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one_hot

Syntologyfunction-name censuscensus 2026-09-22battery b986f7e04d79all samples with this name

one_hot: 18 implementations from 25 papers ran on one shared input (census 2026-09-22, battery b986f7e04d79); they produced 10 distinct outputs across 6 buckets, one shared input per bucket.

Identical values to six decimals (the recorded digest) on the shared input are agreement on those inputs, not equivalence. Implementations are compared only within one bucket, the positional (rank, kind, dtype) of each array argument; the argument name is not part of the key because the harness draws the shared array from (rank, kind) and casts it to the dtype, whatever the name; each bucket's shared input is fixed by that key, so members of one bucket saw bitwise-identical inputs under their own scalar arguments. A cluster is the set of members whose recorded output digest is identical. Nothing here says which computation a paper's method intended, and nothing reproduces a paper's results.

Not compared, and not in the tables or the counts above:

Bucket 1 of 6: arg 1: rank 1, kind int, dtype int64

10 implementations from 14 papers share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 4 distinct outputs, largest cluster first. Values are the first 8 of the recorded output, flattened.

Cluster (same digest to six decimals)MembersShared output on this bucket's input
7 implementations
9 papers
7bcb5c10457d
recorded values identical
one code sha held from 2 papers' repositories
utils.py 4728dc20
recorded x:1/int/int64; num_classes=4, on_value=1.0, off_value=0.0, device='cpu'
one code sha held from 2 papers' repositories
code/Raindrop.py e5da4e42
recorded y_:1/int/int64

lib/consolidate.py 8431f92b
recorded data:1/int/int64; max_value=4

code/models/FeatureBanks.py a67d611e
recorded y:1/int/int64; max_size=None

src/cnn_model.py af1cb734
recorded y_:1/int/int64

compute_metrics.py edfd7151
recorded a:1/int/int64

models/anchor_net.py fed03b1d
recorded labels:1/int/int64; num_classes=4
[0, 0, 1, 0, 0, 1, 0, 0, …]
shape [8, 4] · float32 · Tensor
1 implementation
3 papers
941f711d4274
one code sha held from 3 papers' repositories
trades_r/sodef_eval_ode.py 64975423
recorded x:1/int/int64; K=3
[0, 0, 1, 0, 1, 0, 0, 0, …]
shape [8, 3] · int64 · ndarray
1 implementation
1 paper
8e24ea8fa1be

RVFL.py ed89c1bf
recorded x:1/int/int64; n_class=2
[0, 0, 0, 1, 0, 0, 1, 0, …]
shape [8, 2] · float64 · ndarray
1 implementation
1 paper
e4c8691c6997

MEDM_VisDA_Res50.py a50f333c
recorded label:1/int/int64
[0, 0, 1, 0, 0, 0, 0, 0, …]
shape [8, 12] · float32 · Tensor

Bucket 2 of 6: arg 1: rank 2, kind int, dtype int64

4 implementations from 6 papers share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 2 distinct outputs, largest cluster first. Values are the first 8 of the recorded output, flattened.

Cluster (same digest to six decimals)MembersShared output on this bucket's input
3 implementations
3 papers
60069f246d8e
recorded values identical

modules/modeling_moebert_gate.py 882d0552
recorded indices:2/int/int64; num_classes=4

model.py b95bc817
recorded indices:2/int/int64; depth=4, dim=2

utils.py defd9ff9
recorded a:2/int/int64; num_classes=4
[0, 0, 1, 0, 0, 0, 0, 1, …]
shape [4, 8, 4] · int64 · Tensor
1 implementation
3 papers
b9fb866b9df0
one code sha held from 3 papers' repositories
train_aug.py 7c64c35b
recorded indices:2/int/int64; depth=4
[1, 0, 0, 0, 1, 0, 0, 0, …]
shape [4, 8, 4] · float32 · Tensor

Bucket 3 of 6: arg 1: rank 1, kind float, dtype float32

1 implementation from 1 paper share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 1 distinct output, largest cluster first. Values are the first 8 of the recorded output, flattened.

Cluster (same digest to six decimals)MembersShared output on this bucket's input
1 implementation
1 paper
dc768749f172

code/mgcvae.py 8cfd0918
recorded labels:1/float/float32; class_size=4
[0, 0, 0, 1, 1, 0, 0, 0, …]
shape [8, 4] · float32 · Tensor

Bucket 4 of 6: arg 1: rank 3, kind float, dtype float32

1 implementation from 2 papers share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 1 distinct output, largest cluster first. Values are the first 8 of the recorded output, flattened.

Cluster (same digest to six decimals)MembersShared output on this bucket's input
1 implementation
2 papers
ee0d534dd385
one code sha held from 2 papers' repositories
train_s4GAN.py 3d0fa603
recorded label:3/float/float32
[0, 0, 0, 0, 0, 0, 0, 0, …]
shape [2, 21, 4, 8] · float32 · Tensor

Bucket 5 of 6: arg 1: rank 3, kind int, dtype int64

1 implementation from 1 paper share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 1 distinct output, largest cluster first. Values are the first 8 of the recorded output, flattened.

Cluster (same digest to six decimals)MembersShared output on this bucket's input
1 implementation
1 paper
7c2a2a00abe3

models/hscnet.py 3dea70a3
recorded x:3/int/int64; N=25
[0, 1, 0, 0, 0, 0, 0, 0, …]
shape [2, 25, 4, 8] · float32 · Tensor

Bucket 6 of 6: arg 1: rank 4, kind float, dtype float32 · arg 2: rank 3, kind int, dtype int64

1 implementation from 1 paper share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 1 distinct output, largest cluster first. Values are the first 8 of the recorded output, flattened.

Cluster (same digest to six decimals)MembersShared output on this bucket's input
1 implementation
1 paper
473565989e72

yolov1.py 76c3b477
recorded output:4/float/float32, label:3/int/int64; device='cpu'
[0, 0, 1, 0, 1, 0, 0, 0, …]
shape [2, 3, 4, 4] · float32 · Tensor

Identical values to six decimals (the recorded digest) on the shared input are agreement on those inputs, not equivalence; where a cluster's members carry recorded values, the largest difference among them is shown under the cluster. Paper titles are the archive's archive 2025-07-28 where the paper is in the archive and the graph's where it was added by Syntology; papers with no page here are shown by their recorded paper id only. A paper count above the implementation count means one implementation (one code sha) is held from several papers' repositories and counts once. Per-sample status, licence and fingerprint records for each paper are on its paper page. JSON twin: /census/one-hot.json.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections