A curated list of AWS resources to prepare for the AWS Certifications
A curated list of awesome AWS resources you need to prepare for the all 5 AWS Certifications. This gist will include: open source repos, blogs & blogposts, ebooks, PDF, whitepapers, video courses, free lecture, slides, sample test and many other resources.
| import csv | |
| import comware | |
| class HPEConf(object): | |
| def __init__(self, input_filenames, output_filename): | |
| self.input_filenames = input_filenames | |
| self.output_filename = output_filename | |
| def _writerows(self, data): |
| from tensorflow.examples.tutorials.mnist import input_data | |
| import tensorflow as tf | |
| import numpy as np | |
| from helper import batches # Helper function created in Mini-batching section | |
| def print_epoch_stats(epoch_i, sess, last_features, last_labels): | |
| """ | |
| Print cost and validation accuracy of an epoch | |
| """ |
| /* | |
| * Superuser processes are usually more important, so we make it | |
| * less likely that we kill those. | |
| */ | |
| if (cap_t(p->cap_effective) & CAP_TO_MASK(CAP_SYS_ADMIN) || | |
| p->uid == 0 || p->euid == 0) | |
| points /= 4; | |
| /* | |
| * We don't want to kill a process with direct hardware access. |
| s = int_sqrt(cpu_time); | |
| if (s) | |
| points /= s; | |
| s = int_sqrt(int_sqrt(run_time)); | |
| if (s) | |
| points /= s; | |
| /* | |
| * Niced processes are most likely less important, so double | |
| * their badness points. |
| /* | |
| * Processes which fork a lot of child processes are likely | |
| * a good choice. We add the vmsize of the childs if they | |
| * have an own mm. This prevents forking servers to flood the | |
| * machine with an endless amount of childs | |
| */ | |
| ... | |
| if (chld->mm != p->mm && chld->mm) | |
| points += chld->mm->total_vm; |
| /* | |
| * The memory size of the process is the basis for the badness. | |
| */ | |
| points = p->mm->total_vm; |
| /* | |
| * oom_badness - calculate a numeric value for how bad this task has been | |
| * @p: task struct of which task we should calculate | |
| * @p: current uptime in seconds | |
| * | |
| * The formula used is relatively simple and documented inline in the | |
| * function. The main rationale is that we want to select a good task | |
| * to kill when we run out of memory. | |
| * | |
| * Good in this context means that: |
| $ dmesg | grep "Out of memory" | |
| [ 3635.537538] Out of memory: Kill process 21580 (jupyter-noteboo) score 37 or sacrifice child | |
| [ 3636.822607] Out of memory: Kill process 22714 (jupyter-noteboo) score 37 or sacrifice child | |
| [ 3643.006328] Out of memory: Kill process 24976 (jupyter-noteboo) score 37 or sacrifice child | |
| [ 3654.916468] Out of memory: Kill process 26118 (jupyter-noteboo) score 37 or sacrifice child | |
| [ 3658.712286] Out of memory: Kill process 28364 (jupyter-noteboo) score 35 or sacrifice child | |
| [ 3666.654763] Out of memory: Kill process 30603 (jupyter-noteboo) score 36 or sacrifice child | |
| [ 3685.390829] Out of memory: Kill process 30620 (jupyter-noteboo) score 36 or sacrifice child |
| $ free -m | |
| total used free shared buff/cache available | |
| Mem: 990 851 20 24 119 54 | |
| Swap: 0 0 0 |
