philschmid

#!/bin/bash

docker login docker.pkg.github.com -u talosinsight -p TOKEN
docker pull docker.pkg.github.com/talosinsight/insight-translator/translator:latest
--//

philschmid

Short Gist for using Pytorch with GPUs

pytorch gpu docker

https://github.com/anibali/docker-pytorch/blob/master/cuda-10.0/Dockerfile

fairseq sagemaker example

https://github.com/awslabs/amazon-sagemaker-examples/blob/master/advanced_functionality/fairseq_translation/fairseq_sagemaker_translate_de2en.ipynb

pytroch docker

https://github.com/anibali/docker-pytorch

philschmid

// Imports the Google Cloud client library
const language = require('@google-cloud/language');

// Creates a client
const client = new language.LanguageServiceClient();

const  categorizeText = async(document:string) => {

// Prepares a document, representing the provided text
const document = {

philschmid

resource "google_cloud_run_service" "default" {
  name     = "tftest-cloudrun"
  location = "us-central1"
  provider = "google-beta"

  metadata {
    namespace = "my-project-name"
  }

  spec {

philschmid

Cloudbuild Example for private github-repository + Docker build and push + run Terraform script

HOW TO

run tf apply var=_GIT_USERNAME=test var=_GIT_Password=abc .... lokal. This will create a cloudbuild-trigger on the defined branch
of the repository. Afterwards you can push to the Branch an the Cloudbuild will be triggered and run the steps definden in the cloudbuild.yam

philschmid

def get_string_from_dict(input_dict=''):
    try:
        result_string=''
        # loops trough dict
        for key, value in input_dict.items():
            # checks if value is string then translates it
            if(type(value) == str or type(value_text) == int):

philschmid

const fetch = require('node-fetch');
import {transformEntities} from './transformEntities.ts'
const knowYourGraph = (apiKey:string, queryString:string, limit = 50, lng = "en") => {
  return new Promise(async (resolve, reject) => {
    try {
      // building Url for Knowledge Graph
      const url:string = `https://kgsearch.googleapis.com/v1/entities:search?indent=true&languages=${lng}&limit=${limit}&query=${queryString}&key=${apiKey}`;
      // request API
      const response = await fetch(url, {
        headers: {

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def entity_parser(entity_array):
  res_ent=[]
  for ent in inpust_list:
    if ent['sailence'] > 0 and ent['type] != 'OTHER':
       res_ent.append({"name":ent['name'], "type":ent['type'].capitalize(), 
                      "relation": f"is{ent['type'].capitalize()}", "sailence": ent['sailence']})
  return res_ent


def create_article_script(input_article=None):

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def add_entity_to_words(sentence='',entities=''):
  print(sentence)
  res_sen_tpl = []
  sentence= sentence.lower()
  words_in_sentence = tokenize_to_word(sentence)
  for wrd_idx,word in enumerate(words_in_sentence):
    if len(word) > 1:
      r_word = f"{word}"
      word = word.lower()
      for ent in entities:

philschmid

Patent Crawler for Talos-jobs

1. Talos-Job gets created
2. Patent Crawler gets triggered once (noramlly it runs everyday once)
3. Patent Crawler queries "company-patent-table" (not defined yet) should be a table where we match companies to patent assignee for example siemens healthineers doesn hold any patents but siemens healthcare does (not required @ beginning).
4. Patent crawler request url with correct company (rather name not excatly defined and filter in csv), for example : Siemens
   a. url see below
   b. result is a csv
5. patent crawler parses results and compares the result of csv with patent-link-table. (only add last 5-10 years)
6. "new patents" which are not in the "patent-link-table" will be added and the patent crawler crawls them