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trigger CI to test CI duration -- Do not merge #574

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trigger CI to test CI duration -- Do not merge #574

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SamuelBrand1
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@SamuelBrand1 SamuelBrand1 commented Jan 20, 2025 •
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This is a test to trigger the CI and record the duration. The reason is that #569 CI is now taking a very long time, despite no evidence of slower model calls from our benchmarking.

NB: I'm not finding a slow down on running the test suite from local, and the inference examples in the documentation seem to run and render in normal time. Quite mysterious.

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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="trigger-ci", subdir="EpiAware")
using EpiAware

@SamuelBrand1 SamuelBrand1 mentioned this pull request Jan 20, 2025
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Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 90.96%. Comparing base (104bdd8) to head (3f29070).

Additional details and impacted files 
@@           Coverage Diff           @@
##             main     #574   +/-   ##
=======================================
  Coverage   90.96%   90.96%           
=======================================
  Files          60       60           
  Lines         863      863           
=======================================
  Hits          785      785           
  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 Jan 2025 - 10:57
    • Baseline: 20 Jan 2025 - 11:32
  • Package commits:
    • Target: 3ed886
    • 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
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.09 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 1.07 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.06 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.08 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "Intercept", "evaluation", "linked"] 1.10 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "Intercept", "evaluation", "standard"] 1.05 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.06 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "MA", "evaluation", "standard"] 0.94 (5%) ✅ 1.00 (1%)
["EpiLatentModels", "RandomWalk", "evaluation", "linked"] 1.69 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 0.95 (5%) ✅ 1.00 (1%)
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 0.91 (5%) ✅ 1.00 (1%)
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.07 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.08 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 0.92 (5%) ✅ 1.00 (1%)
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 1.08 (5%) ❌ 1.00 (1%)
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.07 (5%) ❌ 1.00 (1%)
["EpiObsModels", "observation_error", "partially missing obs", "evaluation", "linked"] 0.94 (5%) ✅ 1.00 (1%)
["EpiObsModels", "observation_error", "partially missing obs", "evaluation", "standard"] 0.94 (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       8138 s          0 s        672 s      18503 s          0 s
       #2     0 MHz      12609 s          0 s        822 s      13893 s          0 s
       #3     0 MHz       8646 s          0 s        739 s      17923 s          0 s
       #4     0 MHz      10366 s          0 s        789 s      16198 s          0 s
  Memory: 15.615280151367188 GB (12757.94921875 MB free)
  Uptime: 2742.48 sec
  Load Avg:  1.03  1.07  1.17
  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      11900 s          0 s       1060 s      35202 s          0 s
       #2     0 MHz      19055 s          0 s       1298 s      27827 s          0 s
       #3     0 MHz      13086 s          0 s       1139 s      33937 s          0 s
       #4     0 MHz      15687 s          0 s       1269 s      31252 s          0 s
  Memory: 15.615280151367188 GB (12447.76171875 MB free)
  Uptime: 4830.35 sec
  Load Avg:  1.01  1.01  1.0
  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 Jan 2025 - 10:57
  • Package commit: 3ed886
  • 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"] 2.097 μs (5%) 416 bytes (1%) 10
["EpiInfModels", "DirectInfections", "evaluation", "linked"] 269.732 ns (5%) 464 bytes (1%) 10
["EpiInfModels", "DirectInfections", "evaluation", "standard"] 263.627 ns (5%) 464 bytes (1%) 10
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 403.741 ns (5%) 816 bytes (1%) 18
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 406.160 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"] 10.229 μs (5%) 5.55 KiB (1%) 125
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 487.426 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 481.774 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "ExpGrowthRate", "evaluation", "linked"] 176.563 ns (5%) 288 bytes (1%) 8
["EpiInfModels", "ExpGrowthRate", "evaluation", "standard"] 169.430 ns (5%) 288 bytes (1%) 8
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 264.590 ns (5%) 544 bytes (1%) 15
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 256.366 ns (5%) 544 bytes (1%) 15
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 10.099 μs (5%) 5.53 KiB (1%) 124
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 10.059 μs (5%) 5.53 KiB (1%) 124
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 493.861 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 493.964 ns (5%) 256 bytes (1%) 7
["EpiLatentModels", "AR", "evaluation", "linked"] 12.813 μs (5%) 8.44 KiB (1%) 171
["EpiLatentModels", "AR", "evaluation", "standard"] 12.062 μs (5%) 5.77 KiB (1%) 158
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 14.006 μs (5%) 16.45 KiB (1%) 188
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 13.165 μs (5%) 13.20 KiB (1%) 171
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 140.272 μs (5%) 59.31 KiB (1%) 1296
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 95.107 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"] 17.834 μs (5%) 6.69 KiB (1%) 188
["EpiLatentModels", "BroadcastLatentModel", "evaluation", "linked"] 1.410 μs (5%) 4.36 KiB (1%) 48
["EpiLatentModels", "BroadcastLatentModel", "evaluation", "standard"] 966.800 ns (5%) 2.61 KiB (1%) 40
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.746 μs (5%) 6.42 KiB (1%) 59
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.315 μs (5%) 4.67 KiB (1%) 51
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 49.893 μs (5%) 25.59 KiB (1%) 465
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 32.060 μs (5%) 17.64 KiB (1%) 353
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.911 μs (5%) 848 bytes (1%) 24
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 2.694 μs (5%) 848 bytes (1%) 24
["EpiLatentModels", "CombineLatentModels", "evaluation", "linked"] 24.847 μs (5%) 50.69 KiB (1%) 433
["EpiLatentModels", "CombineLatentModels", "evaluation", "standard"] 21.159 μs (5%) 33.30 KiB (1%) 381
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 54.422 μs (5%) 115.75 KiB (1%) 905
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 46.507 μs (5%) 80.12 KiB (1%) 793
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 158.716 μs (5%) 105.61 KiB (1%) 1626
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 113.612 μs (5%) 74.91 KiB (1%) 1251
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 19.746 μs (5%) 7.92 KiB (1%) 225
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 18.425 μs (5%) 6.80 KiB (1%) 189
["EpiLatentModels", "ConcatLatentModels", "evaluation", "linked"] 53.049 μs (5%) 41.75 KiB (1%) 576
["EpiLatentModels", "ConcatLatentModels", "evaluation", "standard"] 49.993 μs (5%) 31.62 KiB (1%) 540
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 54.362 μs (5%) 45.27 KiB (1%) 591
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 50.995 μs (5%) 35.14 KiB (1%) 555
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 123.260 μs (5%) 67.14 KiB (1%) 1077
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 102.802 μs (5%) 52.27 KiB (1%) 938
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.383 μs (5%) 1.89 KiB (1%) 46
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.181 μs (5%) 1.89 KiB (1%) 46
["EpiLatentModels", "DiffLatentModel", "evaluation", "linked"] 16.080 μs (5%) 9.78 KiB (1%) 182
["EpiLatentModels", "DiffLatentModel", "evaluation", "standard"] 15.129 μs (5%) 6.41 KiB (1%) 170
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 17.313 μs (5%) 18.09 KiB (1%) 195
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 16.420 μs (5%) 14.72 KiB (1%) 183
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 94.206 μs (5%) 43.50 KiB (1%) 877
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 74.970 μs (5%) 35.38 KiB (1%) 762
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.711 μs (5%) 1.94 KiB (1%) 45
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 6.584 μs (5%) 1.94 KiB (1%) 45
["EpiLatentModels", "HierarchicalNormal", "evaluation", "linked"] 571.612 ns (5%) 1.50 KiB (1%) 20
["EpiLatentModels", "HierarchicalNormal", "evaluation", "standard"] 425.266 ns (5%) 1.19 KiB (1%) 18
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.176 μs (5%) 5.59 KiB (1%) 29
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.052 μs (5%) 5.28 KiB (1%) 27
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 35.657 μs (5%) 17.12 KiB (1%) 338
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 20.950 μs (5%) 12.06 KiB (1%) 233
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 934.433 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 775.157 ns (5%) 176 bytes (1%) 3
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["EpiLatentModels", "IID", "evaluation", "standard"] 197.422 ns (5%) 560 bytes (1%) 10
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 511.581 ns (5%) 3.59 KiB (1%) 17
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 463.052 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"] 13.244 μs (5%) 7.58 KiB (1%) 153
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 402.100 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 410.965 ns (5%) 176 bytes (1%) 3
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["EpiLatentModels", "Intercept", "evaluation", "standard"] 201.460 ns (5%) 400 bytes (1%) 10
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 293.832 ns (5%) 704 bytes (1%) 17
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 279.953 ns (5%) 704 bytes (1%) 17
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 5.218 μs (5%) 3.62 KiB (1%) 87
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 5.306 μs (5%) 3.62 KiB (1%) 87
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 408.565 ns (5%) 208 bytes (1%) 4
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["EpiLatentModels", "MA", "evaluation", "standard"] 1.134 μs (5%) 3.25 KiB (1%) 62
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.792 μs (5%) 14.38 KiB (1%) 85
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.279 μs (5%) 12.48 KiB (1%) 73
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 102.171 μs (5%) 49.22 KiB (1%) 1076
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 64.421 μs (5%) 34.45 KiB (1%) 743
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 18.154 μs (5%) 7.81 KiB (1%) 224
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 17.092 μs (5%) 6.69 KiB (1%) 188
["EpiLatentModels", "PrefixLatentModel", "evaluation", "linked"] 2.019 μs (5%) 4.05 KiB (1%) 46
["EpiLatentModels", "PrefixLatentModel", "evaluation", "standard"] 1.777 μs (5%) 3.42 KiB (1%) 42
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.833 μs (5%) 8.14 KiB (1%) 55
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.470 μs (5%) 7.52 KiB (1%) 51
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 38.352 μs (5%) 19.53 KiB (1%) 363
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 23.373 μs (5%) 14.16 KiB (1%) 256
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["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 787.226 ns (5%) 176 bytes (1%) 3
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["EpiLatentModels", "RandomWalk", "evaluation", "standard"] 719.656 ns (5%) 2.02 KiB (1%) 29
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.845 μs (5%) 9.62 KiB (1%) 46
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.514 μs (5%) 8.31 KiB (1%) 40
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 51.005 μs (5%) 26.28 KiB (1%) 480
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 34.825 μs (5%) 20.22 KiB (1%) 371
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 3.277 μs (5%) 1.08 KiB (1%) 24
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 2.859 μs (5%) 1.08 KiB (1%) 24
["EpiLatentModels", "RecordExpectedLatent", "evaluation", "linked"] 708.634 ns (5%) 1.72 KiB (1%) 26
["EpiLatentModels", "RecordExpectedLatent", "evaluation", "standard"] 523.115 ns (5%) 1.25 KiB (1%) 23
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 883.607 ns (5%) 2.25 KiB (1%) 35
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 681.400 ns (5%) 1.78 KiB (1%) 32
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 35.727 μs (5%) 16.59 KiB (1%) 344
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 20.679 μs (5%) 11.38 KiB (1%) 238
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 867.293 ns (5%) 112 bytes (1%) 3
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 706.916 ns (5%) 112 bytes (1%) 3
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["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 5.594 μs (5%) 3.93 KiB (1%) 95
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 474.658 ns (5%) 160 bytes (1%) 4
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["EpiLatentModels", "broadcast_dayofweek", "evaluation", "linked"] 1.721 μs (5%) 5.36 KiB (1%) 57
["EpiLatentModels", "broadcast_dayofweek", "evaluation", "standard"] 1.211 μs (5%) 3.17 KiB (1%) 47
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.666 μs (5%) 11.38 KiB (1%) 68
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.084 μs (5%) 9.19 KiB (1%) 58
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 67.175 μs (5%) 35.97 KiB (1%) 690
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 49.874 μs (5%) 29.03 KiB (1%) 577
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 4.810 μs (5%) 1.00 KiB (1%) 24
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 4.663 μs (5%) 1.00 KiB (1%) 24
["EpiLatentModels", "broadcast_weekly", "evaluation", "linked"] 16.551 μs (5%) 10.03 KiB (1%) 193
["EpiLatentModels", "broadcast_weekly", "evaluation", "standard"] 15.529 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"] 15.990 μs (5%) 9.39 KiB (1%) 190
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 114.785 μs (5%) 47.12 KiB (1%) 934
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 73.567 μs (5%) 32.80 KiB (1%) 675
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.659 μs (5%) 1.69 KiB (1%) 48
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 4.737 μs (5%) 1.56 KiB (1%) 44
["EpiObsModels", "Ascertainment", "evaluation", "linked"] 3.256 μs (5%) 3.58 KiB (1%) 63
["EpiObsModels", "Ascertainment", "evaluation", "standard"] 3.197 μs (5%) 3.58 KiB (1%) 63
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 4.053 μs (5%) 3.92 KiB (1%) 72
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 4.003 μs (5%) 3.92 KiB (1%) 72
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 75.612 μs (5%) 38.77 KiB (1%) 918
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 60.974 μs (5%) 34.02 KiB (1%) 815
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.582 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.529 μs (5%) 96 bytes (1%) 3
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["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 17.453 μs (5%) 22.30 KiB (1%) 419
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 17.562 μs (5%) 22.30 KiB (1%) 419
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 530.972 μs (5%) 293.05 KiB (1%) 7011
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 510.192 μs (5%) 288.30 KiB (1%) 6908
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["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.525 μs (5%) 624 bytes (1%) 17
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 72.435 μs (5%) 35.95 KiB (1%) 903
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 57.608 μs (5%) 31.20 KiB (1%) 800
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.646 μs (5%) 96 bytes (1%) 3
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["EpiObsModels", "PoissonError", "evaluation", "linked"] 1.337 μs (5%) 1.83 KiB (1%) 30
["EpiObsModels", "PoissonError", "evaluation", "standard"] 1.021 μs (5%) 1.47 KiB (1%) 26
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 3.110 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"] 166.371 μs (5%) 86.44 KiB (1%) 1870
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 48.571 μs (5%) 29.38 KiB (1%) 727
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.073 μs (5%) 176 bytes (1%) 3
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 4.073 μs (5%) 176 bytes (1%) 3
["EpiObsModels", "PrefixObservationModel", "evaluation", "linked"] 1.618 μs (5%) 1.56 KiB (1%) 34
["EpiObsModels", "PrefixObservationModel", "evaluation", "standard"] 1.544 μs (5%) 1.56 KiB (1%) 34
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.759 μs (5%) 1.78 KiB (1%) 41
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.685 μs (5%) 1.78 KiB (1%) 41
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 26.499 μs (5%) 12.59 KiB (1%) 290
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 12.804 μs (5%) 7.84 KiB (1%) 187
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.093 μs (5%) 96 bytes (1%) 3
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["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 987.364 ns (5%) 704 bytes (1%) 21
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 45.334 μs (5%) 22.98 KiB (1%) 537
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 32.270 μs (5%) 18.23 KiB (1%) 434
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 3.108 μs (5%) 96 bytes (1%) 3
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["EpiObsModels", "StackObservationModels", "evaluation", "standard"] 6.665 μs (5%) 5.81 KiB (1%) 117
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 7.584 μs (5%) 6.16 KiB (1%) 126
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 7.504 μs (5%) 6.16 KiB (1%) 126
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 87.444 μs (5%) 49.09 KiB (1%) 1044
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 71.032 μs (5%) 44.34 KiB (1%) 941
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["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 57.658 μs (5%) 30.84 KiB (1%) 766
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["EpiObsModels", "ascertainment_dayofweek", "evaluation", "linked"] 4.344 μs (5%) 9.59 KiB (1%) 106
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["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 6.089 μs (5%) 16.72 KiB (1%) 117
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 5.510 μs (5%) 15.31 KiB (1%) 108
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 95.919 μs (5%) 58.03 KiB (1%) 1121
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 79.398 μs (5%) 51.88 KiB (1%) 1009
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.225 μs (5%) 160 bytes (1%) 3
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.080 μs (5%) 160 bytes (1%) 3
["EpiObsModels", "observation_error", "missing obs", "evaluation", "linked"] 1.405 μs (5%) 3.05 KiB (1%) 38
["EpiObsModels", "observation_error", "missing obs", "evaluation", "standard"] 863.206 ns (5%) 1.48 KiB (1%) 28
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.761 μs (5%) 4.11 KiB (1%) 48
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.209 μs (5%) 2.55 KiB (1%) 38
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 40.325 μs (5%) 25.78 KiB (1%) 533
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 23.494 μs (5%) 18.80 KiB (1%) 401
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.177 μs (5%) 144 bytes (1%) 3
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.976 μs (5%) 144 bytes (1%) 3
["EpiObsModels", "observation_error", "no missing obs", "evaluation", "linked"] 411.220 ns (5%) 352 bytes (1%) 10
["EpiObsModels", "observation_error", "no missing obs", "evaluation", "standard"] 356.276 ns (5%) 352 bytes (1%) 10
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 523.440 ns (5%) 576 bytes (1%) 17
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 461.883 ns (5%) 576 bytes (1%) 17
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 32.671 μs (5%) 19.64 KiB (1%) 446
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 18.094 μs (5%) 14.22 KiB (1%) 324
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.853 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"] 29.886 μs (5%) 3.02 KiB (1%) 64
["EpiObsModels", "observation_error", "partially missing obs", "evaluation", "standard"] 29.776 μs (5%) 2.70 KiB (1%) 62
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 21.270 μs (5%) 2.73 KiB (1%) 51
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 21.089 μs (5%) 2.42 KiB (1%) 49
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 63.909 μs (5%) 26.11 KiB (1%) 555
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 44.263 μs (5%) 20.38 KiB (1%) 431
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.157 μs (5%) 112 bytes (1%) 3
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.935 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       8138 s          0 s        672 s      18503 s          0 s
       #2     0 MHz      12609 s          0 s        822 s      13893 s          0 s
       #3     0 MHz       8646 s          0 s        739 s      17923 s          0 s
       #4     0 MHz      10366 s          0 s        789 s      16198 s          0 s
  Memory: 15.615280151367188 GB (12757.94921875 MB free)
  Uptime: 2742.48 sec
  Load Avg:  1.03  1.07  1.17
  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 Jan 2025 - 11:32
  • 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"] 2.089 μs (5%) 416 bytes (1%) 10
["EpiInfModels", "DirectInfections", "evaluation", "linked"] 266.767 ns (5%) 464 bytes (1%) 10
["EpiInfModels", "DirectInfections", "evaluation", "standard"] 268.675 ns (5%) 464 bytes (1%) 10
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 415.503 ns (5%) 816 bytes (1%) 18
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 414.020 ns (5%) 816 bytes (1%) 18
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 10.379 μs (5%) 5.55 KiB (1%) 125
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 10.260 μs (5%) 5.55 KiB (1%) 125
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 492.052 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 496.649 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "ExpGrowthRate", "evaluation", "linked"] 181.439 ns (5%) 288 bytes (1%) 8
["EpiInfModels", "ExpGrowthRate", "evaluation", "standard"] 170.995 ns (5%) 288 bytes (1%) 8
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 261.426 ns (5%) 544 bytes (1%) 15
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 255.124 ns (5%) 544 bytes (1%) 15
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 10.139 μs (5%) 5.53 KiB (1%) 124
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 10.029 μs (5%) 5.53 KiB (1%) 124
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 500.830 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 496.701 ns (5%) 256 bytes (1%) 7
["EpiLatentModels", "AR", "evaluation", "linked"] 12.724 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"] 14.618 μs (5%) 16.45 KiB (1%) 188
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 13.355 μs (5%) 13.20 KiB (1%) 171
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 140.252 μs (5%) 59.31 KiB (1%) 1296
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 94.296 μs (5%) 43.33 KiB (1%) 960
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 17.533 μs (5%) 7.81 KiB (1%) 224
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 17.513 μs (5%) 6.69 KiB (1%) 188
["EpiLatentModels", "BroadcastLatentModel", "evaluation", "linked"] 1.369 μs (5%) 4.36 KiB (1%) 48
["EpiLatentModels", "BroadcastLatentModel", "evaluation", "standard"] 954.800 ns (5%) 2.61 KiB (1%) 40
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.782 μs (5%) 6.42 KiB (1%) 59
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.329 μs (5%) 4.67 KiB (1%) 51
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 49.092 μs (5%) 25.59 KiB (1%) 465
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 29.895 μs (5%) 17.64 KiB (1%) 353
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.977 μs (5%) 848 bytes (1%) 24
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 2.750 μs (5%) 848 bytes (1%) 24
["EpiLatentModels", "CombineLatentModels", "evaluation", "linked"] 25.077 μs (5%) 50.69 KiB (1%) 433
["EpiLatentModels", "CombineLatentModels", "evaluation", "standard"] 21.450 μs (5%) 33.30 KiB (1%) 381
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 55.654 μs (5%) 115.75 KiB (1%) 905
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 47.018 μs (5%) 80.12 KiB (1%) 793
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 161.692 μs (5%) 105.61 KiB (1%) 1626
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 114.253 μs (5%) 74.91 KiB (1%) 1251
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 19.716 μs (5%) 7.92 KiB (1%) 225
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 18.145 μs (5%) 6.80 KiB (1%) 189
["EpiLatentModels", "ConcatLatentModels", "evaluation", "linked"] 52.277 μs (5%) 41.75 KiB (1%) 576
["EpiLatentModels", "ConcatLatentModels", "evaluation", "standard"] 48.851 μs (5%) 31.62 KiB (1%) 540
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 53.961 μs (5%) 45.27 KiB (1%) 591
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 50.144 μs (5%) 35.14 KiB (1%) 555
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 123.381 μs (5%) 67.14 KiB (1%) 1077
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 102.893 μs (5%) 52.27 KiB (1%) 938
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.378 μs (5%) 1.89 KiB (1%) 46
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.185 μs (5%) 1.89 KiB (1%) 46
["EpiLatentModels", "DiffLatentModel", "evaluation", "linked"] 16.070 μs (5%) 9.78 KiB (1%) 182
["EpiLatentModels", "DiffLatentModel", "evaluation", "standard"] 15.128 μs (5%) 6.41 KiB (1%) 170
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 17.543 μs (5%) 18.09 KiB (1%) 195
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 16.361 μs (5%) 14.72 KiB (1%) 183
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 93.545 μs (5%) 43.50 KiB (1%) 877
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 74.149 μs (5%) 35.38 KiB (1%) 762
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.330 μs (5%) 1.94 KiB (1%) 45
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 6.550 μs (5%) 1.94 KiB (1%) 45
["EpiLatentModels", "HierarchicalNormal", "evaluation", "linked"] 555.070 ns (5%) 1.50 KiB (1%) 20
["EpiLatentModels", "HierarchicalNormal", "evaluation", "standard"] 425.417 ns (5%) 1.19 KiB (1%) 18
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.193 μs (5%) 5.59 KiB (1%) 29
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.035 μs (5%) 5.28 KiB (1%) 27
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 35.416 μs (5%) 17.12 KiB (1%) 338
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 20.599 μs (5%) 12.06 KiB (1%) 233
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 963.190 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 794.356 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "IID", "evaluation", "linked"] 200.826 ns (5%) 560 bytes (1%) 10
["EpiLatentModels", "IID", "evaluation", "standard"] 195.120 ns (5%) 560 bytes (1%) 10
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 472.455 ns (5%) 3.59 KiB (1%) 17
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 451.573 ns (5%) 3.59 KiB (1%) 17
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 13.385 μs (5%) 7.58 KiB (1%) 153
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 13.215 μs (5%) 7.58 KiB (1%) 153
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 393.213 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 399.495 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "Intercept", "evaluation", "linked"] 188.927 ns (5%) 400 bytes (1%) 10
["EpiLatentModels", "Intercept", "evaluation", "standard"] 191.531 ns (5%) 400 bytes (1%) 10
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 286.841 ns (5%) 704 bytes (1%) 17
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 263.528 ns (5%) 704 bytes (1%) 17
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 5.375 μs (5%) 3.62 KiB (1%) 87
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 5.378 μs (5%) 3.62 KiB (1%) 87
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 394.590 ns (5%) 208 bytes (1%) 4
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 407.010 ns (5%) 208 bytes (1%) 4
["EpiLatentModels", "MA", "evaluation", "linked"] 1.659 μs (5%) 4.70 KiB (1%) 72
["EpiLatentModels", "MA", "evaluation", "standard"] 1.202 μs (5%) 3.25 KiB (1%) 62
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.867 μs (5%) 14.38 KiB (1%) 85
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.312 μs (5%) 12.48 KiB (1%) 73
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 103.012 μs (5%) 49.22 KiB (1%) 1076
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 63.508 μs (5%) 34.45 KiB (1%) 743
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 18.254 μs (5%) 7.81 KiB (1%) 224
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 17.062 μs (5%) 6.69 KiB (1%) 188
["EpiLatentModels", "PrefixLatentModel", "evaluation", "linked"] 2.035 μs (5%) 4.05 KiB (1%) 46
["EpiLatentModels", "PrefixLatentModel", "evaluation", "standard"] 1.786 μs (5%) 3.42 KiB (1%) 42
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.817 μs (5%) 8.14 KiB (1%) 55
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.558 μs (5%) 7.52 KiB (1%) 51
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 38.422 μs (5%) 19.53 KiB (1%) 363
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 23.334 μs (5%) 14.16 KiB (1%) 256
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 968.684 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 792.116 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "RandomWalk", "evaluation", "linked"] 1.012 μs (5%) 3.33 KiB (1%) 35
["EpiLatentModels", "RandomWalk", "evaluation", "standard"] 687.321 ns (5%) 2.02 KiB (1%) 29
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.948 μs (5%) 9.62 KiB (1%) 46
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.540 μs (5%) 8.31 KiB (1%) 40
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 50.214 μs (5%) 26.28 KiB (1%) 480
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 33.763 μs (5%) 20.22 KiB (1%) 371
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 3.336 μs (5%) 1.08 KiB (1%) 24
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 3.146 μs (5%) 1.08 KiB (1%) 24
["EpiLatentModels", "RecordExpectedLatent", "evaluation", "linked"] 706.810 ns (5%) 1.72 KiB (1%) 26
["EpiLatentModels", "RecordExpectedLatent", "evaluation", "standard"] 528.895 ns (5%) 1.25 KiB (1%) 23
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 854.267 ns (5%) 2.25 KiB (1%) 35
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 683.053 ns (5%) 1.78 KiB (1%) 32
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 35.416 μs (5%) 16.59 KiB (1%) 344
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 20.498 μs (5%) 11.38 KiB (1%) 238
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 882.469 ns (5%) 112 bytes (1%) 3
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 718.447 ns (5%) 112 bytes (1%) 3
["EpiLatentModels", "TransformLatentModel", "evaluation", "linked"] 248.132 ns (5%) 448 bytes (1%) 12
["EpiLatentModels", "TransformLatentModel", "evaluation", "standard"] 236.484 ns (5%) 448 bytes (1%) 12
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 319.939 ns (5%) 768 bytes (1%) 19
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 322.239 ns (5%) 768 bytes (1%) 19
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 5.611 μs (5%) 3.93 KiB (1%) 95
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 5.544 μs (5%) 3.93 KiB (1%) 95
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 469.744 ns (5%) 160 bytes (1%) 4
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 468.020 ns (5%) 160 bytes (1%) 4
["EpiLatentModels", "broadcast_dayofweek", "evaluation", "linked"] 1.686 μs (5%) 5.36 KiB (1%) 57
["EpiLatentModels", "broadcast_dayofweek", "evaluation", "standard"] 1.178 μs (5%) 3.17 KiB (1%) 47
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.652 μs (5%) 11.38 KiB (1%) 68
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.080 μs (5%) 9.19 KiB (1%) 58
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 67.506 μs (5%) 35.97 KiB (1%) 690
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 49.923 μs (5%) 29.03 KiB (1%) 577
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 4.838 μs (5%) 1.00 KiB (1%) 24
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 4.337 μs (5%) 1.00 KiB (1%) 24
["EpiLatentModels", "broadcast_weekly", "evaluation", "linked"] 16.481 μs (5%) 10.03 KiB (1%) 193
["EpiLatentModels", "broadcast_weekly", "evaluation", "standard"] 15.449 μs (5%) 6.52 KiB (1%) 177
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 17.273 μs (5%) 13.23 KiB (1%) 210
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 15.920 μs (5%) 9.39 KiB (1%) 190
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 116.007 μs (5%) 47.12 KiB (1%) 934
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 73.437 μs (5%) 32.80 KiB (1%) 675
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.723 μs (5%) 1.69 KiB (1%) 48
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.131 μs (5%) 1.56 KiB (1%) 44
["EpiObsModels", "Ascertainment", "evaluation", "linked"] 3.331 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"] 4.003 μs (5%) 3.92 KiB (1%) 72
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 4.019 μs (5%) 3.92 KiB (1%) 72
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 75.721 μs (5%) 38.77 KiB (1%) 918
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 60.833 μs (5%) 34.02 KiB (1%) 815
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.625 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.647 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "LatentDelay", "evaluation", "linked"] 14.186 μs (5%) 22.08 KiB (1%) 412
["EpiObsModels", "LatentDelay", "evaluation", "standard"] 14.076 μs (5%) 22.08 KiB (1%) 412
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 18.104 μs (5%) 22.30 KiB (1%) 419
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 18.354 μs (5%) 22.30 KiB (1%) 419
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 533.226 μs (5%) 293.05 KiB (1%) 7011
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 513.669 μs (5%) 288.30 KiB (1%) 6908
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 52.578 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 50.995 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "NegativeBinomialError", "evaluation", "linked"] 1.107 μs (5%) 400 bytes (1%) 10
["EpiObsModels", "NegativeBinomialError", "evaluation", "standard"] 1.071 μs (5%) 400 bytes (1%) 10
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.665 μs (5%) 624 bytes (1%) 17
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.547 μs (5%) 624 bytes (1%) 17
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 72.265 μs (5%) 35.95 KiB (1%) 903
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 53.400 μs (5%) 31.20 KiB (1%) 800
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.739 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.514 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "PoissonError", "evaluation", "linked"] 1.337 μs (5%) 1.83 KiB (1%) 30
["EpiObsModels", "PoissonError", "evaluation", "standard"] 1.012 μs (5%) 1.47 KiB (1%) 26
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 3.126 μs (5%) 7.78 KiB (1%) 43
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.446 μs (5%) 4.70 KiB (1%) 35
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 166.271 μs (5%) 86.44 KiB (1%) 1870
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 47.678 μs (5%) 29.38 KiB (1%) 727
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.071 μs (5%) 176 bytes (1%) 3
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 4.184 μs (5%) 176 bytes (1%) 3
["EpiObsModels", "PrefixObservationModel", "evaluation", "linked"] 1.585 μs (5%) 1.56 KiB (1%) 34
["EpiObsModels", "PrefixObservationModel", "evaluation", "standard"] 1.520 μs (5%) 1.56 KiB (1%) 34
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.769 μs (5%) 1.78 KiB (1%) 41
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.700 μs (5%) 1.78 KiB (1%) 41
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 26.610 μs (5%) 12.59 KiB (1%) 290
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 13.014 μs (5%) 7.84 KiB (1%) 187
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.116 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 990.429 ns (5%) 96 bytes (1%) 3
["EpiObsModels", "RecordExpectedObs", "evaluation", "linked"] 751.149 ns (5%) 480 bytes (1%) 14
["EpiObsModels", "RecordExpectedObs", "evaluation", "standard"] 707.585 ns (5%) 480 bytes (1%) 14
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.041 μs (5%) 704 bytes (1%) 21
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 978.467 ns (5%) 704 bytes (1%) 21
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 45.805 μs (5%) 22.98 KiB (1%) 537
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 31.869 μs (5%) 18.23 KiB (1%) 434
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.909 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 2.967 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "StackObservationModels", "evaluation", "linked"] 6.660 μs (5%) 5.81 KiB (1%) 117
["EpiObsModels", "StackObservationModels", "evaluation", "standard"] 6.522 μs (5%) 5.81 KiB (1%) 117
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 7.419 μs (5%) 6.16 KiB (1%) 126
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 7.276 μs (5%) 6.16 KiB (1%) 126
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 88.515 μs (5%) 49.09 KiB (1%) 1044
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 70.812 μs (5%) 44.34 KiB (1%) 941
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.129 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.973 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "TransformObservationModel", "evaluation", "linked"] 1.424 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"] 1.871 μs (5%) 896 bytes (1%) 23
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.787 μs (5%) 896 bytes (1%) 23
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 71.825 μs (5%) 35.59 KiB (1%) 869
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 57.908 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"] 5.455 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "ascertainment_dayofweek", "evaluation", "linked"] 4.440 μs (5%) 9.59 KiB (1%) 106
["EpiObsModels", "ascertainment_dayofweek", "evaluation", "standard"] 3.793 μs (5%) 8.19 KiB (1%) 97
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 6.234 μs (5%) 16.72 KiB (1%) 117
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 5.692 μs (5%) 15.31 KiB (1%) 108
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 95.789 μs (5%) 58.03 KiB (1%) 1121
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 78.517 μs (5%) 51.88 KiB (1%) 1009
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.345 μs (5%) 160 bytes (1%) 3
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.104 μs (5%) 160 bytes (1%) 3
["EpiObsModels", "observation_error", "missing obs", "evaluation", "linked"] 1.409 μs (5%) 3.05 KiB (1%) 38
["EpiObsModels", "observation_error", "missing obs", "evaluation", "standard"] 886.566 ns (5%) 1.48 KiB (1%) 28
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.789 μs (5%) 4.11 KiB (1%) 48
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.205 μs (5%) 2.55 KiB (1%) 38
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 39.995 μs (5%) 25.78 KiB (1%) 533
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 23.423 μs (5%) 18.80 KiB (1%) 401
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.191 μs (5%) 144 bytes (1%) 3
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.974 μs (5%) 144 bytes (1%) 3
["EpiObsModels", "observation_error", "no missing obs", "evaluation", "linked"] 406.160 ns (5%) 352 bytes (1%) 10
["EpiObsModels", "observation_error", "no missing obs", "evaluation", "standard"] 348.453 ns (5%) 352 bytes (1%) 10
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 532.455 ns (5%) 576 bytes (1%) 17
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 471.183 ns (5%) 576 bytes (1%) 17
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 33.162 μs (5%) 19.64 KiB (1%) 446
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 18.404 μs (5%) 14.22 KiB (1%) 324
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.857 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.614 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "observation_error", "partially missing obs", "evaluation", "linked"] 31.879 μs (5%) 3.02 KiB (1%) 64
["EpiObsModels", "observation_error", "partially missing obs", "evaluation", "standard"] 31.749 μs (5%) 2.70 KiB (1%) 62
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 21.340 μs (5%) 2.73 KiB (1%) 51
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 21.069 μs (5%) 2.42 KiB (1%) 49
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 65.232 μs (5%) 26.11 KiB (1%) 555
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 44.793 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"] 1.941 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      11900 s          0 s       1060 s      35202 s          0 s
       #2     0 MHz      19055 s          0 s       1298 s      27827 s          0 s
       #3     0 MHz      13086 s          0 s       1139 s      33937 s          0 s
       #4     0 MHz      15687 s          0 s       1269 s      31252 s          0 s
  Memory: 15.615280151367188 GB (12447.76171875 MB free)
  Uptime: 4830.35 sec
  Load Avg:  1.01  1.01  1.0
  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

@SamuelBrand1
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Closing this test PR with the note that all the CI runs where < 30mins.

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@SamuelBrand1 @codecov-commenter