Let's run on this Imagenet10 subset called Imagenette.
First ensure that you get the dummy test data run working as per MLperf v2.1 ResNet.
Next, in the and then let's create the then back on the mlperf directory we download our model:and finally run!which gives on P51:where The
imagenette2 directory, first let's create a 224x224 scaled version of the inputs as required by the benchmark at mlcommons.org/en/inference-datacenter-21/:#!/usr/bin/env bash
rm -rf val224x224
mkdir -p val224x224
for syndir in val/*: do
syn="$(dirname $syndir)"
for img in "$syndir"/*; do
convert "$img" -resize 224x224 "val224x224/$syn/$(basename "$img")"
done
doneval_map.txt file to match the format expected by MLPerf:#!/usr/bin/env bash
wget https://gist.githubusercontent.com/aaronpolhamus/964a4411c0906315deb9f4a3723aac57/raw/aa66dd9dbf6b56649fa3fab83659b2acbf3cbfd1/map_clsloc.txt
i=0
rm -f val_map.txt
while IFS="" read -r p || [ -n "$p" ]; do
synset="$(printf '%s\n' "$p" | cut -d ' ' -f1)"
if [ -d "val224x224/$synset" ]; then
for f in "val224x224/$synset/"*; do
echo "$f $i" >> val_map.txt
done
fi
i=$((i + 1))
done < <( sort map_clsloc.txt )wget https://zenodo.org/record/4735647/files/resnet50_v1.onnxDATA_DIR=/mnt/sda3/data/imagenet/imagenette2 time ./run_local.sh onnxruntime resnet50 cpu --accuracyTestScenario.SingleStream qps=164.06, mean=0.0267, time=23.924, acc=87.134%, queries=3925, tiles=50.0:0.0264,80.0:0.0275,90.0:0.0287,95.0:0.0306,99.0:0.0401,99.9:0.0464qps presumably means "querries per second". And the time results:446.78user 33.97system 2:47.51elapsed 286%CPU (0avgtext+0avgdata 964728maxresident)ktime=23.924 is much smaller than the time executable because of some lengthy pre-loading (TODO not sure what that means) that gets done every time:INFO:imagenet:loaded 3925 images, cache=0, took=52.6sec
INFO:main:starting TestScenario.SingleStreamLet's try on the GPU now:which gives:TODO lower
DATA_DIR=/mnt/sda3/data/imagenet/imagenette2 time ./run_local.sh onnxruntime resnet50 gpu --accuracyTestScenario.SingleStream qps=130.91, mean=0.0287, time=29.983, acc=90.395%, queries=3925, tiles=50.0:0.0265,80.0:0.0285,90.0:0.0405,95.0:0.0425,99.0:0.0490,99.9:0.0512
455.00user 4.96system 1:59.43elapsed 385%CPU (0avgtext+0avgdata 975080maxresident)kqps on GPU! How to use an Oxford Nanopore MinION to extract DNA from river water and determine which bacteria live in it Updated 2025-03-28 +Created 1970-01-01
This article gives an idea of how this kind of biological experiment feels like to a software engineer who has never done any biology like Ciro Santilli.
It is said that you leave Oxford with either
- a First, i.e. First class, good grades
- a Blue, i.e. a sporting achievement
- a spouse, see also Section "The main function of university is sexual selection"
The breadboard of photonics!
For example, that is how most modern microscopes are prototyped, see for example Video "Two Photon Microscopy by Nemonic NeuroNex (2019)".
This is kind of why they are also sometimes called "optical breadboarbds", since breadboards are what we use for early prototyping in electronics. Wikipedia however says "optical breadboard" is a simpler and cheaper type of optical table with less/no stabilization.
- requires intense refrigeration to 15mK in dilution refrigerator. Note that this is much lower than the actual superconducting temperature of the metal, we have to go even lower to reduce noise enough, see e.g. youtu.be/uPw9nkJAwDY?t=471 from Video "Building a quantum computer with superconducting qubits by Daniel Sank (2019)"
- less connectivity, normally limited to 4 nearest neighbours, or maybe 6 for 3D approaches, e.g. compared to trapped ion quantum computers, where each trapped ion can be entangled with every other on the same chip
Present in chormosome 4.
Good video showing what appears to be the adenine nucleotide translocator. although they don't use that name, instead saying ADP/ATP carrier.
The video also briefly depicts the ATP synthase and the mitochondrial phosphate carrier protein.
TODO clear example of the computational problem that it solves.
Interesting because of the Cook-Levin theorem: if only a single NP-complete problem were in P, then all NP-complete problems would also be P!
We all know the answer for this: either false or independent.
University of Cambridge students, CanTabBridgeans.
@cirosantilli/_file/python/typing_cheat/python/typing_cheat/protocol_empty.py Updated 2025-03-28 +Created 1970-01-01
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