bundles|jaxrs-ri|2.31| |org.glassfish.jersey.connectors|jersey-apache-connector|2.31| |org.glassfish.jersey.connectors|jersey-grizzly-connector|2.31| |org.glassfish.jersey.connectors|jersey-jdk-connector|2.31| |org connectors|jersey-jetty-connector|2.31| |org.glassfish.jersey.connectors|jersey-netty-connector|2.31| |org.glassfish.jersey.containers|jersey-container-grizzly2-http|2.31| |org.glassfish.jersey.containe containers|jersey-container-grizzly2-servlet|2.31| |org.glassfish.jersey.containers|jersey-container-jdk-http|2.31| |org.glassfish.jersey.containers|jersey-container-jetty-http|2.31| |Group ID|Artifact ID|Version|

std::pair<unsigned int const, std::pair<unsigned ...|run\_demo|8.67%|23.2%|28.1%| |► \_int\_free|libc-2.31.so|4.17%|0.466%|0.439%| |► std::\_Rb\_tree\_increment(std::\_Rb\_tree\_node\_base\_const\*)|libstdc++ , std::\_R...|libstdc++.so...|3.55%|1.92%|1.12%| |► \_int\_malloc|libc-2.31.so|2.98%|2.4%|2.79%| |► \_GI\_libc\_malloc|libc-2.31.so|1.92%|0.759%|0.175%| |► void std::\_push\_heap<\_gnu\_cxx::\_norm al\_iterator<cppcon::Transition\*, ...|run\_demo|1.29%|0.509%|0.163%| |► \_GI\_libc\_free|libc-2.31.so|1.17%|0.296%|0.253%| |► std::\_Rb\_tree<unsigned int, std::pair<unsigned int const, std::pair<unsigned

Network），透過這個層疊網路，將資料封包原封不動地傳遞到目標容器內。 透過圖 2.31 來看看 Funnel 是如何實現這兩點，如圖 2.31 所示。  圖 2.31 Flannel 架構圖 透過圖 2.31 可以看到，首先 Flannel 建立了一個 flannel0

8)); var v_i_16 = "ff"; console.log("parseInt(ff, 16) = " + parseInt(v_i_16, 16)); 页面效果如图 2.31 所示。使用带参数的 parseInt() 函数方法可以将目标值按照参数指定的进制数进行转换。另外，parseInt() 函数方法默认参数为 10，也就是说 parseInt() 方法默认就是将字符串转换成十进制数。 方法默认就是将字符串转换成十进制数。  图 2.31 parseInt() 函数方法 (2) 最后，看一个使用 parseFloat() 函数方法将字符串转换成浮点数字操作的代码示例（详见源代码 ch02 目录中 ch02-js-parseFloat

6 Architecture: core2-64 OE: busybox Homepage: https://www.busybox.net Depends: libc6 (>= 2.31+git0+1094741224), update-alternatives-opkg Recommends: busybox-udhcpc Source: busybox_1

"register": {"states": {"current": 2}}, "system": {"load": {"1": 2.31, "15": 2.72, "5": 2.56, "norm": {"1": 0.1444, "15": 0.17,

2MB / 7.93MB|17.1MB / 0B|10| |dd3f0e8294fa|drone-mysql\_mysql-server\_1|0.09%|184.3MiB / 7.786GiB|2.31%|4.75MB / 9.34MB|29.8MB / 8.19kB|33| |34fbf6057fa9|registry|0.00%|3.965MiB / 7.786GiB|0.05%|39.4kB

[132]: factor Out[132]: [(1.27, 2.31], (0.231, 1.27], (-0.809, 0.231], (-1.853, -0.809], (1.27, 2.31], ... →(0.231, 1.27], (-0.809, 0.231], (-1.853, -0.809], (1.27, 2.31], (0.231, 1.27]) Length: 20 Categories Categories (4, interval[float64]): [(-1.853, -0.809] < (-0.809, 0.231] < (0.231, 1. →27] < (1.27, 2.31]) In [133]: factor = pd.cut(arr, [-5, -1, 0, 1, 5]) In [134]: factor Out[134]: [(1, 5], (0, 1]

"architecture": "x86_64", "platform": "Linux-5.10.0-28-cloud-amd64-x86_64-with-glibc2.31", "gpu_count": 2, "gpu_type": "NVIDIA L4", "gpu_memory_per_device":