Closed GTorlai closed 2 years ago
Merging #231 (51acb6d) into master (11c250b) will increase coverage by
5.40%
. The diff coverage is85.50%
.
@@ Coverage Diff @@
## master #231 +/- ##
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+ Coverage 80.30% 85.71% +5.40%
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Files 21 22 +1
Lines 2326 2401 +75
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+ Hits 1868 2058 +190
+ Misses 458 343 -115
Impacted Files | Coverage Δ | |
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src/PastaQ.jl | 100.00% <ø> (ø) |
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src/deprecated.jl | 75.00% <ø> (+75.00%) |
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src/circuits/getsamples.jl | 64.04% <67.93%> (-24.49%) |
:arrow_down: |
src/circuits/productstates.jl | 86.66% <73.33%> (+30.41%) |
:arrow_up: |
src/io.jl | 71.95% <74.28%> (ø) |
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src/tomography/quantumtomography.jl | 85.71% <85.71%> (ø) |
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src/utils.jl | 74.77% <96.55%> (+6.17%) |
:arrow_up: |
src/distances.jl | 95.00% <96.72%> (+1.66%) |
:arrow_up: |
src/optimizers.jl | 96.96% <96.96%> (+47.60%) |
:arrow_up: |
src/tomography/fulltomography.jl | 97.43% <97.43%> (ø) |
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... and 19 more |
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Ready to merge once Observers.jl is registered (late Tuesday evening)
It looks like there has been some work splitting off the Flux Optimisers to a separate package (https://github.com/FluxML/Optimisers.jl), should we try using that so we don't have the full Flux dependency?
Right now we only use the optimizer, but once we merge the variationalcircuit branch we will also use AD. Maybe there is a way to also only import chunks of it.
You don't need all of Flux for AD, just Zygote. Flux basically just adds a neural network framework on top of Zygote.
This PR applies the following changes:
getsamples
array
function in ITensors parses the dimension of two similar TNs (e.g. an MPS and its gradients) in a consistent way. We do so by fixing the order of the indices just before the TN is flattened."earlystop"
, where if a certain condition dependent on the train/test loss is met, the training is halted.tomography
function (in the qst and qpt files) into a single one, now in quantumtomography.jl. This file contains also the interface for full tomography, which the other 3 files now contains lower level functions of these methods.earlystop=true
in the tomography function. This avoid to having to redefine the early stop function in the observer every time. However, if such function is defined it supersedes the default one.