sai-prasanna

import tensorflow as tf #We need tensorflow 2.x
import numpy as np

#The hashlength in bits
hashLength = 256

def buildModel():
    #we can set the seed to simulate the fact that this network is known and doesn't change between runs
    #tf.random.set_seed(42)
    model = tf.keras.Sequential()

sai-prasanna

pip install git+https://github.com/sai-prasanna/spacy-pattern-builder.git
pip install streamlit
python -m spacy download en # Or any other model you wish to use.
streamlit run streamlit_pattern_builder.py

sai-prasanna

from collections import namedtuple
from typing import Any, List, Iterator, Tuple

import torch
import copy



class FairseqHubInferer:
    """

sai-prasanna

import streamlit as st
import numpy as np
from lmproof.scorer import TransformerLMScorer
from lmproof.candidate_generators import (MatchedGenerator,
                                          EnglishInflectedGenerator,
                                          SpellCorrectGenerator)


@st.cache(ignore_hash=True)
def model():

sai-prasanna

import csv
from typing import Dict, Optional
import logging
import torch
import random
from collections import Counter
import numpy as np

from overrides import overrides
from torch.utils.data import Dataset, IterableDataset, DataLoader, DistributedSampler

sai-prasanna

;; Put this in root directory of your project
;; Install pyls in the project environment
;; pip install python-language-server
((python-mode . ((eval . (progn (require 'lsp-mode)
                                (lsp-register-client
                                 (make-lsp-client :new-connection (lsp-tramp-connection "~/miniconda3/envs/znlp/bin/pyls")
                                                  :major-modes '(python-mode)
                                                  :remote? t
                                                  :server-id 'remote-pyls))))
                 (eval . (setq lsp-clients-python-command '("~/miniconda3/envs/znlp/bin/pyls")))

sai-prasanna

import os
import tempfile
import logging
import sentencepiece as spm
from typing import List
from overrides import overrides

from allennlp.common import Params
from allennlp.data.tokenizers.token import Token
from allennlp.data.tokenizers.tokenizer import Tokenizer

sai-prasanna

#!/bin/bash

OLD_XCODE_PATH=${1:-/Applications/Xcode7.app}
NEW_XCODE_PATH=${2:-/Applications/Xcode.app}
IOS_NEW_VERSION=10
DEVICE_SUPPORT_PATH=Contents/Developer/Platforms/iPhoneOS.platform/DeviceSupport
ln -s $NEW_XCODE_PATH/$DEVICE_SUPPORT_PATH/$IOS_NEW_VERSION.* $OLD_XCODE_PATH/$DEVICE_SUPPORT_PATH/

sai-prasanna

/**
 * @providesModule PatientList
 */
import NavigationBar from 'react-native-navbar';
import NavigationButtons from 'NavigationButtons';
import React, { ListView, Navigator, StyleSheet, Text, TextInput, TouchableHighlight, View } from 'react-native';
import { connect } from 'react-redux/native'

@connect(state => ({
  patients: state.patients

sai-prasanna

extension UITableView {
    
    func reloadDataAnimated(animated:Bool) {
        reloadData()
        if animated {
            let animation = CATransition()
            animation.type = kCATransitionPush
            animation.subtype = kCATransitionFromBottom
            animation.timingFunction = CAMediaTimingFunction(name: kCAMediaTimingFunctionEaseInEaseOut)