Use generic trace methods when possible

[abraunst]

No description provided.

[codecov]

Codecov Report

All modified lines are covered by tests ✅

Comparison is base (bd71c4f) 96.75% compared to head (92e3e40) 95.70%.
Report is 6 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main      #16      +/-   ##
==========================================
- Coverage   96.75%   95.70%   -1.05%     
==========================================
  Files           6        6              
  Lines         431      326     -105     
==========================================
- Hits          417      312     -105     
  Misses         14       14              

Files	Coverage Δ
src/abstract_tensor_train.jl	100.00% <100.00%> (ø)
src/periodic_tensor_train.jl	100.00% <ø> (ø)
src/tensor_train.jl	100.00% <ø> (ø)

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[stecrotti]

Here's a comparison of runtimes for Target = this branch, Baseline = main. It looks pretty good!

---

Benchmark Report for TensorTrains

Job Properties

• Time of benchmarks:
  • Target: 18 Oct 2023 - 10:41
  • Baseline: 18 Oct 2023 - 10:43
• Package commits:
  • Target: 92e3e4
  • Baseline: 444657
• Julia commits:
  • Target: bed2cd
  • Baseline: bed2cd
• 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 ✅). All results are shown below.

ID	time ratio	memory ratio
["accumulators", "accumL_periodic"]	0.06 (5%) ✅	0.01 (1%) ✅
["accumulators", "accumL_tensortrain"]	0.55 (5%) ✅	0.11 (1%) ✅
["dot", "dot_periodic"]	0.26 (5%) ✅	0.28 (1%) ✅
["dot", "dot_tensortrain"]	1.00 (5%)	1.00 (1%)
["marginals", "marginals_periodic"]	0.18 (5%) ✅	0.05 (1%) ✅
["marginals", "marginals_tensortrain"]	0.73 (5%) ✅	0.12 (1%) ✅
["marginals", "twovar_marginals_periodic"]	0.00 (5%) ✅	0.01 (1%) ✅
["marginals", "twovar_marginals_tensortrain"]	0.02 (5%) ✅	2.97 (1%) ❌
["orthogonalize", "orth_left_periodic"]	0.00 (5%) ✅	0.54 (1%) ✅
["orthogonalize", "orth_left_tensortrain"]	1.05 (5%) ❌	1.00 (1%)
["sampling", "sample_periodic"]	0.34 (5%) ✅	0.14 (1%) ✅
["sampling", "sample_tensortrain"]	0.82 (5%) ✅	0.33 (1%) ✅

Benchmark Group List

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

• ["accumulators"]
• ["dot"]
• ["marginals"]
• ["orthogonalize"]
• ["sampling"]

Julia versioninfo

Target

Julia Version 1.9.3
Commit bed2cd540a1 (2023-08-24 14:43 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  uname: Linux 3.10.0-1160.15.2.el7.x86_64 #1 SMP Wed Feb 3 15:06:38 UTC 2021 x86_64 x86_64
  CPU: Intel(R) Xeon(R) CPU E5-2640 v4 @ 2.40GHz: 
                 speed         user         nice          sys         idle          irq
       #1-40  2599 MHz    3287700 s       3154 s    2743495 s   29503921 s          0 s
  Memory: 503.51097869873047 GB (458090.171875 MB free)
  Uptime: 88871.78 sec
  Load Avg:  18.96  21.54  22.59
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-14.0.6 (ORCJIT, broadwell)
  Threads: 1 on 40 virtual cores

Baseline

Julia Version 1.9.3
Commit bed2cd540a1 (2023-08-24 14:43 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  uname: Linux 3.10.0-1160.15.2.el7.x86_64 #1 SMP Wed Feb 3 15:06:38 UTC 2021 x86_64 x86_64
  CPU: Intel(R) Xeon(R) CPU E5-2640 v4 @ 2.40GHz: 
                 speed         user         nice          sys         idle          irq
       #1-40  2599 MHz    3300003 s       3154 s    2754116 s   29520928 s          0 s
  Memory: 503.51097869873047 GB (457673.15234375 MB free)
  Uptime: 88971.65 sec
  Load Avg:  19.76  21.14  22.34
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-14.0.6 (ORCJIT, broadwell)
  Threads: 1 on 40 virtual cores