pszemraj

# -*- coding: utf-8 -*-
"""

caption_image.py - basic captioning example using lavis

usage: caption_image.py [-h] -i IMAGE_PATH [-m MODEL_TYPE] [-d DEVICE] [-v VERBOSE]
# lavis

https://github.com/salesforce/LAVIS
"""

ailzhang

Functionalization

Link to prototype branch: https://github.com/ailzhang/pytorch/commit/83f647e9f14a89e61378c8e834aec4dfbcb74a00

Quick summary:

This prototype only focus on getting rid of aliasing in view ops, after this Func2 you can safely assume that after Func2 kernel you won't see any view ops, but only view_op_copy ops that returns completely new storage.

You can build this branch and check some examples by running python test/base_to_view.py and python test/view_to_base.py. But this branch is only a proof of concept and comes with a lot of hacks, and requires some careful design work described in the section below.

GMNGeoffrey

Some little scripts I've found useful for development. git-watch retriggers a command when your git repo changes, so can give interactive rebuilds like ibazel except I found that https://github.com/bazelbuild/bazel-watcher didn't work for me at all. This is also completely agnostic to the command, so can be used with CMake as well, for instance.

dougallj

# IDA (disassembler) and Hex-Rays (decompiler) plugin for Apple AMX
#
# WIP research. (This was edited to add more info after someone posted it to
# Hacker News. Click "Revisions" to see full changes.)
#
# Copyright (c) 2020 dougallj


# Based on Python port of VMX intrinsics plugin:
# Copyright (c) 2019 w4kfu - Synacktiv

yaroslavvb

"""Benchmark tensorflow distributed by adding vector of ones on worker2
to variable on worker1 as fast as possible.

On 2014 macbook, TensorFlow 0.10 this shows

Local rate:       2175.28 MB per second
Distributed rate: 107.13 MB per second

"""

vasanthk

System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

Basic Steps

1. Clarify and agree on the scope of the system

• User cases (description of sequences of events that, taken together, lead to a system doing something useful)
  • Who is going to use it?
  • How are they going to use it?

vene

# Author: Vlad Niculae <vlad@vene.ro>
# Licence: BSD

from __future__ import division, print_function
import numpy as np
from sklearn.utils import check_random_state


class SquaredLoss(object):
    def loss(self, y, pred):

k1xme

class Solution{
  public static boolean isPermutation(String s1, String s2){
    if(s1 === null || s2 == null ) return false;
    if(s1.length() != s2.length()) return false;
    if(s1.length() == 0) return true; // If s1.length() == s2.length() and s1 is a empty string, s2 is the permutation of s1.
    
    char[] sc1 = s1.toCharArray();
    char[] sc2 = s2.toCharArray();
    
    HashMap<String, int> temp = new HashMap<String, boolean>();

MLnick

import sys

from pyspark.context import SparkContext
from numpy import array, random as np_random
from sklearn import linear_model as lm
from sklearn.base import copy

N = 10000   # Number of data points
D = 10      # Numer of dimensions
ITERATIONS = 5

pprett

{"error": 42716.2954, "samples": 506, "value": [22.532806324110698], "label": "RM <= 6.94", "type": "split", "children": [{"error": 17317.3210, "samples": 430, "value": [19.93372093023257], "label": "LSTAT <= 14.40", "type": "split", "children": [{"error": 6632.2175, "samples": 255, "value": [23.349803921568636], "label": "DIS <= 1.38", "type": "split", "children": [{"error": 390.7280, "samples": 5, "value": [45.58], "label": "CRIM <= 10.59", "type": "split", "children": [{"error": 0.0000, "samples": 4, "value": [50.0], "label": "Leaf - 4", "type": "leaf"}, {"error": 0.0000, "samples": 1, "value": [27.9], "label": "Leaf - 5", "type": "leaf"}]}, {"error": 3721.1632, "samples": 250, "value": [22.90520000000001], "label": "RM <= 6.54", "type": "split", "children": [{"error": 1636.0675, "samples": 195, "value": [21.629743589743576], "label": "LSTAT <= 7.57", "type": "split", "children": [{"error": 129.6307, "samples": 43, "value": [23.969767441860473], "label": "TAX <= 222.50", "type": "split", "children": [{"err