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import datetime | |
import logging | |
import logging.handlers | |
import os | |
import sys | |
import requests | |
from llava.constants import LOGDIR | |
server_error_msg = "**NETWORK ERROR DUE TO HIGH TRAFFIC. PLEASE REGENERATE OR REFRESH THIS PAGE.**" | |
moderation_msg = "YOUR INPUT VIOLATES OUR CONTENT MODERATION GUIDELINES. PLEASE TRY AGAIN." | |
handler = None | |
import torch.distributed as dist | |
def rank0_print(*args): | |
if dist.is_initialized(): | |
if dist.get_rank() == 0: | |
print(f"Rank {dist.get_rank()}: ", *args) | |
def build_logger(logger_name, logger_filename): | |
global handler | |
formatter = logging.Formatter( | |
fmt="%(asctime)s | %(levelname)s | %(name)s | %(message)s", | |
datefmt="%Y-%m-%d %H:%M:%S", | |
) | |
# Set the format of root handlers | |
if not logging.getLogger().handlers: | |
logging.basicConfig(level=logging.INFO) | |
logging.getLogger().handlers[0].setFormatter(formatter) | |
# Redirect stdout and stderr to loggers | |
stdout_logger = logging.getLogger("stdout") | |
stdout_logger.setLevel(logging.INFO) | |
sl = StreamToLogger(stdout_logger, logging.INFO) | |
sys.stdout = sl | |
stderr_logger = logging.getLogger("stderr") | |
stderr_logger.setLevel(logging.ERROR) | |
sl = StreamToLogger(stderr_logger, logging.ERROR) | |
sys.stderr = sl | |
# Get logger | |
logger = logging.getLogger(logger_name) | |
logger.setLevel(logging.INFO) | |
# Add a file handler for all loggers | |
if handler is None: | |
os.makedirs(LOGDIR, exist_ok=True) | |
filename = os.path.join(LOGDIR, logger_filename) | |
handler = logging.handlers.TimedRotatingFileHandler(filename, when="D", utc=True) | |
handler.setFormatter(formatter) | |
for name, item in logging.root.manager.loggerDict.items(): | |
if isinstance(item, logging.Logger): | |
item.addHandler(handler) | |
return logger | |
class StreamToLogger(object): | |
""" | |
Fake file-like stream object that redirects writes to a logger instance. | |
""" | |
def __init__(self, logger, log_level=logging.INFO): | |
self.terminal = sys.stdout | |
self.logger = logger | |
self.log_level = log_level | |
self.linebuf = "" | |
def __getattr__(self, attr): | |
return getattr(self.terminal, attr) | |
def write(self, buf): | |
temp_linebuf = self.linebuf + buf | |
self.linebuf = "" | |
for line in temp_linebuf.splitlines(True): | |
# From the io.TextIOWrapper docs: | |
# On output, if newline is None, any '\n' characters written | |
# are translated to the system default line separator. | |
# By default sys.stdout.write() expects '\n' newlines and then | |
# translates them so this is still cross platform. | |
if line[-1] == "\n": | |
self.logger.log(self.log_level, line.rstrip()) | |
else: | |
self.linebuf += line | |
def flush(self): | |
if self.linebuf != "": | |
self.logger.log(self.log_level, self.linebuf.rstrip()) | |
self.linebuf = "" | |
def disable_torch_init(): | |
""" | |
Disable the redundant torch default initialization to accelerate model creation. | |
""" | |
import torch | |
setattr(torch.nn.Linear, "reset_parameters", lambda self: None) | |
setattr(torch.nn.LayerNorm, "reset_parameters", lambda self: None) | |
def violates_moderation(text): | |
""" | |
Check whether the text violates OpenAI moderation API. | |
""" | |
url = "https://api.openai.com/v1/moderations" | |
headers = {"Content-Type": "application/json", "Authorization": "Bearer " + os.environ["OPENAI_API_KEY"]} | |
text = text.replace("\n", "") | |
data = "{" + '"input": ' + f'"{text}"' + "}" | |
data = data.encode("utf-8") | |
try: | |
ret = requests.post(url, headers=headers, data=data, timeout=5) | |
flagged = ret.json()["results"][0]["flagged"] | |
except requests.exceptions.RequestException as e: | |
flagged = False | |
except KeyError as e: | |
flagged = False | |
return flagged | |
def pretty_print_semaphore(semaphore): | |
if semaphore is None: | |
return "None" | |
return f"Semaphore(value={semaphore._value}, locked={semaphore.locked()})" | |