joeyism

#!/bin/bash
CURRENT_ID=$(dig +short myip.opendns.com @resolver1.opendns.com)

read -p "Server Name [$CURRENT_ID]: " SERVER_NAME
SERVER_NAME=${SERVER_NAME:-${CURRENT_ID}}

CURRENT_WORK_DIR=$(pwd)
read -e -p "Working Directory [$CURRENT_WORK_DIR]: " WORKING_DIR
WORKING_DIR=${WORKING_DIR:-${CURRENT_WORK_DIR}}
read -e -p "GUnicorn Executable (i.e. /usr/bin/gunicorn): " GUNICORN_EXEC

joeyism

joeyism

from transformers import GPT2Tokenizer, GPT2LMHeadModel
import torch
import numpy as np

OUTPUT_DIR = "./output"
device = 'cpu'
if torch.cuda.is_available():
    device = 'cuda'

tokenizer = GPT2Tokenizer.from_pretrained(OUTPUT_DIR)

joeyism

import torch.multiprocessing as mp

QUEUE_SIZE = mp.Value('i', 0)

def _decrease_queue():
  with QUEUE_SIZE.get_lock():
    QUEUE_SIZE.value -= 1

def _increase_queue():
  with QUEUE_SIZE.get_lock():

joeyism

import torch.multiprocessing as mp

QUEUE_SIZE = mp.Value('i', 0)

def _decrease_queue():
  with QUEUE_SIZE.get_lock():
    QUEUE_SIZE.value -= 1

def _increase_queue():
  with QUEUE_SIZE.get_lock():

joeyism

import string
import copy
import gpt2

predictor = gpt2.Gpt2Predictor()

def predict_until_punctuation(input_str):
  if not input_str:
    raise Exception('input string required')
  output_str = copy.deepcopy(input_str)

joeyism

{"logits": [-166.17694091796875,
  -166.25209045410156,
  -166.281494140625,
  -166.30458068847656,
  -166.33673095703125,
  -166.34226989746094,
  -166.35443115234375,
  -166.36343383789062,
  -166.37081909179688,
  -166.40570068359375],

joeyism

import gpt2
predictor = gpt2.Gpt2Predictor()
result = predictor.predict_json({"previous": "Toronto Raptors, who are currently tied for the league leader in wins"})

joeyism

import gpt2
predictor = gpt2.Gpt2Predictor()

joeyism

from allennlp.predictors import Predictor
from pytorch_pretrained_bert.tokenization_gpt2 import GPT2Tokenizer
from pytorch_pretrained_bert.modeling_gpt2 import GPT2LMHeadModel
import torch

SMALL_MODEL = 'gpt2'
MEDIUM_MODEL = 'https://storage.googleapis.com/allennlp/models/gpt2-345M-dump'

class Gpt2Predictor(Predictor):
    """