seanie12

import tensorflow as tf
import os
import numpy as np

# settings for GPU
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
config = tf.ConfigProto()
config.gpu_options.allow_growth = True
config.gpu_options.per_process_gpu_memory_fraction = 0.9
sess = tf.Session(config=config)

seanie12

import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
import random
import numpy as np
import re, unicodedata

random.seed(1024)

seanie12

import json
import logging
import os
import shutil

import torch
import torch.utils.data as data

import config

seanie12

import numpy as np
import pickle

train_x_file = "./data/train_x"
train_y_file = "./data/train_y"
dev_x_file = "./data/dev_x"
dev_y_file = "./data/dev_y"

input_file = "./data/input.pkl"
label_file = "./data/label.pkl"

seanie12

import json
from pytorch_pretrained_bert.tokenization import whitespace_tokenize
import collections
from copy import deepcopy
class SquadExample(object):
    """
       A single training/test example for the Squad dataset.
       For examples without an answer, the start and end position are -1.
       """

seanie12

import torch
from pytorch_pretrained_bert import BertTokenizer
import random
import numpy as np
from squad_utils import convert_examples_to_features, read_squad_examples
import config

tokenizer = BertTokenizer.from_pretrained("bert-base-uncased", do_lower_case=True)
train_examples = read_squad_examples("./squad/train-v1.1.json", is_training=True, debug=False)
train_features = convert_examples_to_features(train_examples, tokenizer=tokenizer,

seanie12

<better case>

golden: when did abc first start ?
dual: when was abc originally launched by edward j . noble ?
base: what is the name of abc ' s radio network ?

golden : what kind of markets did nbc red serve ?
dual: when was nbc red served by nbc red ?
base: when was the nbc blue network created ?

seanie12

import collections
import json
import re
import string
import sys

import torch
from pytorch_pretrained_bert import BertForQuestionAnswering, BertTokenizer
from torch.utils.data import SequentialSampler, DataLoader, TensorDataset

seanie12

from model import Seq2seq
import os
from squad_utils import read_squad_examples, convert_examples_to_features, write_predictions
from pytorch_pretrained_bert import BertTokenizer, BertForQuestionAnswering
import torch
from torch.utils.data import DataLoader, TensorDataset
import torch.nn.functional as F
import config
import collections
import re, string, sys, json

seanie12

# old files
train_src_file = "./squad/para-train.txt"
train_trg_file = "./squad/tgt-train.txt"
dev_src_file = "./squad/para-dev.txt"
dev_trg_file = "./squad/tgt-dev.txt"
test_src_file = "./squad/para-test.txt"
test_trg_file = "./squad/tgt-test.txt"
embedding = "./data/embedding.pkl"
word2idx_file = "./data/word2idx.pkl"