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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}" # Convert entry to a string
full_path = entry_str
entry_str = entry_str.replace('\\','/')
entry_str = entry_str.replace(f"{directory}", "") # Remove directory part
subfolders.append(entry_str)
return subfolders
def get_available_loras_local(_sortedByTime):
model_dir = shared.args.lora_dir # Update with the appropriate directory path
subfolders = []
if _sortedByTime:
subfolders = list_subfoldersByTime(model_dir)
else:
subfolders = utils.get_available_loras()
return subfolders
# FPHAM SPLIT BY SENTENCE BLOCK ===============
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
# The goal of following code is to create blocks of text + overlapping blocks while:
# respects sentence boundaries
# always uses all the text
# hard cut defined by hard_cut_string or </s> will always end at the end of data block
# no overlapping blocks will be created across hard cut or across </s> token
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 = '<//>' #hardcut placeholder
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}")
#overlap strategies:
# don't overlap across HARD CUT (EOSX)
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 by chance EOSX is at the end then it's acceptable
if currentSentence.endswith(EOSX_str) and len(currentSentence.strip()) > min_chars_cut:
sentencelist.append(currentSentence.strip())
# otherwise don't cross hard cut
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, '')
#someone may have had stop strings in the raw text...
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}")
#final check for useless lines
sentencelist = [item for item in sentencelist if item.strip() != "</s>"]
sentencelist = [item for item in sentencelist if item.strip() != ""]
if debug_slicer:
# Write the log file
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 = '<//>' #hardcut placeholder
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
#print(f"max_cut: {max_cut}")
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, '')
#someone may have had stop strings in the raw text...
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}")
#final check for useless lines
sentencelist = [item for item in sentencelist if item.strip() != "</s>"]
sentencelist = [item for item in sentencelist if item.strip() != ""]
if debug_slicer:
# Write the log file
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
# Example usage:
# download_file_from_url('https://example.com/path/to/your/file.ext', '/output/directory')
def download_file_from_url(url, overwrite, output_dir_in, valid_extensions = {'.txt', '.json'}):
try:
# Validate and sanitize the URL
#parsed_url = urllib.parse.urlparse(url)
#if not parsed_url.netloc:
# raise ValueError("Invalid URL")
#filename = os.path.basename(parsed_url.path)
# Get the filename from the URL
session = requests.Session()
headers = {}
mode = 'wb'
filename = url.split('/')[-1]
output_dir = str(output_dir_in)
# Construct the full path to the output file
local_filename = os.path.join(output_dir, filename)
# Check if the local file already exists
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()
# Send an HTTP GET request to the URL with a timeout
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()
# total size can be wildly inaccurate
#total_size = int(r.headers.get('content-length', 0))
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
# Verify file size if possible
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:
# Close the session to release resources
session.close()
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