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timestep_embedding
timestep_embedding: 22 implementations from 27 papers ran on one shared input (census 2026-09-22, battery b986f7e04d79); they produced 6 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:
- 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 2: arg 1: rank 1, kind float, dtype float32
13 implementations from 17 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 |
|---|---|---|
| 10 implementations 13 papers cddd37cd7c51 recorded values identical |
libs/uvit.py 262b18d8 recorded timesteps:1/float/float32; dim=4, max_period=10000
see2sound/codi/models/latent_diffusion/diffusion_unet.py 7e83c65f recorded timesteps:1/float/float32; dim=4, max_period=10000, repeat_only=False hyvideo/modules/models.py 1919bf55 recorded t:1/float/float32; dim=4, max_period=10000
models/unet.py 1b261a79 recorded timesteps:1/float/float32; dim=4, max_period=10000, repeat_only=False
model/BrownianBridge/BrownianBridgeModel_c2v.py 1d718716 recorded timesteps:1/float/float32; dim=4, max_period=10000, repeat_only=False model/RecModel.py 59afc50c recorded timesteps:1/float/float32; dim=4, device='cpu', max_period=10000
JGA-LBD/DDBM/ddbm/unet3d.py 6b0b644d recorded timesteps:1/float/float32; dim=4, max_period=10000, dtype=torch.float32 model/big_unet.py b0aa348a recorded timesteps:1/float/float32; dim=4, max_period=10000 model/networks/diffusion_networks/sg_diff.py b4f50214 recorded timesteps:1/float/float32; dim=4, max_period=10000, repeat_only=False
models/amfd_loss.py ecd79b71 recorded t:1/float/float32; dim=4, max_period=10000, time_factor=1.0 |
[0.618559, 0.999959, -0.785738, -0.00903877, 0.98768, 0.999999, 0.156486, 0.00157131, …] shape [8, 4] · float32 · Tensor |
| 2 implementations 2 papers d1b6df964f7a recorded values identical |
pretrained_diffusion/unet.py a4255e26 recorded timesteps:1/float/float32; dim=8, max_period=10000, dtype=torch.float32 Protein/codes/nn/models.py df97c543 recorded timesteps:1/float/float32; dim=8, max_period=10000 |
[0.618559, 0.995918, 0.999959, 1, -0.785738, -0.0902659, -0.00903877, -0.000903889, …] shape [8, 8] · float32 · Tensor |
| 1 implementation 2 papers a4027afbb776 |
library/flux_models.py 0a1aadb0 recorded t:1/float/float32; dim=4, max_period=10000, time_factor=1000.0 |
[0.62964, -0.926465, 0.776887, -0.376382, 0.998657, -0.000518366, 0.0518138, 1, …] shape [8, 4] · float32 · Tensor |
Bucket 2 of 2: arg 1: rank 1, kind int, dtype int64
9 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); 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 |
|---|---|---|
| 7 implementations 11 papers 5bee047eaa31 recorded values identical |
libs/uvit.py b494dd29 recorded timesteps:1/int/int64; dim=4, max_period=10000
src/models/polygon_models/polygon_net.py 12d88e58 recorded timesteps:1/int/int64; dim=4, max_period=10000 one code sha held from 2 papers' repositories models/uvit.py 270cd726 recorded timesteps:1/int/int64; dim=4, max_period=10000 model.py 226b182e recorded t:1/int/int64; dim=4, max_period=10000 ddpm/unet.py 8ceaa69a recorded timesteps:1/int/int64; dim=4, max_period=10000 cldm/cldm.py 9df11570 recorded timesteps:1/int/int64; dim=4, max_period=10000, repeat_only=False
utils/models/mono.py dd00f566 recorded timesteps:1/int/int64; dim=4, max_period=10000 |
[-0.416147, 0.9998, 0.909297, 0.0199987, 0.540302, 0.99995, 0.841471, 0.00999983, …] shape [8, 4] · float32 · Tensor |
| 1 implementation 1 paper 3f9eb471628a |
mr_traj/models.py 61ee83ed recorded timesteps:1/int/int64; dim=4 |
[0.909297, 0.0002, -0.416147, 1, 0.841471, 0.0001, 0.540302, 1, …] shape [8, 4] · float32 · Tensor |
| 1 implementation 1 paper e0a454ec42c0 |
model.py 88867f4d recorded timesteps:1/int/int64; dim=8, max_period=10000 |
[-0.416147, 0.980067, 0.9998, 0.999998, 0.909297, 0.198669, 0.0199987, 0.002, …] shape [8, 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/timestep-embedding.json.
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