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CompatHelper: bump compat for DynamicPPL to 0.34 for package EpiAware, (drop existing compat) #572

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CompatHelper: bump compat for DynamicPPL to 0.34 for package EpiAware, (drop existing compat) #572

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This pull request changes the compat entry for the DynamicPPL package from 0.30 to 0.34 for package EpiAware.
This drops the compat entries for earlier versions.

Note: I have not tested your package with this new compat entry.
It is your responsibility to make sure that your package tests pass before you merge this pull request.

@seabbs seabbs force-pushed the compathelper/new_version/2025-01-17-01-57-02-996-02422286372 branch from eca55ff to c3d4fc6 Compare January 17, 2025 01:57
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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: 17 Jan 2025 - 02:46
    • Baseline: 17 Jan 2025 - 03:26
  • Package commits:
    • Target: ebe4a0
    • Baseline: 104bdd
  • Julia commits:
    • Target: 5e9a32
    • Baseline: 5e9a32
  • 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
["EpiInfModels", "DirectInfections", "evaluation", "linked"] 0.91 (5%) ✅ 1.00 (1%)
["EpiInfModels", "DirectInfections", "evaluation", "standard"] 0.94 (5%) ✅ 1.00 (1%)
["EpiInfModels", "ExpGrowthRate", "evaluation", "linked"] 0.95 (5%) ✅ 1.00 (1%)
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 0.92 (5%) ✅ 1.00 (1%)
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 1.06 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "HierarchicalNormal", "evaluation", "linked"] 0.95 (5%) ✅ 1.00 (1%)
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 0.91 (5%) ✅ 1.00 (1%)
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 0.93 (5%) ✅ 1.00 (1%)
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.06 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.06 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "PrefixLatentModel", "evaluation", "standard"] 0.94 (5%) ✅ 1.00 (1%)
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.07 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.05 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "RecordExpectedLatent", "evaluation", "linked"] 0.95 (5%) ✅ 1.00 (1%)
["EpiLatentModels", "RecordExpectedLatent", "evaluation", "standard"] 0.90 (5%) ✅ 1.00 (1%)
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 0.89 (5%) ✅ 1.00 (1%)
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.07 (5%) ❌ 1.00 (1%)
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.07 (5%) ❌ 1.00 (1%)
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 0.90 (5%) ✅ 1.00 (1%)
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 0.95 (5%) ✅ 1.00 (1%)
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.10 (5%) ❌ 1.00 (1%)
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.10 (5%) ❌ 1.00 (1%)
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 0.95 (5%) ✅ 1.00 (1%)
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.12 (5%) ❌ 1.00 (1%)
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.11 (5%) ❌ 1.00 (1%)
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.18 (5%) ❌ 1.00 (1%)
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.14 (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", "IID", "evaluation"]
  • ["EpiLatentModels", "IID", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "IID", "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", "MA", "evaluation"]
  • ["EpiLatentModels", "MA", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "MA", "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 1.11.2
Commit 5e9a32e7af2 (2024-12-01 20:02 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.1 LTS
  uname: Linux 6.8.0-1017-azure #20-Ubuntu SMP Tue Oct 22 03:43:13 UTC 2024 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      10361 s          0 s        875 s      20743 s          0 s
       #2     0 MHz      11801 s          0 s        918 s      19232 s          0 s
       #3     0 MHz       9718 s          0 s        810 s      21438 s          0 s
       #4     0 MHz      11427 s          0 s        828 s      19690 s          0 s
  Memory: 15.615280151367188 GB (12899.390625 MB free)
  Uptime: 3207.12 sec
  Load Avg:  1.08  1.07  1.15
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Baseline

Julia Version 1.11.2
Commit 5e9a32e7af2 (2024-12-01 20:02 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.1 LTS
  uname: Linux 6.8.0-1017-azure #20-Ubuntu SMP Tue Oct 22 03:43:13 UTC 2024 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      15615 s          0 s       1396 s      38849 s          0 s
       #2     0 MHz      17731 s          0 s       1446 s      36660 s          0 s
       #3     0 MHz      15141 s          0 s       1300 s      39412 s          0 s
       #4     0 MHz      17768 s          0 s       1381 s      36683 s          0 s
  Memory: 15.615280151367188 GB (12629.33984375 MB free)
  Uptime: 5599.0 sec
  Load Avg:  1.0  1.02  1.02
  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: 17 Jan 2025 - 2:46
  • Package commit: ebe4a0
  • Julia commit: 5e9a32
  • 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"] 271.369 ns (5%) 464 bytes (1%) 10
["EpiInfModels", "DirectInfections", "evaluation", "standard"] 270.677 ns (5%) 464 bytes (1%) 10
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 412.025 ns (5%) 816 bytes (1%) 18
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 407.095 ns (5%) 816 bytes (1%) 18
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 10.380 μs (5%) 5.55 KiB (1%) 125
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 10.439 μs (5%) 5.55 KiB (1%) 125
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 476.738 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 486.605 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "ExpGrowthRate", "evaluation", "linked"] 174.442 ns (5%) 288 bytes (1%) 8
["EpiInfModels", "ExpGrowthRate", "evaluation", "standard"] 166.404 ns (5%) 288 bytes (1%) 8
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 278.443 ns (5%) 544 bytes (1%) 15
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 266.633 ns (5%) 544 bytes (1%) 15
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 10.249 μs (5%) 5.53 KiB (1%) 124
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 10.229 μs (5%) 5.53 KiB (1%) 124
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 500.886 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 497.461 ns (5%) 256 bytes (1%) 7
["EpiLatentModels", "AR", "evaluation", "linked"] 12.813 μs (5%) 8.44 KiB (1%) 171
["EpiLatentModels", "AR", "evaluation", "standard"] 12.112 μs (5%) 5.77 KiB (1%) 158
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 14.357 μs (5%) 16.45 KiB (1%) 188
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 13.846 μs (5%) 13.20 KiB (1%) 171
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 143.278 μs (5%) 59.31 KiB (1%) 1296
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 98.435 μs (5%) 43.33 KiB (1%) 960
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 19.095 μs (5%) 7.81 KiB (1%) 224
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 17.713 μs (5%) 6.69 KiB (1%) 188
["EpiLatentModels", "BroadcastLatentModel", "evaluation", "linked"] 1.401 μs (5%) 4.36 KiB (1%) 48
["EpiLatentModels", "BroadcastLatentModel", "evaluation", "standard"] 947.800 ns (5%) 2.61 KiB (1%) 40
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.861 μs (5%) 6.42 KiB (1%) 59
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.359 μs (5%) 4.67 KiB (1%) 51
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 49.834 μs (5%) 25.59 KiB (1%) 465
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 32.721 μs (5%) 17.64 KiB (1%) 353
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.923 μs (5%) 848 bytes (1%) 24
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 2.712 μs (5%) 848 bytes (1%) 24
["EpiLatentModels", "CombineLatentModels", "evaluation", "linked"] 25.127 μs (5%) 50.69 KiB (1%) 433
["EpiLatentModels", "CombineLatentModels", "evaluation", "standard"] 21.139 μs (5%) 33.30 KiB (1%) 381
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 55.574 μs (5%) 115.75 KiB (1%) 905
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 46.978 μs (5%) 80.12 KiB (1%) 793
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 162.625 μs (5%) 105.61 KiB (1%) 1626
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 112.962 μs (5%) 74.91 KiB (1%) 1251
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 19.636 μs (5%) 7.92 KiB (1%) 225
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 18.125 μs (5%) 6.80 KiB (1%) 189
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["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 56.947 μs (5%) 45.27 KiB (1%) 591
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 53.541 μs (5%) 35.14 KiB (1%) 555
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 132.218 μs (5%) 67.14 KiB (1%) 1077
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 110.677 μs (5%) 52.27 KiB (1%) 938
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.341 μs (5%) 1.89 KiB (1%) 46
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.099 μs (5%) 1.89 KiB (1%) 46
["EpiLatentModels", "DiffLatentModel", "evaluation", "linked"] 16.300 μs (5%) 9.78 KiB (1%) 182
["EpiLatentModels", "DiffLatentModel", "evaluation", "standard"] 15.509 μs (5%) 6.41 KiB (1%) 170
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 18.204 μs (5%) 18.09 KiB (1%) 195
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 16.862 μs (5%) 14.72 KiB (1%) 183
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 100.428 μs (5%) 43.50 KiB (1%) 877
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["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.655 μs (5%) 1.94 KiB (1%) 45
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 6.544 μs (5%) 1.94 KiB (1%) 45
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["EpiLatentModels", "HierarchicalNormal", "evaluation", "standard"] 424.663 ns (5%) 1.19 KiB (1%) 18
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.276 μs (5%) 5.59 KiB (1%) 29
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.066 μs (5%) 5.28 KiB (1%) 27
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 36.639 μs (5%) 17.12 KiB (1%) 338
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 21.430 μs (5%) 12.06 KiB (1%) 233
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 974.611 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 794.577 ns (5%) 176 bytes (1%) 3
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["EpiLatentModels", "IID", "evaluation", "standard"] 194.834 ns (5%) 560 bytes (1%) 10
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["EpiLatentModels", "IID", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 500.728 ns (5%) 3.59 KiB (1%) 17
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 13.485 μs (5%) 7.58 KiB (1%) 153
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 13.395 μs (5%) 7.58 KiB (1%) 153
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["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 298.709 ns (5%) 704 bytes (1%) 17
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["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.824 μs (5%) 8.14 KiB (1%) 55
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.498 μs (5%) 7.52 KiB (1%) 51
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 39.063 μs (5%) 19.53 KiB (1%) 363
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 24.296 μs (5%) 14.16 KiB (1%) 256
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["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 34.965 μs (5%) 20.22 KiB (1%) 371
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["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 3.102 μs (5%) 1.08 KiB (1%) 24
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["EpiLatentModels", "RecordExpectedLatent", "evaluation", "standard"] 519.711 ns (5%) 1.25 KiB (1%) 23
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 881.660 ns (5%) 2.25 KiB (1%) 35
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 680.477 ns (5%) 1.78 KiB (1%) 32
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 36.488 μs (5%) 16.59 KiB (1%) 344
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 21.300 μs (5%) 11.38 KiB (1%) 238
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 883.490 ns (5%) 112 bytes (1%) 3
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["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 5.512 μs (5%) 3.93 KiB (1%) 95
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["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.430 μs (5%) 11.38 KiB (1%) 68
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.190 μs (5%) 9.19 KiB (1%) 58
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["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 50.885 μs (5%) 29.03 KiB (1%) 577
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 4.735 μs (5%) 1.00 KiB (1%) 24
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 4.623 μs (5%) 1.00 KiB (1%) 24
["EpiLatentModels", "broadcast_weekly", "evaluation", "linked"] 16.541 μs (5%) 10.03 KiB (1%) 193
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["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 17.242 μs (5%) 13.23 KiB (1%) 210
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 15.900 μs (5%) 9.39 KiB (1%) 190
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 119.163 μs (5%) 47.12 KiB (1%) 934
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 76.724 μs (5%) 32.80 KiB (1%) 675
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.644 μs (5%) 1.69 KiB (1%) 48
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.071 μs (5%) 1.56 KiB (1%) 44
["EpiObsModels", "Ascertainment", "evaluation", "linked"] 3.381 μs (5%) 3.58 KiB (1%) 63
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["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 4.085 μs (5%) 3.92 KiB (1%) 72
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["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 74.960 μs (5%) 38.77 KiB (1%) 918
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["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 72.055 μs (5%) 35.95 KiB (1%) 903
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 57.758 μs (5%) 31.20 KiB (1%) 800
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["EpiObsModels", "PoissonError", "evaluation", "standard"] 1.044 μs (5%) 1.47 KiB (1%) 26
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["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 165.290 μs (5%) 86.44 KiB (1%) 1870
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["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 26.219 μs (5%) 12.59 KiB (1%) 290
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["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 6.376 μs (5%) 16.72 KiB (1%) 117
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["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 98.946 μs (5%) 58.03 KiB (1%) 1121
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 81.933 μs (5%) 51.88 KiB (1%) 1009
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["EpiObsModels", "observation_error", "missing obs", "evaluation", "linked"] 1.388 μs (5%) 3.05 KiB (1%) 38
["EpiObsModels", "observation_error", "missing obs", "evaluation", "standard"] 886.293 ns (5%) 1.48 KiB (1%) 28
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.818 μs (5%) 4.11 KiB (1%) 48
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.216 μs (5%) 2.55 KiB (1%) 38
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 41.037 μs (5%) 25.78 KiB (1%) 533
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 23.684 μs (5%) 18.80 KiB (1%) 401
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.421 μs (5%) 144 bytes (1%) 3
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 2.149 μs (5%) 144 bytes (1%) 3
["EpiObsModels", "observation_error", "no missing obs", "evaluation", "linked"] 409.065 ns (5%) 352 bytes (1%) 10
["EpiObsModels", "observation_error", "no missing obs", "evaluation", "standard"] 351.363 ns (5%) 352 bytes (1%) 10
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 544.725 ns (5%) 576 bytes (1%) 17
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 474.357 ns (5%) 576 bytes (1%) 17
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 33.072 μs (5%) 19.64 KiB (1%) 446
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 18.154 μs (5%) 14.22 KiB (1%) 324
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.057 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.793 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "observation_error", "partially missing obs", "evaluation", "linked"] 30.658 μs (5%) 3.02 KiB (1%) 64
["EpiObsModels", "observation_error", "partially missing obs", "evaluation", "standard"] 30.447 μs (5%) 2.70 KiB (1%) 62
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 21.230 μs (5%) 2.73 KiB (1%) 51
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 20.959 μs (5%) 2.42 KiB (1%) 49
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 65.052 μs (5%) 26.11 KiB (1%) 555
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 44.634 μs (5%) 20.38 KiB (1%) 431
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.550 μs (5%) 112 bytes (1%) 3
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 2.249 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", "IID", "evaluation"]
  • ["EpiLatentModels", "IID", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "IID", "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", "MA", "evaluation"]
  • ["EpiLatentModels", "MA", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "MA", "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 1.11.2
Commit 5e9a32e7af2 (2024-12-01 20:02 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.1 LTS
  uname: Linux 6.8.0-1017-azure #20-Ubuntu SMP Tue Oct 22 03:43:13 UTC 2024 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      10361 s          0 s        875 s      20743 s          0 s
       #2     0 MHz      11801 s          0 s        918 s      19232 s          0 s
       #3     0 MHz       9718 s          0 s        810 s      21438 s          0 s
       #4     0 MHz      11427 s          0 s        828 s      19690 s          0 s
  Memory: 15.615280151367188 GB (12899.390625 MB free)
  Uptime: 3207.12 sec
  Load Avg:  1.08  1.07  1.15
  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: 17 Jan 2025 - 3:26
  • Package commit: 104bdd
  • Julia commit: 5e9a32
  • 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"] 2.096 μs (5%) 416 bytes (1%) 10
["EpiInfModels", "DirectInfections", "evaluation", "linked"] 299.275 ns (5%) 464 bytes (1%) 10
["EpiInfModels", "DirectInfections", "evaluation", "standard"] 289.455 ns (5%) 464 bytes (1%) 10
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 406.865 ns (5%) 816 bytes (1%) 18
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 403.105 ns (5%) 816 bytes (1%) 18
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 10.339 μs (5%) 5.55 KiB (1%) 125
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 10.380 μs (5%) 5.55 KiB (1%) 125
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 492.732 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 499.907 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "ExpGrowthRate", "evaluation", "linked"] 183.967 ns (5%) 288 bytes (1%) 8
["EpiInfModels", "ExpGrowthRate", "evaluation", "standard"] 168.005 ns (5%) 288 bytes (1%) 8
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 267.715 ns (5%) 544 bytes (1%) 15
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 257.555 ns (5%) 544 bytes (1%) 15
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 10.109 μs (5%) 5.53 KiB (1%) 124
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 9.919 μs (5%) 5.53 KiB (1%) 124
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 496.758 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 494.067 ns (5%) 256 bytes (1%) 7
["EpiLatentModels", "AR", "evaluation", "linked"] 12.824 μs (5%) 8.44 KiB (1%) 171
["EpiLatentModels", "AR", "evaluation", "standard"] 12.043 μs (5%) 5.77 KiB (1%) 158
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 14.487 μs (5%) 16.45 KiB (1%) 188
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 13.455 μs (5%) 13.20 KiB (1%) 171
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 138.759 μs (5%) 59.31 KiB (1%) 1296
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 96.000 μs (5%) 43.33 KiB (1%) 960
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 19.196 μs (5%) 7.81 KiB (1%) 224
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 17.683 μs (5%) 6.69 KiB (1%) 188
["EpiLatentModels", "BroadcastLatentModel", "evaluation", "linked"] 1.445 μs (5%) 4.36 KiB (1%) 48
["EpiLatentModels", "BroadcastLatentModel", "evaluation", "standard"] 986.900 ns (5%) 2.61 KiB (1%) 40
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.873 μs (5%) 6.42 KiB (1%) 59
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.470 μs (5%) 4.67 KiB (1%) 51
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 50.324 μs (5%) 25.59 KiB (1%) 465
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 31.319 μs (5%) 17.64 KiB (1%) 353
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.936 μs (5%) 848 bytes (1%) 24
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 2.708 μs (5%) 848 bytes (1%) 24
["EpiLatentModels", "CombineLatentModels", "evaluation", "linked"] 25.037 μs (5%) 50.69 KiB (1%) 433
["EpiLatentModels", "CombineLatentModels", "evaluation", "standard"] 21.320 μs (5%) 33.30 KiB (1%) 381
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 55.875 μs (5%) 115.75 KiB (1%) 905
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 46.978 μs (5%) 80.12 KiB (1%) 793
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 166.973 μs (5%) 105.61 KiB (1%) 1626
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 115.487 μs (5%) 74.91 KiB (1%) 1251
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 19.907 μs (5%) 7.92 KiB (1%) 225
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 18.254 μs (5%) 6.80 KiB (1%) 189
["EpiLatentModels", "ConcatLatentModels", "evaluation", "linked"] 56.246 μs (5%) 41.75 KiB (1%) 576
["EpiLatentModels", "ConcatLatentModels", "evaluation", "standard"] 52.518 μs (5%) 31.62 KiB (1%) 540
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 57.448 μs (5%) 45.27 KiB (1%) 591
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 54.342 μs (5%) 35.14 KiB (1%) 555
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 129.974 μs (5%) 67.14 KiB (1%) 1077
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 107.942 μs (5%) 52.27 KiB (1%) 938
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.394 μs (5%) 1.89 KiB (1%) 46
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.178 μs (5%) 1.89 KiB (1%) 46
["EpiLatentModels", "DiffLatentModel", "evaluation", "linked"] 16.511 μs (5%) 9.78 KiB (1%) 182
["EpiLatentModels", "DiffLatentModel", "evaluation", "standard"] 15.459 μs (5%) 6.41 KiB (1%) 170
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 17.613 μs (5%) 18.09 KiB (1%) 195
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 16.811 μs (5%) 14.72 KiB (1%) 183
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 95.138 μs (5%) 43.50 KiB (1%) 877
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 76.703 μs (5%) 35.38 KiB (1%) 762
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.851 μs (5%) 1.94 KiB (1%) 45
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 6.651 μs (5%) 1.94 KiB (1%) 45
["EpiLatentModels", "HierarchicalNormal", "evaluation", "linked"] 584.754 ns (5%) 1.50 KiB (1%) 20
["EpiLatentModels", "HierarchicalNormal", "evaluation", "standard"] 442.949 ns (5%) 1.19 KiB (1%) 18
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.261 μs (5%) 5.59 KiB (1%) 29
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.099 μs (5%) 5.28 KiB (1%) 27
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 36.037 μs (5%) 17.12 KiB (1%) 338
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 21.159 μs (5%) 12.06 KiB (1%) 233
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 968.350 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 795.424 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "IID", "evaluation", "linked"] 198.488 ns (5%) 560 bytes (1%) 10
["EpiLatentModels", "IID", "evaluation", "standard"] 189.446 ns (5%) 560 bytes (1%) 10
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 562.418 ns (5%) 3.59 KiB (1%) 17
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 538.905 ns (5%) 3.59 KiB (1%) 17
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 13.405 μs (5%) 7.58 KiB (1%) 153
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 13.485 μs (5%) 7.58 KiB (1%) 153
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 399.145 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 393.174 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "Intercept", "evaluation", "linked"] 206.834 ns (5%) 400 bytes (1%) 10
["EpiLatentModels", "Intercept", "evaluation", "standard"] 192.119 ns (5%) 400 bytes (1%) 10
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 293.757 ns (5%) 704 bytes (1%) 17
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 282.775 ns (5%) 704 bytes (1%) 17
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 5.425 μs (5%) 3.62 KiB (1%) 87
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 5.363 μs (5%) 3.62 KiB (1%) 87
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 394.500 ns (5%) 208 bytes (1%) 4
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 389.342 ns (5%) 208 bytes (1%) 4
["EpiLatentModels", "MA", "evaluation", "linked"] 1.690 μs (5%) 4.70 KiB (1%) 72
["EpiLatentModels", "MA", "evaluation", "standard"] 1.253 μs (5%) 3.25 KiB (1%) 62
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 3.071 μs (5%) 14.38 KiB (1%) 85
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.514 μs (5%) 12.48 KiB (1%) 73
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 104.736 μs (5%) 49.22 KiB (1%) 1076
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 64.771 μs (5%) 34.45 KiB (1%) 743
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 18.865 μs (5%) 7.81 KiB (1%) 224
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 17.553 μs (5%) 6.69 KiB (1%) 188
["EpiLatentModels", "PrefixLatentModel", "evaluation", "linked"] 2.128 μs (5%) 4.05 KiB (1%) 46
["EpiLatentModels", "PrefixLatentModel", "evaluation", "standard"] 1.866 μs (5%) 3.42 KiB (1%) 42
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.809 μs (5%) 8.14 KiB (1%) 55
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.462 μs (5%) 7.52 KiB (1%) 51
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 39.635 μs (5%) 19.53 KiB (1%) 363
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 23.774 μs (5%) 14.16 KiB (1%) 256
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 964.611 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 792.619 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "RandomWalk", "evaluation", "linked"] 1.055 μs (5%) 3.33 KiB (1%) 35
["EpiLatentModels", "RandomWalk", "evaluation", "standard"] 733.779 ns (5%) 2.02 KiB (1%) 29
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.857 μs (5%) 9.62 KiB (1%) 46
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.573 μs (5%) 8.31 KiB (1%) 40
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 51.937 μs (5%) 26.28 KiB (1%) 480
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 34.355 μs (5%) 20.22 KiB (1%) 371
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 3.317 μs (5%) 1.08 KiB (1%) 24
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 3.132 μs (5%) 1.08 KiB (1%) 24
["EpiLatentModels", "RecordExpectedLatent", "evaluation", "linked"] 754.047 ns (5%) 1.72 KiB (1%) 26
["EpiLatentModels", "RecordExpectedLatent", "evaluation", "standard"] 576.346 ns (5%) 1.25 KiB (1%) 23
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 868.154 ns (5%) 2.25 KiB (1%) 35
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 673.062 ns (5%) 1.78 KiB (1%) 32
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 35.686 μs (5%) 16.59 KiB (1%) 344
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 20.930 μs (5%) 11.38 KiB (1%) 238
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 890.809 ns (5%) 112 bytes (1%) 3
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 725.634 ns (5%) 112 bytes (1%) 3
["EpiLatentModels", "TransformLatentModel", "evaluation", "linked"] 259.130 ns (5%) 448 bytes (1%) 12
["EpiLatentModels", "TransformLatentModel", "evaluation", "standard"] 246.126 ns (5%) 448 bytes (1%) 12
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 331.751 ns (5%) 768 bytes (1%) 19
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 316.648 ns (5%) 768 bytes (1%) 19
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 5.762 μs (5%) 3.93 KiB (1%) 95
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 5.737 μs (5%) 3.93 KiB (1%) 95
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 477.423 ns (5%) 160 bytes (1%) 4
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 478.179 ns (5%) 160 bytes (1%) 4
["EpiLatentModels", "broadcast_dayofweek", "evaluation", "linked"] 1.780 μs (5%) 5.36 KiB (1%) 57
["EpiLatentModels", "broadcast_dayofweek", "evaluation", "standard"] 1.214 μs (5%) 3.17 KiB (1%) 47
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.717 μs (5%) 11.38 KiB (1%) 68
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.117 μs (5%) 9.19 KiB (1%) 58
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 69.490 μs (5%) 35.97 KiB (1%) 690
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 50.224 μs (5%) 29.03 KiB (1%) 577
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 4.842 μs (5%) 1.00 KiB (1%) 24
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 4.667 μs (5%) 1.00 KiB (1%) 24
["EpiLatentModels", "broadcast_weekly", "evaluation", "linked"] 16.651 μs (5%) 10.03 KiB (1%) 193
["EpiLatentModels", "broadcast_weekly", "evaluation", "standard"] 15.570 μs (5%) 6.52 KiB (1%) 177
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 17.202 μs (5%) 13.23 KiB (1%) 210
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 16.051 μs (5%) 9.39 KiB (1%) 190
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 118.994 μs (5%) 47.12 KiB (1%) 934
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 76.544 μs (5%) 32.80 KiB (1%) 675
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.777 μs (5%) 1.69 KiB (1%) 48
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.145 μs (5%) 1.56 KiB (1%) 44
["EpiObsModels", "Ascertainment", "evaluation", "linked"] 3.241 μs (5%) 3.58 KiB (1%) 63
["EpiObsModels", "Ascertainment", "evaluation", "standard"] 3.161 μs (5%) 3.58 KiB (1%) 63
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 4.085 μs (5%) 3.92 KiB (1%) 72
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 4.020 μs (5%) 3.92 KiB (1%) 72
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 75.362 μs (5%) 38.77 KiB (1%) 918
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 60.032 μs (5%) 34.02 KiB (1%) 815
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.585 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.480 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "LatentDelay", "evaluation", "linked"] 14.346 μs (5%) 22.08 KiB (1%) 412
["EpiObsModels", "LatentDelay", "evaluation", "standard"] 14.788 μs (5%) 22.08 KiB (1%) 412
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 18.254 μs (5%) 22.30 KiB (1%) 419
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 17.713 μs (5%) 22.30 KiB (1%) 419
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 518.662 μs (5%) 293.05 KiB (1%) 7011
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 501.520 μs (5%) 288.30 KiB (1%) 6908
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 51.176 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 49.843 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "NegativeBinomialError", "evaluation", "linked"] 1.126 μs (5%) 400 bytes (1%) 10
["EpiObsModels", "NegativeBinomialError", "evaluation", "standard"] 1.083 μs (5%) 400 bytes (1%) 10
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.578 μs (5%) 624 bytes (1%) 17
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.545 μs (5%) 624 bytes (1%) 17
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 72.255 μs (5%) 35.95 KiB (1%) 903
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 57.719 μs (5%) 31.20 KiB (1%) 800
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.728 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.530 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "PoissonError", "evaluation", "linked"] 1.343 μs (5%) 1.83 KiB (1%) 30
["EpiObsModels", "PoissonError", "evaluation", "standard"] 1.020 μs (5%) 1.47 KiB (1%) 26
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 3.103 μs (5%) 7.78 KiB (1%) 43
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.422 μs (5%) 4.70 KiB (1%) 35
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 164.748 μs (5%) 86.44 KiB (1%) 1870
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 46.797 μs (5%) 29.38 KiB (1%) 727
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.518 μs (5%) 176 bytes (1%) 3
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 4.109 μs (5%) 176 bytes (1%) 3
["EpiObsModels", "PrefixObservationModel", "evaluation", "linked"] 1.646 μs (5%) 1.56 KiB (1%) 34
["EpiObsModels", "PrefixObservationModel", "evaluation", "standard"] 1.575 μs (5%) 1.56 KiB (1%) 34
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.793 μs (5%) 1.78 KiB (1%) 41
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.716 μs (5%) 1.78 KiB (1%) 41
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 26.800 μs (5%) 12.59 KiB (1%) 290
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 13.035 μs (5%) 7.84 KiB (1%) 187
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.119 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 957.053 ns (5%) 96 bytes (1%) 3
["EpiObsModels", "RecordExpectedObs", "evaluation", "linked"] 765.405 ns (5%) 480 bytes (1%) 14
["EpiObsModels", "RecordExpectedObs", "evaluation", "standard"] 712.783 ns (5%) 480 bytes (1%) 14
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 993.900 ns (5%) 704 bytes (1%) 21
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 991.833 ns (5%) 704 bytes (1%) 21
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 45.495 μs (5%) 22.98 KiB (1%) 537
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 31.419 μs (5%) 18.23 KiB (1%) 434
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 3.067 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 3.301 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "StackObservationModels", "evaluation", "linked"] 6.737 μs (5%) 5.81 KiB (1%) 117
["EpiObsModels", "StackObservationModels", "evaluation", "standard"] 6.650 μs (5%) 5.81 KiB (1%) 117
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 7.594 μs (5%) 6.16 KiB (1%) 126
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 7.447 μs (5%) 6.16 KiB (1%) 126
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 87.685 μs (5%) 49.09 KiB (1%) 1044
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 70.873 μs (5%) 44.34 KiB (1%) 941
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.182 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.961 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "TransformObservationModel", "evaluation", "linked"] 1.409 μs (5%) 672 bytes (1%) 16
["EpiObsModels", "TransformObservationModel", "evaluation", "standard"] 1.363 μs (5%) 672 bytes (1%) 16
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.951 μs (5%) 896 bytes (1%) 23
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.802 μs (5%) 896 bytes (1%) 23
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 71.655 μs (5%) 35.59 KiB (1%) 869
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 57.949 μs (5%) 30.84 KiB (1%) 766
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.674 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"] 4.418 μs (5%) 9.59 KiB (1%) 106
["EpiObsModels", "ascertainment_dayofweek", "evaluation", "standard"] 3.807 μs (5%) 8.19 KiB (1%) 97
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 6.260 μs (5%) 16.72 KiB (1%) 117
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 5.889 μs (5%) 15.31 KiB (1%) 108
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 99.827 μs (5%) 58.03 KiB (1%) 1121
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 81.683 μs (5%) 51.88 KiB (1%) 1009
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.273 μs (5%) 160 bytes (1%) 3
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.096 μs (5%) 160 bytes (1%) 3
["EpiObsModels", "observation_error", "missing obs", "evaluation", "linked"] 1.410 μs (5%) 3.05 KiB (1%) 38
["EpiObsModels", "observation_error", "missing obs", "evaluation", "standard"] 919.429 ns (5%) 1.48 KiB (1%) 28
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.822 μs (5%) 4.11 KiB (1%) 48
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.234 μs (5%) 2.55 KiB (1%) 38
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 39.344 μs (5%) 25.78 KiB (1%) 533
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 23.795 μs (5%) 18.80 KiB (1%) 401
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.203 μs (5%) 144 bytes (1%) 3
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.957 μs (5%) 144 bytes (1%) 3
["EpiObsModels", "observation_error", "no missing obs", "evaluation", "linked"] 423.307 ns (5%) 352 bytes (1%) 10
["EpiObsModels", "observation_error", "no missing obs", "evaluation", "standard"] 350.564 ns (5%) 352 bytes (1%) 10
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 553.497 ns (5%) 576 bytes (1%) 17
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 501.299 ns (5%) 576 bytes (1%) 17
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 32.761 μs (5%) 19.64 KiB (1%) 446
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 18.455 μs (5%) 14.22 KiB (1%) 324
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.840 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.612 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "observation_error", "partially missing obs", "evaluation", "linked"] 30.627 μs (5%) 3.02 KiB (1%) 64
["EpiObsModels", "observation_error", "partially missing obs", "evaluation", "standard"] 30.547 μs (5%) 2.70 KiB (1%) 62
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 21.370 μs (5%) 2.73 KiB (1%) 51
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 21.119 μs (5%) 2.42 KiB (1%) 49
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 64.931 μs (5%) 26.11 KiB (1%) 555
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 44.915 μs (5%) 20.38 KiB (1%) 431
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.164 μs (5%) 112 bytes (1%) 3
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.967 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", "IID", "evaluation"]
  • ["EpiLatentModels", "IID", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "IID", "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", "MA", "evaluation"]
  • ["EpiLatentModels", "MA", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)"]
  • ["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff()"]
  • ["EpiLatentModels", "MA", "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 1.11.2
Commit 5e9a32e7af2 (2024-12-01 20:02 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.1 LTS
  uname: Linux 6.8.0-1017-azure #20-Ubuntu SMP Tue Oct 22 03:43:13 UTC 2024 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      15615 s          0 s       1396 s      38849 s          0 s
       #2     0 MHz      17731 s          0 s       1446 s      36660 s          0 s
       #3     0 MHz      15141 s          0 s       1300 s      39412 s          0 s
       #4     0 MHz      17768 s          0 s       1381 s      36683 s          0 s
  Memory: 15.615280151367188 GB (12629.33984375 MB free)
  Uptime: 5599.0 sec
  Load Avg:  1.0  1.02  1.02
  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:                             4890.86
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 vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves user_shstk 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 Reg file data sampling: 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

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