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#!/usr/local/miniconda3/bin/python
# A snippet for reading a Unicode string from clipboard, convert the string to one that is ASCII compatible, and then paste it to the clipboard. This converts for example "ß" to "ss"..
# The code is based on the answer https://stackoverflow.com/a/25802742/3706018.
import pasteboard
import subprocess
from unidecode import unidecode

pb = pasteboard.Pasteboard()
asciidata = unidecode(pb.get_contents())

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class MaxNorm(object):
    def __init__(self, max_value=1, frequency=5):
        self.frequency = frequency
        self.max_value = max_value
        self.tiny = _finfo(torch.FloatTensor([])).tiny

    def __call__(self, module):
        if hasattr(module, "weight"):
            w = module.weight.data
            norms = w.norm(p=2, dim=w.dim() - 1, keepdim=True)

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@font-face {
 font-family: "DejaVu Sans Mono";
 font-weight: normal;
 font-style: normal;
 src: local('"DejaVu Sans Mono"'), url('fonts/dejavu.ttf') format('truetype');
}
@font-face {
 font-family: "DejaVu Sans Mono";
 font-weight: normal;
 font-style: italic;

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;;; emacs-zotero-bib-fetch.el --- Manage Zotero collections from emacs
;;
;; Filename: emacs-zotero-bib-fetch.el
;; Author: Anders Johansson, based on zotelo by Spinu Vitalie
;; Maintainer: Anders Johansson
;; Copyright (C) 2011-2014, Anders Johansson and Spinu Vitalie
;; Created: 1 Jul 2014
;; Version: 1.2
;; URL: https://github.com/andersjohansson/emacs-zotero-bib-fetch
;; Keywords: zotero, emacs, reftex, bibtex, bibliography manager

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/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/

/*
The following CSS variables define the main, public API for styling JupyterLab.
These variables should be used by all plugins wherever possible. In other
words, plugins should not define custom colors, sizes, etc unless absolutely
necessary. This enables users to change the visual theme of JupyterLab

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{
    "shortcuts": [
        {
            "command": "notebook:toggle-all-cell-line-numbers",
            "keys": [
                "Alt L"
            ],
            "selector": ".jp-Notebook:focus"
        },        
        // Moving cells

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#!/bin/bash

# Install CUDA Toolkit 10
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.0.130-1_amd64.deb
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub && sudo apt update
sudo dpkg -i cuda-repo-ubuntu1804_10.0.130-1_amd64.deb

sudo apt update
sudo apt install -y cuda

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{
    "title": "Emacs keys",
    "rules": [
	{
            "description": "Change right_option + a to right_control + a",
	    "manipulators": [
		{
		    "type": "basic",
		    "from": {
			"key_code": "a",

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from collections import OrderedDict

from torchvision import models


def gen_feature_extractor(model, output_layer):
    layers = OrderedDict()
    for (k, v) in model._modules.items():
        layers[k] = v
        if k == output_layer:

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import torch


def hamming_score(pred, answer):
    out = ((pred & answer).sum(dim=1) / (pred | answer).sum(dim=1)).mean()
    if out.isnan():
        out = torch.tensor(1.0)
    return out

answer = torch.tensor([[0, 1, 0], [0, 1, 1], [1, 0, 1], [0, 0, 1]])