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Issue 529: Create null Latent model #530

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merged 4 commits into from
Nov 20, 2024
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SamuelBrand1
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This small PR closes #529 .

This PR contributes a Null struct which defines the concept of having a nothing latent process. This is useful to reusing patterns that we already have (e.g. EpiProblem) in situations where we don't actually want a latent process.

Potentially it might be better to sequence this to after resolving #525 , because like the ODE parameter objects this not a naturally indexable latent model.

@SamuelBrand1 SamuelBrand1 linked an issue Nov 20, 2024 that may be closed by this pull request
@SamuelBrand1 SamuelBrand1 requested a review from seabbs November 20, 2024 11:07
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Try this Pull Request!

Open Julia and type:

import Pkg
Pkg.activate(temp=true)
Pkg.add(url="https://github.com/CDCgov/Rt-without-renewal", rev="529-create-nulllatentmodel", subdir="EpiAware")
using EpiAware

@seabbs seabbs force-pushed the 529-create-nulllatentmodel branch from 68f1b29 to ee2f565 Compare November 20, 2024 11:08
@seabbs seabbs enabled auto-merge November 20, 2024 11:08
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seabbs commented Nov 20, 2024

I think this is fine to go in for now. Noting that we only need this whilst we take Z_t as an input and once that is shifted to be model internal we should no longer need this and can remove?

seabbs
seabbs previously approved these changes Nov 20, 2024
@SamuelBrand1
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I think this is fine to go in for now. Noting that we only need this whilst we take Z_t as an input and once that is shifted to be model internal we should no longer need this and can remove?

Yes, hard to imagine we'll need this with a suitably flexible interface.

@SamuelBrand1 SamuelBrand1 requested a review from seabbs November 20, 2024 11:19
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Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 90.54%. Comparing base (7fd98c8) to head (564e574).

Additional details and impacted files
@@            Coverage Diff             @@
##             main     #530      +/-   ##
==========================================
+ Coverage   90.51%   90.54%   +0.03%     
==========================================
  Files          56       57       +1     
  Lines         822      825       +3     
==========================================
+ Hits          744      747       +3     
  Misses         78       78              

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.


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Benchmark result

Judge result

Benchmark Report for /home/runner/work/Rt-without-renewal/Rt-without-renewal

Job Properties

  • Time of benchmarks:
    • Target: 20 Nov 2024 - 11:57
    • Baseline: 20 Nov 2024 - 12:31
  • Package commits:
    • Target: 28fd4c
    • Baseline: 7fd98c
  • Julia commits:
    • Target: 8f5b7c
    • Baseline: 8f5b7c
  • Julia command flags:
    • Target: None
    • Baseline: None
  • Environment variables:
    • Target: None
    • Baseline: None

Results

A ratio greater than 1.0 denotes a possible regression (marked with ❌), while a ratio less
than 1.0 denotes a possible improvement (marked with ✅). Only significant results - results
that indicate possible regressions or improvements - are shown below (thus, an empty table means that all
benchmark results remained invariant between builds).

ID time ratio memory ratio
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 0.94 (5%) ✅ 1.00 (1%)
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 0.94 (5%) ✅ 1.00 (1%)
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.06 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.07 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.05 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.07 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.07 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.06 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.06 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.06 (5%) ❌ 1.00 (1%)
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.08 (5%) ❌ 1.00 (1%)
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.05 (5%) ❌ 1.00 (1%)
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.06 (5%) ❌ 1.00 (1%)
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.06 (5%) ❌ 1.00 (1%)

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["EpiAwareUtils"]
  • ["EpiInfModels", "DirectInfections", "evaluation"]
  • ["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiInfModels", "ExpGrowthRate", "evaluation"]
  • ["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "AR", "evaluation"]
  • ["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "BroadcastLatentModel", "evaluation"]
  • ["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "CombineLatentModels", "evaluation"]
  • ["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "ConcatLatentModels", "evaluation"]
  • ["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "DiffLatentModel", "evaluation"]
  • ["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "HierarchicalNormal", "evaluation"]
  • ["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "Intercept", "evaluation"]
  • ["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "PrefixLatentModel", "evaluation"]
  • ["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "RandomWalk", "evaluation"]
  • ["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "RecordExpectedLatent", "evaluation"]
  • ["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "TransformLatentModel", "evaluation"]
  • ["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "broadcast_dayofweek", "evaluation"]
  • ["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "broadcast_weekly", "evaluation"]
  • ["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "Ascertainment", "evaluation"]
  • ["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "LatentDelay", "evaluation"]
  • ["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "NegativeBinomialError", "evaluation"]
  • ["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "PoissonError", "evaluation"]
  • ["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "PrefixObservationModel", "evaluation"]
  • ["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "RecordExpectedObs", "evaluation"]
  • ["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "StackObservationModels", "evaluation"]
  • ["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "TransformObservationModel", "evaluation"]
  • ["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "ascertainment_dayofweek", "evaluation"]
  • ["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "observation_error", "missing obs", "evaluation"]
  • ["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "observation_error", "no missing obs", "evaluation"]
  • ["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "observation_error", "partially missing obs", "evaluation"]
  • ["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]

Julia versioninfo

Target

Julia Version 1.11.1
Commit 8f5b7ca12ad (2024-10-16 10:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 22.04.5 LTS
  uname: Linux 6.5.0-1025-azure #26~22.04.1-Ubuntu SMP Thu Jul 11 22:33:04 UTC 2024 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      10362 s          0 s        761 s      17005 s          0 s
       #2     0 MHz      10262 s          0 s        764 s      17091 s          0 s
       #3     0 MHz      10067 s          0 s        735 s      17334 s          0 s
       #4     0 MHz      10018 s          0 s        775 s      17343 s          0 s
  Memory: 15.606491088867188 GB (12863.53515625 MB free)
  Uptime: 2820.22 sec
  Load Avg:  1.07  1.04  1.13
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Baseline

Julia Version 1.11.1
Commit 8f5b7ca12ad (2024-10-16 10:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 22.04.5 LTS
  uname: Linux 6.5.0-1025-azure #26~22.04.1-Ubuntu SMP Thu Jul 11 22:33:04 UTC 2024 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      15716 s          1 s       1214 s      31760 s          0 s
       #2     0 MHz      13588 s          0 s       1168 s      33923 s          0 s
       #3     0 MHz      15813 s          0 s       1168 s      31726 s          0 s
       #4     0 MHz      15345 s          1 s       1245 s      32116 s          0 s
  Memory: 15.606491088867188 GB (12579.63671875 MB free)
  Uptime: 4880.87 sec
  Load Avg:  1.07  1.06  1.04
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Target result

Benchmark Report for /home/runner/work/Rt-without-renewal/Rt-without-renewal

Job Properties

  • Time of benchmark: 20 Nov 2024 - 11:57
  • Package commit: 28fd4c
  • Julia commit: 8f5b7c
  • Julia command flags: None
  • Environment variables: None

Results

Below is a table of this job's results, obtained by running the benchmarks.
The values listed in the ID column have the structure [parent_group, child_group, ..., key], and can be used to
index into the BaseBenchmarks suite to retrieve the corresponding benchmarks.
The percentages accompanying time and memory values in the below table are noise tolerances. The "true"
time/memory value for a given benchmark is expected to fall within this percentage of the reported value.
An empty cell means that the value was zero.

ID time GC time memory allocations
["EpiAwareUtils", "censored_pmf"] 2.101 μs (5%) 416 bytes (1%) 10
["EpiInfModels", "DirectInfections", "evaluation", "linked"] 279.428 ns (5%) 464 bytes (1%) 10
["EpiInfModels", "DirectInfections", "evaluation", "standard"] 275.244 ns (5%) 464 bytes (1%) 10
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 427.131 ns (5%) 816 bytes (1%) 18
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 424.362 ns (5%) 816 bytes (1%) 18
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 10.219 μs (5%) 5.55 KiB (1%) 125
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 10.169 μs (5%) 5.55 KiB (1%) 125
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 501.814 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 512.249 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "ExpGrowthRate", "evaluation", "linked"] 184.534 ns (5%) 288 bytes (1%) 8
["EpiInfModels", "ExpGrowthRate", "evaluation", "standard"] 176.832 ns (5%) 288 bytes (1%) 8
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 274.070 ns (5%) 544 bytes (1%) 15
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 262.473 ns (5%) 544 bytes (1%) 15
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 9.998 μs (5%) 5.53 KiB (1%) 124
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 9.988 μs (5%) 5.53 KiB (1%) 124
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 499.180 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 496.056 ns (5%) 256 bytes (1%) 7
["EpiLatentModels", "AR", "evaluation", "linked"] 4.865 μs (5%) 4.19 KiB (1%) 91
["EpiLatentModels", "AR", "evaluation", "standard"] 4.507 μs (5%) 3.20 KiB (1%) 84
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 6.268 μs (5%) 12.20 KiB (1%) 108
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 5.731 μs (5%) 10.64 KiB (1%) 97
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 129.883 μs (5%) 54.25 KiB (1%) 1214
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 84.107 μs (5%) 39.95 KiB (1%) 884
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 18.775 μs (5%) 7.81 KiB (1%) 224
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 17.793 μs (5%) 6.69 KiB (1%) 188
["EpiLatentModels", "BroadcastLatentModel", "evaluation", "linked"] 943.529 ns (5%) 2.75 KiB (1%) 34
["EpiLatentModels", "BroadcastLatentModel", "evaluation", "standard"] 704.935 ns (5%) 1.88 KiB (1%) 30
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.329 μs (5%) 4.83 KiB (1%) 45
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.083 μs (5%) 3.95 KiB (1%) 41
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 48.992 μs (5%) 23.58 KiB (1%) 458
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 31.650 μs (5%) 16.50 KiB (1%) 350
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 3.100 μs (5%) 992 bytes (1%) 29
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 2.917 μs (5%) 992 bytes (1%) 29
["EpiLatentModels", "CombineLatentModels", "evaluation", "linked"] 22.031 μs (5%) 45.67 KiB (1%) 383
["EpiLatentModels", "CombineLatentModels", "evaluation", "standard"] 19.066 μs (5%) 31.16 KiB (1%) 339
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 49.993 μs (5%) 105.72 KiB (1%) 805
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 42.389 μs (5%) 75.84 KiB (1%) 709
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 163.014 μs (5%) 99.81 KiB (1%) 1574
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 112.179 μs (5%) 71.98 KiB (1%) 1207
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 19.096 μs (5%) 7.92 KiB (1%) 225
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 18.214 μs (5%) 6.80 KiB (1%) 189
["EpiLatentModels", "ConcatLatentModels", "evaluation", "linked"] 44.142 μs (5%) 37.27 KiB (1%) 496
["EpiLatentModels", "ConcatLatentModels", "evaluation", "standard"] 41.488 μs (5%) 28.83 KiB (1%) 466
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 45.455 μs (5%) 40.86 KiB (1%) 511
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 42.139 μs (5%) 32.42 KiB (1%) 481
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 123.480 μs (5%) 62.64 KiB (1%) 1012
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 100.457 μs (5%) 49.45 KiB (1%) 879
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.530 μs (5%) 2.06 KiB (1%) 51
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.373 μs (5%) 2.06 KiB (1%) 51
["EpiLatentModels", "DiffLatentModel", "evaluation", "linked"] 7.992 μs (5%) 5.55 KiB (1%) 102
["EpiLatentModels", "DiffLatentModel", "evaluation", "standard"] 7.494 μs (5%) 3.86 KiB (1%) 96
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 9.207 μs (5%) 13.92 KiB (1%) 115
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 8.686 μs (5%) 12.23 KiB (1%) 109
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 87.634 μs (5%) 39.58 KiB (1%) 824
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 67.626 μs (5%) 33.14 KiB (1%) 715
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 7.097 μs (5%) 2.12 KiB (1%) 50
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 6.853 μs (5%) 2.12 KiB (1%) 50
["EpiLatentModels", "HierarchicalNormal", "evaluation", "linked"] 392.256 ns (5%) 1.03 KiB (1%) 14
["EpiLatentModels", "HierarchicalNormal", "evaluation", "standard"] 297.833 ns (5%) 896 bytes (1%) 13
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.010 μs (5%) 5.12 KiB (1%) 23
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 927.700 ns (5%) 4.97 KiB (1%) 22
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 44.202 μs (5%) 19.03 KiB (1%) 381
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 28.774 μs (5%) 14.17 KiB (1%) 278
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.155 μs (5%) 608 bytes (1%) 9
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 963.800 ns (5%) 608 bytes (1%) 9
["EpiLatentModels", "Intercept", "evaluation", "linked"] 230.391 ns (5%) 400 bytes (1%) 10
["EpiLatentModels", "Intercept", "evaluation", "standard"] 207.333 ns (5%) 400 bytes (1%) 10
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 307.551 ns (5%) 704 bytes (1%) 17
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 296.849 ns (5%) 704 bytes (1%) 17
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 5.482 μs (5%) 3.62 KiB (1%) 87
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 5.482 μs (5%) 3.62 KiB (1%) 87
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 411.920 ns (5%) 208 bytes (1%) 4
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 414.270 ns (5%) 208 bytes (1%) 4
["EpiLatentModels", "PrefixLatentModel", "evaluation", "linked"] 1.818 μs (5%) 3.56 KiB (1%) 40
["EpiLatentModels", "PrefixLatentModel", "evaluation", "standard"] 1.629 μs (5%) 3.09 KiB (1%) 37
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.563 μs (5%) 7.66 KiB (1%) 49
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.378 μs (5%) 7.19 KiB (1%) 46
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 46.857 μs (5%) 21.42 KiB (1%) 406
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 31.699 μs (5%) 16.25 KiB (1%) 301
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.139 μs (5%) 608 bytes (1%) 9
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 965.519 ns (5%) 608 bytes (1%) 9
["EpiLatentModels", "RandomWalk", "evaluation", "linked"] 585.782 ns (5%) 1.72 KiB (1%) 21
["EpiLatentModels", "RandomWalk", "evaluation", "standard"] 446.569 ns (5%) 1.28 KiB (1%) 19
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.502 μs (5%) 8.11 KiB (1%) 32
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.325 μs (5%) 7.67 KiB (1%) 30
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 54.151 μs (5%) 25.47 KiB (1%) 501
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 37.119 μs (5%) 20.28 KiB (1%) 396
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 3.736 μs (5%) 1.28 KiB (1%) 29
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 3.543 μs (5%) 1.28 KiB (1%) 29
["EpiLatentModels", "RecordExpectedLatent", "evaluation", "linked"] 545.697 ns (5%) 1.25 KiB (1%) 20
["EpiLatentModels", "RecordExpectedLatent", "evaluation", "standard"] 416.558 ns (5%) 960 bytes (1%) 18
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 708.971 ns (5%) 1.78 KiB (1%) 29
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 569.828 ns (5%) 1.47 KiB (1%) 27
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 43.000 μs (5%) 18.31 KiB (1%) 387
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 28.483 μs (5%) 13.30 KiB (1%) 283
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.077 μs (5%) 352 bytes (1%) 9
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 877.463 ns (5%) 352 bytes (1%) 9
["EpiLatentModels", "TransformLatentModel", "evaluation", "linked"] 264.662 ns (5%) 448 bytes (1%) 12
["EpiLatentModels", "TransformLatentModel", "evaluation", "standard"] 255.285 ns (5%) 448 bytes (1%) 12
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 353.916 ns (5%) 768 bytes (1%) 19
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 347.069 ns (5%) 768 bytes (1%) 19
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 5.716 μs (5%) 3.93 KiB (1%) 95
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 5.721 μs (5%) 3.93 KiB (1%) 95
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 490.451 ns (5%) 160 bytes (1%) 4
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 483.403 ns (5%) 160 bytes (1%) 4
["EpiLatentModels", "broadcast_dayofweek", "evaluation", "linked"] 1.239 μs (5%) 3.73 KiB (1%) 43
["EpiLatentModels", "broadcast_dayofweek", "evaluation", "standard"] 917.344 ns (5%) 2.42 KiB (1%) 37
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.202 μs (5%) 9.80 KiB (1%) 54
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.791 μs (5%) 8.48 KiB (1%) 48
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 69.290 μs (5%) 34.64 KiB (1%) 699
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 51.917 μs (5%) 28.58 KiB (1%) 590
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.296 μs (5%) 1.19 KiB (1%) 29
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.176 μs (5%) 1.19 KiB (1%) 29
["EpiLatentModels", "broadcast_weekly", "evaluation", "linked"] 8.482 μs (5%) 5.78 KiB (1%) 113
["EpiLatentModels", "broadcast_weekly", "evaluation", "standard"] 7.707 μs (5%) 3.95 KiB (1%) 103
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 8.826 μs (5%) 8.98 KiB (1%) 130
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 8.319 μs (5%) 6.83 KiB (1%) 116
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 104.806 μs (5%) 42.11 KiB (1%) 852
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 64.891 μs (5%) 29.47 KiB (1%) 599
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.717 μs (5%) 1.69 KiB (1%) 48
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.110 μs (5%) 1.56 KiB (1%) 44
["EpiObsModels", "Ascertainment", "evaluation", "linked"] 3.336 μs (5%) 3.58 KiB (1%) 63
["EpiObsModels", "Ascertainment", "evaluation", "standard"] 3.264 μs (5%) 3.58 KiB (1%) 63
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 4.060 μs (5%) 3.92 KiB (1%) 72
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 4.016 μs (5%) 3.92 KiB (1%) 72
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 78.045 μs (5%) 38.77 KiB (1%) 918
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 61.776 μs (5%) 34.02 KiB (1%) 815
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.821 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.729 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "LatentDelay", "evaluation", "linked"] 14.367 μs (5%) 22.08 KiB (1%) 412
["EpiObsModels", "LatentDelay", "evaluation", "standard"] 14.376 μs (5%) 22.08 KiB (1%) 412
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 17.934 μs (5%) 22.30 KiB (1%) 419
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 17.964 μs (5%) 22.30 KiB (1%) 419
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 539.097 μs (5%) 293.05 KiB (1%) 7011
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 520.111 μs (5%) 288.30 KiB (1%) 6908
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 51.847 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 51.656 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "NegativeBinomialError", "evaluation", "linked"] 1.158 μs (5%) 400 bytes (1%) 10
["EpiObsModels", "NegativeBinomialError", "evaluation", "standard"] 1.117 μs (5%) 400 bytes (1%) 10
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.709 μs (5%) 624 bytes (1%) 17
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.570 μs (5%) 624 bytes (1%) 17
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 72.615 μs (5%) 35.95 KiB (1%) 903
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 57.878 μs (5%) 31.20 KiB (1%) 800
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.908 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.757 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "PoissonError", "evaluation", "linked"] 1.339 μs (5%) 1.83 KiB (1%) 30
["EpiObsModels", "PoissonError", "evaluation", "standard"] 1.004 μs (5%) 1.47 KiB (1%) 26
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 3.142 μs (5%) 7.78 KiB (1%) 43
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.423 μs (5%) 4.70 KiB (1%) 35
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 166.530 μs (5%) 86.44 KiB (1%) 1870
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 46.367 μs (5%) 29.38 KiB (1%) 727
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.468 μs (5%) 176 bytes (1%) 3
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 4.371 μs (5%) 176 bytes (1%) 3
["EpiObsModels", "PrefixObservationModel", "evaluation", "linked"] 1.690 μs (5%) 1.56 KiB (1%) 34
["EpiObsModels", "PrefixObservationModel", "evaluation", "standard"] 1.617 μs (5%) 1.56 KiB (1%) 34
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.829 μs (5%) 1.78 KiB (1%) 41
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.746 μs (5%) 1.78 KiB (1%) 41
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 27.341 μs (5%) 12.59 KiB (1%) 290
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 13.495 μs (5%) 7.84 KiB (1%) 187
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.127 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 978.286 ns (5%) 96 bytes (1%) 3
["EpiObsModels", "RecordExpectedObs", "evaluation", "linked"] 785.330 ns (5%) 480 bytes (1%) 14
["EpiObsModels", "RecordExpectedObs", "evaluation", "standard"] 743.441 ns (5%) 480 bytes (1%) 14
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.064 μs (5%) 704 bytes (1%) 21
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.016 μs (5%) 704 bytes (1%) 21
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 46.747 μs (5%) 22.98 KiB (1%) 537
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 32.541 μs (5%) 18.23 KiB (1%) 434
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 3.239 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 3.048 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "StackObservationModels", "evaluation", "linked"] 6.731 μs (5%) 5.81 KiB (1%) 117
["EpiObsModels", "StackObservationModels", "evaluation", "standard"] 6.604 μs (5%) 5.81 KiB (1%) 117
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 7.562 μs (5%) 6.16 KiB (1%) 126
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 7.414 μs (5%) 6.16 KiB (1%) 126
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 90.479 μs (5%) 49.09 KiB (1%) 1044
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 72.486 μs (5%) 44.34 KiB (1%) 941
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.334 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 6.190 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "TransformObservationModel", "evaluation", "linked"] 1.424 μs (5%) 672 bytes (1%) 16
["EpiObsModels", "TransformObservationModel", "evaluation", "standard"] 1.382 μs (5%) 672 bytes (1%) 16
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.897 μs (5%) 896 bytes (1%) 23
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.814 μs (5%) 896 bytes (1%) 23
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 73.627 μs (5%) 35.59 KiB (1%) 869
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 58.950 μs (5%) 30.84 KiB (1%) 766
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.791 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.614 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "ascertainment_dayofweek", "evaluation", "linked"] 4.131 μs (5%) 9.09 KiB (1%) 100
["EpiObsModels", "ascertainment_dayofweek", "evaluation", "standard"] 3.688 μs (5%) 7.84 KiB (1%) 92
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 5.953 μs (5%) 16.22 KiB (1%) 111
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 5.454 μs (5%) 14.97 KiB (1%) 103
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 108.402 μs (5%) 59.83 KiB (1%) 1164
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 89.147 μs (5%) 53.88 KiB (1%) 1054
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.575 μs (5%) 496 bytes (1%) 9
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.520 μs (5%) 496 bytes (1%) 9
["EpiObsModels", "observation_error", "missing obs", "evaluation", "linked"] 1.380 μs (5%) 3.05 KiB (1%) 38
["EpiObsModels", "observation_error", "missing obs", "evaluation", "standard"] 890.556 ns (5%) 1.48 KiB (1%) 28
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.811 μs (5%) 4.11 KiB (1%) 48
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.253 μs (5%) 2.55 KiB (1%) 38
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 40.846 μs (5%) 25.78 KiB (1%) 533
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 24.055 μs (5%) 18.80 KiB (1%) 401
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.245 μs (5%) 144 bytes (1%) 3
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 2.022 μs (5%) 144 bytes (1%) 3
["EpiObsModels", "observation_error", "no missing obs", "evaluation", "linked"] 446.692 ns (5%) 352 bytes (1%) 10
["EpiObsModels", "observation_error", "no missing obs", "evaluation", "standard"] 375.361 ns (5%) 352 bytes (1%) 10
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 548.049 ns (5%) 576 bytes (1%) 17
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 484.716 ns (5%) 576 bytes (1%) 17
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 33.432 μs (5%) 19.64 KiB (1%) 446
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 18.565 μs (5%) 14.22 KiB (1%) 324
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.912 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.645 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "observation_error", "partially missing obs", "evaluation", "linked"] 27.531 μs (5%) 3.02 KiB (1%) 64
["EpiObsModels", "observation_error", "partially missing obs", "evaluation", "standard"] 27.271 μs (5%) 2.70 KiB (1%) 62
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 19.636 μs (5%) 2.73 KiB (1%) 51
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 19.356 μs (5%) 2.42 KiB (1%) 49
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 63.839 μs (5%) 26.11 KiB (1%) 555
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 43.421 μs (5%) 20.38 KiB (1%) 431
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.242 μs (5%) 112 bytes (1%) 3
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 2.042 μs (5%) 112 bytes (1%) 3

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["EpiAwareUtils"]
  • ["EpiInfModels", "DirectInfections", "evaluation"]
  • ["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiInfModels", "ExpGrowthRate", "evaluation"]
  • ["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "AR", "evaluation"]
  • ["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "BroadcastLatentModel", "evaluation"]
  • ["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "CombineLatentModels", "evaluation"]
  • ["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "ConcatLatentModels", "evaluation"]
  • ["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "DiffLatentModel", "evaluation"]
  • ["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "HierarchicalNormal", "evaluation"]
  • ["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "Intercept", "evaluation"]
  • ["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "PrefixLatentModel", "evaluation"]
  • ["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "RandomWalk", "evaluation"]
  • ["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "RecordExpectedLatent", "evaluation"]
  • ["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "TransformLatentModel", "evaluation"]
  • ["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "broadcast_dayofweek", "evaluation"]
  • ["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "broadcast_weekly", "evaluation"]
  • ["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "Ascertainment", "evaluation"]
  • ["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "LatentDelay", "evaluation"]
  • ["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "NegativeBinomialError", "evaluation"]
  • ["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "PoissonError", "evaluation"]
  • ["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "PrefixObservationModel", "evaluation"]
  • ["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "RecordExpectedObs", "evaluation"]
  • ["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "StackObservationModels", "evaluation"]
  • ["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "TransformObservationModel", "evaluation"]
  • ["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "ascertainment_dayofweek", "evaluation"]
  • ["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "observation_error", "missing obs", "evaluation"]
  • ["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "observation_error", "no missing obs", "evaluation"]
  • ["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "observation_error", "partially missing obs", "evaluation"]
  • ["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]

Julia versioninfo

Julia Version 1.11.1
Commit 8f5b7ca12ad (2024-10-16 10:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 22.04.5 LTS
  uname: Linux 6.5.0-1025-azure #26~22.04.1-Ubuntu SMP Thu Jul 11 22:33:04 UTC 2024 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      10362 s          0 s        761 s      17005 s          0 s
       #2     0 MHz      10262 s          0 s        764 s      17091 s          0 s
       #3     0 MHz      10067 s          0 s        735 s      17334 s          0 s
       #4     0 MHz      10018 s          0 s        775 s      17343 s          0 s
  Memory: 15.606491088867188 GB (12863.53515625 MB free)
  Uptime: 2820.22 sec
  Load Avg:  1.07  1.04  1.13
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Baseline result

Benchmark Report for /home/runner/work/Rt-without-renewal/Rt-without-renewal

Job Properties

  • Time of benchmark: 20 Nov 2024 - 12:31
  • Package commit: 7fd98c
  • Julia commit: 8f5b7c
  • Julia command flags: None
  • Environment variables: None

Results

Below is a table of this job's results, obtained by running the benchmarks.
The values listed in the ID column have the structure [parent_group, child_group, ..., key], and can be used to
index into the BaseBenchmarks suite to retrieve the corresponding benchmarks.
The percentages accompanying time and memory values in the below table are noise tolerances. The "true"
time/memory value for a given benchmark is expected to fall within this percentage of the reported value.
An empty cell means that the value was zero.

ID time GC time memory allocations
["EpiAwareUtils", "censored_pmf"] 2.104 μs (5%) 416 bytes (1%) 10
["EpiInfModels", "DirectInfections", "evaluation", "linked"] 282.262 ns (5%) 464 bytes (1%) 10
["EpiInfModels", "DirectInfections", "evaluation", "standard"] 280.698 ns (5%) 464 bytes (1%) 10
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 409.015 ns (5%) 816 bytes (1%) 18
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 404.205 ns (5%) 816 bytes (1%) 18
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 10.409 μs (5%) 5.55 KiB (1%) 125
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 10.379 μs (5%) 5.55 KiB (1%) 125
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 478.268 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 496.438 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "ExpGrowthRate", "evaluation", "linked"] 182.646 ns (5%) 288 bytes (1%) 8
["EpiInfModels", "ExpGrowthRate", "evaluation", "standard"] 176.956 ns (5%) 288 bytes (1%) 8
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 270.472 ns (5%) 544 bytes (1%) 15
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 264.018 ns (5%) 544 bytes (1%) 15
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 10.299 μs (5%) 5.53 KiB (1%) 124
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 10.259 μs (5%) 5.53 KiB (1%) 124
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 503.585 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 499.232 ns (5%) 256 bytes (1%) 7
["EpiLatentModels", "AR", "evaluation", "linked"] 4.859 μs (5%) 4.19 KiB (1%) 91
["EpiLatentModels", "AR", "evaluation", "standard"] 4.448 μs (5%) 3.20 KiB (1%) 84
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 6.562 μs (5%) 12.20 KiB (1%) 108
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 6.066 μs (5%) 10.64 KiB (1%) 97
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 129.762 μs (5%) 54.25 KiB (1%) 1214
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 85.980 μs (5%) 39.95 KiB (1%) 884
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 18.835 μs (5%) 7.81 KiB (1%) 224
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 17.813 μs (5%) 6.69 KiB (1%) 188
["EpiLatentModels", "BroadcastLatentModel", "evaluation", "linked"] 939.333 ns (5%) 2.75 KiB (1%) 34
["EpiLatentModels", "BroadcastLatentModel", "evaluation", "standard"] 701.873 ns (5%) 1.88 KiB (1%) 30
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.293 μs (5%) 4.83 KiB (1%) 45
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.059 μs (5%) 3.95 KiB (1%) 41
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 49.313 μs (5%) 23.58 KiB (1%) 458
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 32.060 μs (5%) 16.50 KiB (1%) 350
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 3.048 μs (5%) 992 bytes (1%) 29
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 2.869 μs (5%) 992 bytes (1%) 29
["EpiLatentModels", "CombineLatentModels", "evaluation", "linked"] 22.052 μs (5%) 45.67 KiB (1%) 383
["EpiLatentModels", "CombineLatentModels", "evaluation", "standard"] 18.775 μs (5%) 31.16 KiB (1%) 339
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 48.941 μs (5%) 105.72 KiB (1%) 805
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 42.420 μs (5%) 75.84 KiB (1%) 709
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 164.958 μs (5%) 99.81 KiB (1%) 1574
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 114.354 μs (5%) 71.98 KiB (1%) 1207
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 19.286 μs (5%) 7.92 KiB (1%) 225
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 18.124 μs (5%) 6.80 KiB (1%) 189
["EpiLatentModels", "ConcatLatentModels", "evaluation", "linked"] 43.030 μs (5%) 37.27 KiB (1%) 496
["EpiLatentModels", "ConcatLatentModels", "evaluation", "standard"] 40.797 μs (5%) 28.83 KiB (1%) 466
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 44.573 μs (5%) 40.86 KiB (1%) 511
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 42.409 μs (5%) 32.42 KiB (1%) 481
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 121.427 μs (5%) 62.64 KiB (1%) 1012
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 98.694 μs (5%) 49.45 KiB (1%) 879
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.457 μs (5%) 2.06 KiB (1%) 51
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.261 μs (5%) 2.06 KiB (1%) 51
["EpiLatentModels", "DiffLatentModel", "evaluation", "linked"] 7.908 μs (5%) 5.55 KiB (1%) 102
["EpiLatentModels", "DiffLatentModel", "evaluation", "standard"] 7.447 μs (5%) 3.86 KiB (1%) 96
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 9.067 μs (5%) 13.92 KiB (1%) 115
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 8.607 μs (5%) 12.23 KiB (1%) 109
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 89.117 μs (5%) 39.58 KiB (1%) 824
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 69.610 μs (5%) 33.14 KiB (1%) 715
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.963 μs (5%) 2.12 KiB (1%) 50
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 6.672 μs (5%) 2.12 KiB (1%) 50
["EpiLatentModels", "HierarchicalNormal", "evaluation", "linked"] 397.124 ns (5%) 1.03 KiB (1%) 14
["EpiLatentModels", "HierarchicalNormal", "evaluation", "standard"] 295.472 ns (5%) 896 bytes (1%) 13
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.062 μs (5%) 5.12 KiB (1%) 23
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 981.812 ns (5%) 4.97 KiB (1%) 22
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 44.804 μs (5%) 19.03 KiB (1%) 381
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 29.034 μs (5%) 14.17 KiB (1%) 278
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.085 μs (5%) 608 bytes (1%) 9
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 904.069 ns (5%) 608 bytes (1%) 9
["EpiLatentModels", "Intercept", "evaluation", "linked"] 223.274 ns (5%) 400 bytes (1%) 10
["EpiLatentModels", "Intercept", "evaluation", "standard"] 209.616 ns (5%) 400 bytes (1%) 10
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 306.473 ns (5%) 704 bytes (1%) 17
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 295.922 ns (5%) 704 bytes (1%) 17
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 5.427 μs (5%) 3.62 KiB (1%) 87
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 5.440 μs (5%) 3.62 KiB (1%) 87
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 399.249 ns (5%) 208 bytes (1%) 4
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 392.771 ns (5%) 208 bytes (1%) 4
["EpiLatentModels", "PrefixLatentModel", "evaluation", "linked"] 1.851 μs (5%) 3.56 KiB (1%) 40
["EpiLatentModels", "PrefixLatentModel", "evaluation", "standard"] 1.653 μs (5%) 3.09 KiB (1%) 37
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.635 μs (5%) 7.66 KiB (1%) 49
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.396 μs (5%) 7.19 KiB (1%) 46
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 47.729 μs (5%) 21.42 KiB (1%) 406
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 31.610 μs (5%) 16.25 KiB (1%) 301
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.093 μs (5%) 608 bytes (1%) 9
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 920.333 ns (5%) 608 bytes (1%) 9
["EpiLatentModels", "RandomWalk", "evaluation", "linked"] 595.607 ns (5%) 1.72 KiB (1%) 21
["EpiLatentModels", "RandomWalk", "evaluation", "standard"] 444.111 ns (5%) 1.28 KiB (1%) 19
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.398 μs (5%) 8.11 KiB (1%) 32
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.341 μs (5%) 7.67 KiB (1%) 30
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 54.772 μs (5%) 25.47 KiB (1%) 501
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 37.309 μs (5%) 20.28 KiB (1%) 396
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 3.648 μs (5%) 1.28 KiB (1%) 29
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 3.448 μs (5%) 1.28 KiB (1%) 29
["EpiLatentModels", "RecordExpectedLatent", "evaluation", "linked"] 564.280 ns (5%) 1.25 KiB (1%) 20
["EpiLatentModels", "RecordExpectedLatent", "evaluation", "standard"] 405.205 ns (5%) 960 bytes (1%) 18
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 737.031 ns (5%) 1.78 KiB (1%) 29
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 576.957 ns (5%) 1.47 KiB (1%) 27
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 44.653 μs (5%) 18.31 KiB (1%) 387
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 28.613 μs (5%) 13.30 KiB (1%) 283
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.011 μs (5%) 352 bytes (1%) 9
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 824.044 ns (5%) 352 bytes (1%) 9
["EpiLatentModels", "TransformLatentModel", "evaluation", "linked"] 268.613 ns (5%) 448 bytes (1%) 12
["EpiLatentModels", "TransformLatentModel", "evaluation", "standard"] 259.301 ns (5%) 448 bytes (1%) 12
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 352.318 ns (5%) 768 bytes (1%) 19
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 340.959 ns (5%) 768 bytes (1%) 19
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 5.794 μs (5%) 3.93 KiB (1%) 95
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 5.732 μs (5%) 3.93 KiB (1%) 95
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 473.908 ns (5%) 160 bytes (1%) 4
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 503.567 ns (5%) 160 bytes (1%) 4
["EpiLatentModels", "broadcast_dayofweek", "evaluation", "linked"] 1.256 μs (5%) 3.73 KiB (1%) 43
["EpiLatentModels", "broadcast_dayofweek", "evaluation", "standard"] 937.548 ns (5%) 2.42 KiB (1%) 37
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.170 μs (5%) 9.80 KiB (1%) 54
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.800 μs (5%) 8.48 KiB (1%) 48
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 71.784 μs (5%) 34.64 KiB (1%) 699
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 52.909 μs (5%) 28.58 KiB (1%) 590
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 4.988 μs (5%) 1.19 KiB (1%) 29
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 4.883 μs (5%) 1.19 KiB (1%) 29
["EpiLatentModels", "broadcast_weekly", "evaluation", "linked"] 8.265 μs (5%) 5.78 KiB (1%) 113
["EpiLatentModels", "broadcast_weekly", "evaluation", "standard"] 7.667 μs (5%) 3.95 KiB (1%) 103
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 8.696 μs (5%) 8.98 KiB (1%) 130
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 8.302 μs (5%) 6.83 KiB (1%) 116
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 106.168 μs (5%) 42.11 KiB (1%) 852
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 65.192 μs (5%) 29.47 KiB (1%) 599
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.532 μs (5%) 1.69 KiB (1%) 48
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 4.975 μs (5%) 1.56 KiB (1%) 44
["EpiObsModels", "Ascertainment", "evaluation", "linked"] 3.341 μs (5%) 3.58 KiB (1%) 63
["EpiObsModels", "Ascertainment", "evaluation", "standard"] 3.270 μs (5%) 3.58 KiB (1%) 63
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 3.996 μs (5%) 3.92 KiB (1%) 72
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 3.974 μs (5%) 3.92 KiB (1%) 72
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 77.635 μs (5%) 38.77 KiB (1%) 918
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 63.098 μs (5%) 34.02 KiB (1%) 815
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.644 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.699 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "LatentDelay", "evaluation", "linked"] 14.417 μs (5%) 22.08 KiB (1%) 412
["EpiObsModels", "LatentDelay", "evaluation", "standard"] 14.457 μs (5%) 22.08 KiB (1%) 412
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 18.504 μs (5%) 22.30 KiB (1%) 419
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 18.014 μs (5%) 22.30 KiB (1%) 419
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 551.419 μs (5%) 293.05 KiB (1%) 7011
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 526.814 μs (5%) 288.30 KiB (1%) 6908
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 51.225 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 50.604 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "NegativeBinomialError", "evaluation", "linked"] 1.126 μs (5%) 400 bytes (1%) 10
["EpiObsModels", "NegativeBinomialError", "evaluation", "standard"] 1.086 μs (5%) 400 bytes (1%) 10
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.586 μs (5%) 624 bytes (1%) 17
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.571 μs (5%) 624 bytes (1%) 17
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 72.736 μs (5%) 35.95 KiB (1%) 903
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 58.970 μs (5%) 31.20 KiB (1%) 800
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.617 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.492 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "PoissonError", "evaluation", "linked"] 1.341 μs (5%) 1.83 KiB (1%) 30
["EpiObsModels", "PoissonError", "evaluation", "standard"] 1.011 μs (5%) 1.47 KiB (1%) 26
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 3.112 μs (5%) 7.78 KiB (1%) 43
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.410 μs (5%) 4.70 KiB (1%) 35
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 164.978 μs (5%) 86.44 KiB (1%) 1870
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 47.448 μs (5%) 29.38 KiB (1%) 727
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.097 μs (5%) 176 bytes (1%) 3
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 4.214 μs (5%) 176 bytes (1%) 3
["EpiObsModels", "PrefixObservationModel", "evaluation", "linked"] 1.671 μs (5%) 1.56 KiB (1%) 34
["EpiObsModels", "PrefixObservationModel", "evaluation", "standard"] 1.602 μs (5%) 1.56 KiB (1%) 34
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.825 μs (5%) 1.78 KiB (1%) 41
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.743 μs (5%) 1.78 KiB (1%) 41
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 26.880 μs (5%) 12.59 KiB (1%) 290
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 13.224 μs (5%) 7.84 KiB (1%) 187
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.113 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 982.571 ns (5%) 96 bytes (1%) 3
["EpiObsModels", "RecordExpectedObs", "evaluation", "linked"] 779.283 ns (5%) 480 bytes (1%) 14
["EpiObsModels", "RecordExpectedObs", "evaluation", "standard"] 733.225 ns (5%) 480 bytes (1%) 14
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.044 μs (5%) 704 bytes (1%) 21
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.007 μs (5%) 704 bytes (1%) 21
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 46.938 μs (5%) 22.98 KiB (1%) 537
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 33.192 μs (5%) 18.23 KiB (1%) 434
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 3.142 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 3.066 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "StackObservationModels", "evaluation", "linked"] 6.664 μs (5%) 5.81 KiB (1%) 117
["EpiObsModels", "StackObservationModels", "evaluation", "standard"] 6.576 μs (5%) 5.81 KiB (1%) 117
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 7.591 μs (5%) 6.16 KiB (1%) 126
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 7.346 μs (5%) 6.16 KiB (1%) 126
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 90.449 μs (5%) 49.09 KiB (1%) 1044
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 73.317 μs (5%) 44.34 KiB (1%) 941
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.216 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 6.039 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "TransformObservationModel", "evaluation", "linked"] 1.442 μs (5%) 672 bytes (1%) 16
["EpiObsModels", "TransformObservationModel", "evaluation", "standard"] 1.390 μs (5%) 672 bytes (1%) 16
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.899 μs (5%) 896 bytes (1%) 23
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.823 μs (5%) 896 bytes (1%) 23
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 74.359 μs (5%) 35.59 KiB (1%) 869
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 60.683 μs (5%) 30.84 KiB (1%) 766
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.646 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.489 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "ascertainment_dayofweek", "evaluation", "linked"] 4.172 μs (5%) 9.09 KiB (1%) 100
["EpiObsModels", "ascertainment_dayofweek", "evaluation", "standard"] 3.726 μs (5%) 7.84 KiB (1%) 92
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 5.829 μs (5%) 16.22 KiB (1%) 111
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 5.485 μs (5%) 14.97 KiB (1%) 103
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 107.911 μs (5%) 59.83 KiB (1%) 1164
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 91.050 μs (5%) 53.88 KiB (1%) 1054
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.327 μs (5%) 496 bytes (1%) 9
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.205 μs (5%) 496 bytes (1%) 9
["EpiObsModels", "observation_error", "missing obs", "evaluation", "linked"] 1.391 μs (5%) 3.05 KiB (1%) 38
["EpiObsModels", "observation_error", "missing obs", "evaluation", "standard"] 868.964 ns (5%) 1.48 KiB (1%) 28
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.831 μs (5%) 4.11 KiB (1%) 48
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.253 μs (5%) 2.55 KiB (1%) 38
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 40.425 μs (5%) 25.78 KiB (1%) 533
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 24.185 μs (5%) 18.80 KiB (1%) 401
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.207 μs (5%) 144 bytes (1%) 3
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 2.016 μs (5%) 144 bytes (1%) 3
["EpiObsModels", "observation_error", "no missing obs", "evaluation", "linked"] 427.181 ns (5%) 352 bytes (1%) 10
["EpiObsModels", "observation_error", "no missing obs", "evaluation", "standard"] 366.435 ns (5%) 352 bytes (1%) 10
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 558.048 ns (5%) 576 bytes (1%) 17
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 486.451 ns (5%) 576 bytes (1%) 17
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 32.871 μs (5%) 19.64 KiB (1%) 446
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 18.254 μs (5%) 14.22 KiB (1%) 324
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.875 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.606 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "observation_error", "partially missing obs", "evaluation", "linked"] 28.723 μs (5%) 3.02 KiB (1%) 64
["EpiObsModels", "observation_error", "partially missing obs", "evaluation", "standard"] 28.474 μs (5%) 2.70 KiB (1%) 62
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 19.517 μs (5%) 2.73 KiB (1%) 51
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 19.316 μs (5%) 2.42 KiB (1%) 49
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 63.138 μs (5%) 26.11 KiB (1%) 555
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 43.591 μs (5%) 20.38 KiB (1%) 431
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.175 μs (5%) 112 bytes (1%) 3
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.973 μs (5%) 112 bytes (1%) 3

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["EpiAwareUtils"]
  • ["EpiInfModels", "DirectInfections", "evaluation"]
  • ["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiInfModels", "ExpGrowthRate", "evaluation"]
  • ["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "AR", "evaluation"]
  • ["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "BroadcastLatentModel", "evaluation"]
  • ["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "CombineLatentModels", "evaluation"]
  • ["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "ConcatLatentModels", "evaluation"]
  • ["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "DiffLatentModel", "evaluation"]
  • ["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "HierarchicalNormal", "evaluation"]
  • ["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "Intercept", "evaluation"]
  • ["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "PrefixLatentModel", "evaluation"]
  • ["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "RandomWalk", "evaluation"]
  • ["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "RecordExpectedLatent", "evaluation"]
  • ["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "TransformLatentModel", "evaluation"]
  • ["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "broadcast_dayofweek", "evaluation"]
  • ["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiLatentModels", "broadcast_weekly", "evaluation"]
  • ["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "Ascertainment", "evaluation"]
  • ["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "LatentDelay", "evaluation"]
  • ["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "NegativeBinomialError", "evaluation"]
  • ["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "PoissonError", "evaluation"]
  • ["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "PrefixObservationModel", "evaluation"]
  • ["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "RecordExpectedObs", "evaluation"]
  • ["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "StackObservationModels", "evaluation"]
  • ["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "TransformObservationModel", "evaluation"]
  • ["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "ascertainment_dayofweek", "evaluation"]
  • ["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "observation_error", "missing obs", "evaluation"]
  • ["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "observation_error", "no missing obs", "evaluation"]
  • ["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]
  • ["EpiObsModels", "observation_error", "partially missing obs", "evaluation"]
  • ["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)"]

Julia versioninfo

Julia Version 1.11.1
Commit 8f5b7ca12ad (2024-10-16 10:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 22.04.5 LTS
  uname: Linux 6.5.0-1025-azure #26~22.04.1-Ubuntu SMP Thu Jul 11 22:33:04 UTC 2024 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      15716 s          1 s       1214 s      31760 s          0 s
       #2     0 MHz      13588 s          0 s       1168 s      33923 s          0 s
       #3     0 MHz      15813 s          0 s       1168 s      31726 s          0 s
       #4     0 MHz      15345 s          1 s       1245 s      32116 s          0 s
  Memory: 15.606491088867188 GB (12579.63671875 MB free)
  Uptime: 4880.87 sec
  Load Avg:  1.07  1.06  1.04
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Runtime information

Runtime Info
BLAS #threads 2
BLAS.vendor() lbt
Sys.CPU_THREADS 4

lscpu output:

Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Address sizes:                      48 bits physical, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             4
On-line CPU(s) list:                0-3
Vendor ID:                          AuthenticAMD
Model name:                         AMD EPYC 7763 64-Core Processor
CPU family:                         25
Model:                              1
Thread(s) per core:                 2
Core(s) per socket:                 2
Socket(s):                          1
Stepping:                           1
BogoMIPS:                           4890.84
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl tsc_reliable nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy svm cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext invpcid_single vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves clzero xsaveerptr rdpru arat npt nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload umip vaes vpclmulqdq rdpid fsrm
Virtualization:                     AMD-V
Hypervisor vendor:                  Microsoft
Virtualization type:                full
L1d cache:                          64 KiB (2 instances)
L1i cache:                          64 KiB (2 instances)
L2 cache:                           1 MiB (2 instances)
L3 cache:                           32 MiB (1 instance)
NUMA node(s):                       1
NUMA node0 CPU(s):                  0-3
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit:        Not affected
Vulnerability L1tf:                 Not affected
Vulnerability Mds:                  Not affected
Vulnerability Meltdown:             Not affected
Vulnerability Mmio stale data:      Not affected
Vulnerability Retbleed:             Not affected
Vulnerability Spec rstack overflow: Vulnerable: Safe RET, no microcode
Vulnerability Spec store bypass:    Vulnerable
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; Retpolines; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected
Cpu Property Value
Brand AMD EPYC 7763 64-Core Processor
Vendor :AMD
Architecture :Unknown
Model Family: 0xaf, Model: 0x01, Stepping: 0x01, Type: 0x00
Cores 16 physical cores, 16 logical cores (on executing CPU)
No Hyperthreading hardware capability detected
Clock Frequencies Not supported by CPU
Data Cache Level 1:3 : (32, 512, 32768) kbytes
64 byte cache line size
Address Size 48 bits virtual, 48 bits physical
SIMD 256 bit = 32 byte max. SIMD vector size
Time Stamp Counter TSC is accessible via rdtsc
TSC runs at constant rate (invariant from clock frequency)
Perf. Monitoring Performance Monitoring Counters (PMC) are not supported
Hypervisor Yes, Microsoft

@seabbs seabbs added this pull request to the merge queue Nov 20, 2024
Merged via the queue into main with commit ae73647 Nov 20, 2024
11 checks passed
@seabbs seabbs deleted the 529-create-nulllatentmodel branch November 20, 2024 15:19
seabbs added a commit that referenced this pull request Dec 5, 2024
* Patch: Switch to fork of benchmarkCI (#520)

* patch to fork of benchmarkCI

* put fork version of BenchmarkCI in [sources]

* swap order

* add EpiAware [source]

* fix path

* rm benchmarkCI from project

* Patch fix: add `Manifest.toml` to benchmarking (#524)

* trigger

* Update benchmark.yaml

* Update benchmark.yaml

* commit benchmark Manifest

* try alternate approach

* Update benchmark.yaml

* Update EpiMethod.jl

* Update benchmark.yaml

* change baseline to origin/main

* remove trigger

* rm other trigger

* Issue 465: Add an infection generating model for ODE problems (#510)

* CompatHelper: bump compat for Turing to 0.35 for package EpiAware, (drop existing compat) (#516)

* CompatHelper: bump compat for Turing to 0.35 for package EpiAware, (drop existing compat)

* Update Project.toml

* fix Project.toml

---------

Co-authored-by: CompatHelper Julia <[email protected]>
Co-authored-by: Sam Abbott <[email protected]>
Co-authored-by: Samuel Brand <[email protected]>
Co-authored-by: Samuel Brand <[email protected]>

* CompatHelper: bump compat for DynamicPPL to 0.30 for package EpiAware, (drop existing compat) (#528)

Co-authored-by: CompatHelper Julia <[email protected]>

* rename IDD -> IID

* rename test file

* Issue 529: Create null Latent model (#530)

* Null Latent model

* Null Latent model

* fix doctest

* fix generate_epiaware unit tests

New usage of RW

* fix turing method test

underlying std of step size changed name

* fix broadcast test

Underlying std param changed name

* fix HN unit test

Default std prior had changed

* fix AR unit tests

---------

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: CompatHelper Julia <[email protected]>
Co-authored-by: Sam Abbott <[email protected]>
seabbs added a commit that referenced this pull request Dec 12, 2024
* draft MA method

* draft MA methd

* use IDD for epsilon in all models

* add MA benchmark

* Add docs and  tests for IDD

* make episilon_t a arg of the latent model constructors

* improve MA correctness

* fully import EpiAwareUtils

* add a test for IDD

* add tests for MA.jl

* add doc tests and unit tests + start on helper fn

* more updatres to AR appraoc

* chase down partial arg changes

* clean up AR

* clean up and add arma and arima helpers

* Contributions towards Arma/Arima models (#531)

* Patch: Switch to fork of benchmarkCI (#520)

* patch to fork of benchmarkCI

* put fork version of BenchmarkCI in [sources]

* swap order

* add EpiAware [source]

* fix path

* rm benchmarkCI from project

* Patch fix: add `Manifest.toml` to benchmarking (#524)

* trigger

* Update benchmark.yaml

* Update benchmark.yaml

* commit benchmark Manifest

* try alternate approach

* Update benchmark.yaml

* Update EpiMethod.jl

* Update benchmark.yaml

* change baseline to origin/main

* remove trigger

* rm other trigger

* Issue 465: Add an infection generating model for ODE problems (#510)

* CompatHelper: bump compat for Turing to 0.35 for package EpiAware, (drop existing compat) (#516)

* CompatHelper: bump compat for Turing to 0.35 for package EpiAware, (drop existing compat)

* Update Project.toml

* fix Project.toml

---------

Co-authored-by: CompatHelper Julia <[email protected]>
Co-authored-by: Sam Abbott <[email protected]>
Co-authored-by: Samuel Brand <[email protected]>
Co-authored-by: Samuel Brand <[email protected]>

* CompatHelper: bump compat for DynamicPPL to 0.30 for package EpiAware, (drop existing compat) (#528)

Co-authored-by: CompatHelper Julia <[email protected]>

* rename IDD -> IID

* rename test file

* Issue 529: Create null Latent model (#530)

* Null Latent model

* Null Latent model

* fix doctest

* fix generate_epiaware unit tests

New usage of RW

* fix turing method test

underlying std of step size changed name

* fix broadcast test

Underlying std param changed name

* fix HN unit test

Default std prior had changed

* fix AR unit tests

---------

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: CompatHelper Julia <[email protected]>
Co-authored-by: Sam Abbott <[email protected]>

* revert define_ namming

* clean out repeated utils from merge

* fix MA tests

* fix RW tests - feel made about RandomWalk vs AR naming

* fix remaining unit tests that aren't doctests

* update latent recovery test

* try and fix doctests automatically

* update all doctests to output nothing - this is awful

* add doctests for arima and arma

* fix doctest

* clean up deps

* update replication studies

* add interface tests for combination functions and add benchmarks

* add some basic theoretical properties tests

* name change IDD -> IID benchmarks

* moving all the constructors because this PR is too contained

* catch missing using

* update iid benchmark:

* update extraction

* remove old param namme from case study

* get the dot

* get the dot

* fix initial guess point for MAP opt

* Update index.jl

* add a compile time branch for HN

* add a compile time branch for HN

* update test

* add a new constructor to get old default behaviour

* update docs

* update docs - using the structs for priors is very brittle

* reorder prior plots

---------

Co-authored-by: Samuel Brand <[email protected]>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: CompatHelper Julia <[email protected]>
Co-authored-by: Samuel Brand <[email protected]>
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Create NullLatentModel
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