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PositionalEncoding

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

PositionalEncoding: 13 implementations from 9 papers ran on one shared input (census 2026-09-22, battery b986f7e04d79); they produced 9 distinct outputs across 5 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 5: arg 1: rank 3, kind float, dtype float32

9 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); 5 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
2 papers
10d8865d2703
recorded values differ by up to 1.19e-07
class
model/standard.py 4f5b9488
recorded x:3/float/float32
class
models.py 5dc71b21
recorded x:3/float/float32
class
model/scratch_model.py 92aea12e
recorded x:3/float/float32
[-0.893127, 2.68285, -1.2588, 0.741794, 0.150996, -0.434759, -0.340146, 0.618874, …]
shape [2, 4, 8] · float32 · Tensor
2 implementations
2 papers
28cd979073fb
recorded values identical
class
lib/eeg_transformer.py 429a0628
recorded x:3/float/float32
class
models/TimeDART.py ba3da553
recorded x:3/float/float32
[-0, 2.98095, -1.39867, 0, 0.167773, -0.483066, -0.37794, 0.687638, …]
shape [2, 4, 8] · float32 · Tensor
2 implementations
2 papers
f52b65ca7dca
recorded values identical
class
uniMASK/transformer.py 117a93cf
recorded x:3/float/float32
class
model.py b9af059f
recorded x:3/float/float32
[-0, 2.98095, -1.39867, 0, 0.167773, -0.483066, -0.37794, 0.687638, …]
shape [2, 4, 8] · float32 · Tensor
1 implementation
1 paper
766cc7234ad6
class
grounded_compgen_research/models/imitation/conv_transformer.py 6d88134a
recorded x:3/float/float32
[0, 1, 0, 1, 0.841471, 0.540302, 0.00999983, 0.99995]
shape [2, 1, 4] · float32 · Tensor
1 implementation
1 paper
f5efe631655a
class
model.py 6ae60d8c
recorded x:3/float/float32
[-0, 1.98095, -1.39867, -0, 0.167773, -1.48307, -0.37794, -0.312362, …]
shape [2, 4, 8] · float32 · Tensor

Bucket 2 of 5: 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
a53e4536a65f
class
model.py 078a3713
recorded noise_level:1/float/float32
[0.48179, 0.48179, 0.48179, 0.48179, 0.876287, 0.876287, 0.876287, 0.876287, …]
shape [8, 8] · float32 · Tensor

Bucket 3 of 5: arg 1: rank 1, 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
bea48acc7c12
class
k-edge-identification/src/ehnn/models.py 2fd498d9
recorded x:1/int/int64
[0.909297, -0.416147, 0.0199987, 0.9998, 0.841471, 0.540302, 0.00999983, 0.99995, …]
shape [8, 4] · float32 · Tensor

Bucket 4 of 5: arg 1: rank 2, 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
ac63a8474c76
class
golf/model.py a043ead7
recorded coords:2/float/float32; rays=None
[-0.581084, -0.945823, -0.614184, 0.969382, 0.476075, -0.837326, -0.91554, 0.736511, …]
shape [4, 128] · float32 · Tensor

Bucket 5 of 5: arg 1: rank 2, 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
a721946fbb2c
class
transformer/models.py c1e9ee7b
recorded inputs:2/int/int64
[0.909297, -0.416147, 0.0199987, 0.9998, 0.14112, -0.989992, 0.0299955, 0.99955, …]
shape [4, 8, 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/positionalencoding.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