log_sum_exp
log_sum_exp: 10 implementations from 12 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:
- 1 more implementation of this name was examined but did not run on the shared input (RuntimeError 1).
- 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 3: arg 1: rank 2, kind float, dtype float32
8 implementations from 10 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) | Members | Shared output on this bucket's input |
|---|---|---|
| 5 implementations 6 papers 5e734a878a04 recorded values identical |
modules/vae.py 5efe6eb2 recorded value:2/float/float32; dim=1, keepdim=False i2l/networks/discriminator_model.py 5e054416 recorded value:2/float/float32; dim=1, keepdim=False layers/modules/multibox_loss_gmm.py 99c65fd4 recorded x:2/float/float32 code/models.py a42f23f7 recorded x:2/float/float32 k+1_gan.py ed2c8f94 recorded x:2/float/float32; axis=1 |
[2.43739, 2.91498, 2.08147, 2.48663] shape [4] · float32 · Tensor |
| 2 implementations 4 papers 88436f094ddc recorded values identical |
src/model.py d4329236 recorded smat:2/float/float32 src/model.py bd9ad747 recorded tensor:2/float/float32; dim=0, keepdim=False |
[2.22632, 1.51838, 1.85554, 1.42119, 0.886227, 2.66979, 0.675072, 1.90715] shape [8] · float32 · Tensor |
| 1 implementation 1 paper 325a49dd5d3d |
src/LSTM-CNNs-CRF/model.py ca4d0de3 recorded input:2/float/float32; keepdim=False |
[2.43739, 2.3955, 2.90042, 3.01504, 2.95688, 2.91498, 3.4199, 3.53452, …] shape [4, 4] · float32 · Tensor |
Bucket 2 of 3: arg 1: rank 2, kind float, dtype float32 · arg 2: 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) | Members | Shared output on this bucket's input |
|---|---|---|
| 1 implementation 1 paper 4a41174115ce |
pytorch_generation/CIFAR_NRF_supervised.py 79526833 recorded logits:2/float/float32, mask:2/float/float32; inf=10000000.0 |
[8.02629e+06, 1.32211e+07, -163257, 2.74218e+06] shape [4] · float32 · Tensor |
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) | Members | Shared output on this bucket's input |
|---|---|---|
| 1 implementation 1 paper c6140b78c69e |
mi_estimators.py a1572564 recorded value:3/float/float32; dim=1, keepdim=False |
[2.26966, 2.23923, 0.7411, 1.42071, 1.47988, 2.03071, 1.08024, 2.40372, …] shape [2, 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/log-sum-exp.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