onnx-web-models / setup_53_2d /manifest.json
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3D full finetuning: NDHWC train_graph.json + torch_params.json, structured weight_map to_onnx, 3D runtime; 2D spike peak_mb corrected
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{
"model": "setup_53_2d",
"task": "mito_affinities",
"architecture": "Unet3dIso (2D-collapsed)",
"checkpoint": "student_60000",
"params": 1927907,
"channels": [
"mito_aff_z",
"mito_aff_y",
"mito_aff_x"
],
"input_voxel_size_nm": [
16,
16,
16
],
"output_voxel_size_nm": [
16,
16,
16
],
"output": "raw logits (apply sigmoid / threshold at 0)",
"input_norm": [
{
"name": "MinMaxNormalizer",
"min_value": 0,
"max_value": 255
},
{
"name": "LambdaNormalizer",
"expression": "2*x-1"
}
],
"io": "input 'input' float32 [1,1,1,y,x] (one z-slice); output 'output' float32 [1,C,1,y',x']",
"kind": "2D slice student distilled from the 3D model (train_2d_distill.py)",
"step": 60000,
"distilled_from": "setup_53",
"distilled_from_repo": "cellmap/mito-aff-unetiso-setup-53",
"variants": [
{
"model": "setup_53_2d",
"variant": "fp32",
"input_size": [
1,
300,
300
],
"output_size": [
1,
212,
212
],
"file": "setup_53_mito_affinities_16nm_2d_in300_fp32.onnx",
"file_mb": 7.75,
"max_abs": 2.288818359375e-05,
"flip_frac": 0.0
},
{
"model": "setup_53_2d",
"variant": "fp16",
"input_size": [
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300
],
"output_size": [
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],
"file": "setup_53_mito_affinities_16nm_2d_in300_fp16.onnx",
"file_mb": 3.9,
"max_abs": 0.10926437377929688,
"flip_frac": 4.4499822000712e-05
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{
"model": "setup_53_2d",
"variant": "fp32",
"input_size": [
1,
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],
"output_size": [
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],
"file": "setup_53_mito_affinities_16nm_2d_in556_fp32.onnx",
"file_mb": 7.75,
"max_abs": 2.09808349609375e-05,
"flip_frac": 0.0
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{
"model": "setup_53_2d",
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556
],
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],
"file": "setup_53_mito_affinities_16nm_2d_in556_fp16.onnx",
"file_mb": 3.9,
"max_abs": 0.10926437377929688,
"flip_frac": 3.652567755131858e-05
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{
"model": "setup_53_2d",
"variant": "fp32",
"input_size": [
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],
"output_size": [
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980,
980
],
"file": "setup_53_mito_affinities_16nm_2d_in1068_fp32.onnx",
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"max_abs": 2.574920654296875e-05,
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{
"model": "setup_53_2d",
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1,
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1068
],
"output_size": [
1,
980,
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],
"file": "setup_53_mito_affinities_16nm_2d_in1068_fp16.onnx",
"file_mb": 3.9,
"max_abs": 0.10926437377929688,
"flip_frac": 4.859086491739553e-05
}
],
"val_f1": {
"metric": "affinity F1 (mean of 3 channels), 6 GT val crops, centered 200^3, threshold logit>0",
"student": {
"crop495": 0.8164,
"crop496": 0.796,
"crop1017": 0.9015,
"crop528": 0.9217,
"crop1091": 0.9166,
"crop1081": 0.9481
},
"student_mean": 0.8834,
"teacher_3d": {
"crop495": 0.955,
"crop496": 0.928,
"crop1017": 0.966,
"crop528": 0.9746,
"crop1091": 0.9517,
"crop1081": 0.9456
},
"teacher_3d_mean": 0.9535
},
"torch_version": "2.9.1",
"exporter": "torch.onnx.export (TorchScript, dynamo=False)",
"opset": 18,
"finetune": {
"head": {
"final_layer": "final_conv.c",
"onnx_node": "/final_conv/c/Conv",
"features": "/final_conv/Gather_output_0",
"weight": "final_conv.c.weight",
"bias": "final_conv.c.bias",
"in_channels": 32,
"out_channels": 3,
"activation": "none (logits)",
"files": [
"setup_53_mito_affinities_16nm_2d_in1068_fp16.onnx",
"setup_53_mito_affinities_16nm_2d_in1068_fp32.onnx",
"setup_53_mito_affinities_16nm_2d_in300_fp16.onnx",
"setup_53_mito_affinities_16nm_2d_in300_fp32.onnx",
"setup_53_mito_affinities_16nm_2d_in556_fp16.onnx",
"setup_53_mito_affinities_16nm_2d_in556_fp32.onnx"
],
"initializers": "finetune/initializers.json",
"loss": "masked BCE on logits",
"note": "train the final 1x1 conv on frozen features"
},
"full": {
"library": "tfjs",
"files": [
"finetune/train_graph.json",
"finetune/cellmap_tfjs_train.js"
],
"weight_map": "identity",
"initializers": "finetune/initializers.json",
"write_back": [
"setup_53_mito_affinities_16nm_2d_in1068_fp16.onnx",
"setup_53_mito_affinities_16nm_2d_in1068_fp32.onnx",
"setup_53_mito_affinities_16nm_2d_in300_fp16.onnx",
"setup_53_mito_affinities_16nm_2d_in300_fp32.onnx",
"setup_53_mito_affinities_16nm_2d_in556_fp16.onnx",
"setup_53_mito_affinities_16nm_2d_in556_fp32.onnx"
],
"frozen": [
"encoder0.bn1.running_mean",
"encoder0.bn1.running_var",
"encoder0.bn2.running_mean",
"encoder0.bn2.running_var",
"encoder1.bn1.running_mean",
"encoder1.bn1.running_var",
"encoder1.bn2.running_mean",
"encoder1.bn2.running_var",
"encoder2.bn1.running_mean",
"encoder2.bn1.running_var",
"encoder2.bn2.running_mean",
"encoder2.bn2.running_var",
"bottleneck.bn1.running_mean",
"bottleneck.bn1.running_var",
"bottleneck.bn2.running_mean",
"bottleneck.bn2.running_var",
"decoder2.bn1.running_mean",
"decoder2.bn1.running_var",
"decoder2.bn2.running_mean",
"decoder2.bn2.running_var",
"decoder1.bn1.running_mean",
"decoder1.bn1.running_var",
"decoder1.bn2.running_mean",
"decoder1.bn2.running_var",
"decoder0.bn1.running_mean",
"decoder0.bn1.running_var",
"decoder0.bn2.running_mean",
"decoder0.bn2.running_var"
],
"note": "params named as the ONNX initializers; BatchNorm running stats frozen",
"spike": {
"setup": "TF.js 4.22.0 WebGPU backend, Chrome 154 on macOS, Apple GPU (metal-3, unified memory); batch 1, fp32, masked BCE on logits, Adam lr 1e-4; graph = finetune/train_graph.json, weights read from the served fp32 .onnx; median of 8 steps after 2 warm-up; peak = tf.profile peakBytes above baseline (tracked tensors; the WebGPU buffer pool holds more)",
"date": "2026-10-17",
"params": 1927907,
"full": {
"300": {
"step_ms": 308,
"peak_mb": 980
},
"556": {
"step_ms": 1189,
"peak_mb": 3897
}
},
"head_through_full_graph": {
"300": {
"step_ms": 31
},
"556": {
"step_ms": 133
}
},
"forward_ms": {
"300": 11,
"556": 41
},
"tfjs_webgpu_vs_ort_webgpu_556": {
"max_abs": 1.81e-05,
"flips": 0
},
"note": "2026-10-17 rerun of finetune_spike.html unchanged: peak_mb corrected (the 2026-10-16 values, 320/1307 MB for setup_53_2d, were not reproducible; this rerun matches an independent RTX 2080 Ti run: 980/3897 MB). Peak counts tracked tensors only, the WebGPU buffer pool holds more."
}
}
},
"source_repo": "cellmap/mito-aff-unetiso-setup-53-2d"
}