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| # This file includes code which was modified from https://github.com/openai/gpt-2 | |
| import tensorflow as tf | |
| import os | |
| import json | |
| import regex as re | |
| from functools import lru_cache | |
| import requests | |
| import boto3 | |
| import pdb | |
| def bytes_to_unicode(): | |
| bs = ( | |
| list(range(ord("!"), ord("~") + 1)) | |
| + list(range(ord("¡"), ord("¬") + 1)) | |
| + list(range(ord("®"), ord("ÿ") + 1)) | |
| ) | |
| cs = bs[:] | |
| n = 0 | |
| for b in range(2 ** 8): | |
| if b not in bs: | |
| bs.append(b) | |
| cs.append(2 ** 8 + n) | |
| n += 1 | |
| cs = [chr(n) for n in cs] | |
| return dict(zip(bs, cs)) | |
| def get_pairs(word): | |
| pairs = set() | |
| prev_char = word[0] | |
| for char in word[1:]: | |
| pairs.add((prev_char, char)) | |
| prev_char = char | |
| return pairs | |
| class Encoder: | |
| def __init__(self, encoder, bpe_merges, errors="replace"): | |
| self.encoder = encoder | |
| self.decoder = {v: k for k, v in self.encoder.items()} | |
| self.errors = errors | |
| self.byte_encoder = bytes_to_unicode() | |
| self.byte_decoder = {v: k for k, v in self.byte_encoder.items()} | |
| self.bpe_ranks = dict(zip(bpe_merges, range(len(bpe_merges)))) | |
| self.cache = {} | |
| self.pat = re.compile( | |
| r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+""" | |
| ) | |
| def bpe(self, token): | |
| if token in self.cache: | |
| return self.cache[token] | |
| word = tuple(token) | |
| pairs = get_pairs(word) | |
| if not pairs: | |
| return token | |
| while True: | |
| bigram = min(pairs, key=lambda pair: self.bpe_ranks.get(pair, float("inf"))) | |
| if bigram not in self.bpe_ranks: | |
| break | |
| first, second = bigram | |
| new_word = [] | |
| i = 0 | |
| while i < len(word): | |
| try: | |
| j = word.index(first, i) | |
| new_word.extend(word[i:j]) | |
| i = j | |
| except: | |
| new_word.extend(word[i:]) | |
| break | |
| if word[i] == first and i < len(word) - 1 and word[i + 1] == second: | |
| new_word.append(first + second) | |
| i += 2 | |
| else: | |
| new_word.append(word[i]) | |
| i += 1 | |
| new_word = tuple(new_word) | |
| word = new_word | |
| if len(word) == 1: | |
| break | |
| else: | |
| pairs = get_pairs(word) | |
| word = " ".join(word) | |
| self.cache[token] = word | |
| return word | |
| def encode(self, text): | |
| bpe_tokens = [] | |
| for token in re.findall(self.pat, text): | |
| token = "".join(self.byte_encoder[b] for b in token.encode("utf-8")) | |
| bpe_tokens.extend(self.encoder[bpe_token] for bpe_token in self.bpe(token).split(" ")) | |
| return bpe_tokens | |
| def decode(self, tokens): | |
| text = "".join([self.decoder[token] for token in tokens]) | |
| text = bytearray([self.byte_decoder[c] for c in text]).decode("utf-8", errors=self.errors) | |
| return text | |
| def get_encoder(): | |
| with open("encoder.json", "r") as f: | |
| encoder = json.load(f) | |
| with open("vocab.bpe", "r", encoding="utf-8") as f: | |
| bpe_data = f.read() | |
| bpe_merges = [tuple(merge_str.split()) for merge_str in bpe_data.split("\n")[1:-1]] | |
| return Encoder(encoder=encoder, bpe_merges=bpe_merges) | |
| # encoder = get_encoder() | |
| # print('encoded is ', encoder.encode('hello 👋 world 🌍 This is a long string to test whether or not the emoji issue was fixed!')) |