attention
attention: 11 implementations from 10 papers ran on one shared input (census 2026-09-22, battery b986f7e04d79); they produced 7 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:
- 8 more implementations of this name were examined but did not run on the shared input (RuntimeError 8).
- No implementation of this name ran on its own fixture arguments only: every one that ran took an array argument.
- Every compared output was digested.
Bucket 1 of 5: arg 1: rank 4, kind float, dtype float32 · arg 2: rank 4, kind float, dtype float32 · arg 3: rank 4, kind float, dtype float32 · arg 4: rank 4, kind float, dtype float32
4 implementations from 3 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) | Members | Shared output on this bucket's input |
|---|---|---|
| 3 implementations 2 papers c190e723cd2e recorded values identical |
pykt/models/simplekt.py 5bd62b87 recorded q:4/float/float32, k:4/float/float32, v:4/float/float32, mask:4/float/float32; d_k=5, dropout=Dropout(p=0.1, inplace=False), zero_pad=False
models/pakt.py 72814a15 recorded q:4/float/float32, k:4/float/float32, v:4/float/float32, mask:4/float/float32; d_k=5, dropout=Dropout(p=0.1, inplace=False), zero_pad=False pykt/models/simplekt.py e05cd8a1 recorded q:4/float/float32, k:4/float/float32, v:4/float/float32, mask:4/float/float32; d_k=5, dropout=Dropout(p=0.1, inplace=False), zero_pad=False |
[0.260109, -0.0500833, -0.129173, 0.174312, 0.580391, -0.0257366, -0.549415, 0.807632, …] shape [2, 3, 4, 4] · float32 · Tensor |
| 1 implementation 1 paper ff86505cf778 |
model/TransKT.py 134e95d1 recorded q:4/float/float32, k:4/float/float32, v:4/float/float32, mask:4/float/float32; d_k=5, dropout=Dropout(p=0.1, inplace=False), zero_pad=True |
[0, 0, 0, 0, 0.580391, -0.0257366, -0.549415, 0.807632, …] shape [2, 3, 4, 4] · float32 · Tensor |
Bucket 2 of 5: arg 1: rank 4, kind float, dtype float32
3 implementations from 3 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) | Members | Shared output on this bucket's input |
|---|---|---|
| 3 implementations 3 papers 42c78be7a46f recorded values identical |
one code sha held from 2 papers' repositories unlearn.py b817aa66 recorded x:4/float/float32 Our_code/Pytorch/zero-shot-baseline.py 8031f2b6 recorded x:4/float/float32 Our_code/Pytorch/Basic_experiments/exp-16_2-16_1.py ab5d18fb recorded x:4/float/float32 |
[0.0641893, 0.105176, 0.189701, 0.2541, 0.159976, 0.375468, 0.0196281, 0.29745, …] shape [2, 16] · float32 · Tensor |
Bucket 3 of 5: arg 1: rank 3, kind float, dtype float32 · arg 2: rank 3, kind float, dtype float32 · arg 3: rank 3, kind float, dtype float32
2 implementations 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); 2 distinct outputs, largest cluster first. Values are the first 8 of the recorded output, flattened.
| Cluster (same digest to six decimals) | Members | Shared output on this bucket's input |
|---|---|---|
| 1 implementation 1 paper 02617d7c9917 |
utils.py 72ce5bea recorded Q:3/float/float32, K:3/float/float32, V:3/float/float32 |
[-1.00379, 1.34099, -1.1562, -0.339274, 0.212062, -1.08009, -0.280365, -0.139151, …] shape [2, 4, 8] · float32 · Tensor |
| 1 implementation 1 paper c09ff4f743dd |
kandinsky2/model/text2im_model2_1.py fe304798 recorded q:3/float/float32, k:3/float/float32, v:3/float/float32; d_k=4 |
[-0.992026, 1.49343, -1.20681, -0.310881, 0.204297, -1.2598, -0.297142, -0.264622, …] shape [2, 4, 8] · float32 · Tensor |
Bucket 4 of 5: arg 1: rank 4, kind float, dtype float32 · arg 2: rank 4, kind float, dtype float32 · arg 3: rank 4, kind float, dtype float32 · arg 4: rank 4, 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) | Members | Shared output on this bucket's input |
|---|---|---|
| 1 implementation 1 paper cc2e4b612f8d |
models/oclr.py 86341ad6 recorded q:4/float/float32, k:4/float/float32, v:4/float/float32, mask:4/int/int64; d_k=4, dropout=Dropout(p=0.1, inplace=False) |
[0.0193632, -0.00746569, -0.0671406, -0.000716995, 0.652213, 0.00248403, -0.340817, 1.00866, …] shape [1, 1, 2, 3, 4, 4] · float32 · Tensor |
Bucket 5 of 5: arg 1: rank 4, kind float, dtype float32 · arg 2: rank 4, kind float, dtype float32 · arg 3: rank 4, 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) | Members | Shared output on this bucket's input |
|---|---|---|
| 1 implementation 1 paper ac07ca26d031 |
hyvideo/modules/models.py 7f6ea851 recorded q:4/float/float32, k:4/float/float32, v:4/float/float32; mode='vanilla', drop_rate=0.0, attn_mask=None, causal=False, cu_seqlens_q=None, cu_seqlens_kv=None, max_seqlen_q=None, max_seqlen_kv=None, batch_size=2 |
[0.571789, 0.644474, 1.26234, 0.830062, 0.511626, 0.321406, -0.267345, 0.83323, …] shape [2, 3, 16] · 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/attention-2.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