zommiommy

{"ts": 1787251577.3300862, "spec": "3=q8_0/f16", "kld": 0.653984, "top1_pct": 88.778, "rc": 0, "sec": 54.2, "attempt": 1, "eta": "unknown", "remaining_steps": 96}
{"ts": 1787251625.0608952, "spec": "3=f16/q8_0", "kld": 0.655893, "top1_pct": 88.61, "rc": 0, "sec": 47.7, "attempt": 1, "eta": "1d 22h 15m", "remaining_steps": 96}
{"ts": 1787251672.7003484, "spec": "7=q8_0/f16", "kld": 0.571146, "top1_pct": 89.483, "rc": 0, "sec": 47.6, "attempt": 1, "eta": "1d 19h 29m", "remaining_steps": 96}
{"ts": 1787251720.1224434, "spec": "7=f16/q8_0", "kld": 0.586447, "top1_pct": 89.261, "rc": 0, "sec": 47.4, "attempt": 1, "eta": "1d 18h 32m", "remaining_steps": 96}
{"ts": 1787251767.8411736, "spec": "11=q8_0/f16", "kld": 0.51183, "top1_pct": 89.911, "rc": 0, "sec": 47.7, "attempt": 1, "eta": "1d 18h 0m", "remaining_steps": 96}
{"ts": 1787252127.1609387, "spec": "11=f16/q8_0", "kld": 0.548732, "top1_pct": 89.554, "rc": 0, "sec": 47.1, "attempt": 1, "eta": "1d 17h 44m", "remaining_steps": 96}
{"ts": 1787252174.1313019, "spec

zommiommy

{ pkgs ? import <nixpkgs> {} }:

let
  idaProPath = "$PWD";  # Adjust this to your IDA Pro installation path
  idaExecutable = "${idaProPath}/ida64";  # Adjust if needed for different executables
  fhsEnv = pkgs.buildFHSUserEnv {
    name = "ida-pro-env";
    targetPkgs = pkgs: (with pkgs; [
      glibc
      libGL

zommiommy

def parse_maps(pid):
    with open("/proc/{pid}/maps".format(pid=pid)) as f:
        for line in f.readlines():
            vals = (
                val.strip()
                for val in line.split(" ")
                if val.strip()
            )

            addrs = next(vals)

zommiommy

zommiommy

#![no_std]
extern crate alloc;
use alloc::vec::Vec;
use primitive::Primitive;

/// Implementation of:
/// > An Efficient Representation for Sparse Sets
/// > by Preston Briggs and Linda Torczon
/// > <https://dl.acm.org/doi/pdf/10.1145/176454.176484>
/// > <https://research.swtch.com/sparse>

zommiommy

//! Implementation of SipHash from [Jean-Philippe Aumasson](https://www.aumasson.jp/) and Daniel J. Bernstein.
//!
//! SipHash is a general-purpose hashing function: it runs at a good
//! speed (competitive with Spooky and City) and permits strong _keyed_
//! hashing. This lets you key your hash tables from a strong RNG, such as
//! [`rand::os::OsRng`](https://docs.rs/rand/latest/rand/rngs/struct.OsRng.html).
//!
//! Although the SipHash algorithm is considered to be generally strong,
//! it is not intended for cryptographic purposes. As such, all
//! cryptographic uses of this implementation are _strongly discouraged

zommiommy

/// A simple online linear regression algorithm.
/// See https://en.wikipedia.org/wiki/Simple_linear_regression#Fitting_the_regression_line
/// for details.
pub struct FirstOrderOLS {
    x: f64,
    y: f64,
    xx: f64,
    xy: f64,
    n: usize,

zommiommy

#![feature(test)]
extern crate test;

use test::{black_box, Bencher};
// Optionally include some setup
const NUMBER_OF_ELEMENTS: usize = 10_000;
const BITS: usize = 5;

fn gen_data() -> Vec<u8> {
    let mut res = Vec::with_capacity(NUMBER_OF_ELEMENTS);

zommiommy

#![deny(unconditional_recursion)]
use core::fmt::{Debug, Display, LowerHex, Binary}; 
use core::ops::*;
use core::sync::atomic::*;
use core::num::*;


/// Trait of operations possible on both Signed and Unsiged words
pub trait Number: Sized + Send + Sync +
    Display + LowerHex +

zommiommy

# Version of Elastic products
STACK_VERSION=8.4.2

# Port to expose Elasticsearch HTTP API to the host
ES_PORT=9200

# Port to expose Kibana to the host
KIBANA_PORT=5601

# RAM for each service 4GB