" ] }, { "id": "n-rl10", "type": "output", "name": "output", "position": { "x": 220, "y": 1520 }, "params": {}, "inputs": [ "n-rl9" ], "outputs": [] } ], "connections": [ { "id": "c-rl11", "from": "n-rl0", "to": "n-rl1", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl12", "from": "n-rl1", "to": "n-rl2", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl13", "from": "n-rl2", "to": "n-rl3", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl14", "from": "n-rl3", "to": "n-rl4", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl15", "from": "n-rl4", "to": "n-rl5", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl16", "from": "n-rl5", "to": "n-rl6", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl17", "from": "n-rl6", "to": "n-rl7", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl18", "from": "n-rl7", "to": "n-rl8", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl19", "from": "n-rl8", "to": "n-rl9", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl20", "from": "n-rl9", "to": "n-rl10", "fromPort": "bottom", "toPort": "top" } ] }, "summary": "HYB-S-CV: 9 layers, 812.8K params, will not run (1 blocker: \"pos_enc\" is missing maxLen)", "params": 812810, "layers": 9, "inputShape": [ 1, 28, 28 ], "outputShape": [ 36, 10 ], "fingerprint": "02fcfc4a", "cost": { "estCostUsd": 0.043335289000672655, "estTrainSec": 141.8245821840196, "fitsGpu": "A10G (24GB)", "gpuFits": { "T4": true, "A100_40": true, "H100_80": true }, "assumptions": "Cost is a roofline estimate on the priced GPU for 10 epochs at batch 32 over 50,000 samples (assumed; no dataset attached). GPU fit is fp32 weights plus gradients plus two Adam moments (16 bytes per parameter) with 1.3x headroom; activations are not included and grow with batch size." }, "blockers": [ { "title": "\"pos_enc\" is missing maxLen", "stage": "preflight", "detail": "\"pos_enc\" (positionalEncoding) has no value for maxLen. A layer without these cannot be built, so the run fails at construction rather than part way through.", "fix": "Select the layer and fill the empty fields in the inspector.", "componentIds": [ "n-rl6" ] } ], "warnings": [], "text": "Plan: HYB-S-CV 9 layers · 812.8K params · fingerprint 02fcfc4a\n shape [1,28,28] -> [36,10]\n will run NO (1 blocker)\n fits T4 16GB yes · A100 40GB yes · H100 80GB yes\n train ~$0.04 / 3m on A10G (24GB) (10 epochs, batch 32, 50k samples assumed)\n blockers\n ! \"pos_enc\" is missing maxLen\n policy all lines pass" }, { "id": "HYB-S-CV-1", "family": "HYB", "scale": "S", "origin": "seeded generator, retargeted to 1x28x28 and a 10-way head", "legal": false, "model": { "id": "rl-root", "name": "HYB-S-CV", "components": [ { "id": "n-rl0", "type": "input", "name": "input", "position": { "x": 220, "y": 120 }, "params": { "shape": [ 1, 28, 28 ] }, "inputs": [], "outputs": [ "n-rl1" ] }, { "id": "n-rl1", "type": "conv2d", "name": "stem_c1", "position": { "x": 220, "y": 260 }, "params": { "outChannels": 64, "kernelSize": 7, "stride": 2, "padding": 3 }, "inputs": [ "n-rl0" ], "outputs": [ "n-rl2" ] }, { "id": "n-rl2", "type": "batchNorm", "name": "stem_bn", "position": { "x": 220, "y": 400 }, "params": { "numFeatures": 64 }, "inputs": [ "n-rl1" ], "outputs": [ "n-rl3" ] }, { "id": "n-rl3", "type": "relu", "name": "stem_act", "position": { "x": 220, "y": 540 }, "params": {}, "inputs": [ "n-rl2" ], "outputs": [ "n-rl4" ] }, { "id": "n-rl4", "type": "maxpool2d", "name": "stem_pool", "position": { "x": 220, "y": 680 }, "params": { "kernelSize": 3, "stride": 2 }, "inputs": [ "n-rl3" ], "outputs": [ "n-rl5" ] }, { "id": "n-rl5", "type": "patchEmbed", "name": "patch_proj", "position": { "x": 220, "y": 820 }, "params": { "embedDim": 256, "patchSize": 1, "inChans": 64 }, "inputs": [ "n-rl4" ], "outputs": [ "n-rl6" ] }, { "id": "n-rl6", "type": "positionalEncoding", "name": "pos_enc", "position": { "x": 220, "y": 960 }, "params": {}, "inputs": [ "n-rl5" ], "outputs": [ "n-rl7" ] }, { "id": "n-rl7", "type": "transformerBlock", "name": "block_1", "position": { "x": 220, "y": 1100 }, "params": { "embedDim": 256, "numHeads": 8, "ffDim": 1024 }, "inputs": [ "n-rl6" ], "outputs": [ "n-rl8" ] }, { "id": "n-rl8", "type": "layerNorm", "name": "ln_out", "position": { "x": 220, "y": 1240 }, "params": { "normalizedShape": 256 }, "inputs": [ "n-rl7" ], "outputs": [ "n-rl9" ] }, { "id": "n-rl9", "type": "linear", "name": "head", "position": { "x": 220, "y": 1380 }, "params": { "outFeatures": 10 }, "inputs": [ "n-rl8" ], "outputs": [ "n-rl10" ] }, { "id": "n-rl10", "type": "output", "name": "output", "position": { "x": 220, "y": 1520 }, "params": {}, "inputs": [ "n-rl9" ], "outputs": [] } ], "connections": [ { "id": "c-rl11", "from": "n-rl0", "to": "n-rl1", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl12", "from": "n-rl1", "to": "n-rl2", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl13", "from": "n-rl2", "to": "n-rl3", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl14", "from": "n-rl3", "to": "n-rl4", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl15", "from": "n-rl4", "to": "n-rl5", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl16", "from": "n-rl5", "to": "n-rl6", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl17", "from": "n-rl6", "to": "n-rl7", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl18", "from": "n-rl7", "to": "n-rl8", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl19", "from": "n-rl8", "to": "n-rl9", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl20", "from": "n-rl9", "to": "n-rl10", "fromPort": "bottom", "toPort": "top" } ] }, "summary": "HYB-S-CV: 9 layers, 812.8K params, will not run (1 blocker: \"pos_enc\" is missing maxLen)", "params": 812810, "layers": 9, "inputShape": [ 1, 28, 28 ], "outputShape": [ 36, 10 ], "fingerprint": "02fcfc4a", "cost": { "estCostUsd": 0.043335289000672655, "estTrainSec": 141.8245821840196, "fitsGpu": "A10G (24GB)", "gpuFits": { "T4": true, "A100_40": true, "H100_80": true }, "assumptions": "Cost is a roofline estimate on the priced GPU for 10 epochs at batch 32 over 50,000 samples (assumed; no dataset attached). GPU fit is fp32 weights plus gradients plus two Adam moments (16 bytes per parameter) with 1.3x headroom; activations are not included and grow with batch size." }, "blockers": [ { "title": "\"pos_enc\" is missing maxLen", "stage": "preflight", "detail": "\"pos_enc\" (positionalEncoding) has no value for maxLen. A layer without these cannot be built, so the run fails at construction rather than part way through.", "fix": "Select the layer and fill the empty fields in the inspector.", "componentIds": [ "n-rl6" ] } ], "warnings": [], "text": "Plan: HYB-S-CV 9 layers · 812.8K params · fingerprint 02fcfc4a\n shape [1,28,28] -> [36,10]\n will run NO (1 blocker)\n fits T4 16GB yes · A100 40GB yes · H100 80GB yes\n train ~$0.04 / 3m on A10G (24GB) (10 epochs, batch 32, 50k samples assumed)\n blockers\n ! \"pos_enc\" is missing maxLen\n policy all lines pass" }, { "id": "HYB-M-CV-0", "family": "HYB", "scale": "M", "origin": "seeded generator, retargeted to 1x28x28 and a 10-way head", "legal": false, "model": { "id": "rl-root", "name": "HYB-M-CV", "components": [ { "id": "n-rl0", "type": "input", "name": "input", "position": { "x": 220, "y": 120 }, "params": { "shape": [ 1, 28, 28 ] }, "inputs": [], "outputs": [ "n-rl1" ] }, { "id": "n-rl1", "type": "conv2d", "name": "stem_c1", "position": { "x": 220, "y": 260 }, "params": { "outChannels": 128, "kernelSize": 7, "stride": 2, "padding": 3 }, "inputs": [ "n-rl0" ], "outputs": [ "n-rl2" ] }, { "id": "n-rl2", "type": "batchNorm", "name": "stem_bn", "position": { "x": 220, "y": 400 }, "params": { "numFeatures": 128 }, "inputs": [ "n-rl1" ], "outputs": [ "n-rl3" ] }, { "id": "n-rl3", "type": "relu", "name": "stem_act", "position": { "x": 220, "y": 540 }, "params": {}, "inputs": [ "n-rl2" ], "outputs": [ "n-rl4" ] }, { "id": "n-rl4", "type": "maxpool2d", "name": "stem_pool", "position": { "x": 220, "y": 680 }, "params": { "kernelSize": 3, "stride": 2 }, "inputs": [ "n-rl3" ], "outputs": [ "n-rl5" ] }, { "id": "n-rl5", "type": "patchEmbed", "name": "patch_proj", "position": { "x": 220, "y": 820 }, "params": { "embedDim": 512, "patchSize": 1, "inChans": 128 }, "inputs": [ "n-rl4" ], "outputs": [ "n-rl6" ] }, { "id": "n-rl6", "type": "positionalEncoding", "name": "pos_enc", "position": { "x": 220, "y": 960 }, "params": {}, "inputs": [ "n-rl5" ], "outputs": [ "n-rl7" ] }, { "id": "n-rl7", "type": "transformerBlock", "name": "block_1", "position": { "x": 220, "y": 1100 }, "params": { "embedDim": 512, "numHeads": 8, "ffDim": 2048 }, "inputs": [ "n-rl6" ], "outputs": [ "n-rl8" ] }, { "id": "n-rl8", "type": "transformerBlock", "name": "block_2", "position": { "x": 220, "y": 1240 }, "params": { "embedDim": 512, "numHeads": 8, "ffDim": 2048 }, "inputs": [ "n-rl7" ], "outputs": [ "n-rl9" ] }, { "id": "n-rl9", "type": "transformerBlock", "name": "block_3", "position": { "x": 220, "y": 1380 }, "params": { "embedDim": 512, "numHeads": 8, "ffDim": 2048 }, "inputs": [ "n-rl8" ], "outputs": [ "n-rl10" ] }, { "id": "n-rl10", "type": "layerNorm", "name": "ln_out", "position": { "x": 220, "y": 1520 }, "params": { "normalizedShape": 512 }, "inputs": [ "n-rl9" ], "outputs": [ "n-rl11" ] }, { "id": "n-rl11", "type": "linear", "name": "head", "position": { "x": 220, "y": 1660 }, "params": { "outFeatures": 10 }, "inputs": [ "n-rl10" ], "outputs": [ "n-rl12" ] }, { "id": "n-rl12", "type": "output", "name": "output", "position": { "x": 220, "y": 1800 }, "params": {}, "inputs": [ "n-rl11" ], "outputs": [] } ], "connections": [ { "id": "c-rl13", "from": "n-rl0", "to": "n-rl1", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl14", "from": "n-rl1", "to": "n-rl2", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl15", "from": "n-rl2", "to": "n-rl3", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl16", "from": "n-rl3", "to": "n-rl4", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl17", "from": "n-rl4", "to": "n-rl5", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl18", "from": "n-rl5", "to": "n-rl6", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl19", "from": "n-rl6", "to": "n-rl7", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl20", "from": "n-rl7", "to": "n-rl8", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl21", "from": "n-rl8", "to": "n-rl9", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl22", "from": "n-rl9", "to": "n-rl10", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl23", "from": "n-rl10", "to": "n-rl11", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl24", "from": "n-rl11", "to": "n-rl12", "fromPort": "bottom", "toPort": "top" } ] }, "summary": "HYB-M-CV: 11 layers, 9.5M params, will not run (2 blockers: \"pos_enc\" is missing maxLen)", "params": 9536010, "layers": 11, "inputShape": [ 1, 28, 28 ], "outputShape": [ 36, 10 ], "fingerprint": "d309d072", "cost": { "estCostUsd": 0.05514804528841143, "estTrainSec": 180.48451185298285, "fitsGpu": "A10G (24GB)", "gpuFits": { "T4": true, "A100_40": true, "H100_80": true }, "assumptions": "Cost is a roofline estimate on the priced GPU for 10 epochs at batch 32 over 50,000 samples (assumed; no dataset attached). GPU fit is fp32 weights plus gradients plus two Adam moments (16 bytes per parameter) with 1.3x headroom; activations are not included and grow with batch size." }, "blockers": [ { "title": "\"pos_enc\" is missing maxLen", "stage": "preflight", "detail": "\"pos_enc\" (positionalEncoding) has no value for maxLen. A layer without these cannot be built, so the run fails at construction rather than part way through.", "fix": "Select the layer and fill the empty fields in the inspector.", "componentIds": [ "n-rl6" ] }, { "title": "policy: max_params 1M exceeded (9.5M)", "detail": "max_params: 1M", "fix": "Reduce the model by 8.5M parameters or raise max_params.", "stage": "policy", "componentIds": [] } ], "warnings": [], "text": "Plan: HYB-M-CV 11 layers · 9.5M params · fingerprint d309d072\n shape [1,28,28] -> [36,10]\n will run NO (2 blockers)\n fits T4 16GB yes · A100 40GB yes · H100 80GB yes\n train ~$0.06 / 4m on A10G (24GB) (10 epochs, batch 32, 50k samples assumed)\n blockers\n ! \"pos_enc\" is missing maxLen\n ! policy: max_params 1M exceeded (9.5M)\n policy 1 line violated (listed above)" }, { "id": "HYB-M-CV-1", "family": "HYB", "scale": "M", "origin": "seeded generator, retargeted to 1x28x28 and a 10-way head", "legal": false, "model": { "id": "rl-root", "name": "HYB-M-CV", "components": [ { "id": "n-rl0", "type": "input", "name": "input", "position": { "x": 220, "y": 120 }, "params": { "shape": [ 1, 28, 28 ] }, "inputs": [], "outputs": [ "n-rl1" ] }, { "id": "n-rl1", "type": "conv2d", "name": "stem_c1", "position": { "x": 220, "y": 260 }, "params": { "outChannels": 128, "kernelSize": 7, "stride": 2, "padding": 3 }, "inputs": [ "n-rl0" ], "outputs": [ "n-rl2" ] }, { "id": "n-rl2", "type": "batchNorm", "name": "stem_bn", "position": { "x": 220, "y": 400 }, "params": { "numFeatures": 128 }, "inputs": [ "n-rl1" ], "outputs": [ "n-rl3" ] }, { "id": "n-rl3", "type": "relu", "name": "stem_act", "position": { "x": 220, "y": 540 }, "params": {}, "inputs": [ "n-rl2" ], "outputs": [ "n-rl4" ] }, { "id": "n-rl4", "type": "maxpool2d", "name": "stem_pool", "position": { "x": 220, "y": 680 }, "params": { "kernelSize": 3, "stride": 2 }, "inputs": [ "n-rl3" ], "outputs": [ "n-rl5" ] }, { "id": "n-rl5", "type": "patchEmbed", "name": "patch_proj", "position": { "x": 220, "y": 820 }, "params": { "embedDim": 512, "patchSize": 1, "inChans": 128 }, "inputs": [ "n-rl4" ], "outputs": [ "n-rl6" ] }, { "id": "n-rl6", "type": "positionalEncoding", "name": "pos_enc", "position": { "x": 220, "y": 960 }, "params": {}, "inputs": [ "n-rl5" ], "outputs": [ "n-rl7" ] }, { "id": "n-rl7", "type": "transformerBlock", "name": "block_1", "position": { "x": 220, "y": 1100 }, "params": { "embedDim": 512, "numHeads": 8, "ffDim": 2048 }, "inputs": [ "n-rl6" ], "outputs": [ "n-rl8" ] }, { "id": "n-rl8", "type": "transformerBlock", "name": "block_2", "position": { "x": 220, "y": 1240 }, "params": { "embedDim": 512, "numHeads": 8, "ffDim": 2048 }, "inputs": [ "n-rl7" ], "outputs": [ "n-rl9" ] }, { "id": "n-rl9", "type": "transformerBlock", "name": "block_3", "position": { "x": 220, "y": 1380 }, "params": { "embedDim": 512, "numHeads": 8, "ffDim": 2048 }, "inputs": [ "n-rl8" ], "outputs": [ "n-rl10" ] }, { "id": "n-rl10", "type": "layerNorm", "name": "ln_out", "position": { "x": 220, "y": 1520 }, "params": { "normalizedShape": 512 }, "inputs": [ "n-rl9" ], "outputs": [ "n-rl11" ] }, { "id": "n-rl11", "type": "linear", "name": "head", "position": { "x": 220, "y": 1660 }, "params": { "outFeatures": 10 }, "inputs": [ "n-rl10" ], "outputs": [ "n-rl12" ] }, { "id": "n-rl12", "type": "output", "name": "output", "position": { "x": 220, "y": 1800 }, "params": {}, "inputs": [ "n-rl11" ], "outputs": [] } ], "connections": [ { "id": "c-rl13", "from": "n-rl0", "to": "n-rl1", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl14", "from": "n-rl1", "to": "n-rl2", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl15", "from": "n-rl2", "to": "n-rl3", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl16", "from": "n-rl3", "to": "n-rl4", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl17", "from": "n-rl4", "to": "n-rl5", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl18", "from": "n-rl5", "to": "n-rl6", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl19", "from": "n-rl6", "to": "n-rl7", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl20", "from": "n-rl7", "to": "n-rl8", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl21", "from": "n-rl8", "to": "n-rl9", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl22", "from": "n-rl9", "to": "n-rl10", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl23", "from": "n-rl10", "to": "n-rl11", "fromPort": "bottom", "toPort": "top" }, { "id": "c-rl24", "from": "n-rl11", "to": "n-rl12", "fromPort": "bottom", "toPort": "top" } ] }, "summary": "HYB-M-CV: 11 layers, 9.5M params, will not run (2 blockers: \"pos_enc\" is missing maxLen)", "params": 9536010, "layers": 11, "inputShape": [ 1, 28, 28 ], "outputShape": [ 36, 10 ], "fingerprint": "d309d072", "cost": { "estCostUsd": 0.05514804528841143, "estTrainSec": 180.48451185298285, "fitsGpu": "A10G (24GB)", "gpuFits": { "T4": true, "A100_40": true, "H100_80": true }, "assumptions": "Cost is a roofline estimate on the priced GPU for 10 epochs at batch 32 over 50,000 samples (assumed; no dataset attached). GPU fit is fp32 weights plus gradients plus two Adam moments (16 bytes per parameter) with 1.3x headroom; activations are not included and grow with batch size." }, "blockers": [ { "title": "\"pos_enc\" is missing maxLen", "stage": "preflight", "detail": "\"pos_enc\" (positionalEncoding) has no value for maxLen. A layer without these cannot be built, so the run fails at construction rather than part way through.", "fix": "Select the layer and fill the empty fields in the inspector.", "componentIds": [ "n-rl6" ] }, { "title": "policy: max_params 1M exceeded (9.5M)", "detail": "max_params: 1M", "fix": "Reduce the model by 8.5M parameters or raise max_params.", "stage": "policy", "componentIds": [] } ], "warnings": [], "text": "Plan: HYB-M-CV 11 layers · 9.5M params · fingerprint d309d072\n shape [1,28,28] -> [36,10]\n will run NO (2 blockers)\n fits T4 16GB yes · A100 40GB yes · H100 80GB yes\n train ~$0.06 / 4m on A10G (24GB) (10 epochs, batch 32, 50k samples assumed)\n blockers\n ! \"pos_enc\" is missing maxLen\n ! policy: max_params 1M exceeded (9.5M)\n policy 1 line violated (listed above)" } ], "policy": { "applied": { "max_params": "1M" }, "source": "The repository's own rule, the same field `.neurarch.yml` carries and `/api/v1/plan` and `/api/v1/train` accept.", "note": "`/api/v1/rank` scores the graph and does not read a policy file, so a design this rule excludes can still come back `legal` there. The two are kept apart on purpose." }, "refusedCount": 6, "refusalKinds": { "preflight": 4, "policy": 4 }, "ranking": { "tieBreak": { "rule": "cost", "decided": 4, "note": "4 candidates were placed by estimated cost inside a measured tie. Those positions are your rule, not a measurement; measuredRank is what the verifier said." }, "ranked": [ { "id": "CNN-S-CV-0", "blocking": 0, "warnings": 0, "otherStageBlockers": [], "outcomeFlags": [], "params": 113226, "estCostUsd": 0.042424553250298785, "fitsGpu": "A10G (24GB)", "summary": "No dataset is wired yet, so a run would train on random tensors.", "tier": "legal", "rank": 1, "measuredRank": 1, "tiedWith": 1, "reasons": [ "Runs, and trips no rule with a trained-outcome measurement behind it.", "Tied at measured rank 1 with 3 others; placed by estimated cost (0.042424553250298785) on your tieBreak rule. That is a budget decision, not a claim about the design." ] }, { "id": "CNN-S-CV-1", "blocking": 0, "warnings": 0, "otherStageBlockers": [], "outcomeFlags": [], "params": 75530, "estCostUsd": 0.0444266753026351, "fitsGpu": "A10G (24GB)", "summary": "No dataset is wired yet, so a run would train on random tensors.", "tier": "legal", "rank": 2, "measuredRank": 1, "tiedWith": 1, "reasons": [ "Runs, and trips no rule with a trained-outcome measurement behind it.", "Tied at measured rank 1 with 3 others; placed by estimated cost (0.0444266753026351) on your tieBreak rule. That is a budget decision, not a claim about the design." ] }, { "id": "CNN-M-CV-1", "blocking": 0, "warnings": 0, "otherStageBlockers": [], "outcomeFlags": [], "params": 2221962, "estCostUsd": 0.0462959239375151, "fitsGpu": "A10G (24GB)", "summary": "No dataset is wired yet, so a run would train on random tensors.", "tier": "legal", "rank": 3, "measuredRank": 1, "tiedWith": 1, "reasons": [ "Runs, and trips no rule with a trained-outcome measurement behind it.", "Tied at measured rank 1 with 3 others; placed by estimated cost (0.0462959239375151) on your tieBreak rule. That is a budget decision, not a claim about the design." ] }, { "id": "CNN-M-CV-0", "blocking": 0, "warnings": 0, "otherStageBlockers": [], "outcomeFlags": [], "params": 2071562, "estCostUsd": 0.07699582498087185, "fitsGpu": "A10G (24GB)", "summary": "No dataset is wired yet, so a run would train on random tensors.", "tier": "legal", "rank": 4, "measuredRank": 1, "tiedWith": 1, "reasons": [ "Runs, and trips no rule with a trained-outcome measurement behind it.", "Tied at measured rank 1 with 3 others; placed by estimated cost (0.07699582498087185) on your tieBreak rule. That is a budget decision, not a claim about the design." ] }, { "id": "HYB-S-CV-0", "blocking": 1, "warnings": 0, "otherStageBlockers": [], "outcomeFlags": [], "params": 812810, "estCostUsd": 0.043335289000672655, "fitsGpu": "A10G (24GB)", "summary": "1 blocker would have failed a $0.04 / 3m on an A10G (24GB) run.", "tier": "blocked", "rank": 5, "measuredRank": 5, "tiedWith": 4, "reasons": [ "1 blocking finding: this graph does not forward-pass, so executing it spends budget on a crash." ] }, { "id": "HYB-S-CV-1", "blocking": 1, "warnings": 0, "otherStageBlockers": [], "outcomeFlags": [], "params": 812810, "estCostUsd": 0.043335289000672655, "fitsGpu": "A10G (24GB)", "summary": "1 blocker would have failed a $0.04 / 3m on an A10G (24GB) run.", "tier": "blocked", "rank": 5, "measuredRank": 5, "tiedWith": 4, "reasons": [ "1 blocking finding: this graph does not forward-pass, so executing it spends budget on a crash." ] }, { "id": "HYB-M-CV-0", "blocking": 1, "warnings": 0, "otherStageBlockers": [], "outcomeFlags": [], "params": 9536010, "estCostUsd": 0.05514804528841143, "fitsGpu": "A10G (24GB)", "summary": "1 blocker would have failed a $0.06 / 4m on an A10G (24GB) run.", "tier": "blocked", "rank": 5, "measuredRank": 5, "tiedWith": 4, "reasons": [ "1 blocking finding: this graph does not forward-pass, so executing it spends budget on a crash." ] }, { "id": "HYB-M-CV-1", "blocking": 1, "warnings": 0, "otherStageBlockers": [], "outcomeFlags": [], "params": 9536010, "estCostUsd": 0.05514804528841143, "fitsGpu": "A10G (24GB)", "summary": "1 blocker would have failed a $0.06 / 4m on an A10G (24GB) run.", "tier": "blocked", "rank": 5, "measuredRank": 5, "tiedWith": 4, "reasons": [ "1 blocking finding: this graph does not forward-pass, so executing it spends budget on a crash." ] } ], "recommended": "CNN-S-CV-0", "recommendation": "CNN-S-CV-0 sits alone at the top because you asked ties to be broken on cost. Nothing measured separates it from 3 others at measured rank 1; the choice is your budget's, not the verifier's.", "budget": { "candidates": 8, "blocked": 4, "legal": 4, "wouldNotRun": [ "HYB-S-CV-0", "HYB-S-CV-1", "HYB-M-CV-0", "HYB-M-CV-1" ], "reclaimed": 0.5 }, "calibration": { "exclusion": { "claim": "A design with a pre-flight blocker does not forward-pass.", "evidence": "264-graph study, torch 2.8: 96 of 96 blocked graphs crashed PyTorch forward, 80 of 80 passes ran clean." }, "ordering": { "claim": "Ordering two legal designs is weakly supported and usually abstains.", "pairwiseAccuracy": 0.514, "coverage": 0.083, "sampleSize": 36, "decidedPairs": 3, "quotable": false, "basis": "in-sample: 24 designs over 6 tasks trained end to end on one T4 (scripts/rl-benchmark/grounded-results.json)", "comparators": { "chance": 0.5, "zheng-2026-best": 0.615, "foster-2026-best": 0.6935 } }, "outOfSample": { "ran": "2026-09-01", "trainedRows": 15, "judgedPairs": 15, "decidedPairs": 4, "abstained": 11, "quotable": false, "note": "Held-out campaign reproduced the abstention (11 of 15 pairs) but decided too few pairs to promote an accuracy. See scripts/rl-benchmark/CALIBRATION.md.", "codeReadingJudges": { "basis": "same 15 held-out pairs, exported PyTorch, both orderings, position flips scored as abstentions (scripts/rl-benchmark/llm-baseline-results.json)", "claude-opus-5": { "decidedPairs": 15, "correct": 12, "pairwiseAccuracy": 0.8, "coverage": 1 }, "grok-4.3": { "decidedPairs": 15, "correct": 11, "pairwiseAccuracy": 0.7333, "coverage": 1 } }, "trivialBaseline": { "id": "largest-params", "decidedPairs": 15, "correct": 11, "pairwiseAccuracy": 0.7333, "coverage": 1, "note": "A no-model rule within a few pairs of both judges on this set. Neither judge number is evidence that reading code sees what parameter count does not." } }, "source": "https://neurarch.com/docs/structural-checks" } }, "chosen": { "id": "CNN-S-CV-0", "planUrl": "https://www.neurarch.com/p/hf8wvtqnq2", "fingerprint": "4f78dfe7" }, "questions": [ { "stage": "data", "id": "dataset", "question": "Which data should this train on?", "because": "Everything else about the run is derived from the graph. This is not: the design says it wants vision input of shape (1, 28, 28), but not which corpus you have.", "options": [ { "label": "CIFAR-10", "value": "hf:cifar10", "hint": "60k 32×32 colour images, 10 classes" }, { "label": "MNIST", "value": "hf:mnist", "hint": "70k 28×28 greyscale digits, 10 classes" }, { "label": "Upload my own images", "value": "upload:image_zip", "hint": "ImageFolder .zip, goes to your private storage" }, { "label": "No data yet, smoke-test it", "value": "synthetic", "hint": "Random tensors matching the input contract, so train.py runs end to end" } ], "answer": "hf:mnist", "answeredWhy": "The visitor said \"handwritten digits\". Which corpus that is remains theirs to say." }, { "stage": "train", "id": "train-mode", "question": "How do you want to train it?", "because": "The estimate and the hardware fit are derived. Whether you want to spend the time or the money is not.", "options": [ { "label": "Simulate it (free, instant)", "value": "simulate", "hint": "Architecture-based curves, useful to check the wiring, not a measurement" }, { "label": "Free GPU (Colab / Kaggle)", "value": "free_gpu", "hint": "A notebook you run yourself; results report back into the app" }, { "label": "Managed GPU (about $0.04)", "value": "managed_gpu", "hint": "3m on an A10G (24GB), confirmed in the runner before anything starts" } ], "answer": "managed_gpu", "answeredWhy": "Nothing in the graph can decide whether this run is worth paying for." } ], "history": { "fingerprint": "4f78dfe7", "rows": [ { "at": "2026-09-04T08:25:52.186+00:00", "metric": "valAcc", "value": 0.9723, "epochs": 10, "wallSec": 120, "estCostUsd": 0.0257, "source": "via=v1/train job=job_1788510352186_pngead", "jobId": "job_1788510352186_pngead" }, { "at": "2026-09-04T07:46:35.842+00:00", "metric": "valAcc", "value": 0.9683, "epochs": 10, "wallSec": 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1 } }, "ledger": "written" }, "browserModel": { "file": "model.onnx", "candidateId": "CNN-S-CV-0", "weights": "trained", "weightsSource": "managed-run", "weightsJobId": "job_1788510352186_pngead", "weightsFormat": "onnx", "weightsNote": "Exported inside the training process from the weights the run finished with (modal_trainer.py, export_onnx), uploaded by the worker, and downloaded here from the `model_url` that `GET /api/v1/train?job=` returned. It is the model this run trained.", "weightsBytes": 454422, "verification": { "runtime": "onnxruntime 1.19.2", "testAcc": 0.9547, "testRight": 9547, "testCount": 10000, "digitsAcc": 0.8, "digitsRight": 8, "digitsCount": 10, "digitsPredicted": [ 0, 1, 2, 3, 4, 2, 8, 7, 8, 9 ], "onnxBytes": 454422, "preprocessing": "uint8 to [0,1], then (x - 0.1307) / 0.3081, one channel, 28 by 28" }, "preprocessing": { "size": [ 28, 28 ], "channels": 1, "normalize": { "mean": 0.1307, "std": 0.3081 }, "note": "Exactly what modal_trainer.py::_build_mnist_script feeds: ToTensor to [0,1], then (x - 0.1307) / 0.3081, one channel, 28 by 28, white digit on black." } } }