I hereby claim:
- I am brianhung on github.
- I am blh (https://keybase.io/blh) on keybase.
- I have a public key ASCM2M22DbC7kHRp54zMxm2W_Iv2YVZmZPFwvD6jOXywiwo
To claim this, I am signing this object:
I hereby claim:
To claim this, I am signing this object:
| def Floyd_Warshall(distance_matrix): | |
| """ | |
| An algorithm for finding shortest paths in a weighted graph (with no negative cycles). | |
| Source | |
| - https://en.wikipedia.org/wiki/Floyd–Warshall_algorithm | |
| Output: | |
| - shortest_distance: n**3 matrix from j to k using at most i vertices. |
| def row_reduce(M): | |
| """ | |
| Assume M is a square matrix whose entries are of type Fraction. | |
| """ | |
| num_rows, num_columns = len(M), len(M[0]) | |
| for i in range(num_rows): | |
| # Finds next row to act as ith pivot. | |
| next_row = find_next_row(M, i) | |
| if next_row == None: |
| from __future__ import print_function | |
| import pickle | |
| import os.path | |
| from googleapiclient.discovery import build | |
| from google_auth_oauthlib.flow import InstalledAppFlow | |
| from google.auth.transport.requests import Request | |
| from apiclient import errors | |
| from apiclient.http import MediaIoBaseDownload | |
| from googleapiclient.discovery import build |
| async function clearMessages() { | |
| const server = ""; // server id number | |
| const author = ""; // user id number | |
| const authToken = ""; // authToken - look inside a network packet | |
| const headers = { 'Authorization': authToken, 'Content-Type': 'application/json' }; | |
| const baseURL = `https://discordapp.com/api/v6/channels`; | |
| let searchURL = `https://discordapp.com/api/v6/guilds/${server}/messages/search?author_id=${author}`; | |
| if (typeof channel !== 'undefined') searchURL = searchURL + `&channel_id=${channel}`; |
| import nltk | |
| nltk.download('stopwords') | |
| from nltk import ngrams | |
| from nltk.tokenize import RegexpTokenizer | |
| from nltk.corpus import stopwords | |
| # Faster than looking at entire list; have to lowercase input. | |
| stop_words = set(stopwords.words("english")) |
| def unrolled_UNet3D(inputs): | |
| """ | |
| Implements the UNet model with 3D Convolutions. Refer to the following | |
| source code: https://github.com/jocicmarko/ultrasound-nerve-segmentation. | |
| """ | |
| conv1 = Conv3D( 32, (3, 3), activation='relu', padding='same')(inputs) | |
| conv1 = Conv3D( 32, (3, 3), activation='relu', padding='same')(conv1) | |
| pool1 = MaxPooling3D(pool_size=(2, 2))(conv1) |
| !function(e){var t={};function i(n){if(t[n])return t[n].exports;var o=t[n]={i:n,l:!1,exports:{}};return e[n].call(o.exports,o,o.exports,i),o.l=!0,o.exports}i.m=e,i.c=t,i.d=function(e,t,n){i.o(e,t)||Object.defineProperty(e,t,{enumerable:!0,get:n})},i.r=function(e){"undefined"!=typeof Symbol&&Symbol.toStringTag&&Object.defineProperty(e,Symbol.toStringTag,{value:"Module"}),Object.defineProperty(e,"__esModule",{value:!0})},i.t=function(e,t){if(1&t&&(e=i(e)),8&t)return e;if(4&t&&"object"==typeof e&&e&&e.__esModule)return e;var n=Object.create(null);if(i.r(n),Object.defineProperty(n,"default",{enumerable:!0,value:e}),2&t&&"string"!=typeof e)for(var o in e)i.d(n,o,function(t){return e[t]}.bind(null,o));return n},i.n=function(e){var t=e&&e.__esModule?function(){return e.default}:function(){return e};return i.d(t,"a",t),t},i.o=function(e,t){return Object.prototype.hasOwnProperty.call(e,t)},i.p="",i(i.s=44)}([function(e,t,i){(function(t){const{TimeoutError:n}=i(7),o=i(25)("puppeteer:error"),a=i(11);class r{static evalu |
| import {EditorState } from "prosemirror-state" | |
| import {StepMap } from "prosemirror-transform" | |
| import {keymap } from "prosemirror-keymap" | |
| import {undo, redo } from "prosemirror-history" | |
| import {EditorView } from "prosemirror-view" | |
| import {InputRule } from "prosemirror-inputrules" | |
| import {Node, Plugin } from 'tiptap' | |
| import {PluginKey } from 'tiptap' | |
| import {nodeInputRule } from 'tiptap-commands' | |
| import {NodeSelection } from "prosemirror-state" |
| .ProseMirror .Math { | |
| display: contents; | |
| } | |
| .ProseMirror .Math .katex-editor { | |
| display: inline; | |
| } | |
| .ProseMirror .Math .katex-render .katex { | |
| font-size: 1em; |