Spaces:
Runtime error
Runtime error
| # Modified from: | |
| # PixArt: https://github.com/PixArt-alpha/PixArt-alpha/blob/master/diffusion/model/t5.py | |
| import os | |
| import re | |
| import html | |
| import urllib.parse as ul | |
| import ftfy | |
| import torch | |
| from bs4 import BeautifulSoup | |
| from transformers import T5EncoderModel, AutoTokenizer | |
| from huggingface_hub import hf_hub_download | |
| class T5Embedder: | |
| available_models = ['t5-v1_1-xxl', 't5-v1_1-xl', 'flan-t5-xl'] | |
| bad_punct_regex = re.compile(r'['+'#®•©™&@·º½¾¿¡§~'+'\)'+'\('+'\]'+'\['+'\}'+'\{'+'\|'+'\\'+'\/'+'\*' + r']{1,}') # noqa | |
| def __init__(self, device, dir_or_name='t5-v1_1-xxl', *, local_cache=False, cache_dir=None, hf_token=None, use_text_preprocessing=True, | |
| t5_model_kwargs=None, torch_dtype=None, use_offload_folder=None, model_max_length=120): | |
| self.device = torch.device(device) | |
| self.torch_dtype = torch_dtype or torch.bfloat16 | |
| if t5_model_kwargs is None: | |
| t5_model_kwargs = {'low_cpu_mem_usage': True, 'torch_dtype': self.torch_dtype} | |
| t5_model_kwargs['device_map'] = {'shared': self.device, 'encoder': self.device} | |
| self.use_text_preprocessing = use_text_preprocessing | |
| self.hf_token = hf_token | |
| self.cache_dir = cache_dir or os.path.expanduser('~/.cache/IF_') | |
| self.dir_or_name = dir_or_name | |
| tokenizer_path, path = dir_or_name, dir_or_name | |
| if local_cache: | |
| cache_dir = os.path.join(self.cache_dir, dir_or_name) | |
| tokenizer_path, path = cache_dir, cache_dir | |
| elif dir_or_name in self.available_models: | |
| cache_dir = os.path.join(self.cache_dir, dir_or_name) | |
| for filename in [ | |
| 'config.json', 'special_tokens_map.json', 'spiece.model', 'tokenizer_config.json', | |
| 'pytorch_model.bin.index.json', 'pytorch_model-00001-of-00002.bin', 'pytorch_model-00002-of-00002.bin' | |
| ]: | |
| hf_hub_download(repo_id=f'DeepFloyd/{dir_or_name}', filename=filename, cache_dir=cache_dir, | |
| force_filename=filename, token=self.hf_token) | |
| tokenizer_path, path = cache_dir, cache_dir | |
| else: | |
| cache_dir = os.path.join(self.cache_dir, 't5-v1_1-xxl') | |
| for filename in [ | |
| 'config.json', 'special_tokens_map.json', 'spiece.model', 'tokenizer_config.json', | |
| ]: | |
| hf_hub_download(repo_id='DeepFloyd/t5-v1_1-xxl', filename=filename, cache_dir=cache_dir, | |
| force_filename=filename, token=self.hf_token) | |
| tokenizer_path = cache_dir | |
| print(tokenizer_path) | |
| self.tokenizer = AutoTokenizer.from_pretrained(tokenizer_path) | |
| self.model = T5EncoderModel.from_pretrained(path, **t5_model_kwargs).eval() | |
| self.model_max_length = model_max_length | |
| def get_text_embeddings(self, texts): | |
| texts = [self.text_preprocessing(text) for text in texts] | |
| text_tokens_and_mask = self.tokenizer( | |
| texts, | |
| max_length=self.model_max_length, | |
| padding='max_length', | |
| truncation=True, | |
| return_attention_mask=True, | |
| add_special_tokens=True, | |
| return_tensors='pt' | |
| ) | |
| text_tokens_and_mask['input_ids'] = text_tokens_and_mask['input_ids'] | |
| text_tokens_and_mask['attention_mask'] = text_tokens_and_mask['attention_mask'] | |
| with torch.no_grad(): | |
| text_encoder_embs = self.model( | |
| input_ids=text_tokens_and_mask['input_ids'].to(self.device), | |
| attention_mask=text_tokens_and_mask['attention_mask'].to(self.device), | |
| )['last_hidden_state'].detach() | |
| return text_encoder_embs, text_tokens_and_mask['attention_mask'].to(self.device) | |
| def text_preprocessing(self, text): | |
| if self.use_text_preprocessing: | |
| # The exact text cleaning as was in the training stage: | |
| text = self.clean_caption(text) | |
| text = self.clean_caption(text) | |
| return text | |
| else: | |
| return text.lower().strip() | |
| def basic_clean(text): | |
| text = ftfy.fix_text(text) | |
| text = html.unescape(html.unescape(text)) | |
| return text.strip() | |
| def clean_caption(self, caption): | |
| caption = str(caption) | |
| caption = ul.unquote_plus(caption) | |
| caption = caption.strip().lower() | |
| caption = re.sub('<person>', 'person', caption) | |
| # urls: | |
| caption = re.sub( | |
| r'\b((?:https?:(?:\/{1,3}|[a-zA-Z0-9%])|[a-zA-Z0-9.\-]+[.](?:com|co|ru|net|org|edu|gov|it)[\w/-]*\b\/?(?!@)))', # noqa | |
| '', caption) # regex for urls | |
| caption = re.sub( | |
| r'\b((?:www:(?:\/{1,3}|[a-zA-Z0-9%])|[a-zA-Z0-9.\-]+[.](?:com|co|ru|net|org|edu|gov|it)[\w/-]*\b\/?(?!@)))', # noqa | |
| '', caption) # regex for urls | |
| # html: | |
| caption = BeautifulSoup(caption, features='html.parser').text | |
| # @<nickname> | |
| caption = re.sub(r'@[\w\d]+\b', '', caption) | |
| # 31C0—31EF CJK Strokes | |
| # 31F0—31FF Katakana Phonetic Extensions | |
| # 3200—32FF Enclosed CJK Letters and Months | |
| # 3300—33FF CJK Compatibility | |
| # 3400—4DBF CJK Unified Ideographs Extension A | |
| # 4DC0—4DFF Yijing Hexagram Symbols | |
| # 4E00—9FFF CJK Unified Ideographs | |
| caption = re.sub(r'[\u31c0-\u31ef]+', '', caption) | |
| caption = re.sub(r'[\u31f0-\u31ff]+', '', caption) | |
| caption = re.sub(r'[\u3200-\u32ff]+', '', caption) | |
| caption = re.sub(r'[\u3300-\u33ff]+', '', caption) | |
| caption = re.sub(r'[\u3400-\u4dbf]+', '', caption) | |
| caption = re.sub(r'[\u4dc0-\u4dff]+', '', caption) | |
| caption = re.sub(r'[\u4e00-\u9fff]+', '', caption) | |
| ####################################################### | |
| # все виды тире / all types of dash --> "-" | |
| caption = re.sub( | |
| r'[\u002D\u058A\u05BE\u1400\u1806\u2010-\u2015\u2E17\u2E1A\u2E3A\u2E3B\u2E40\u301C\u3030\u30A0\uFE31\uFE32\uFE58\uFE63\uFF0D]+', # noqa | |
| '-', caption) | |
| # кавычки к одному стандарту | |
| caption = re.sub(r'[`´«»“”¨]', '"', caption) | |
| caption = re.sub(r'[‘’]', "'", caption) | |
| # " | |
| caption = re.sub(r'"?', '', caption) | |
| # & | |
| caption = re.sub(r'&', '', caption) | |
| # ip adresses: | |
| caption = re.sub(r'\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}', ' ', caption) | |
| # article ids: | |
| caption = re.sub(r'\d:\d\d\s+$', '', caption) | |
| # \n | |
| caption = re.sub(r'\\n', ' ', caption) | |
| # "#123" | |
| caption = re.sub(r'#\d{1,3}\b', '', caption) | |
| # "#12345.." | |
| caption = re.sub(r'#\d{5,}\b', '', caption) | |
| # "123456.." | |
| caption = re.sub(r'\b\d{6,}\b', '', caption) | |
| # filenames: | |
| caption = re.sub(r'[\S]+\.(?:png|jpg|jpeg|bmp|webp|eps|pdf|apk|mp4)', '', caption) | |
| # | |
| caption = re.sub(r'[\"\']{2,}', r'"', caption) # """AUSVERKAUFT""" | |
| caption = re.sub(r'[\.]{2,}', r' ', caption) # """AUSVERKAUFT""" | |
| caption = re.sub(self.bad_punct_regex, r' ', caption) # ***AUSVERKAUFT***, #AUSVERKAUFT | |
| caption = re.sub(r'\s+\.\s+', r' ', caption) # " . " | |
| # this-is-my-cute-cat / this_is_my_cute_cat | |
| regex2 = re.compile(r'(?:\-|\_)') | |
| if len(re.findall(regex2, caption)) > 3: | |
| caption = re.sub(regex2, ' ', caption) | |
| caption = self.basic_clean(caption) | |
| caption = re.sub(r'\b[a-zA-Z]{1,3}\d{3,15}\b', '', caption) # jc6640 | |
| caption = re.sub(r'\b[a-zA-Z]+\d+[a-zA-Z]+\b', '', caption) # jc6640vc | |
| caption = re.sub(r'\b\d+[a-zA-Z]+\d+\b', '', caption) # 6640vc231 | |
| caption = re.sub(r'(worldwide\s+)?(free\s+)?shipping', '', caption) | |
| caption = re.sub(r'(free\s)?download(\sfree)?', '', caption) | |
| caption = re.sub(r'\bclick\b\s(?:for|on)\s\w+', '', caption) | |
| caption = re.sub(r'\b(?:png|jpg|jpeg|bmp|webp|eps|pdf|apk|mp4)(\simage[s]?)?', '', caption) | |
| caption = re.sub(r'\bpage\s+\d+\b', '', caption) | |
| caption = re.sub(r'\b\d*[a-zA-Z]+\d+[a-zA-Z]+\d+[a-zA-Z\d]*\b', r' ', caption) # j2d1a2a... | |
| caption = re.sub(r'\b\d+\.?\d*[xх×]\d+\.?\d*\b', '', caption) | |
| caption = re.sub(r'\b\s+\:\s+', r': ', caption) | |
| caption = re.sub(r'(\D[,\./])\b', r'\1 ', caption) | |
| caption = re.sub(r'\s+', ' ', caption) | |
| caption.strip() | |
| caption = re.sub(r'^[\"\']([\w\W]+)[\"\']$', r'\1', caption) | |
| caption = re.sub(r'^[\'\_,\-\:;]', r'', caption) | |
| caption = re.sub(r'[\'\_,\-\:\-\+]$', r'', caption) | |
| caption = re.sub(r'^\.\S+$', '', caption) | |
| return caption.strip() |