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# https://github.com/matsui528/faiss_tips | |
import faiss | |
import numpy as np | |
D = 256 | |
N = 10000 | |
X = np.random.random((N, D)).astype(np.float32) | |
# Setup | |
index = faiss.index_factory(D, "IVF25,Flat", faiss.METRIC_INNER_PRODUCT) |
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use std::{ | |
fs::File, | |
io::{BufRead, BufReader}, | |
path::PathBuf, | |
time::Instant, | |
}; | |
use faiss::{error::Error, index_factory, read_index, write_index, Index, MetricType}; | |
use itertools_num::linspace; | |
use structopt::StructOpt; |
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use std::{path::PathBuf, time::Instant}; | |
use faiss::{error::Error, index_factory, read_index, write_index, Index, MetricType}; | |
use itertools_num::linspace; | |
use structopt::StructOpt; | |
#[derive(Debug, StructOpt)] | |
#[structopt(name = "dann", about = "Demo ANN")] | |
struct DannOpt { | |
/// FAISS Index factory string |
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use std::time::Instant; | |
use faiss::{error::Error, index_factory, Index, MetricType}; | |
use itertools_num::linspace; | |
fn main() -> Result<(), Error> { | |
let d: u32 = 64; | |
// let my_data: Vec<f32> = (1u16..(d * 10) as u16).map(f32::from).collect(); | |
// above way of generating f32 ranges is limited in d size wrt default traits | |
// https://users.rust-lang.org/t/collect-f32-range-into-a-vector/15936/3 |
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use faiss::{error::Error, index_factory, Index, MetricType}; | |
fn main() -> Result<(), Error> { | |
let my_data = vec![1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0]; | |
let mut index = index_factory(8, "Flat", MetricType::L2)?; | |
index.add(&my_data)?; | |
let result = index.search(&my_data, 5)?; | |
for (i, (l, d)) in result | |
.labels | |
.iter() | |
.zip(result.distances.iter()) |
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#![deny(warnings)] | |
use std::{collections::HashMap, convert::Infallible, sync::Arc}; | |
use tokio::sync::RwLock; | |
use warp::{Filter, Rejection}; | |
fn with_store( | |
store: Arc<RwLock<HashMap<String, u64>>>, | |
) -> impl Filter<Extract = (Arc<RwLock<HashMap<String, u64>>>,), Error = Infallible> + Clone { | |
warp::any().map(move || store.clone()) | |
} |
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#![deny(warnings)] | |
use std::{collections::HashMap, convert::Infallible, str::FromStr, sync::Arc}; | |
use tokio::sync::RwLock; | |
use warp::{Filter, Rejection}; | |
fn with_store( | |
store: Arc<RwLock<HashMap<String, u64>>>, | |
) -> impl Filter<Extract = (Arc<RwLock<HashMap<String, u64>>>,), Error = Infallible> + Clone { | |
warp::any().map(move || store.clone()) | |
} |
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import math | |
def permutations(to_go, path_taken='', paths=[]): | |
if not to_go: | |
print(path_taken) | |
paths.append(path_taken) | |
else: | |
for i in range(len(to_go)): | |
here = to_go[i] | |
elsewhere = to_go[:i] + to_go[i+1:] |
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cjson = require "cjson" | |
ngx. req. read_body() -- explicitly read the req body | |
local data = ngx. req. get_body_data() | |
local jsonBody = cjson. decode(data); | |
if data then | |
local reqs = { } | |
--ngx. say("body data:") | |
for key, value in pairs(jsonBody) do | |
--ngx.print(key) |
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# a script to load seshat data into Elasticsearch | |
# seshat data is clearly graphdb data, but ES is nifty, so... | |
# assumes you have set up elasticsearch and kibana | |
import pandas as pd | |
from elasticsearch import Elasticsearch | |
from elasticsearch.helpers import parallel_bulk | |
# assumes local ES | |
es = Elasticsearch() |