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import platform |
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import re |
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import socket |
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import time |
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import uuid |
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from inference.core.cache import cache |
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from inference.core.logger import logger |
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from inference.core.version import __version__ |
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def get_model_metrics( |
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inference_server_id: str, model_id: str, min: float = -1, max: float = float("inf") |
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) -> dict: |
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""" |
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Gets the metrics for a given model between a specified time range. |
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Args: |
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device_id (str): The identifier of the device. |
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model_id (str): The identifier of the model. |
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start (float, optional): The starting timestamp of the time range. Defaults to -1. |
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stop (float, optional): The ending timestamp of the time range. Defaults to float("inf"). |
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Returns: |
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dict: A dictionary containing the metrics of the model: |
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- num_inferences (int): The number of inferences made. |
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- avg_inference_time (float): The average inference time. |
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- num_errors (int): The number of errors occurred. |
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""" |
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now = time.time() |
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inferences_with_times = cache.zrangebyscore( |
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f"inference:{inference_server_id}:{model_id}", min=min, max=max, withscores=True |
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) |
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num_inferences = len(inferences_with_times) |
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inference_times = [] |
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for inference, t in inferences_with_times: |
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response = inference["response"] |
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if isinstance(response, list): |
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times = [r["time"] for r in response if "time" in r] |
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inference_times.extend(times) |
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else: |
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if "time" in response: |
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inference_times.append(response["time"]) |
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avg_inference_time = ( |
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sum(inference_times) / len(inference_times) if len(inference_times) > 0 else 0 |
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) |
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errors_with_times = cache.zrangebyscore( |
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f"error:{inference_server_id}:{model_id}", min=min, max=max, withscores=True |
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) |
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num_errors = len(errors_with_times) |
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return { |
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"num_inferences": num_inferences, |
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"avg_inference_time": avg_inference_time, |
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"num_errors": num_errors, |
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} |
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def get_system_info() -> dict: |
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"""Collects system information such as platform, architecture, hostname, IP address, MAC address, and processor details. |
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Returns: |
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dict: A dictionary containing detailed system information. |
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""" |
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info = {} |
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try: |
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info["platform"] = platform.system() |
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info["platform_release"] = platform.release() |
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info["platform_version"] = platform.version() |
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info["architecture"] = platform.machine() |
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info["hostname"] = socket.gethostname() |
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info["ip_address"] = socket.gethostbyname(socket.gethostname()) |
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info["mac_address"] = ":".join(re.findall("..", "%012x" % uuid.getnode())) |
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info["processor"] = platform.processor() |
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return info |
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except Exception as e: |
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logger.exception(e) |
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finally: |
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return info |
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def get_inference_results_for_model( |
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inference_server_id: str, model_id: str, min: float = -1, max: float = float("inf") |
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): |
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inferences_with_times = cache.zrangebyscore( |
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f"inference:{inference_server_id}:{model_id}", min=min, max=max, withscores=True |
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) |
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inference_results = [] |
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for result, score in inferences_with_times: |
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if result.get("request", {}).get("image"): |
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del result["request"]["image"] |
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responses = result.get("response") |
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if responses: |
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if not isinstance(responses, list): |
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responses = [responses] |
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for resp in responses: |
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if resp.get("image"): |
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del resp["image"] |
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inference_results.append({"request_time": score, "inference": result}) |
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return inference_results |
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