redknightlois

class Ralamb(Optimizer):

    def __init__(self, params, lr=1e-3, betas=(0.9, 0.999), eps=1e-8, weight_decay=0):
        defaults = dict(lr=lr, betas=betas, eps=eps, weight_decay=weight_decay)
        self.buffer = [[None, None, None] for ind in range(10)]
        super(Ralamb, self).__init__(params, defaults)

    def __setstate__(self, state):
        super(Ralamb, self).__setstate__(state)

stephenroller

#!/usr/bin/env python3

"""
Example of a generic Mixout implementation. (Lee et al., 2019).
https://arxiv.org/abs/1909.11299

Implementation by Stephen Roller (https://stephenroller.com).

Updated 2020-02-10 to include 1/(1 - p) correction term. Thanks to
Cheolhyoung Lee for making this correction.

mblondel

# Authors: Mathieu Blondel, Vlad Niculae
# License: BSD 3 clause

import numpy as np


def _gen_pairs(gen, max_iter, max_inner, random_state, verbose):
    rng = np.random.RandomState(random_state)

    # if tuple, interpret as randn

y0ast

# Now available here: https://github.com/y0ast/pytorch-snippets/tree/main/minimal_cifar

connorbell

from tkinter import *
from PIL import ImageTk,Image
import time
import os

targetImageWidth = 850
targetImageHeight = 400

inputImageWidth = 0
inputImageHeight = 0

radekosmulski

Summary of Fastai.ai's in-depth discussion of types of normalization

# simulated batch of images
x = torch.rand(64, 3, 224, 224)
# or some number of layers up the convolutional stack
x = torch.rand(64, 256, 32, 32)

BatchNorm:

andreyryabtsev

thomwolf

import os; import psutil; import timeit
from datasets import load_dataset

mem_before = psutil.Process(os.getpid()).memory_info().rss >> 20
wiki = load_dataset("wikipedia", "20200501.en", split='train')
mem_after = psutil.Process(os.getpid()).memory_info().rss >> 20
print(f"RAM memory used: {(mem_after - mem_before)} MB")

s = """batch_size = 1000
for i in range(0, len(wiki), batch_size):

ClementNerma

ZSH CheatSheet

This is a cheat sheet for how to perform various actions to ZSH, which can be tricky to find on the web as the syntax is not intuitive and it is generally not very well-documented.

Strings

Description	Syntax
Get the length of a string	${#VARNAME}
Get a single character	${VARNAME[index]}

neubig

# NOTE:
# You can find an updated, more robust and feature-rich implementation
# in Zeno Build
# - Zeno Build: https://github.com/zeno-ml/zeno-build/
# - Implementation: https://github.com/zeno-ml/zeno-build/blob/main/zeno_build/models/providers/openai_utils.py

import openai
import asyncio
from typing import Any