| import os |
| from modules import shared, utils |
| from pathlib import Path |
| import requests |
| import tqdm |
| import json |
|
|
| ''' |
| def get_gpu_memory_usage(rank): |
| return { |
| 'total': round(torch.cuda.get_device_properties(rank).total_memory / (1024**3), 2), |
| 'max': round(torch.cuda.max_memory_allocated(rank) / (1024**3), 2), |
| 'reserved': round(torch.cuda.memory_reserved(rank) / (1024**3), 2), |
| 'allocated': round(torch.cuda.memory_allocated(rank) / (1024**3), 2) |
| } |
| ''' |
|
|
| def list_subfoldersByTime(directory): |
|
|
| if not directory.endswith('/'): |
| directory += '/' |
| subfolders = [] |
| subfolders.append('None') |
| path = directory |
| name_list = os.listdir(path) |
| full_list = [os.path.join(path,i) for i in name_list] |
| time_sorted_list = sorted(full_list, key=os.path.getmtime,reverse=True) |
|
|
| for entry in time_sorted_list: |
| if os.path.isdir(entry): |
| entry_str = f"{entry}" |
| full_path = entry_str |
| entry_str = entry_str.replace('\\','/') |
| entry_str = entry_str.replace(f"{directory}", "") |
| subfolders.append(entry_str) |
|
|
| return subfolders |
|
|
| def get_available_loras_local(_sortedByTime): |
| |
| model_dir = shared.args.lora_dir |
| subfolders = [] |
| if _sortedByTime: |
| subfolders = list_subfoldersByTime(model_dir) |
| else: |
| subfolders = utils.get_available_loras() |
|
|
| return subfolders |
|
|
|
|
| |
| |
| def split_sentences(text: str, cutoff_len: int): |
| sentences = [] |
| sentence = '' |
| delimiters = ['. ', '? ', '! ', '... ', '.\n', '?\n', '!\n','...\n','</s>','<//>'] |
| abbreviations = ['Mr. ', 'Mrs. ', 'Dr. ', 'Ms. ', 'St. ', 'Prof. ', 'Jr. ', 'Ltd. ', 'Capt. ', 'Col. ', 'Gen. ', 'Ave. ', 'Blvd. ', 'Co. ', 'Corp. ', 'Dept. ', 'Est. ', 'Gov. ', 'Inc. ', 'Ph.D. ', 'Univ. '] |
| errors = 0 |
| max_cut = cutoff_len-1 |
| prev_char = '' |
|
|
| for char in text: |
| sentence += char |
|
|
| |
| if (any(sentence.endswith(delimiter) for delimiter in delimiters) and |
| not (prev_char.isupper() and len(sentence) >= 3 and sentence[-3] != ' ') and |
| not any(sentence.endswith(abbreviation) for abbreviation in abbreviations)): |
| tokens = shared.tokenizer.encode(sentence) |
| |
| if len(tokens) > max_cut: |
| tokens = tokens[:max_cut] |
| sentence = shared.tokenizer.decode(tokens, skip_special_tokens=True) |
| errors = errors + 1 |
|
|
| sentences.append({'text': sentence, 'size': len(tokens)}) |
| |
| sentence = '' |
|
|
| prev_char = char |
|
|
| if sentence: |
| tokens = shared.tokenizer.encode(sentence) |
| if len(tokens) > max_cut: |
| tokens = tokens[:max_cut] |
| sentence = shared.tokenizer.decode(tokens, skip_special_tokens=True) |
| errors = errors + 1 |
|
|
| sentences.append({'text': sentence, 'size': len(tokens)}) |
|
|
| if errors > 0: |
| print(f"Trimmed sentences beyond Cutoff Length: {errors}") |
|
|
| return sentences |
|
|
| |
| |
| |
| |
| |
|
|
| def precise_cut(text: str, overlap: bool, min_chars_cut: int, eos_to_hc: bool, cutoff_len: int, hard_cut_string: str, debug_slicer:bool): |
|
|
| EOSX_str = '<//>' |
| EOS_str = '</s>' |
| print("Precise raw text slicer: ON") |
| |
| cut_string = hard_cut_string.replace('\\n', '\n') |
| text = text.replace(cut_string, EOSX_str) |
| sentences = split_sentences(text, cutoff_len) |
|
|
| print(f"Sentences: {len(sentences)}") |
| sentencelist = [] |
| currentSentence = '' |
| totalLength = 0 |
| max_cut = cutoff_len-1 |
| half_cut = cutoff_len//2 |
| halfcut_length = 0 |
|
|
| edgeindex = [] |
| half_index = 0 |
|
|
| for index, item in enumerate(sentences): |
| |
| if halfcut_length+ item['size'] < half_cut: |
| halfcut_length += item['size'] |
| half_index = index |
| else: |
| edgeindex.append(half_index) |
| halfcut_length = -2 * max_cut |
|
|
|
|
| if totalLength + item['size'] < max_cut and not currentSentence.endswith(EOSX_str): |
| currentSentence += item['text'] |
| totalLength += item['size'] |
| else: |
|
|
| if len(currentSentence.strip()) > min_chars_cut: |
| sentencelist.append(currentSentence.strip()) |
|
|
| currentSentence = item['text'] |
| totalLength = item['size'] |
| halfcut_length = item['size'] |
| |
| if len(currentSentence.strip()) > min_chars_cut: |
| sentencelist.append(currentSentence.strip()) |
|
|
| unique_blocks = len(sentencelist) |
| print(f"Text Blocks: {unique_blocks}") |
|
|
| |
| |
| if overlap: |
| for edge_idx in edgeindex: |
| currentSentence = '' |
| totalLength = 0 |
|
|
| for item in sentences[edge_idx:]: |
| if totalLength + item['size'] < max_cut: |
| currentSentence += item['text'] |
| totalLength += item['size'] |
| else: |
| |
| if currentSentence.endswith(EOSX_str) and len(currentSentence.strip()) > min_chars_cut: |
| sentencelist.append(currentSentence.strip()) |
| |
| elif EOSX_str not in currentSentence and len(currentSentence.strip()) > min_chars_cut: |
| sentencelist.append(currentSentence.strip()) |
| |
| currentSentence = '' |
| totalLength = 0 |
| break |
| |
| print(f"+ Overlapping blocks: {len(sentencelist)-unique_blocks}") |
|
|
| num_EOS = 0 |
| for i in range(len(sentencelist)): |
| if eos_to_hc: |
| sentencelist[i] = sentencelist[i].replace(EOSX_str, EOS_str) |
| else: |
| sentencelist[i] = sentencelist[i].replace(EOSX_str, '') |
| |
| |
| sentencelist[i] = sentencelist[i].replace("</s></s>", EOS_str) |
| num_EOS += sentencelist[i].count(EOS_str) |
|
|
| if num_EOS > 0: |
| print(f"+ EOS count: {num_EOS}") |
|
|
| |
| sentencelist = [item for item in sentencelist if item.strip() != "</s>"] |
| sentencelist = [item for item in sentencelist if item.strip() != ""] |
|
|
|
|
| if debug_slicer: |
| |
| Path('logs').mkdir(exist_ok=True) |
| sentencelist_dict = {index: sentence for index, sentence in enumerate(sentencelist)} |
| output_file = "logs/sentencelist.json" |
| with open(output_file, 'w') as f: |
| json.dump(sentencelist_dict, f,indent=2) |
| |
| print("Saved sentencelist.json in logs folder") |
| |
| return sentencelist |
|
|
|
|
| def sliding_block_cut(text: str, min_chars_cut: int, eos_to_hc: bool, cutoff_len: int, hard_cut_string: str, debug_slicer:bool): |
|
|
| EOSX_str = '<//>' |
| EOS_str = '</s>' |
| print("Mega Block Overlap: ON") |
| |
| cut_string = hard_cut_string.replace('\\n', '\n') |
| text = text.replace(cut_string, EOSX_str) |
| sentences = split_sentences(text, cutoff_len) |
|
|
| print(f"Sentences: {len(sentences)}") |
| sentencelist = [] |
| |
| max_cut = cutoff_len-1 |
|
|
| |
| advancing_to = 0 |
|
|
| prev_block_lastsentence = "" |
| |
|
|
| for i in range(len(sentences)): |
| totalLength = 0 |
| currentSentence = '' |
| lastsentence = "" |
| |
| if i >= advancing_to: |
| for k in range(i, len(sentences)): |
| |
| current_length = sentences[k]['size'] |
|
|
| if totalLength + current_length <= max_cut and not currentSentence.endswith(EOSX_str): |
| currentSentence += sentences[k]['text'] |
| totalLength += current_length |
| lastsentence = sentences[k]['text'] |
| else: |
| if len(currentSentence.strip()) > min_chars_cut: |
| if prev_block_lastsentence!=lastsentence: |
| sentencelist.append(currentSentence.strip()) |
| prev_block_lastsentence = lastsentence |
| |
| advancing_to = 0 |
| if currentSentence.endswith(EOSX_str): |
| advancing_to = k |
|
|
| currentSentence = "" |
| totalLength = 0 |
| break |
| |
| if currentSentence != "": |
| if len(currentSentence.strip()) > min_chars_cut: |
| sentencelist.append(currentSentence.strip()) |
|
|
| unique_blocks = len(sentencelist) |
| print(f"Text Blocks: {unique_blocks}") |
| num_EOS = 0 |
| for i in range(len(sentencelist)): |
| if eos_to_hc: |
| sentencelist[i] = sentencelist[i].replace(EOSX_str, EOS_str) |
| else: |
| sentencelist[i] = sentencelist[i].replace(EOSX_str, '') |
| |
| |
| sentencelist[i] = sentencelist[i].replace("</s></s>", EOS_str) |
| num_EOS += sentencelist[i].count(EOS_str) |
|
|
| if num_EOS > 0: |
| print(f"+ EOS count: {num_EOS}") |
|
|
| |
| sentencelist = [item for item in sentencelist if item.strip() != "</s>"] |
| sentencelist = [item for item in sentencelist if item.strip() != ""] |
|
|
|
|
| if debug_slicer: |
| |
| Path('logs').mkdir(exist_ok=True) |
| sentencelist_dict = {index: sentence for index, sentence in enumerate(sentencelist)} |
| output_file = "logs/sentencelist.json" |
| with open(output_file, 'w') as f: |
| json.dump(sentencelist_dict, f,indent=2) |
| |
| print("Saved sentencelist.json in logs folder") |
| |
| return sentencelist |
|
|
| |
| |
|
|
| def download_file_from_url(url, overwrite, output_dir_in, valid_extensions = {'.txt', '.json'}): |
| try: |
| |
| |
| |
| |
| |
|
|
| |
|
|
| session = requests.Session() |
| headers = {} |
| mode = 'wb' |
| filename = url.split('/')[-1] |
|
|
| output_dir = str(output_dir_in) |
| |
| local_filename = os.path.join(output_dir, filename) |
|
|
| |
| overw = '' |
| if os.path.exists(local_filename): |
| if not overwrite: |
| yield f"File '{local_filename}' already exists. Aborting." |
| return |
| else: |
| overw = ' [Overwrite existing]' |
|
|
| filename_lower = filename.lower() |
|
|
| |
| file_extension = os.path.splitext(filename_lower)[-1] |
| |
| if file_extension not in valid_extensions: |
| yield f"Invalid file extension: {file_extension}. Only {valid_extensions} files are supported." |
| return |
|
|
| with session.get(url, stream=True, headers=headers, timeout=10) as r: |
| r.raise_for_status() |
| |
| |
| |
| block_size = 1024 * 4 |
| with open(local_filename, mode) as f: |
| count = 0 |
| for data in r.iter_content(block_size): |
| f.write(data) |
| count += len(data) |
|
|
| yield f"Downloaded: {count} " + overw |
|
|
| |
| if os.path.exists(local_filename): |
| downloaded_size = os.path.getsize(local_filename) |
| if downloaded_size > 0: |
| yield f"File '{filename}' downloaded to '{output_dir}' ({downloaded_size} bytes)." |
| print("File Downloaded") |
| else: |
| print("Downloaded file is zero") |
| yield f"Failed. Downloaded file size is zero)." |
| else: |
| print(f"Error: {local_filename} failed to download.") |
| yield f"Error: {local_filename} failed to download" |
|
|
| except Exception as e: |
| print(f"An error occurred: {e}") |
| yield f"An error occurred: {e}" |
|
|
| finally: |
| |
| session.close() |
|
|
|
|