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get_timestep_embedding

Syntologyfunction-name censuscensus 2026-09-22battery b986f7e04d79all samples with this name

get_timestep_embedding: 11 implementations from 15 papers ran on one shared input (census 2026-09-22, battery b986f7e04d79); they produced 5 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:

Bucket 1 of 2: arg 1: rank 1, kind int, dtype int64

9 implementations from 13 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)MembersShared output on this bucket's input
5 implementations
9 papers
3f9eb471628a
recorded values identical
one code sha held from 5 papers' repositories
papers/Conditional_Schrodinger_Bridge_Imputation/models/DGLSB/dglsb.py cb49209c
recorded timesteps:1/int/int64; embedding_dim=4

experiments/ddpm/ddpm/models/deepcache_diffusion.py 3ee5b366
recorded timesteps:1/int/int64; embedding_dim=4

models/unet_models.py 5bed1adc
recorded timesteps:1/int/int64; embedding_dim=4

diffusion/models/ddpm_arch/sige_fused_unet.py b8dedf14
recorded timesteps:1/int/int64; embedding_dim=4

models/unet.py e3f5c3d2
recorded timesteps:1/int/int64; embedding_dim=4
[0.909297, 0.0002, -0.416147, 1, 0.841471, 0.0001, 0.540302, 1, …]
shape [8, 4] · float32 · Tensor
2 implementations
2 papers
938fec0031e5
recorded values identical

pipeline.py 0df38640
recorded timesteps:1/int/int64; embedding_dim=8

opencood/models/gencomm_modules/cond_diff.py b77c7549
recorded timesteps:1/int/int64; embedding_dim=8
[0.909297, 0.0926985, 0.00430886, 0.0002, -0.416147, 0.995694, 0.999991, 1, …]
shape [8, 8] · float32 · Tensor
1 implementation
1 paper
70f8342d38b2

sample.py f9a074c3
recorded timesteps:1/int/int64; embedding_dim=4, downscale_freq_shift=0.0, max_period=10000
[0.909297, 0.0199987, -0.416147, 0.9998, 0.841471, 0.00999983, 0.540302, 0.99995, …]
shape [8, 4] · float32 · Tensor
1 implementation
1 paper
ace22b357558

model.py 8426c417
recorded timesteps:1/int/int64; embedding_dim=8, max_period=10000
[0.909297, 0.198669, 0.0199987, 0.002, -0.416147, 0.980067, 0.9998, 0.999998, …]
shape [8, 8] · float32 · Tensor

Bucket 2 of 2: arg 1: rank 1, kind float, dtype float32

2 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); 1 distinct output, largest cluster first. Values are the first 8 of the recorded output, flattened.

Cluster (same digest to six decimals)MembersShared output on this bucket's input
2 implementations
2 papers
21039c3853b8
recorded values identical

model/TPDM/diffusion.py 93dc2a74
recorded timesteps:1/float/float32; embedding_dim=4, flip_sin_to_cos=False, downscale_freq_shift=1.0, scale=1.0, max_period=10000

toy_example.py f3cf5a0b
recorded timesteps:1/float/float32; embedding_dim=4, dtype=torch.float32, max_time=1000.0
[-0.785738, -9.03889e-05, 0.618559, 1, 0.156486, 1.57131e-05, 0.98768, 1, …]
shape [8, 4] · 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/get-timestep-embedding.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