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sglang/python/sglang/multimodal_gen/runtime/utils/logging_utils.py
Mick 1dedb63860 [diffusion] chore: minor code cleanups (#15190)
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
2025-12-15 23:57:02 +08:00

521 lines
15 KiB
Python

# Copied and adapted from: https://github.com/hao-ai-lab/FastVideo
# SPDX-License-Identifier: Apache-2.0
# adapted from vllm: https://github.com/vllm-project/vllm/blob/v0.7.3/vllm/logger.py
"""Logging configuration for sglang.multimodal_gen."""
import argparse
import contextlib
import datetime
import logging
import os
import sys
import time
import warnings
from contextlib import contextmanager
from functools import lru_cache, partial
from logging import Logger
from types import MethodType
from typing import Any, cast
import sglang.multimodal_gen.envs as envs
SGLANG_DIFFUSION_CONFIGURE_LOGGING = envs.SGLANG_DIFFUSION_CONFIGURE_LOGGING
SGLANG_DIFFUSION_LOGGING_CONFIG_PATH = envs.SGLANG_DIFFUSION_LOGGING_CONFIG_PATH
SGLANG_DIFFUSION_LOGGING_LEVEL = envs.SGLANG_DIFFUSION_LOGGING_LEVEL
SGLANG_DIFFUSION_LOGGING_PREFIX = envs.SGLANG_DIFFUSION_LOGGING_PREFIX
# color
CYAN = "\033[1;36m"
RED = "\033[91m"
GREEN = "\033[92m"
YELLOW = "\033[93m"
RESET = "\033[0;0m"
_FORMAT = (
f"{SGLANG_DIFFUSION_LOGGING_PREFIX}%(levelname)s %(asctime)s "
"[%(filename)s: %(lineno)d] %(message)s"
)
# _FORMAT = "[%(asctime)s] %(message)s"
_DATE_FORMAT = "%m-%d %H:%M:%S"
DEFAULT_LOGGING_CONFIG = {
"formatters": {
"sgl_diffusion": {
"class": "sglang.multimodal_gen.runtime.utils.logging_utils.ColoredFormatter",
"datefmt": _DATE_FORMAT,
"format": _FORMAT,
},
},
"handlers": {
"sgl_diffusion": {
"class": "logging.StreamHandler",
"formatter": "sgl_diffusion",
"level": SGLANG_DIFFUSION_LOGGING_LEVEL,
"stream": "ext://sys.stdout",
},
},
"loggers": {
"sgl_diffusion": {
"handlers": ["sgl_diffusion"],
"level": "WARNING",
"propagate": False,
},
},
"root": {
"handlers": ["sgl_diffusion"],
"level": "DEBUG",
},
"version": 1,
"disable_existing_loggers": False,
}
class NewLineFormatter(logging.Formatter):
"""Adds logging prefix to newlines to align multi-line messages."""
def __init__(self, fmt, datefmt=None, style="%"):
logging.Formatter.__init__(self, fmt, datefmt, style)
def format(self, record):
msg = logging.Formatter.format(self, record)
if record.message != "":
parts = msg.split(record.message)
msg = msg.replace("\n", "\r\n" + parts[0])
return msg
class ColoredFormatter(NewLineFormatter):
"""A logging formatter that adds color to log levels."""
LEVEL_COLORS = {
logging.ERROR: RED,
logging.WARNING: YELLOW,
}
def format(self, record: logging.LogRecord) -> str:
"""Adds color to the log level name."""
original_levelname = record.levelname
color = self.LEVEL_COLORS.get(record.levelno)
if color:
record.levelname = f"{color}{original_levelname}{RESET}"
formatted_message = super().format(record)
if color:
record.levelname = original_levelname
return formatted_message
class SortedHelpFormatter(argparse.HelpFormatter):
"""SortedHelpFormatter that sorts arguments by their option strings."""
def add_arguments(self, actions):
actions = sorted(actions, key=lambda x: x.option_strings)
super().add_arguments(actions)
@lru_cache
def _print_info_once(logger: Logger, msg: str) -> None:
# Set the stacklevel to 2 to print the original caller's line info
logger.info(msg, stacklevel=2)
@lru_cache
def _print_warning_once(logger: Logger, msg: str) -> None:
# Set the stacklevel to 2 to print the original caller's line info
logger.warning(msg, stacklevel=2)
def get_is_main_process():
try:
rank = int(os.environ["RANK"])
except (KeyError, ValueError):
rank = 0
return rank == 0
def get_is_local_main_process():
try:
rank = int(os.environ["LOCAL_RANK"])
except (KeyError, ValueError):
rank = 0
return rank == 0
def _log_process_aware(
level: int,
logger_self: Logger,
msg: object,
*args: Any,
main_process_only: bool,
local_main_process_only: bool,
**kwargs: Any,
) -> None:
"""Helper function to log a message if the process rank matches the criteria."""
is_main_process = get_is_main_process()
is_local_main_process = get_is_local_main_process()
should_log = (
not main_process_only
and not local_main_process_only
or (main_process_only and is_main_process)
or (local_main_process_only and is_local_main_process)
)
if should_log:
# stacklevel=3 to show the original caller's location,
# as this function is called by the patched methods.
logger_self.log(level, msg, *args, stacklevel=3, **kwargs)
class _SGLDiffusionLogger(Logger):
"""
Note:
This class is just to provide type information.
We actually patch the methods directly on the :class:`logging.Logger`
instance to avoid conflicting with other libraries such as
`intel_extension_for_pytorch.utils._logger`.
"""
def info_once(self, msg: str) -> None:
"""
As :meth:`info`, but subsequent calls with the same message
are silently dropped.
"""
_print_info_once(self, msg)
def warning_once(self, msg: str) -> None:
"""
As :meth:`warning`, but subsequent calls with the same message
are silently dropped.
"""
_print_warning_once(self, msg)
def info( # type: ignore[override]
self,
msg: object,
*args: Any,
main_process_only: bool = True,
local_main_process_only: bool = True,
**kwargs: Any,
) -> None: ...
def debug( # type: ignore[override]
self,
msg: object,
*args: Any,
main_process_only: bool = True,
local_main_process_only: bool = True,
**kwargs: Any,
) -> None: ...
def warning( # type: ignore[override]
self,
msg: object,
*args: Any,
main_process_only: bool = False,
local_main_process_only: bool = True,
**kwargs: Any,
) -> None: ...
def error( # type: ignore[override]
self,
msg: object,
*args: Any,
main_process_only: bool = False,
local_main_process_only: bool = True,
**kwargs: Any,
) -> None: ...
def init_logger(name: str) -> _SGLDiffusionLogger:
"""The main purpose of this function is to ensure that loggers are
retrieved in such a way that we can be sure the root sgl_diffusion logger has
already been configured."""
logger = logging.getLogger(name)
# Patch instance methods
setattr(logger, "info_once", MethodType(_print_info_once, logger))
setattr(logger, "warning_once", MethodType(_print_warning_once, logger))
def _create_patched_method(
level: int,
main_process_only_default: bool,
local_main_process_only_default: bool,
):
def _method(
self: Logger,
msg: object,
*args: Any,
main_process_only: bool = main_process_only_default,
local_main_process_only: bool = local_main_process_only_default,
**kwargs: Any,
) -> None:
_log_process_aware(
level,
self,
msg,
*args,
main_process_only=main_process_only,
local_main_process_only=local_main_process_only,
**kwargs,
)
return _method
setattr(
logger,
"info",
MethodType(_create_patched_method(logging.INFO, True, True), logger),
)
setattr(
logger,
"debug",
MethodType(_create_patched_method(logging.DEBUG, True, True), logger),
)
setattr(
logger,
"warning",
MethodType(_create_patched_method(logging.WARNING, False, True), logger),
)
setattr(
logger,
"error",
MethodType(_create_patched_method(logging.ERROR, False, True), logger),
)
return cast(_SGLDiffusionLogger, logger)
logger = init_logger(__name__)
def _trace_calls(log_path, root_dir, frame, event, arg=None):
if event in ["call", "return"]:
# Extract the filename, line number, function name, and the code object
filename = frame.f_code.co_filename
lineno = frame.f_lineno
func_name = frame.f_code.co_name
if not filename.startswith(root_dir):
# only log the functions in the sgl_diffusion root_dir
return
# Log every function call or return
try:
last_frame = frame.f_back
if last_frame is not None:
last_filename = last_frame.f_code.co_filename
last_lineno = last_frame.f_lineno
last_func_name = last_frame.f_code.co_name
else:
# initial frame
last_filename = ""
last_lineno = 0
last_func_name = ""
with open(log_path, "a") as f:
ts = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f")
if event == "call":
f.write(
f"{ts} Call to"
f" {func_name} in {filename}:{lineno}"
f" from {last_func_name} in {last_filename}:"
f"{last_lineno}\n"
)
else:
f.write(
f"{ts} Return from"
f" {func_name} in {filename}:{lineno}"
f" to {last_func_name} in {last_filename}:"
f"{last_lineno}\n"
)
except NameError:
# modules are deleted during shutdown
pass
return partial(_trace_calls, log_path, root_dir)
def enable_trace_function_call(log_file_path: str, root_dir: str | None = None):
"""
Enable tracing of every function call in code under `root_dir`.
This is useful for debugging hangs or crashes.
`log_file_path` is the path to the log file.
`root_dir` is the root directory of the code to trace. If None, it is the
sgl_diffusion root directory.
Note that this call is thread-level, any threads calling this function
will have the trace enabled. Other threads will not be affected.
"""
logger.warning(
"SGLANG_DIFFUSION_TRACE_FUNCTION is enabled. It will record every"
" function executed by Python. This will slow down the code. It "
"is suggested to be used for debugging hang or crashes only."
)
logger.info("Trace frame log is saved to %s", log_file_path)
if root_dir is None:
# by default, this is the sgl_diffusion root directory
root_dir = os.path.dirname(os.path.dirname(__file__))
sys.settrace(partial(_trace_calls, log_file_path, root_dir))
def set_uvicorn_logging_configs():
from uvicorn.config import LOGGING_CONFIG
LOGGING_CONFIG["formatters"]["default"][
"fmt"
] = "[%(asctime)s] %(levelprefix)s %(message)s"
LOGGING_CONFIG["formatters"]["default"]["datefmt"] = "%Y-%m-%d %H:%M:%S"
LOGGING_CONFIG["formatters"]["access"][
"fmt"
] = '[%(asctime)s] %(levelprefix)s %(client_addr)s - "%(request_line)s" %(status_code)s'
LOGGING_CONFIG["formatters"]["access"]["datefmt"] = "%Y-%m-%d %H:%M:%S"
def configure_logger(server_args, prefix: str = ""):
log_format = f"[%(asctime)s{prefix}] %(message)s"
datefmt = "%m-%d %H:%M:%S"
logging.basicConfig(
level=getattr(logging, server_args.log_level.upper()),
format=log_format,
datefmt=datefmt,
force=True,
)
set_uvicorn_logging_configs()
def suppress_loggers(loggers_to_suppress: list[str], level: int = logging.WARNING):
original_levels = {}
for logger_name in loggers_to_suppress:
logger = logging.getLogger(logger_name)
original_levels[logger_name] = logger.level
logger.setLevel(level)
return original_levels
@contextmanager
def suppress_other_loggers(not_suppress_on_main_rank: bool = False):
"""
A context manager to temporarily suppress specified loggers.
Args:
not_suppress_on_main_rank (bool): If True, loggers will not be
suppressed on the main process (rank 0).
"""
# This is a global setting that we want to apply to all ranks
warnings.filterwarnings(
"ignore", category=UserWarning, message="The given NumPy array is not writable"
)
should_suppress = True
if not_suppress_on_main_rank:
if get_is_main_process():
should_suppress = False
loggers_to_suppress = [
"urllib3",
"imageio",
"imageio_ffmpeg",
"PIL",
"PIL_Image",
]
filelock_loggers = [
"filelock",
]
original_levels = suppress_loggers(loggers_to_suppress)
original_levels.update(suppress_loggers(filelock_loggers, level=logging.ERROR))
try:
yield
finally:
if should_suppress:
for logger_name, level in original_levels.items():
logging.getLogger(logger_name).setLevel(level)
# source: https://github.com/vllm-project/vllm/blob/a11f4a81e027efd9ef783b943489c222950ac989/vllm/utils/system_utils.py#L60
@contextlib.contextmanager
def suppress_stdout():
"""
Suppress stdout from C libraries at the file descriptor level.
Only suppresses stdout, not stderr, to preserve error messages.
Example:
with suppress_stdout():
# C library calls that would normally print to stdout
torch.distributed.new_group(ranks, backend="gloo")
"""
# Don't suppress if logging level is DEBUG
stdout_fd = sys.stdout.fileno()
stdout_dup = os.dup(stdout_fd)
devnull_fd = os.open(os.devnull, os.O_WRONLY)
try:
sys.stdout.flush()
os.dup2(devnull_fd, stdout_fd)
yield
finally:
sys.stdout.flush()
os.dup2(stdout_dup, stdout_fd)
os.close(stdout_dup)
os.close(devnull_fd)
class GenerationTimer:
def __init__(self):
self.start_time = 0.0
self.end_time = 0.0
self.duration = 0.0
@contextmanager
def log_generation_timer(
logger: logging.Logger,
prompt: str,
request_idx: int | None = None,
total_requests: int | None = None,
):
if request_idx is not None and total_requests is not None:
logger.info(
"Processing prompt %d/%d: %s",
request_idx,
total_requests,
prompt[:100],
)
timer = GenerationTimer()
timer.start_time = time.perf_counter()
try:
yield timer
timer.end_time = time.perf_counter()
timer.duration = timer.end_time - timer.start_time
logger.info("Pixel data generated successfully in %.2f seconds", timer.duration)
except Exception as e:
if request_idx is not None:
logger.error(
"Failed to generate output for prompt %d: %s",
request_idx,
e,
exc_info=True,
)
else:
logger.error(
f"Failed to generate output for prompt: {e}",
exc_info=True,
)
raise
def log_batch_completion(
logger: logging.Logger, num_outputs: int, total_time: float
) -> None:
logger.info(
"Completed batch processing. Generated %d outputs in %.2f seconds.",
num_outputs,
total_time,
)