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DynamicPPL bump to 0.32 #581

Merged
merged 1 commit into from
Jan 21, 2025
Merged

DynamicPPL bump to 0.32 #581

merged 1 commit into from
Jan 21, 2025

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SamuelBrand1
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This small PR bumps DPPL to 0.32 using the new CI approach from #580 .

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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="bump-dppl-0-32", subdir="EpiAware")
using EpiAware

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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: 21 Jan 2025 - 01:30
    • Baseline: 21 Jan 2025 - 02:06
  • Package commits:
    • Target: 3ac097
    • Baseline: 3d51b3
  • Julia commits:
    • Target: 5e9a32
    • Baseline: 5e9a32
  • Julia command flags:
    • Target: None
    • Baseline: None
  • Environment variables:
    • Target: None
    • Baseline: None

Results

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

ID time ratio memory ratio
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.11 (5%) ❌ 1.00 (1%)
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.11 (5%) ❌ 1.00 (1%)
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 0.95 (5%) ✅ 1.00 (1%)
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.09 (5%) ❌ 1.00 (1%)
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.09 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.07 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.06 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.05 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.05 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.07 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.06 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.12 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.11 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 0.95 (5%) ✅ 1.00 (1%)
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.07 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.10 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.12 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.09 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.11 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.09 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.06 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.15 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.12 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.12 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.12 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.11 (5%) ❌ 1.00 (1%)
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.09 (5%) ❌ 1.00 (1%)
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.13 (5%) ❌ 1.00 (1%)
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.15 (5%) ❌ 1.00 (1%)
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.12 (5%) ❌ 1.00 (1%)
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.13 (5%) ❌ 1.00 (1%)
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.13 (5%) ❌ 1.00 (1%)
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.14 (5%) ❌ 1.00 (1%)
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.28 (5%) ❌ 1.00 (1%)
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.18 (5%) ❌ 1.00 (1%)
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.14 (5%) ❌ 1.00 (1%)
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.09 (5%) ❌ 1.00 (1%)
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.13 (5%) ❌ 1.00 (1%)
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.13 (5%) ❌ 1.00 (1%)
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.16 (5%) ❌ 1.00 (1%)
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.13 (5%) ❌ 1.00 (1%)
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.15 (5%) ❌ 1.00 (1%)
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.14 (5%) ❌ 1.00 (1%)
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.17 (5%) ❌ 1.00 (1%)
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.12 (5%) ❌ 1.00 (1%)
["EpiObsModels", "observation_error", "missing obs", "evaluation", "linked"] 0.95 (5%) ✅ 1.00 (1%)
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 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       9862 s          0 s        759 s      17556 s          0 s
       #2     0 MHz      10174 s          0 s        805 s      17215 s          0 s
       #3     0 MHz       9872 s          0 s        723 s      17646 s          0 s
       #4     0 MHz      10974 s          0 s        841 s      16408 s          0 s
  Memory: 15.615276336669922 GB (12683.2890625 MB free)
  Uptime: 2832.56 sec
  Load Avg:  1.02  1.02  1.12
  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      14140 s          0 s       1210 s      34374 s          0 s
       #2     0 MHz      16941 s          0 s       1332 s      31472 s          0 s
       #3     0 MHz      13382 s          0 s       1110 s      35296 s          0 s
       #4     0 MHz      17078 s          0 s       1306 s      31394 s          0 s
  Memory: 15.615276336669922 GB (12583.83984375 MB free)
  Uptime: 4990.38 sec
  Load Avg:  1.15  1.08  1.03
  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: 21 Jan 2025 - 1:30
  • Package commit: 3ac097
  • 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"] 2.088 μs (5%) 416 bytes (1%) 10
["EpiInfModels", "DirectInfections", "evaluation", "linked"] 265.646 ns (5%) 464 bytes (1%) 10
["EpiInfModels", "DirectInfections", "evaluation", "standard"] 265.644 ns (5%) 464 bytes (1%) 10
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 410.915 ns (5%) 816 bytes (1%) 18
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 402.050 ns (5%) 816 bytes (1%) 18
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 10.439 μs (5%) 5.55 KiB (1%) 125
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 10.560 μs (5%) 5.55 KiB (1%) 125
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 545.990 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 551.703 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "ExpGrowthRate", "evaluation", "linked"] 177.257 ns (5%) 288 bytes (1%) 8
["EpiInfModels", "ExpGrowthRate", "evaluation", "standard"] 170.048 ns (5%) 288 bytes (1%) 8
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 262.929 ns (5%) 544 bytes (1%) 15
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 258.510 ns (5%) 544 bytes (1%) 15
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 10.499 μs (5%) 5.53 KiB (1%) 124
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 10.580 μs (5%) 5.53 KiB (1%) 124
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 563.182 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 550.249 ns (5%) 256 bytes (1%) 7
["EpiLatentModels", "AR", "evaluation", "linked"] 13.195 μs (5%) 8.44 KiB (1%) 171
["EpiLatentModels", "AR", "evaluation", "standard"] 12.393 μs (5%) 5.77 KiB (1%) 158
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 14.827 μs (5%) 16.45 KiB (1%) 188
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 13.716 μs (5%) 13.20 KiB (1%) 171
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["EpiLatentModels", "BroadcastLatentModel", "evaluation", "standard"] 938.929 ns (5%) 2.61 KiB (1%) 40
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.825 μs (5%) 6.42 KiB (1%) 59
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.323 μs (5%) 4.67 KiB (1%) 51
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["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 114.733 μs (5%) 74.91 KiB (1%) 1251
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 20.048 μs (5%) 7.92 KiB (1%) 225
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["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 877.926 ns (5%) 2.25 KiB (1%) 35
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["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.188 μs (5%) 1.56 KiB (1%) 44
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["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 58.759 μs (5%) 31.20 KiB (1%) 800
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["EpiObsModels", "PoissonError", "evaluation", "standard"] 1.028 μs (5%) 1.47 KiB (1%) 26
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["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 166.500 μs (5%) 86.44 KiB (1%) 1870
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["EpiObsModels", "TransformObservationModel", "evaluation", "standard"] 1.365 μs (5%) 672 bytes (1%) 16
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.928 μs (5%) 896 bytes (1%) 23
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.814 μs (5%) 896 bytes (1%) 23
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 72.104 μs (5%) 35.59 KiB (1%) 869
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 58.379 μs (5%) 30.84 KiB (1%) 766
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.604 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 6.303 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "ascertainment_dayofweek", "evaluation", "linked"] 4.328 μs (5%) 9.59 KiB (1%) 106
["EpiObsModels", "ascertainment_dayofweek", "evaluation", "standard"] 3.803 μs (5%) 8.19 KiB (1%) 97
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 6.272 μs (5%) 16.72 KiB (1%) 117
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 5.741 μs (5%) 15.31 KiB (1%) 108
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 98.523 μs (5%) 58.03 KiB (1%) 1121
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 79.948 μs (5%) 51.88 KiB (1%) 1009
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.170 μs (5%) 160 bytes (1%) 3
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.923 μs (5%) 160 bytes (1%) 3
["EpiObsModels", "observation_error", "missing obs", "evaluation", "linked"] 1.419 μs (5%) 3.05 KiB (1%) 38
["EpiObsModels", "observation_error", "missing obs", "evaluation", "standard"] 888.455 ns (5%) 1.48 KiB (1%) 28
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.797 μs (5%) 4.11 KiB (1%) 48
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.226 μs (5%) 2.55 KiB (1%) 38
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 41.196 μs (5%) 25.78 KiB (1%) 533
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 24.265 μs (5%) 18.80 KiB (1%) 401
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.225 μs (5%) 144 bytes (1%) 3
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.985 μs (5%) 144 bytes (1%) 3
["EpiObsModels", "observation_error", "no missing obs", "evaluation", "linked"] 413.935 ns (5%) 352 bytes (1%) 10
["EpiObsModels", "observation_error", "no missing obs", "evaluation", "standard"] 353.615 ns (5%) 352 bytes (1%) 10
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 523.644 ns (5%) 576 bytes (1%) 17
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 470.469 ns (5%) 576 bytes (1%) 17
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 33.582 μs (5%) 19.64 KiB (1%) 446
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 18.385 μs (5%) 14.22 KiB (1%) 324
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.899 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"] 31.879 μs (5%) 3.02 KiB (1%) 64
["EpiObsModels", "observation_error", "partially missing obs", "evaluation", "standard"] 31.679 μs (5%) 2.70 KiB (1%) 62
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 21.280 μs (5%) 2.73 KiB (1%) 51
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 21.079 μs (5%) 2.42 KiB (1%) 49
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 65.862 μs (5%) 26.11 KiB (1%) 555
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 45.244 μs (5%) 20.38 KiB (1%) 431
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.168 μs (5%) 112 bytes (1%) 3
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.990 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       9862 s          0 s        759 s      17556 s          0 s
       #2     0 MHz      10174 s          0 s        805 s      17215 s          0 s
       #3     0 MHz       9872 s          0 s        723 s      17646 s          0 s
       #4     0 MHz      10974 s          0 s        841 s      16408 s          0 s
  Memory: 15.615276336669922 GB (12683.2890625 MB free)
  Uptime: 2832.56 sec
  Load Avg:  1.02  1.02  1.12
  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: 21 Jan 2025 - 2:6
  • Package commit: 3d51b3
  • 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"] 2.123 μs (5%) 416 bytes (1%) 10
["EpiInfModels", "DirectInfections", "evaluation", "linked"] 278.161 ns (5%) 464 bytes (1%) 10
["EpiInfModels", "DirectInfections", "evaluation", "standard"] 267.867 ns (5%) 464 bytes (1%) 10
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 421.835 ns (5%) 816 bytes (1%) 18
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 412.415 ns (5%) 816 bytes (1%) 18
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 10.499 μs (5%) 5.55 KiB (1%) 125
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 10.399 μs (5%) 5.55 KiB (1%) 125
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 493.546 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "DirectInfections", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 499.227 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "ExpGrowthRate", "evaluation", "linked"] 178.509 ns (5%) 288 bytes (1%) 8
["EpiInfModels", "ExpGrowthRate", "evaluation", "standard"] 168.617 ns (5%) 288 bytes (1%) 8
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 277.463 ns (5%) 544 bytes (1%) 15
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 256.036 ns (5%) 544 bytes (1%) 15
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 10.209 μs (5%) 5.53 KiB (1%) 124
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 10.349 μs (5%) 5.53 KiB (1%) 124
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 515.125 ns (5%) 256 bytes (1%) 7
["EpiInfModels", "ExpGrowthRate", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 506.907 ns (5%) 256 bytes (1%) 7
["EpiLatentModels", "AR", "evaluation", "linked"] 13.154 μs (5%) 8.44 KiB (1%) 171
["EpiLatentModels", "AR", "evaluation", "standard"] 12.312 μs (5%) 5.77 KiB (1%) 158
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 14.296 μs (5%) 16.45 KiB (1%) 188
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 13.525 μs (5%) 13.20 KiB (1%) 171
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 141.592 μs (5%) 59.31 KiB (1%) 1296
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 96.739 μs (5%) 43.33 KiB (1%) 960
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 18.474 μs (5%) 7.81 KiB (1%) 224
["EpiLatentModels", "AR", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 17.533 μs (5%) 6.69 KiB (1%) 188
["EpiLatentModels", "BroadcastLatentModel", "evaluation", "linked"] 1.395 μs (5%) 4.36 KiB (1%) 48
["EpiLatentModels", "BroadcastLatentModel", "evaluation", "standard"] 948.545 ns (5%) 2.61 KiB (1%) 40
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.917 μs (5%) 6.42 KiB (1%) 59
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.353 μs (5%) 4.67 KiB (1%) 51
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 50.645 μs (5%) 25.59 KiB (1%) 465
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 32.180 μs (5%) 17.64 KiB (1%) 353
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.933 μs (5%) 848 bytes (1%) 24
["EpiLatentModels", "BroadcastLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 2.743 μs (5%) 848 bytes (1%) 24
["EpiLatentModels", "CombineLatentModels", "evaluation", "linked"] 25.507 μs (5%) 50.69 KiB (1%) 433
["EpiLatentModels", "CombineLatentModels", "evaluation", "standard"] 20.898 μs (5%) 33.30 KiB (1%) 381
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 56.916 μs (5%) 115.75 KiB (1%) 905
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 47.819 μs (5%) 80.12 KiB (1%) 793
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 167.361 μs (5%) 105.61 KiB (1%) 1626
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 116.917 μs (5%) 74.91 KiB (1%) 1251
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 19.416 μs (5%) 7.92 KiB (1%) 225
["EpiLatentModels", "CombineLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 18.374 μs (5%) 6.80 KiB (1%) 189
["EpiLatentModels", "ConcatLatentModels", "evaluation", "linked"] 53.981 μs (5%) 41.75 KiB (1%) 576
["EpiLatentModels", "ConcatLatentModels", "evaluation", "standard"] 51.375 μs (5%) 31.62 KiB (1%) 540
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 56.054 μs (5%) 45.27 KiB (1%) 591
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 52.868 μs (5%) 35.14 KiB (1%) 555
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 129.851 μs (5%) 67.14 KiB (1%) 1077
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 107.910 μs (5%) 52.27 KiB (1%) 938
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.308 μs (5%) 1.89 KiB (1%) 46
["EpiLatentModels", "ConcatLatentModels", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.111 μs (5%) 1.89 KiB (1%) 46
["EpiLatentModels", "DiffLatentModel", "evaluation", "linked"] 16.941 μs (5%) 9.78 KiB (1%) 182
["EpiLatentModels", "DiffLatentModel", "evaluation", "standard"] 15.919 μs (5%) 6.41 KiB (1%) 170
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 18.174 μs (5%) 18.09 KiB (1%) 195
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 17.272 μs (5%) 14.72 KiB (1%) 183
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 97.772 μs (5%) 43.50 KiB (1%) 877
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 78.175 μs (5%) 35.38 KiB (1%) 762
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.694 μs (5%) 1.94 KiB (1%) 45
["EpiLatentModels", "DiffLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 6.468 μs (5%) 1.94 KiB (1%) 45
["EpiLatentModels", "HierarchicalNormal", "evaluation", "linked"] 562.387 ns (5%) 1.50 KiB (1%) 20
["EpiLatentModels", "HierarchicalNormal", "evaluation", "standard"] 421.839 ns (5%) 1.19 KiB (1%) 18
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.172 μs (5%) 5.59 KiB (1%) 29
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.026 μs (5%) 5.28 KiB (1%) 27
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 36.157 μs (5%) 17.12 KiB (1%) 338
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 21.380 μs (5%) 12.06 KiB (1%) 233
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 980.789 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "HierarchicalNormal", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 803.247 ns (5%) 176 bytes (1%) 3
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["EpiLatentModels", "IID", "evaluation", "standard"] 191.099 ns (5%) 560 bytes (1%) 10
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 522.364 ns (5%) 3.59 KiB (1%) 17
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 525.162 ns (5%) 3.59 KiB (1%) 17
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 13.545 μs (5%) 7.58 KiB (1%) 153
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 13.515 μs (5%) 7.58 KiB (1%) 153
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 417.005 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "IID", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 408.360 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "Intercept", "evaluation", "linked"] 209.664 ns (5%) 400 bytes (1%) 10
["EpiLatentModels", "Intercept", "evaluation", "standard"] 192.276 ns (5%) 400 bytes (1%) 10
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 295.015 ns (5%) 704 bytes (1%) 17
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 278.136 ns (5%) 704 bytes (1%) 17
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 5.477 μs (5%) 3.62 KiB (1%) 87
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 5.343 μs (5%) 3.62 KiB (1%) 87
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 399.552 ns (5%) 208 bytes (1%) 4
["EpiLatentModels", "Intercept", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 401.245 ns (5%) 208 bytes (1%) 4
["EpiLatentModels", "MA", "evaluation", "linked"] 1.645 μs (5%) 4.70 KiB (1%) 72
["EpiLatentModels", "MA", "evaluation", "standard"] 1.157 μs (5%) 3.25 KiB (1%) 62
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.979 μs (5%) 14.38 KiB (1%) 85
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.449 μs (5%) 12.48 KiB (1%) 73
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 106.548 μs (5%) 49.22 KiB (1%) 1076
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 65.021 μs (5%) 34.45 KiB (1%) 743
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 18.395 μs (5%) 7.81 KiB (1%) 224
["EpiLatentModels", "MA", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 17.042 μs (5%) 6.69 KiB (1%) 188
["EpiLatentModels", "PrefixLatentModel", "evaluation", "linked"] 2.092 μs (5%) 4.05 KiB (1%) 46
["EpiLatentModels", "PrefixLatentModel", "evaluation", "standard"] 1.844 μs (5%) 3.42 KiB (1%) 42
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.869 μs (5%) 8.14 KiB (1%) 55
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.579 μs (5%) 7.52 KiB (1%) 51
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 39.212 μs (5%) 19.53 KiB (1%) 363
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 23.694 μs (5%) 14.16 KiB (1%) 256
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 973.368 ns (5%) 176 bytes (1%) 3
["EpiLatentModels", "PrefixLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 804.505 ns (5%) 176 bytes (1%) 3
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["EpiLatentModels", "RandomWalk", "evaluation", "standard"] 718.924 ns (5%) 2.02 KiB (1%) 29
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.900 μs (5%) 9.62 KiB (1%) 46
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.549 μs (5%) 8.31 KiB (1%) 40
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 52.678 μs (5%) 26.28 KiB (1%) 480
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 35.145 μs (5%) 20.22 KiB (1%) 371
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 3.335 μs (5%) 1.08 KiB (1%) 24
["EpiLatentModels", "RandomWalk", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 3.163 μs (5%) 1.08 KiB (1%) 24
["EpiLatentModels", "RecordExpectedLatent", "evaluation", "linked"] 740.785 ns (5%) 1.72 KiB (1%) 26
["EpiLatentModels", "RecordExpectedLatent", "evaluation", "standard"] 529.204 ns (5%) 1.25 KiB (1%) 23
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 911.694 ns (5%) 2.25 KiB (1%) 35
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 695.541 ns (5%) 1.78 KiB (1%) 32
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 36.478 μs (5%) 16.59 KiB (1%) 344
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 21.400 μs (5%) 11.38 KiB (1%) 238
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 892.255 ns (5%) 112 bytes (1%) 3
["EpiLatentModels", "RecordExpectedLatent", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 727.189 ns (5%) 112 bytes (1%) 3
["EpiLatentModels", "TransformLatentModel", "evaluation", "linked"] 253.751 ns (5%) 448 bytes (1%) 12
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["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 318.847 ns (5%) 768 bytes (1%) 19
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 5.597 μs (5%) 3.93 KiB (1%) 95
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 5.615 μs (5%) 3.93 KiB (1%) 95
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 467.619 ns (5%) 160 bytes (1%) 4
["EpiLatentModels", "TransformLatentModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 475.401 ns (5%) 160 bytes (1%) 4
["EpiLatentModels", "broadcast_dayofweek", "evaluation", "linked"] 1.735 μs (5%) 5.36 KiB (1%) 57
["EpiLatentModels", "broadcast_dayofweek", "evaluation", "standard"] 1.177 μs (5%) 3.17 KiB (1%) 47
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 2.822 μs (5%) 11.38 KiB (1%) 68
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.162 μs (5%) 9.19 KiB (1%) 58
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 70.501 μs (5%) 35.97 KiB (1%) 690
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 50.905 μs (5%) 29.03 KiB (1%) 577
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 4.739 μs (5%) 1.00 KiB (1%) 24
["EpiLatentModels", "broadcast_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 4.610 μs (5%) 1.00 KiB (1%) 24
["EpiLatentModels", "broadcast_weekly", "evaluation", "linked"] 17.041 μs (5%) 10.03 KiB (1%) 193
["EpiLatentModels", "broadcast_weekly", "evaluation", "standard"] 15.890 μs (5%) 6.52 KiB (1%) 177
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 17.783 μs (5%) 13.23 KiB (1%) 210
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 16.501 μs (5%) 9.39 KiB (1%) 190
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 116.086 μs (5%) 47.12 KiB (1%) 934
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 76.392 μs (5%) 32.80 KiB (1%) 675
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.647 μs (5%) 1.69 KiB (1%) 48
["EpiLatentModels", "broadcast_weekly", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.078 μs (5%) 1.56 KiB (1%) 44
["EpiObsModels", "Ascertainment", "evaluation", "linked"] 3.373 μs (5%) 3.58 KiB (1%) 63
["EpiObsModels", "Ascertainment", "evaluation", "standard"] 3.307 μs (5%) 3.58 KiB (1%) 63
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 4.026 μs (5%) 3.92 KiB (1%) 72
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 3.987 μs (5%) 3.92 KiB (1%) 72
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 77.244 μs (5%) 38.77 KiB (1%) 918
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 61.735 μs (5%) 34.02 KiB (1%) 815
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.727 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "Ascertainment", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.584 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "LatentDelay", "evaluation", "linked"] 14.166 μs (5%) 22.08 KiB (1%) 412
["EpiObsModels", "LatentDelay", "evaluation", "standard"] 14.136 μs (5%) 22.08 KiB (1%) 412
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 18.014 μs (5%) 22.30 KiB (1%) 419
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 17.743 μs (5%) 22.30 KiB (1%) 419
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 536.838 μs (5%) 293.05 KiB (1%) 7011
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 518.002 μs (5%) 288.30 KiB (1%) 6908
["EpiObsModels", "LatentDelay", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 51.746 μs (5%) 96 bytes (1%) 3
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["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.547 μs (5%) 624 bytes (1%) 17
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 73.376 μs (5%) 35.95 KiB (1%) 903
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 59.271 μs (5%) 31.20 KiB (1%) 800
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.699 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "NegativeBinomialError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.540 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "PoissonError", "evaluation", "linked"] 1.377 μs (5%) 1.83 KiB (1%) 30
["EpiObsModels", "PoissonError", "evaluation", "standard"] 1.039 μs (5%) 1.47 KiB (1%) 26
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 3.073 μs (5%) 7.78 KiB (1%) 43
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 2.409 μs (5%) 4.70 KiB (1%) 35
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 164.826 μs (5%) 86.44 KiB (1%) 1870
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 47.158 μs (5%) 29.38 KiB (1%) 727
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 6.188 μs (5%) 176 bytes (1%) 3
["EpiObsModels", "PoissonError", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 4.135 μs (5%) 176 bytes (1%) 3
["EpiObsModels", "PrefixObservationModel", "evaluation", "linked"] 1.642 μs (5%) 1.56 KiB (1%) 34
["EpiObsModels", "PrefixObservationModel", "evaluation", "standard"] 1.569 μs (5%) 1.56 KiB (1%) 34
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.775 μs (5%) 1.78 KiB (1%) 41
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.675 μs (5%) 1.78 KiB (1%) 41
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 26.349 μs (5%) 12.59 KiB (1%) 290
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 12.994 μs (5%) 7.84 KiB (1%) 187
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.119 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "PrefixObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 972.467 ns (5%) 96 bytes (1%) 3
["EpiObsModels", "RecordExpectedObs", "evaluation", "linked"] 766.609 ns (5%) 480 bytes (1%) 14
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["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.023 μs (5%) 704 bytes (1%) 21
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 981.071 ns (5%) 704 bytes (1%) 21
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 46.857 μs (5%) 22.98 KiB (1%) 537
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 32.691 μs (5%) 18.23 KiB (1%) 434
["EpiObsModels", "RecordExpectedObs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 3.174 μs (5%) 96 bytes (1%) 3
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["EpiObsModels", "StackObservationModels", "evaluation", "standard"] 6.568 μs (5%) 5.81 KiB (1%) 117
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 7.356 μs (5%) 6.16 KiB (1%) 126
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 7.271 μs (5%) 6.16 KiB (1%) 126
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 88.545 μs (5%) 49.09 KiB (1%) 1044
["EpiObsModels", "StackObservationModels", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 71.392 μs (5%) 44.34 KiB (1%) 941
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["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 59.121 μs (5%) 30.84 KiB (1%) 766
["EpiObsModels", "TransformObservationModel", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.726 μs (5%) 96 bytes (1%) 3
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["EpiObsModels", "ascertainment_dayofweek", "evaluation", "linked"] 4.397 μs (5%) 9.59 KiB (1%) 106
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["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 6.382 μs (5%) 16.72 KiB (1%) 117
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 5.674 μs (5%) 15.31 KiB (1%) 108
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 98.072 μs (5%) 58.03 KiB (1%) 1121
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 80.479 μs (5%) 51.88 KiB (1%) 1009
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 5.270 μs (5%) 160 bytes (1%) 3
["EpiObsModels", "ascertainment_dayofweek", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 5.298 μs (5%) 160 bytes (1%) 3
["EpiObsModels", "observation_error", "missing obs", "evaluation", "linked"] 1.501 μs (5%) 3.05 KiB (1%) 38
["EpiObsModels", "observation_error", "missing obs", "evaluation", "standard"] 908.133 ns (5%) 1.48 KiB (1%) 28
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 1.909 μs (5%) 4.11 KiB (1%) 48
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 1.241 μs (5%) 2.55 KiB (1%) 38
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 40.987 μs (5%) 25.78 KiB (1%) 533
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 24.054 μs (5%) 18.80 KiB (1%) 401
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.183 μs (5%) 144 bytes (1%) 3
["EpiObsModels", "observation_error", "missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.975 μs (5%) 144 bytes (1%) 3
["EpiObsModels", "observation_error", "no missing obs", "evaluation", "linked"] 431.960 ns (5%) 352 bytes (1%) 10
["EpiObsModels", "observation_error", "no missing obs", "evaluation", "standard"] 348.858 ns (5%) 352 bytes (1%) 10
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 541.378 ns (5%) 576 bytes (1%) 17
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 469.959 ns (5%) 576 bytes (1%) 17
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 33.833 μs (5%) 19.64 KiB (1%) 446
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 19.005 μs (5%) 14.22 KiB (1%) 324
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 1.889 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "observation_error", "no missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 1.625 μs (5%) 96 bytes (1%) 3
["EpiObsModels", "observation_error", "partially missing obs", "evaluation", "linked"] 31.960 μs (5%) 3.02 KiB (1%) 64
["EpiObsModels", "observation_error", "partially missing obs", "evaluation", "standard"] 31.729 μs (5%) 2.70 KiB (1%) 62
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "linked"] 21.299 μs (5%) 2.73 KiB (1%) 51
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoForwardDiff(chunksize=0)", "standard"] 21.039 μs (5%) 2.42 KiB (1%) 49
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()", "linked"] 65.842 μs (5%) 26.11 KiB (1%) 555
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff()", "standard"] 45.355 μs (5%) 20.38 KiB (1%) 431
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "linked"] 2.233 μs (5%) 112 bytes (1%) 3
["EpiObsModels", "observation_error", "partially missing obs", "gradient", "ADTypes.AutoReverseDiff(compile=true)", "standard"] 2.000 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      14140 s          0 s       1210 s      34374 s          0 s
       #2     0 MHz      16941 s          0 s       1332 s      31472 s          0 s
       #3     0 MHz      13382 s          0 s       1110 s      35296 s          0 s
       #4     0 MHz      17078 s          0 s       1306 s      31394 s          0 s
  Memory: 15.615276336669922 GB (12583.83984375 MB free)
  Uptime: 4990.38 sec
  Load Avg:  1.15  1.08  1.03
  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:                             4890.85
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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Collaborator Author

Self review: The reason the checks didn't pass was because of timeout induced by depwarn not being suppressed. Enough tests passed to be confident that this worked so I am merging.

The best solution will be resolving #573

@SamuelBrand1 SamuelBrand1 merged commit fa75b2a into main Jan 21, 2025
9 of 13 checks passed
@SamuelBrand1 SamuelBrand1 deleted the bump-dppl-0-32 branch January 21, 2025 10:21
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