j/ ddlZddlZddlZddlmZddlmZddlmZm Z ddl m Z m Z ddl mZmZmZmZmZmZmZmZddlmZddlmZdd ed ed ed dfdZGddZeZdS)N)Path)Thread)Requesturlopen)SETTINGS __version__)ARGV ENVIRONMENTGITIS_PIP_PACKAGEONLINEPYTHON_VERSIONRANK TESTS_RUNNING)GITHUB_ASSETS_NAMES) get_cpu_info@urldatatimeoutreturnc tj|d}t||ddi}t ||dS#t $rYdSwxYw)z"Send a one-shot JSON POST request.),:) separatorsz Content-Typezapplication/json)rheaders)rN)jsondumpsencoderrclose Exception)rrrbodyreqs ]/home/longshao/multi-rider-rag/.venv/lib/python3.11/site-packages/ultralytics/utils/events.py_postr%s z$:666==??c~?Q.RSSSW%%%++-----      sAA## A10A1c(eZdZdZdZddZdddZdS) EventsaCollect and send anonymous usage analytics with rate-limiting. Event collection and transmission are enabled when sync is enabled in settings, the current process is rank -1 or 0, tests are not running, the environment is online, and the installation source is either pip or the official Ultralytics GitHub repository. Attributes: url (str): Measurement Protocol endpoint for receiving anonymous events. events (list[dict]): In-memory queue of event payloads awaiting transmission. rate_limit (float): Minimum time in seconds between POST requests. t (float): Timestamp of the last transmission in seconds since the epoch. metadata (dict): Static metadata describing runtime, installation source, and environment. enabled (bool): Flag indicating whether analytics collection is active. Methods: __init__: Initialize the event queue, rate limiter, and runtime metadata. __call__: Queue an event and trigger a non-blocking send when the rate limit elapses. zihttps://www.google-analytics.com/mp/collect?measurement_id=G-X8NCJYTQXM&api_secret=QLQrATrNSwGRFRLE-cbHJwrNc g|_d|_d|_ttdjdkt jrdn trdndtj dd dtttttjd zd d |_t"d o.t$dvo%t& ot(otpt jdk|_dS)zRInitialize the Events instance with queue, rate limiter, and environment metadata.g>@gryologitpipother.g4&k Ci)cliinstallpythonCPUversionenv session_idengagement_time_msecsync>rz.https://github.com/ultralytics/ultralytics.gitN)events rate_limittrr namer is_repor rrsplitrrr roundrandommetadatarrrr originenabled)selfs r$__init__zEvents.__init__0s Q==%/ # Uuu.1Ug$+C33A6>>" $ 677$(     V  c c!! c c a3:1a#a c~|jsdSt|jdkri|j|j|jt vr|jndt|d}|jdkr |j |d<|jdkr|t|j nd|d<|j |j|d tj }||jz |jkrdSt!|j}t#t$|jt(d |d fd g|_||_dS)aQueue an event and flush the queue asynchronously when the rate limit elapses. Args: cfg (IterableSimpleNamespace): The configuration object containing mode and task information. device (torch.device | str, optional): The device type (e.g., 'cpu', 'cuda'). backend (object | None, optional): The inference backend instance used during prediction. Ncustom)taskmodeldeviceexportformatpredictbackend)r<paramsuuid) client_idr9T)targetargsdaemon)rClenr9rArJrKrstrmoderNtype__name__appendtimer;r:listrr%rrstart)rDcfgrLrPrQr;payload_eventss r$__call__zEvents.__call__HsZ|  F t{  b -&)i3F&F&FHf++ F x8###&:x x9$$>E>QDMM$:$:W[y! K  FCC D D D IKK J$/ ) ) Fdk**((6*:nUUV    %''' rF)rN)NN)r[ __module__ __qualname____doc__rrErbrFr$r'r'sS& vC    0)))))))rFr')r) rr@r]pathlibr threadingrurllib.requestrr ultralyticsrrultralytics.utilsr r r r r rrrultralytics.utils.downloadsrultralytics.utils.torch_utilsrrXdictfloatr%r'r9rfrFr$rpsM ++++++++--------qqqqqqqqqqqqqqqqqqqq;;;;;;666666  s $      WWWWWWWWt rF