| """ | |
| This module contains the implementation of the LoraPlus optimizer. | |
| """ | |
| from operator import attrgetter | |
| import torch.nn as nn | |
| from torch.optim import Optimizer | |
| from transformers.pytorch_utils import ALL_LAYERNORM_LAYERS | |
| from transformers.trainer_pt_utils import get_parameter_names |
| """Benchmark offline inference throughput.""" | |
| import argparse | |
| import json | |
| import os | |
| import random | |
| import time | |
| from typing import List, Optional, Tuple | |
| import modal |
| package gallant | |
| import ( | |
| "context" | |
| "encoding/json" | |
| "reflect" | |
| "github.com/go-playground/validator/v10" | |
| "github.com/pkg/errors" | |
| "gopkg.in/yaml.v3" |
The USDC contract is at 0xdac17f958d2ee523a2206206994597c13d831ec7 -- code is pulled from https://etherscan.io/address/0xdac17f958d2ee523a2206206994597c13d831ec7#code
The mint/burn logic is controlled by issue and redeem
// Issue a new amount of tokens
// these tokens are deposited into the owner address
//
// @param _amount Number of tokens to be issued
function issue(uint amount) public onlyOwner {
| library(gtrendsR) | |
| library(CausalImpact) | |
| library(tidyverse) | |
| plot_for_name <- function(food, time="today+5-y") { | |
| df <- gtrendsR::gtrends(food, geo="US", time=time) | |
| idx <- length(df$interest_over_time$date) - 6 | |
| ggplot2::ggplot(df$interest_over_time, aes(x=date, y=hits)) + | |
| ggtitle(paste0("Search volume for '", food, "'"), subtitle = "Source: Google Trends, US Data") + geom_line() + | |
| geom_vline(xintercept = df$interest_over_time$date[idx], color='red') + |
| import pandas as pd | |
| import numpy as np | |
| def fast_groupby_listagg(df, grouping_idx, presorted): | |
| """ | |
| given a grouping column, (or set of columns), we find all grouping sets. | |
| note that this code expects a 2-d array and outputs a 3-d array. | |
| we also convert values to float32 (trading precision for performance). | |
| id,date_account_created,timestamp_first_active,date_first_booking,gender,age,signup_method,signup_flow,language,affiliate_channel,affiliate_provider,first_affiliate_tracked,signup_app,first_device_type,first_browser,country_destination | |
| gxn3p5htnn,2010-06-28,20090319043255,,-unknown-,,facebook,0,en,direct,direct,untracked,Web,Mac Desktop,Chrome,NDF | |
| 820tgsjxq7,2011-05-25,20090523174809,,MALE,38.0,facebook,0,en,seo,google,untracked,Web,Mac Desktop,Chrome,NDF | |
| 4ft3gnwmtx,2010-09-28,20090609231247,2010-08-02,FEMALE,56.0,basic,3,en,direct,direct,untracked,Web,Windows Desktop,IE,US | |
| bjjt8pjhuk,2011-12-05,20091031060129,2012-09-08,FEMALE,42.0,facebook,0,en,direct,direct,untracked,Web,Mac Desktop,Firefox,other | |
| 87mebub9p4,2010-09-14,20091208061105,2010-02-18,-unknown-,41.0,basic,0,en,direct,direct,untracked,Web,Mac Desktop,Chrome,US | |
| osr2jwljor,2010-01-01,20100101215619,2010-01-02,-unknown-,,basic,0,en,other,other,omg,Web,Mac Desktop,Chrome,US | |
| lsw9q7uk0j,2010-01-02,20100102012558,2010-01-05,FEMALE,46.0,basic,0,en,other,cr |
| :root { | |
| --dark-primary-color): #D32F2F; | |
| --default-primary-color: #F44336; | |
| --light-primary-color: #FFCDD2; | |
| --text-primary-color: #FFFFFF; | |
| --accent-color: #607D8B; | |
| --primary-text-color: #212121; | |
| --secondary-text-color: #757575; | |
| --divider-color: #BDBDBD; | |
| --bg-light-color:#fafafa; |
The first story Ellen Pao told was about the “ice cream man.” There's no cheerful jingle to this story, just a law firm partner who stood outside a female lawyer's office everyday after lunch, licking an ice cream cone while staring at her. Management's response to these instances of sexism were invariably dismissive, e.g. “you should be flattered he's interested in you,” or “it's just one weird guy, but overall it's not that bad, right?” The result is an environment that views sexism as the product of just one bad apple, but it's instead the product of a bad system: one which condones and encourages “boys club” behavior. Staffing decisions were made at all-male steak dinners and strip club visits, which reifies the structural exclusion present within VC and tech.
It's now clear that tech has a diversity problem, given the wide range of stories over the last few years: Amazon, Susan Fowler at Uber, Leslie Miley at Twitter, SoFi recently, and almost certainly more we haven't heard.
| execute pathogen#infect() | |
| syntax on | |
| filetype plugin indent on | |
| set title | |
| set ruler | |
| set wrap | |
| set autoread | |
| set wildmenu |