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MultiHeadAttention
MultiHeadAttention: 9 implementations from 7 papers ran on one shared input (census 2026-09-22, battery b986f7e04d79); they produced 9 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:
- 10 more implementations of this name were examined but did not run on the shared input (RuntimeError 8, AssertionError 2).
- 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.
- 9 compared members are class-bearing (tagged class): the class was constructed with seeded weights in evaluation mode and then called, so its recorded output depends on that initialisation as well as on the forward computation.
Bucket 1 of 3: arg 1: rank 3, kind float, dtype float32 · arg 2: rank 3, kind float, dtype float32 · arg 3: rank 3, kind float, dtype float32
4 implementations from 4 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) | Members | Shared output on this bucket's input |
|---|---|---|
| 1 implementation 1 paper 0cabec910b03 |
libfewshot_core/model/metric/feat.py abb0132a recorded q:3/float/float32, k:3/float/float32, v:3/float/float32 |
[-1.26393, 1.92103, -0.729993, 0.608796, 0.419665, -0.96795, 0.595852, -0.583477, …] shape [2, 4, 8] · float32 · Tensor |
| 1 implementation 1 paper 58fd5c1158b2 |
class src/nlp/layers/encoder.py 9c478f15 recorded q:3/float/float32, k:3/float/float32, v:3/float/float32; mask=None |
[-0, 1.32319, -1.21911, -0, 0.189581, -0.886993, -0.304486, 0, …] shape [2, 4, 8] · float32 · Tensor |
| 1 implementation 1 paper b47c72b25d74 |
class summarizer_transformer.py db4e1c41 recorded q:3/float/float32, k:3/float/float32, v:3/float/float32; mask=False, cover=None |
[0.035665, -0.413472, -0.177767, -0.208916, 0.23824, 0.435368, 0.0700511, 0.0641225, …] shape [2, 4, 8] · float32 · Tensor |
| 1 implementation 1 paper f1e879c2058d |
class bpp/model.py 337e5971 recorded query:3/float/float32, key:3/float/float32, value:3/float/float32; mask=None |
[0.240397, -0.0802591, -0.205289, 0.0541918, -0.292073, 0.605929, -0.417172, -0.00929932, …] shape [2, 4, 8] · float32 · Tensor |
Bucket 2 of 3: arg 1: rank 3, kind float, dtype float32
4 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); 4 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 4dfb8cb5987d |
class models/mae.py f6a1ed2d recorded x:3/float/float32 |
[0.534887, 0.247349, 0.471544, -0.00193934, -0.292215, -0.146134, 0.290468, -0.0427631, …] shape [2, 4, 8] · float32 · Tensor |
| 1 implementation 1 paper 57f8a2a43047 |
class mobileclip/clip.py 88f8bcf4 recorded x_q:3/float/float32; x_kv=None, key_padding_mask=None, attn_mask=None |
[-0.0803661, -0.117569, -0.0700971, 0.24619, 0.236701, 0.305764, -0.00580824, 0.411263, …] shape [2, 4, 8] · float32 · Tensor |
| 1 implementation 1 paper a8d86eb7e123 |
class vision_transformer.py 6082f915 recorded x:3/float/float32 |
[-0.171513, 0.542943, -0.0983858, -0.315013, 0.1322, 0.576283, -0.350209, 1.13742, …] shape [2, 4, 8] · float32 · Tensor |
| 1 implementation 1 paper c60576142d8a |
class src/ViT.py 6bad9911 recorded x:3/float/float32 |
[0.18117, -0.0366058, -0.364896, 0.00403607, -0.253827, 0.626424, -0.379873, -0.0199547, …] shape [2, 4, 8] · float32 · Tensor |
Bucket 3 of 3: arg 1: rank 3, kind float, dtype float32 · arg 2: 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) | Members | Shared output on this bucket's input |
|---|---|---|
| 1 implementation 1 paper 8132fe143af3 |
class nets/attention_model.py 3e9c7f43 recorded q:3/float/float32, h:3/float/float32; mask=None |
[0.149484, 0.172254, -0.103393, 0.0170991, -0.14438, -0.105019, 0.102146, -0.14146, …] shape [2, 4, 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/multiheadattention.json.
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