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import atexit |
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import functools |
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import logging |
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import os |
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import sys |
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import time |
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from collections import Counter |
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import torch |
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from tabulate import tabulate |
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from termcolor import colored |
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from annotator.oneformer.detectron2.utils.file_io import PathManager |
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__all__ = ["setup_logger", "log_first_n", "log_every_n", "log_every_n_seconds"] |
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class _ColorfulFormatter(logging.Formatter): |
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def __init__(self, *args, **kwargs): |
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self._root_name = kwargs.pop("root_name") + "." |
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self._abbrev_name = kwargs.pop("abbrev_name", "") |
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if len(self._abbrev_name): |
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self._abbrev_name = self._abbrev_name + "." |
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super(_ColorfulFormatter, self).__init__(*args, **kwargs) |
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def formatMessage(self, record): |
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record.name = record.name.replace(self._root_name, self._abbrev_name) |
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log = super(_ColorfulFormatter, self).formatMessage(record) |
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if record.levelno == logging.WARNING: |
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prefix = colored("WARNING", "red", attrs=["blink"]) |
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elif record.levelno == logging.ERROR or record.levelno == logging.CRITICAL: |
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prefix = colored("ERROR", "red", attrs=["blink", "underline"]) |
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else: |
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return log |
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return prefix + " " + log |
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@functools.lru_cache() |
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def setup_logger( |
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output=None, distributed_rank=0, *, color=True, name="detectron2", abbrev_name=None |
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): |
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""" |
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Initialize the detectron2 logger and set its verbosity level to "DEBUG". |
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Args: |
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output (str): a file name or a directory to save log. If None, will not save log file. |
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If ends with ".txt" or ".log", assumed to be a file name. |
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Otherwise, logs will be saved to `output/log.txt`. |
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name (str): the root module name of this logger |
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abbrev_name (str): an abbreviation of the module, to avoid long names in logs. |
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Set to "" to not log the root module in logs. |
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By default, will abbreviate "detectron2" to "d2" and leave other |
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modules unchanged. |
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Returns: |
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logging.Logger: a logger |
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""" |
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logger = logging.getLogger(name) |
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logger.setLevel(logging.DEBUG) |
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logger.propagate = False |
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if abbrev_name is None: |
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abbrev_name = "d2" if name == "detectron2" else name |
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plain_formatter = logging.Formatter( |
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"[%(asctime)s] %(name)s %(levelname)s: %(message)s", datefmt="%m/%d %H:%M:%S" |
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) |
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if distributed_rank == 0: |
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ch = logging.StreamHandler(stream=sys.stdout) |
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ch.setLevel(logging.DEBUG) |
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if color: |
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formatter = _ColorfulFormatter( |
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colored("[%(asctime)s %(name)s]: ", "green") + "%(message)s", |
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datefmt="%m/%d %H:%M:%S", |
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root_name=name, |
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abbrev_name=str(abbrev_name), |
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) |
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else: |
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formatter = plain_formatter |
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ch.setFormatter(formatter) |
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logger.addHandler(ch) |
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if output is not None: |
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if output.endswith(".txt") or output.endswith(".log"): |
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filename = output |
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else: |
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filename = os.path.join(output, "log.txt") |
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if distributed_rank > 0: |
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filename = filename + ".rank{}".format(distributed_rank) |
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PathManager.mkdirs(os.path.dirname(filename)) |
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fh = logging.StreamHandler(_cached_log_stream(filename)) |
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fh.setLevel(logging.DEBUG) |
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fh.setFormatter(plain_formatter) |
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logger.addHandler(fh) |
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return logger |
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@functools.lru_cache(maxsize=None) |
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def _cached_log_stream(filename): |
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io = PathManager.open(filename, "a", buffering=1024 if "://" in filename else -1) |
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atexit.register(io.close) |
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return io |
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""" |
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Below are some other convenient logging methods. |
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They are mainly adopted from |
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https://github.com/abseil/abseil-py/blob/master/absl/logging/__init__.py |
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""" |
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def _find_caller(): |
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""" |
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Returns: |
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str: module name of the caller |
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tuple: a hashable key to be used to identify different callers |
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""" |
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frame = sys._getframe(2) |
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while frame: |
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code = frame.f_code |
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if os.path.join("utils", "logger.") not in code.co_filename: |
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mod_name = frame.f_globals["__name__"] |
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if mod_name == "__main__": |
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mod_name = "detectron2" |
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return mod_name, (code.co_filename, frame.f_lineno, code.co_name) |
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frame = frame.f_back |
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_LOG_COUNTER = Counter() |
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_LOG_TIMER = {} |
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def log_first_n(lvl, msg, n=1, *, name=None, key="caller"): |
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""" |
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Log only for the first n times. |
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Args: |
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lvl (int): the logging level |
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msg (str): |
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n (int): |
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name (str): name of the logger to use. Will use the caller's module by default. |
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key (str or tuple[str]): the string(s) can be one of "caller" or |
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"message", which defines how to identify duplicated logs. |
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For example, if called with `n=1, key="caller"`, this function |
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will only log the first call from the same caller, regardless of |
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the message content. |
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If called with `n=1, key="message"`, this function will log the |
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same content only once, even if they are called from different places. |
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If called with `n=1, key=("caller", "message")`, this function |
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will not log only if the same caller has logged the same message before. |
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""" |
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if isinstance(key, str): |
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key = (key,) |
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assert len(key) > 0 |
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caller_module, caller_key = _find_caller() |
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hash_key = () |
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if "caller" in key: |
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hash_key = hash_key + caller_key |
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if "message" in key: |
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hash_key = hash_key + (msg,) |
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_LOG_COUNTER[hash_key] += 1 |
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if _LOG_COUNTER[hash_key] <= n: |
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logging.getLogger(name or caller_module).log(lvl, msg) |
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def log_every_n(lvl, msg, n=1, *, name=None): |
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""" |
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Log once per n times. |
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Args: |
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lvl (int): the logging level |
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msg (str): |
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n (int): |
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name (str): name of the logger to use. Will use the caller's module by default. |
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""" |
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caller_module, key = _find_caller() |
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_LOG_COUNTER[key] += 1 |
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if n == 1 or _LOG_COUNTER[key] % n == 1: |
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logging.getLogger(name or caller_module).log(lvl, msg) |
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def log_every_n_seconds(lvl, msg, n=1, *, name=None): |
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""" |
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Log no more than once per n seconds. |
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Args: |
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lvl (int): the logging level |
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msg (str): |
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n (int): |
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name (str): name of the logger to use. Will use the caller's module by default. |
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""" |
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caller_module, key = _find_caller() |
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last_logged = _LOG_TIMER.get(key, None) |
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current_time = time.time() |
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if last_logged is None or current_time - last_logged >= n: |
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logging.getLogger(name or caller_module).log(lvl, msg) |
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_LOG_TIMER[key] = current_time |
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def create_small_table(small_dict): |
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""" |
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Create a small table using the keys of small_dict as headers. This is only |
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suitable for small dictionaries. |
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Args: |
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small_dict (dict): a result dictionary of only a few items. |
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Returns: |
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str: the table as a string. |
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""" |
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keys, values = tuple(zip(*small_dict.items())) |
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table = tabulate( |
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[values], |
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headers=keys, |
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tablefmt="pipe", |
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floatfmt=".3f", |
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stralign="center", |
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numalign="center", |
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) |
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return table |
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def _log_api_usage(identifier: str): |
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""" |
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Internal function used to log the usage of different detectron2 components |
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inside facebook's infra. |
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""" |
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torch._C._log_api_usage_once("detectron2." + identifier) |
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