介绍 想要针对安全/沙盒实时Odoo实例测试其集成/ RPC代码的Odoo开发人员可以使用此软件包。 Runbot服务器提供了许多此类实例,该模块可以访问这些实例以查找并返回其中一些实时实例的url,数据库和用户凭据。 尝试轻描淡写地进行测试,不要滥用Odoo的runbot服务器。 下面是一些基本的用法示例,但请看一下代码,以了解其他一些有用的方法。 用法 #### 1。 使用默认值的简单示例: from odoo_find_runbot_instance import get_runbot_url_db , runbot_admin_user_credentials import httpx url , db = get_runbot_url_db ( httpx ) username , passwd = runbot_admin_user_credentials () ##
2021-04-02 12:07:45 6KB Python
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cookiecutter-cruft-poery-tox-pre-commit-ci-cd-instance 文档: : 源代码: : 概述 去做 特征 去做 要求 去做 目录 安装 您可以通过安装Cookiecutter Cruft Poetry Tox Pre Commit Ci Cd实例: pip install cookiecutter-cruft-poetry-tox-pre-commit-ci-cd-instance 用法 去做高级用法概述 去做步骤0说明 import cookiecutter_cruft_poetry_tox_pre_commit_ci_cd_instance # TODO 发展 :memo: 笔记为了方便起见,下面的许多过程都被抽象并封装在单个目标中。 :fire: 提示调用不带任何参数的make将在可用命令上显示自动生成的文档。 软件包和依赖项安装 确保
2021-04-01 10:05:13 68KB Makefile
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Decision trees are particularly promising in symbolic representation and reasoning due to their comprehensible nature, which resembles the hierarchical process of human decision making. However, their drawbacks, caused by the single-tree structure, cannot be ignored. A rigid decision path may cause the majority class to overwhelm other class when dealing with imbalanced data sets, and pruning removes not only superfluous nodes, but also subtrees. The proposed learning algorithm, flexible hybrid decision forest (FHDF), mines information implicated in each instance to form logical rules on the basis of a chain rule of local mutual information, then forms different decision tree structures and decision forests later. The most credible decision path from the decision forest can be selected to make a prediction. Furthermore, functional dependencies (FDs), which are extracted from the whole data set based on association rule analysis, perform embeddedattribute selection to remove nodes rather than subtrees, thus helping to achieve different levels of knowledge representation and improve model comprehension in the framework of semi-supervised learning. Naive Bayes replaces the leaf nodes at the bottom of the tree hierarchy, where the conditional independence assumption may hold. This techniquereduces the potential for overfitting and overtraining and improves the prediction quality and generalization. Experimental results on UCI data sets demonstrate the efficacy of the proposed approach.
2021-03-28 17:07:16 269KB decision forest; naive Bayes;
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该数据集也称为PanNuke,包含半自动生成的核实例分割和分类图像,包含19种不同组织类型的详尽核标签。 Cancer Instance Segmentation and Classification 1_datasets.txt Cancer Instance Segmentation and Classification 1_datasets.zip
2021-03-12 09:08:53 673.89MB 数据集
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terraform-aws-ec2-instance 这个terraform模块创建一个ec2实例。 它支持以下配置: n个AWS EC2实例数 (可选)创建ec2密钥对 (可选)创建EC2实例自动恢复cloudwatch警报 可选的cloud-init gzip + base64 userdata输入 可选的cloud-init纯文本userdata输入 通过本地执行程序供应器支持推送供应 推送配置支持来自本地执行配置器的节点定位。 实例上下文属性作为local-exec环境变量公开。 切换api终止保护 将标签映射应用于所有可标签资源 地形版本 v0.12 提供者 名称 版 ws 〜> 2.3 输入项 名称 描述 类型 默认 需要 add_num_suffix 将计数器索引作为后缀添加到实例Name标签 bool true 没有 ami_id ami id strin
2021-02-08 19:07:13 370KB HCL
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OpenGL ES 学习教程(十七) Unity GPU Instance 原理及 GLES 实现(一)
2021-01-28 04:53:44 13.01MB opengles
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OpenGL ES 学习教程(十七) Unity GPU Instance 原理及 GLES 实现(二)
2021-01-28 04:02:49 11.75MB opengl
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