客户端心跳时打印显卡温度功耗和算力日志，并带回今日预估积分。
Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
dekun
+284
-50
@@ -78,6 +78,7 @@ import hashlib
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import json
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import os
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import subprocess
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import sys
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import time
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import urllib.error
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import urllib.request
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@@ -86,17 +87,29 @@ import uuid
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CONFIG = json.loads(__CONFIG__)
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def hardware():
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gpu_model, vram_gb, gpu_uuid = _gpu()
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return {
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"sn": CONFIG["sn"],
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"token": CONFIG["token"],
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"gpu_model": gpu_model,
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"vram_gb": vram_gb,
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"cpu_count": os.cpu_count(),
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"memory_gb": _memory_gb(),
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"hardware_fingerprint": _fingerprint(gpu_uuid),
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}
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SHARES = 0
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_REFERENCE_MH = (
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("4090", 130.0),
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("4080 SUPER", 95.0),
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("4080", 90.0),
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("4070 TI SUPER", 75.0),
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("4070 TI", 70.0),
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("4070 SUPER", 62.0),
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("4070", 55.0),
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("3090 TI", 125.0),
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("3090", 115.0),
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("3080 TI", 105.0),
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("3080", 95.0),
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("3070 TI", 65.0),
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("3070", 60.0),
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("3060 TI", 48.5),
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("3060", 40.0),
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)
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def current_mode():
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mode = os.environ.get("HYPERNODE_MODE") or CONFIG.get("current_mode") or "pow_mining"
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return mode if mode in {"pow_mining", "gpu_rental"} else "pow_mining"
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def _fingerprint(gpu_uuid):
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@@ -134,72 +147,136 @@ def _board_serial():
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def _gpu():
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probed = _pynvml()
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if probed[0]:
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if probed and probed.get("name"):
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return probed
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return _nvidia_smi()
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probed = _nvidia_smi()
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return probed or {}
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def _blank_gpu():
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return {
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"name": None,
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"vram_gb": None,
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"uuid": None,
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"vram_used_mb": None,
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"vram_total_mb": None,
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"gpu_temp": None,
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"fan_speed": None,
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"power_usage": None,
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"utilization": None,
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}
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def _pynvml():
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try:
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import pynvml
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except ImportError:
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return None, None, None
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return None
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try:
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pynvml.nvmlInit()
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best_name = None
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best = None
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best_bytes = -1
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best_uuid = None
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for index in range(pynvml.nvmlDeviceGetCount()):
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handle = pynvml.nvmlDeviceGetHandleByIndex(index)
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name = pynvml.nvmlDeviceGetName(handle)
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if isinstance(name, bytes):
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name = name.decode()
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total = int(pynvml.nvmlDeviceGetMemoryInfo(handle).total)
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if total > best_bytes:
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uid = pynvml.nvmlDeviceGetUUID(handle)
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if isinstance(uid, bytes):
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uid = uid.decode()
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best_name = str(name)
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best_bytes = total
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best_uuid = str(uid)
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memory = pynvml.nvmlDeviceGetMemoryInfo(handle)
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total = int(memory.total)
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if total <= best_bytes:
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continue
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uid = pynvml.nvmlDeviceGetUUID(handle)
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if isinstance(uid, bytes):
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uid = uid.decode()
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best_bytes = total
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best = _blank_gpu()
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best.update({
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"name": str(name),
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"vram_gb": round(total / (1024 ** 3), 2),
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"uuid": str(uid),
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"vram_used_mb": int(round(int(memory.used) / (1024 ** 2))),
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"vram_total_mb": int(round(total / (1024 ** 2))),
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"gpu_temp": _nvml_call(pynvml.nvmlDeviceGetTemperature, handle, pynvml.NVML_TEMPERATURE_GPU),
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"fan_speed": _nvml_call(pynvml.nvmlDeviceGetFanSpeed, handle),
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"power_usage": _nvml_watts(pynvml, handle),
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"utilization": _nvml_util(pynvml, handle),
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})
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pynvml.nvmlShutdown()
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except Exception:
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return None, None, None
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if not best_name or best_bytes < 0:
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return None, None, None
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return best_name, round(best_bytes / (1024 ** 3), 2), best_uuid
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return None
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return best
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def _nvml_call(func, *args):
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try:
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value = func(*args)
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return int(value)
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except Exception:
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return None
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def _nvml_watts(pynvml, handle):
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try:
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return round(pynvml.nvmlDeviceGetPowerUsage(handle) / 1000, 1)
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except Exception:
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return None
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def _nvml_util(pynvml, handle):
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try:
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return int(pynvml.nvmlDeviceGetUtilizationRates(handle).gpu)
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except Exception:
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return None
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def _nvidia_smi():
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query = "name,memory.total,memory.used,uuid,temperature.gpu,fan.speed,power.draw,utilization.gpu"
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try:
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output = subprocess.check_output(
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["nvidia-smi", "--query-gpu=name,memory.total,uuid", "--format=csv,noheader,nounits"],
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["nvidia-smi", "--query-gpu=" + query, "--format=csv,noheader,nounits"],
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stderr=subprocess.DEVNULL,
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timeout=8,
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text=True,
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)
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except (OSError, subprocess.SubprocessError):
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return None, None, None
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best_name = None
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return None
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best = None
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best_mib = -1.0
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best_uuid = None
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for line in output.splitlines():
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parts = [part.strip() for part in line.split(",", 2)]
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if len(parts) < 2:
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parts = [part.strip() for part in line.split(",")]
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if len(parts) < 8:
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continue
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name, memory = parts[0], parts[1]
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gpu_uuid = parts[2] if len(parts) > 2 else None
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try:
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mib = float(memory)
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except ValueError:
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total = _number(parts[-7])
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if total is None or total <= best_mib:
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continue
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if mib > best_mib:
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best_name = name or None
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best_mib = mib
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best_uuid = gpu_uuid or None
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if best_name is None:
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return None, None, None
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return best_name, round(best_mib / 1024, 2), best_uuid
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best_mib = total
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best = _blank_gpu()
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best.update({
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"name": ",".join(parts[:-7]).strip() or None,
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"vram_gb": round(total / 1024, 2),
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"vram_total_mb": int(round(total)),
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"vram_used_mb": _int_number(parts[-6]),
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"uuid": parts[-5] or None,
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"gpu_temp": _int_number(parts[-4]),
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"fan_speed": _int_number(parts[-3]),
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"power_usage": _number(parts[-2]),
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"utilization": _int_number(parts[-1]),
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})
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return best
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def _number(value):
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try:
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return float(value)
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except (TypeError, ValueError):
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return None
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def _int_number(value):
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number = _number(value)
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if number is None:
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return None
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return int(round(number))
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def _memory_gb():
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@@ -233,28 +310,185 @@ def _memory_gb():
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def beat():
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body = json.dumps(hardware()).encode()
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global SHARES
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gpu = _gpu()
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payload = hardware_from(gpu)
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body = json.dumps(payload).encode()
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request = urllib.request.Request(
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CONFIG["base"] + "/api/v1/node/heartbeat",
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data=body,
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headers={"Content-Type": "application/json"},
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)
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with urllib.request.urlopen(request, timeout=20) as response:
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print(response.read().decode())
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reply = json.loads(response.read().decode())
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SHARES += 1
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_save_shares(SHARES)
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_report(gpu, reply, SHARES)
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def hardware_from(gpu):
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card = gpu or {}
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return {
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"sn": CONFIG["sn"],
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"token": CONFIG["token"],
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"gpu_model": card.get("name"),
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"vram_gb": card.get("vram_gb"),
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"cpu_count": os.cpu_count(),
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"memory_gb": _memory_gb(),
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"hardware_fingerprint": _fingerprint(card.get("uuid")),
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}
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def _report(gpu, reply, shares):
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card = gpu or {}
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name = card.get("name") or "GPU not detected"
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vram = card.get("vram_gb")
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vram_text = f"{vram:.2f} GB" if isinstance(vram, (int, float)) else "n/a"
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_log("INFO", f"{name} · {vram_text}")
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_log("HARDWARE", _hardware_line(card))
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if current_mode() == "gpu_rental":
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load = card.get("utilization")
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load_text = f"{load}% Load" if load is not None else "n/a"
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_log("TASK", f"[AI Task Executing] · {load_text}")
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else:
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rate = _hashrate(name)
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rate_text = f"{rate:.1f} MH/s" if rate is not None else "n/a"
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_log("HASHRATE", f"{rate_text} · Accepted {shares}")
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weight = reply.get("hardware_weight")
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weight_text = f"{float(weight):.1f}" if isinstance(weight, (int, float)) else "n/a"
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node_id = reply.get("display_node_id") or "----"
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status = reply.get("status") or "unknown"
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_log("HEARTBEAT", f"{status} · Node #{node_id} · Weight {weight_text}")
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_log("RECOVERY", _recovery_line(reply))
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print(flush=True)
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def _hardware_line(card):
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used = card.get("vram_used_mb")
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total = card.get("vram_total_mb")
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vram = f"{used} / {total} MB" if used is not None and total is not None else "n/a"
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return " · ".join([
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_suffix(card.get("gpu_temp"), "°C"),
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"Fan " + _suffix(card.get("fan_speed"), "%"),
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_suffix(card.get("power_usage"), " W"),
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"VRAM " + vram,
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])
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def _recovery_line(reply):
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days = int(reply.get("recovery_days") or 0)
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purchase = _decimal(reply.get("purchase_amount"))
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remaining = _decimal(reply.get("recoverable_stake_amount"))
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estimate = reply.get("estimated_daily_points") or "0"
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if purchase is not None and remaining is not None and purchase > 0:
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done = max(0.0, (purchase - remaining) / purchase * 100)
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progress = f"{done:.1f}% returned"
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else:
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progress = "n/a"
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title = "30-day fast recovery" if days == 30 else f"{days}-day recovery"
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return f"{title} · {progress} · Est. Points {estimate}"
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def _hashrate(name):
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upper = (name or "").upper().replace("-", " ")
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for token, rate in _REFERENCE_MH:
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if token in upper:
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return rate
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return None
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def _suffix(value, suffix):
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if value is None:
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return "n/a"
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return f"{value}{suffix}"
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def _decimal(value):
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if value is None or value == "":
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return None
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try:
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return float(value)
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except (TypeError, ValueError):
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return None
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def _log(tag, message):
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color = {
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"INFO": "36",
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"HARDWARE": "33",
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"HASHRATE": "32",
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"TASK": "32",
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"HEARTBEAT": "96",
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"RECOVERY": "33",
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"WARN": "31",
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}.get(tag, "37")
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label = f"[{tag}]".ljust(12)
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if sys.stdout.isatty():
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label = f"\033[1;{color}m{label}\033[0m"
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stamp = time.strftime("%Y-%m-%d %H:%M:%S")
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print(f"{stamp} {label} {message}", flush=True)
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def _share_path():
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folder = os.path.dirname(os.path.abspath(__file__))
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return os.path.join(folder, "." + CONFIG["sn"] + ".shares")
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def _load_shares():
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try:
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with open(_share_path(), encoding="utf-8") as handle:
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return max(0, int(handle.read().strip() or "0"))
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except (OSError, ValueError):
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return 0
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def _save_shares(count):
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try:
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with open(_share_path(), "w", encoding="utf-8") as handle:
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handle.write(str(count))
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except OSError:
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return None
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def _enable_ansi():
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if os.name != "nt":
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return
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try:
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kernel = ctypes.windll.kernel32
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handle = kernel.GetStdHandle(-11)
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mode = ctypes.c_ulong()
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if kernel.GetConsoleMode(handle, ctypes.byref(mode)):
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kernel.SetConsoleMode(handle, mode.value | 0x0004)
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except Exception:
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return None
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if __name__ == "__main__":
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_enable_ansi()
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SHARES = _load_shares()
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_log("INFO", "HyperNode client · " + CONFIG["sn"] + " · " + current_mode())
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while True:
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try:
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beat()
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except urllib.error.HTTPError as exc:
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detail = exc.read().decode(errors="replace").strip()
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_log("WARN", f"heartbeat {exc.code} {detail}")
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except (urllib.error.URLError, TimeoutError, OSError) as exc:
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print(exc)
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_log("WARN", str(exc))
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time.sleep(60)
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"""
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def render_client(sn: str, token: str, base_url: str) -> str:
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config = json.dumps({"sn": sn, "token": token, "base": base_url.rstrip("/")}, ensure_ascii=True)
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config = json.dumps(
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{
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"sn": sn,
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"token": token,
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"base": base_url.rstrip("/"),
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"current_mode": "pow_mining",
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},
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ensure_ascii=True,
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)
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return _CLIENT.replace("__CONFIG__", repr(config))
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Reference in New Issue
Block a user