'{0}' is required for package management. Please make sure it is installed and set up correctly.包管理需要“{0}”。请确保其已安装并正确设置。......Action操作Add new新增Are you sure you want to delete model '{0}?确定要删除模型“{0}”?Are you sure you want to install required packages?是否确实要安装所需的包?Azure ML workspaceAzure ML 工作区Azure Machine LearningAzure 机器学习Azure accountAzure 帐户Azure modelsAzure 模型Azure sign in or refresh accountAzure 登录或刷新帐户Azure subscriptionAzure 订阅Cancel取消Cannot find Python executable '{0}'. Please make sure Python is installed and configured correctly找不到 Python 可执行文件“{0}”。请确保已正确安装和配置 PythonCannot find R executable '{0}'. Please make sure R is installed and configured correctly找不到 R 可执行文件“{0}”。请确保已正确安装和配置 RClick to review warning details单击以查看警告详细信息Close关闭Config配置Could not find the specified resource无法找到指定的资源Create notebook创建笔记本Database数据库Date created已创建日期Date imported已导入日期Delete删除Description说明Differences in data type数据类型的差异Disable禁用Display name显示名称Downloading正在下载Downloading Model from Azure正在从 Azure 下载模型Edit编辑Edit model编辑模型Enable启用Enabled已启用Enter model details输入模型详细信息Environment variables环境变量Error while downloading下载时出错Error: {0}错误: {0}Existing table现有表Extension file Name扩展文件名External Execute Script外部执行脚本External script configuration is required for this action.此操作需要外部脚本配置。External script is required for package management. Are you sure you want to enable that.包管理需要外部脚本。是否确实要启用它?Failed to complete task '{0}'. Error: {1}无法完成任务“{0}”。错误: {1}Failed to enable External script.未能启用外部脚本。Failed to get installed python packages. Error: {0}未能获取已安装的 python 包。错误: {0}Failed to install language未能安装语言Failed to load model parameters'未能加载模型参数’Failed to modify Machine Learning Services configurations未能修改机器学习服务配置Failed to register the model: {0} ,file: {1}未能注册模型: {0},文件: {1}Failed to update language未能更新语言Failed to update the model未能更新模型Failed to update the model未能更新模型File文件File Browser文件浏览器File paths of the models to import要导入的模型的文件路径File upload文件上传Filter筛选器Framework框架Framework version框架版本Generate a predicted value or scores using a managed model使用托管模型生成预测值或分数Get started with Machine Learning Services in Azure SQL Managed Instances.Azure SQL 托管实例中的机器学习服务入门。Get started with Machine Learning Services on SQL Server and how to install it on Windows and Linux.SQL Server 上的机器学习服务入门,以及如何在 Windows 和 Linux 上安装它。Get started with machine learning in Azure SQL Database EdgeAzure SQL 数据库 Edge 中的机器学习入门Import导入Import from Azure Machine Learning从 Azure 机器学习导入Import models导入模型Import or view machine learning models stored in database导入或查看存储在数据库中的机器学习模型Import or view models导入或查看模型Imported models导入的模型Install安装Install the Microsoft ODBC driver for SQL Server安装 Microsoft ODBC driver for SQL ServerInstalled已安装Installed已安装Installing dependencies ...正在安装依赖项...Installing required packages ...正在安装所需的包...Invalid Azure resourceAzure 资源无效Invalid model id. model url: {0}模型 ID 无效。模型 URL: {0}Invalid model to predict要预测的模型无效Invalid model to register要注册的模型无效Invalid table for importing models. database name: {0} ,table name: {1}导入模型的表无效。数据库名: {0},表名: {1}Invalid table structure!表结构无效!Language extension location语言扩展位置Language extension path语言扩展路径Languages语言Latest最新Learn how to use Machine Learning extension in Azure Data Studio, to manage packages, make predictions, and import models.了解如何在 Azure Data Studio 中使用机器学习扩展来管理包、进行预测和导入模型。Learn how to use machine learning in SQL Server and SQL on Azure, to run Python and R scripts on relational data.了解如何在 Azure 上的 SQL Server 和 SQL 中使用机器学习,以对关系数据运行 Python 和 R 脚本。Learn more了解详细信息Learn more.了解详细信息。Local models本地模型MSSQL extension is not loaded未加载 MSSQL 扩展Machine Learning机器学习Machine Learning Services Enabled已启用机器学习服务Machine Learning Services in Azure SQL Managed InstanceAzure SQL 托管实例中的机器学习服务Machine Learning extension in Azure Data StudioAzure Data Studio 中的机器学习扩展Machine Learning for SQL databases针对 SQL 数据库的机器学习Machine Learning models can be stored in one or more databases and tables. Select the model database and table to view the models within them.机器学习模型可以存储在一个或多个数据库和表中。选择模型数据库和表以查看其中的模型。Machine learning and AI with ONNX in SQL Database Edge PreviewSQL 数据库 Edge 预览版中使用 ONNX 的机器学习和 AIMake predictions进行预测Map source data to model将源数据映射到模型Model Input mapping模型输入映射Model doesn't have any artifact. model url: {0}模型没有任何项目。模型 URL: {0}Model failed to register模型未能注册Model input模型输入Model name is required.模型名称是必填项。Model output模型输出Model registered successfully已成功注册类型Model updated successfully已成功更新模型Models模型Models模型Name名称Name名称Name名称New table新建表No否No Result returned未返回任何结果No connection selected未选择连接No models found找不到任何模型No models found找不到任何模型Not supported event args不受支持的事件参数Notebook extension is not loaded未加载笔记本扩展OK确定ONNX runtime is not supported in current server当前服务器中不支持 ONNX 运行时Package info request failed with error: {0} {1}包信息请求失败,出现错误: {0} {1}Package management is not supported for the server. Make sure you have Python or R installed.服务器不支持包管理。请确保已安装 Python 或 R。Parameters参数Platform平台Please select a valid model请选择一个有效模型Please select a valid table请选择一个有效任务Please select at least one model to import.请至少选择一个要导入的模型。Please select valid source table and model parameters请选择有效的源表和模型参数Predict预测PythonPythonPython executable is not configured未配置 Python 可执行文件RRR executable is not configured未配置 R 可执行文件Required packages are already installed.已安装所需的包。Resource group资源组Run experiments and create models in a notebook在笔记本中运行试验和创建模型SQL Server Machine Learning Services (Python and R)SQL Server 机器学习服务(Python 和 R)SQL machine learning documentationSQL 机器学习文档Save保存Select Database选择数据库Select a database to store the new model.选择要存储新模型的数据库。Select a database where existing / imported models are stored.选择存储现有/导入模型的数据库。Select a model table to view the list of existing / imported models.选择模型表以查看现有/导入的模型的列表。Select an existing table that conforms the model schema or create a new one to store the imported model.选择符合模型架构的现有表或创建一个新表以存储导入的模型。Select another Azure ML workspace选择另一个 Azure ML 工作区Select another database or table选择其他数据库或表Select column...选择列...Select database选择数据库Select database with models选择具有模型的数据库Select imported model选择导入的模型Select model source type选择模型源类型Select models table选择模型表Select or enter the location to import the models to选择或输入要将模型导入到的位置Select table选择表Select table选择表Select tables with models选择具有模型的表Select the database containing the dataset to apply the prediction.选择包含数据集的数据库以应用预测。Select the table containing the dataset to apply the prediction.选择包含数据集的表以应用预测。Selected Path所选路径Show less收起Show more显示更多Showing {0} model(s)正在显示 {0} 个模型Source columns源列Source database源数据库Source files源文件Source location源位置Source table源表Table表Table meets requirements!表满足要求!Table schema is not supported for model import. Database name: {0}, table name: {1}.模型导入不支持表架构。数据库名: {0},表名: {1}。Target目标The data type of output column does not match the output field’s type.输出列的数据类型与输出字段类型不匹配。The data type of the source table column does not match the required input field’s type.源表列的数据类型与所需的输入字段类型不匹配。The extension failed to load because of it's dependency to Notebook extension. Please check the output log for Notebook extension to get more details扩展因其对笔记本扩展的依赖项而未能加载。请检查笔记本扩展的输出日志以获取更多详细信息The following Python packages are required to install: {0}需要安装以下 Python 包: {0}The following R packages are required to install: {0}安装需要以下 R 包: {0}The models are stored in one or more databases and tables. Select the model database and table to view models in them.模型存储在一个或多个数据库和表中。选择模型数据库和表以查看其中的模型。The required packages are not installed未安装所需的包This document explains how to install the Microsoft ODBC Driver for SQL Server.本文档介绍如何安装 Microsoft ODBC Driver for SQL Server。Type类型Upload model file上传模型文件Useful links有用链接Verifying model management dependencies正在验证模型管理依赖项Verifying package management dependencies正在验证包管理依赖项Version版本Video tutorials视频教程View and import models查看和导入模型Yes是localhostlocalhostunsupported不受支持‘Azure Machine Learning’ is selected. This allows you to choose from models stored in Azure Machine Learning workspaces. Click ‘Next’ to continue.已选择“Azure 机器学习”。此操作允许从存储在 Azure 机器学习工作区内的模型中进行选择。单击“下一步”以继续。‘Azure Machine Learning’ is selected. This allows you to import models stored in Azure Machine Learning workspaces in a model database in this SQL instance. Click ‘Next’ to continue.已选择“Azure 机器学习”。此操作允许你导入存储在此 SQL 实例中模型数据库内 Azure 机器学习工作区中的模型。单击“下一步”以继续。 ‘File Upload’ is selected. This allows you to import a model file from your local machine into a model database in this SQL instance. Click ‘Next’ to continue.已选择“文件上传”。这允许你将模型文件从本地计算机导入到此 SQL 实例中的模型数据库中。单击“下一步”以继续。‘File Upload’ is selected. This allows you to upload a model file from your local machine. Click ‘Next’ to continue.已选择“文件上传”。此操作允许从本地计算机上传模型文件。单击“下一步”以继续。‘Imported Models’ is selected. This allows you to choose from models stored in a model table in your database. Click ‘Next’ to continue.已选择“导入的模型”。这使你可以从存储在数据库中模型表内的模型中进行选择。单击“下一步”以继续。Configurations配置Documents文档Enable External script启用外部脚本Enable Python package management in database.在数据库中启用 Python 包管理。Enable R package management in database.在数据库中启用 R 包管理。Endpoints终结点Import model导入模型Install Machine Learning Dependencies安装机器学习依赖项Local path to a preexisting Python installation used by Machine Learning.机器学习使用的预先存在的 Python 安装的本地路径。Local path to a preexisting R installation used by Machine Learning.机器学习使用的预先存在的 R 安装的本地路径。Machine Learning机器学习Machine Learning机器学习Machine Learning Configurations机器学习配置Make prediction进行预测Manage external languages管理外部语言Manage models管理模型Manage packages in database管理数据库中的包Tasks任务