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contrastive_loss
contrastive_loss: 11 implementations from 18 papers ran on one shared input (census 2026-09-22, battery b986f7e04d79); they produced 7 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:
- 7 more implementations of this name were examined but did not run on the shared input (RuntimeError 4, AssertionError 1, IndexError 1, ValueError 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
6 implementations from 12 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 |
|---|---|---|
| 5 implementations 11 papers c4f8f09479c1 recorded values identical |
CLIP-ViP/src/modeling/CLIP_ViP.py 4675779a recorded logits:2/float/float32 one code sha held from 2 papers' repositories M2PT/model/llava_archPT.py 35caa662 recorded logits:2/float/float32
LLaVA/llava/model/language_model/llava_llama.py 83ada93f recorded logits:2/float/float32
MarT/models/modeling_clip.py f2e5f286 recorded logits:2/float/float32 fgclip2/model/strcs/fgclip2.py 54554dd5 recorded logits:2/float/float32 |
[1.42727] shape [] · float32 · Tensor |
| 1 implementation 1 paper 7891d656fa5f |
src/transformers/models/align/modeling_align.py d1d7fb60 recorded logits:2/float/float32 |
[1.54175] shape [] · float32 · Tensor |
Bucket 2 of 3: arg 1: rank 2, kind float, dtype float32 · arg 2: rank 2, 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 2399fcd7f479 |
model/model.py e5fdec8e recorded z_t:2/float/float32, z_f:2/float/float32; tau=0.1 |
[nan] shape [] · float32 · Tensor · non-finite |
| 1 implementation 1 paper 272f78036db6 |
utils/pair_selection_util.py a0ad7c05 recorded f_emb:2/float/float32, v_emb:2/float/float32; margin=1.0, tau=0.5 |
[0.25] shape [] · float32 · Tensor |
| 1 implementation 1 paper 570d68f10e57 |
methods/contrastive.py ba00312b recorded x0:2/float/float32, x1:2/float/float32; tau=0.07, norm=True |
[0.0234837] shape [] · float32 · Tensor |
| 1 implementation 1 paper 7207fa2607ab |
dual_ae_trainer.py 7567a11b recorded z_audio:2/float/float32, z_tag:2/float/float32; t=0.5 |
[0.730524] shape [] · float32 · Tensor |
Bucket 3 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 · arg 4: rank 3, kind float, dtype float32
1 implementation 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); 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 2 papers 74999fd28ab1 |
hete/model.py bd248e25 recorded projected_emd:3/float/float32, v_emd:3/float/float32, sampled_embeddings_u:3/float/float32, sampled_embeddings_neg_v:3/float/float32; tau=0.1, lambda_loss=1.0 |
[nan] shape [] · float32 · Tensor · non-finite |
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/contrastive-loss.json.
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