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l2_normalize

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

l2_normalize: 15 implementations from 13 papers ran on one shared input (census 2026-09-22, battery b986f7e04d79); they produced 5 distinct outputs across 3 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 3: arg 1: rank 2, kind float, dtype float32

13 implementations from 11 papers share this bucket (rank, kind, dtype of each array argument, positional; each member's recorded signature, argument name included, is shown under it); 3 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
8 implementations
7 papers
2803cfee2d9a
recorded values differ by up to 5.96e-08
same digest as torch: last_dim

library-records-dataset/data-analysis/analysis3/gnd_embed_and_polysemy.py 1ff76032
recorded x:2/float/float32; axis=-1, eps=1e-12

main_text.py 2cf4de80
recorded x:2/float/float32

objective.py 6325cd34
recorded x:2/float/float32; dim=1, eps=1e-12

objective.py a08ad4db
recorded x:2/float/float32

main_image.py bc6f5549
recorded x:2/float/float32

core/models/semantic_kitti/geoclass.py d5090a7e
recorded x:2/float/float32

train_TENT.py f06b0faa
recorded x:2/float/float32

src/cosmapdr/cosmapdr.py f1934dc5
recorded X:2/float/float32; eps=1e-12
[0.60254, -0.512675, 0.159124, -0.230934, -0.301783, -0.344442, -0.221532, 0.191492, …]
shape [4, 8] · float32 · ndarray
4 implementations
3 papers
4171f3b5f627
recorded values identical

low_rank_linear.py 00696863
recorded v:2/float/float32; eps=1e-12

skew_ortho_conv.py 5f294d9f
recorded tensor:2/float/float32; eps=1e-12

sn_gan/sn_modules.py bf5a05c7
recorded x:2/float/float32; eps=1e-12

skew_ortho_conv.py d00da207
recorded tensor:2/float/float32; eps=1e-12
[0.316604, -0.269384, 0.0836115, -0.121344, -0.158572, -0.180987, -0.116404, 0.100619, …]
shape [4, 8] · float32 · Tensor
1 implementation
1 paper
58eaef3f9b5e

src/MoA.py 4760e363
recorded x:2/float/float32; axis=1, eps=1e-06
[0.60254, -0.512675, 0.159124, -0.230933, -0.301783, -0.344442, -0.221532, 0.191492, …]
shape [4, 8] · float32 · Tensor

Bucket 2 of 3: arg 1: rank 2, kind float, dtype float64

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
2803cfee2d9a

recipe/leeps/task_sampler.py 4bb9a4bd
recorded values:2/float/float64
[0.60254, -0.512675, 0.159124, -0.230934, -0.301783, -0.344442, -0.221532, 0.191492, …]
shape [4, 8] · float32 · ndarray

Bucket 3 of 3: arg 1: rank 3, 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
0e0d73a888ed

models/mahalanobis.py ddaf1f82
recorded d:3/float/float32
[-0.160311, 0.302062, -0.225948, -0.0463464, 0.0271029, -0.257531, -0.0610541, -0.0684098, …]
shape [2, 4, 8] · 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/l2-normalize.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