Closed GiggleLiu closed 2 years ago
Merging #24 (35e8eab) into master (8903b36) will increase coverage by
0.29%
. The diff coverage is100.00%
.
@@ Coverage Diff @@
## master #24 +/- ##
==========================================
+ Coverage 95.46% 95.75% +0.29%
==========================================
Files 7 8 +1
Lines 684 731 +47
==========================================
+ Hits 653 700 +47
Misses 31 31
Impacted Files | Coverage Δ | |
---|---|---|
src/OMEinsumContractionOrders.jl | 100.00% <ø> (ø) |
|
src/json.jl | 100.00% <100.00%> (ø) |
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Data format
Will generate file
root["label-type"]
is the data type for labels.root["slices"]
are the sliced labels.root["inputs"]
are vectors of labels for input tensors.root["output"]
are labels for the output tensor.root["tree"]
specifies the nested einsum (a contraction tree).eins
is the einsum code for a single step contraction, its siblingsixs
are inputs, which is a vector of vector,iy
is the output, which is a vector.args
specifies the input arguments, which is a vector of leaf nodes or non-leaf nodes. For leaf nodes, we usetensorindex
to specify a tensor in theinputs
, a non-leaf nodes is specified as a nested einsum (subtree).How to benchmark
julia> @benchmark CUDA.@sync optcode_loaded([CUDA.rand(fill(2, length(ix))...) for ix in getixsv(optcode_loaded)]...) BenchmarkTools.Trial: 12 samples with 1 evaluation. Range (min … max): 417.572 ms … 485.062 ms ┊ GC (min … max): 2.28% … 4.11% Time (median): 441.641 ms ┊ GC (median): 4.45% Time (mean ± σ): 444.844 ms ± 24.147 ms ┊ GC (mean ± σ): 3.69% ± 1.22%
█ █ ██ █ █ █ █ █ █ █ █
█▁█▁██▁▁█▁▁█▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█▁▁█▁█▁▁▁▁▁▁█▁▁▁▁▁▁▁▁▁▁▁█▁▁▁▁█ ▁ 418 ms Histogram: frequency by time 485 ms <
Memory estimate: 42.38 MiB, allocs estimate: 739486.