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Parent topic: Using Notebook for AI Development and Debugging
Using Notebook Instances Remotely Through PyCharm Connecting to a Notebook Instance Through PyCharm Toolkit Manually Connecting to a Notebook Instance Through PyCharm Uploading Data to a Notebook Instance Through PyCharm Parent topic: Using Notebook for AI Development and Debugging
Uploading Files to JupyterLab Uploading Files from a Local Path to JupyterLab Cloning GitHub Open-Source Repository Files to JupyterLab Uploading OBS Files to JupyterLab Uploading Remote Files to JupyterLab Parent topic: Using a Notebook Instance for AI Development Through JupyterLab
Connecting to a Notebook Instance Through PyCharm Toolkit AI developers use PyCharm to develop algorithms or models. ModelArts provides the PyCharm Toolkit plug-in to help AI developers quickly submit locally developed code to the ModelArts training environment.
Collecting Text Analysis Indicator Statistics The text analysis indicator statistics function is used to query call record statistics after AI inspection is complete.
Parent topic: Using a Notebook Instance for AI Development Through JupyterLab
Notebook Instances Remotely Through VS Code Connecting to a Notebook Instance Through VS Code Connecting to a Notebook Instance Through VS Code Toolkit Manually Connecting to a Notebook Instance Through VS Code Uploading and Downloading Files in VS Code Parent topic: Using Notebook for AI
Viewing the Running Records of a Workflow All runtime statuses of a workflow are recorded. On the workflow list page, click the name of the target workflow. On the workflow details page, view all runtime records of the workflow in the left pane. Figure 1 Viewing execution records
Creating a Workflow To create a workflow, define each phase by referring to Creating Workflow Phases. Follow these steps: Sort out scenarios, understand preset steps' functions, and determine the DAG structure. Debug single-phase functions like training or inference on ModelArts.
Searching for a Notebook Instance Searching for an Instance All created instances are displayed on the notebook page. To display a specific instance, search for it based on filter criteria. Grant the permission to the IAM user for viewing all notebook instances. Log in to the ModelArts
Can Such Cameras Use AI Capabilities? A: Yes, the data of non-Huawei cameras can be migrated to the cloud through the GB28181 protocol. VIAS provides the AI capabilities and IVM provides the capability of migrating camera data to the cloud.
Importantly, MoXing Framework is decoupled from specific AI engines and can be seamlessly integrated with all major AI engines (including TensorFlow, MXNet, PyTorch, and MindSpore) supported by ModelArts.
Figure 1 Selecting an AI engine After the file is created, the JupyterLab page is displayed by default. Figure 2 Encoding page Calling mox.file. Enter the following code to implement the following simple functions: Introduce MoXing Framework.
Configuring SFS Turbo and OBS Interworking SFS Turbo HPC file systems can access objects stored in OBS buckets seamlessly. You can specify an SFS Turbo interworking directory and associate it with an OBS bucket. Log in to the SFS console. In the left navigation pane, choose SFS Turbo
Configuring Workflow Parameters Description A workflow parameter is a placeholder object that can be configured when the workflow runs. The following data types are supported: int, str, bool, float, Enum, dict, and list. You can display fields (such as algorithm hyperparameters) in
Creating Workflow Phases Creating a Dataset Phase Creating a Dataset Labeling Phase Creating a Dataset Import Phase Creating a Dataset Release Phase Creating a Training Job Phase Creating a Model Registration Phase Creating a Service Deployment Phase Parent topic: Workflow Development
Creating a Multi-Branch Workflow Multi-Branch Workflow Creating a Condition Phase to Control Branch Execution Configuring Phase Parameters to Control Branch Execution Configuring Multi-Branch Phase Data Parent topic: Workflow Development Command Reference
Advanced Workflow Capabilities Using Big Data Capabilities (MRS) in a Workflow Specifying Certain Phases to Run in a Workflow Parent topic: Workflow Development Command Reference
Autocompletion for ma-cli Commands CLI autocomplete enables you to get a list of supported ma-cli commands by typing a command prefix and pressing Tab on your terminal. Autocomplete for ma-cli commands needs to be enabled in Terminal. After running the ma-cli auto-completion command
Introduction to Inference After an AI model is developed, you can use it to create an AI application and quickly deploy the application as an inference service. The AI inference capabilities can be integrated into your IT platform by calling APIs.
