facts是什么意思

根据提供的引用内容，`facts`是指Ansible中的信息收集功能。在Ansible中，可以使用`gather_facts`来控制是否开启信息收集功能。默认情况下，`gather_facts`是开启的，可以通过设置为`False`来禁用信息收集。`facts`可以提供有关目标主机的信息，例如主机名、IP地址、操作系统、内存和CPU等硬件信息，以及其他自定义信息。这些信息可以在Ansible Playbook中使用，以便在执行任务时进行条件检查和决策。

相关问题

Compared with homogeneous network-based methods, het- erogeneous network-based treatment is closer to reality, due to the different kinds of entities with various kinds of relations [22– 24]. In recent years, knowledge graph (KG) has been utilized for data integration and federation [11, 17]. It allows the knowledge graph embedding (KGE) model to excel in the link prediction tasks [18, 19]. For example, Dai et al. provided a method using Wasser- stein adversarial autoencoder-based KGE, which can solve the problem of vanishing gradient on the discrete representation and exploit autoencoder to generate high-quality negative samples [20]. The SumGNN model proposed by Yu et al. succeeds in inte- grating external information of KG by combining high-quality fea- tures and multi-channel knowledge of the sub-graph [21]. Lin et al. proposed KGNN to predict DDI only based on triple facts of KG [66]. Although these methods have used KG information, only focusing on the triple facts or simple data fusion can limit performance and inductive capability [69]. Su et al. successively proposed two DDIs prediction methods [55, 56]. The first one is an end-to-end model called KG2ECapsule based on the biomedical knowledge graph (BKG), which can generate high-quality negative samples and make predictions through feature recursively propagating. Another one learns both drug attributes and triple facts based on attention to extract global representation and obtains good performance. However, these methods also have limited ability or ignore the merging of information from multiple perspectives. Apart from the above, the single perspective has many limitations, such as the need to ensure the integrity of related descriptions, just as network-based methods cannot process new nodes [65]. So, the methods only based on network are not inductive, causing limited generalization [69]. However, it can be alleviated by fully using the intrinsic property of the drug seen as local information, such as chemical structure (CS) [40]. And a handful of existing frameworks can effectively integrate multi-information without losing induction [69]. Thus, there is a necessity for us to propose an effective model to fully learn and fuse the local and global infor- mation for improving performance of DDI identification through multiple information complementing.是什么意思

这段文字讨论了异质网络方法相对于同质网络方法更接近现实的原因，并介绍了知识图谱和知识图谱嵌入模型在链接预测任务中的应用。作者提出了一些方法来解决多信息融合和归纳能力限制等问题，包括使用药物的局部信息如化学结构，以及利用多种信息来提高药物相互作用识别的性能。这段文字主要是关于药物相互作用预测领域的研究。

TASK [Gathering Facts] ******************************************************************************** ok: [192.168.1.128] ok: [192.168.1.104] PLAY RECAP ******************************************************************************************** 192.168.1.104 : ok=1 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0 192.168.1.128 : ok=1 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0 [root@ansible ~]# ansible-playbook /etc/ansible/mariadb.yml PLAY [test01:test02] ********************************************************************************** TASK [Gathering Facts] ******************************************************************************** ok: [192.168.1.104] ok: [192.168.1.128] PLAY RECAP ******************************************************************************************** 192.168.1.104 : ok=1 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0 192.168.1.128 : ok=1 changed=0 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0 什么意思

这段输出表示 Ansible 成功地获取了指定主机的信息，并且没有遇到错误。

在输出的第一个任务 "Gathering Facts" 中，Ansible 会收集有关目标主机的信息，例如操作系统类型、网络配置等。在这个任务中，所有的主机（192.168.1.128 和 192.168.1.104）都成功地完成了信息收集。

在 "PLAY RECAP" 部分，你可以看到每个主机的执行情况。每个主机都显示了完成任务的数量（`ok`），以及是否有变更（`changed`）、不可访问（`unreachable`）、失败（`failed`）、跳过（`skipped`）、救援（`rescued`）或忽略（`ignored`）的情况。在这个例子中，每个主机都成功执行了一个任务，并且没有出现任何变更、不可访问、失败、跳过、救援或忽略的情况。

总体而言，这段输出表示 Ansible 成功地执行了 playbook，并且指定的主机都正常工作，没有遇到问题。