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526d615d9b
...
866a9283d7
4 changed files with 25 additions and 100 deletions
45
flake.lock
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45
flake.lock
generated
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@ -37,22 +37,6 @@
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"type": "github"
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"type": "github"
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}
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}
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},
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},
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"flake-compat": {
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"flake": false,
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"locked": {
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"lastModified": 1767039857,
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"narHash": "sha256-vNpUSpF5Nuw8xvDLj2KCwwksIbjua2LZCqhV1LNRDns=",
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"owner": "NixOS",
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"repo": "flake-compat",
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"rev": "5edf11c44bc78a0d334f6334cdaf7d60d732daab",
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"type": "github"
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},
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"original": {
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"owner": "NixOS",
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"repo": "flake-compat",
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"type": "github"
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}
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},
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"flake-parts": {
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"flake-parts": {
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"inputs": {
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"inputs": {
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"nixpkgs-lib": "nixpkgs-lib"
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"nixpkgs-lib": "nixpkgs-lib"
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@ -73,11 +57,11 @@
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},
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},
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"nixpkgs": {
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"nixpkgs": {
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"locked": {
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"locked": {
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"lastModified": 1772956932,
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"lastModified": 1767364772,
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"narHash": "sha256-M0yS4AafhKxPPmOHGqIV0iKxgNO8bHDWdl1kOwGBwRY=",
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"narHash": "sha256-fFUnEYMla8b7UKjijLnMe+oVFOz6HjijGGNS1l7dYaQ=",
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"owner": "nixos",
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"owner": "nixos",
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"repo": "nixpkgs",
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"repo": "nixpkgs",
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"rev": "608d0cadfed240589a7eea422407a547ad626a14",
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"rev": "16c7794d0a28b5a37904d55bcca36003b9109aaa",
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"type": "github"
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"type": "github"
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},
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},
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"original": {
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"original": {
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@ -137,24 +121,39 @@
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"url": "https://static.rust-lang.org/dist/channel-rust-1.91.0.toml"
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"url": "https://static.rust-lang.org/dist/channel-rust-1.91.0.toml"
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}
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}
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},
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},
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"systems": {
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"locked": {
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"lastModified": 1681028828,
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"narHash": "sha256-Vy1rq5AaRuLzOxct8nz4T6wlgyUR7zLU309k9mBC768=",
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"owner": "nix-systems",
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"repo": "default",
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"rev": "da67096a3b9bf56a91d16901293e51ba5b49a27e",
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"type": "github"
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},
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"original": {
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"owner": "nix-systems",
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"repo": "default",
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"type": "github"
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}
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},
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"typst": {
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"typst": {
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"inputs": {
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"inputs": {
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"crane": "crane",
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"crane": "crane",
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"fenix": "fenix",
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"fenix": "fenix",
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"flake-compat": "flake-compat",
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"flake-parts": "flake-parts",
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"flake-parts": "flake-parts",
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"nixpkgs": [
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"nixpkgs": [
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"nixpkgs"
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"nixpkgs"
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],
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],
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"rust-manifest": "rust-manifest",
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"rust-manifest": "rust-manifest",
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"systems": "systems",
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"typst": "typst_2"
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"typst": "typst_2"
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},
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},
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"locked": {
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"locked": {
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"lastModified": 1769829890,
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"lastModified": 1767654408,
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"narHash": "sha256-MxaI0XTFOdFGhPZ5Vx3w+se3aEY9wBU/LpUw3mlv4XQ=",
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"narHash": "sha256-7YhRyF2u7CuhBLMpKnHZy9D5Y2L6k9LRLGf3SE0AUYc=",
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"owner": "typst",
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"owner": "typst",
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"repo": "typst-flake",
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"repo": "typst-flake",
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"rev": "0862b4b4c562fdc245063519b012507951a53181",
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"rev": "ec2389e45e1014c746a3a1d6a222cde352c56886",
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"type": "github"
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"type": "github"
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},
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},
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"original": {
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"original": {
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@ -2,8 +2,6 @@
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Hello me, this is a list for you to get back on track with the QD-QAS you were working on...
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Hello me, this is a list for you to get back on track with the QD-QAS you were working on...
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Tell Sebastian and Koen "I'm back"
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## Things I've done
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## Things I've done
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I have made baselines for two types of optimization free QAS, namely TF-QAS and GA-QAS.
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I have made baselines for two types of optimization free QAS, namely TF-QAS and GA-QAS.
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@ -3,7 +3,6 @@
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#import "@preview/cetz:0.3.4"
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#import "@preview/cetz:0.3.4"
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#import "@preview/typsium:0.2.0": ce
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#import "@preview/typsium:0.2.0": ce
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#import "@preview/numbly:0.1.0": numbly
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#import "@preview/numbly:0.1.0": numbly
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#import "@preview/fletcher:0.5.8": *
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#import "./theme.typ": *
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#import "./theme.typ": *
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#set heading(numbering: numbly("{1}.", default: "1.1"))
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#set heading(numbering: numbly("{1}.", default: "1.1"))
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@ -56,81 +55,10 @@
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#let today-offset = (datetime.today() - datetime(day: 10, month: 11, year: 2025)).weeks()
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#let today-offset = (datetime.today() - datetime(day: 10, month: 11, year: 2025)).weeks()
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= Week ??
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= Week 13
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Pre-OP wrapup
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Post Surgery
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== Content
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- Research question
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- Solution Architecture
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- Comparing with other methods
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== Research Question
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- Uncertain about the wording
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#pause
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How does Quality-Diversity based Quantum Architecture Search compare to the state-of-the-art in QAS
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in speed, noise performance and transferability between problems?
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== Hypothesis
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I think the speed of the search itself will be comparable to the GA-QAS, which is slower than
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TF-QAS but likely faster then problem specific searches.
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In noise performance I think it would be possible to improve upon both GA-QAS and TF-QAS as neither
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attempts to optimize for it.
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I think the transferability of the output will be a significant improvement over TF-QAS,
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especially when counting the whole set of PQCs.
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== QD-QAS architecture
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#let nodes = ("Make Initial Population", "Create Offspring", "Calculate Cost Function", "Take Best Offspring", "Offspring Becomes Parents")
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#let edges = (
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(0, 1),
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(1, 2),
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(2, 3),
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(3, 4),
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(4, 1),
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)
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#align(center + horizon)[
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#diagram({
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for (i, n) in nodes.enumerate() {
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let θ = -90deg + i*360deg/nodes.len()
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node((θ, 0.8), n, stroke: 0.5pt, name: str(i))
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}
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for (from, to) in edges {
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let bend = if (to, from) in edges { 10deg } else { 5deg }
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// refer to nodes by label, e.g., <1>
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edge(label(str(from)), label(str(to)), "-|>", bend: bend)
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}
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})
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]
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== Comparing
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- Preferences
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- Same benchmarks for all QAS types
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- Not implementing tests multiple times
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- Consistent program outputs
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== Comparing
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- Options I see
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- Replicate other papers to have consistent outputs \
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\- need to get it all working as expected \
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\+ will have identical tests and outputs
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- Create an interface and adapt the other papers to it \
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\- limited by the lowest common denominator \
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\+ don't need to fully replicate papers
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- Use the tests of the other papers \
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\- Likely can't compare all together \
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\- Can't choose tests freely \
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\+ Not necessary to rerun tests of the other papers \
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\+ Don't have to implement tests for the other papers
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==
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= Week 12
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= Week 12
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Making Baselines
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Making Baselines
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0
src/all_qas.py
Executable file → Normal file
0
src/all_qas.py
Executable file → Normal file
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