get_entropy
get_entropy: 7 implementations from 7 papers ran on one shared input (census 2026-09-22, battery b986f7e04d79); they produced 7 distinct outputs across 2 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:
- Every examined implementation of this name that took an array argument ran on the shared input.
- 2 more implementations from 2 papers took no array argument and ran only on their own fixture arguments; no shared input existed for them, so they are not compared (on 2 the recorded shared-output digest is the own-fixture digest).
- Every compared output was digested.
Bucket 1 of 2: arg 1: rank 2, kind float, dtype float32
6 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); 6 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 |
train_yahoo_dataset.py cd0eee90 recorded probs:2/float/float32 |
[nan] shape [] · float32 · Tensor · non-finite |
| 1 implementation 1 paper 74999fd28ab1 |
attribution/mask.py bed3944a recorded saliency:2/float/float32; ids_time=[0, 2], ids_feature=[1, 3], normalize=True, eps=1e-05 |
[nan] shape [] · float64 · float · non-finite |
| 1 implementation 1 paper 7e5824d63f9f |
loss.py b5e4e66a recorded outputs:2/float/float32 |
[1.62273] shape [] · float32 · Tensor |
| 1 implementation 1 paper 947540360b0c |
pouf_lvm/examples/pouf/image_classification/pouf.py a7625322 recorded input_:2/float/float32 |
[nan, nan, nan, nan] shape [4] · float32 · Tensor · non-finite |
| 1 implementation 1 paper ad823c471dd5 |
hypergan_utils.py 410618de recorded mean:2/float/float32 |
[-inf, -inf, -inf, -inf] shape [4] · float32 · ndarray · non-finite |
| 1 implementation 1 paper e0770880d670 |
dime/cmi_estimator.py af280a71 recorded pred:2/float/float32 |
[1.47929, 1.45738, 1.82225, 1.73198] shape [4] · float32 · Tensor |
Bucket 2 of 2: 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) | Members | Shared output on this bucket's input |
|---|---|---|
| 1 implementation 1 paper 5681d12a7b45 |
utils/solvers.py c11ef229 recorded counts_vec:2/int/int64; ret_var=False, pop_size=None, n=None |
[1.84462, 1.86199, 1.32966, 2.00393] shape [4] · float64 · ndarray |
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/get-entropy.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