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DeepView Explore

DeepView Explore

CentML

centml.ai
|
1,971 installs
| (16) | Free
Installation
Launch VS Code Quick Open (Ctrl+P), paste the following command, and press enter.
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DeepView Explore

DeepView

DeepView provides an integrated experience which allows ML practioners to

  • Visually identify model bottlenecks
  • Perform rapid iterative profiling
  • Understand energy consumption and environmental impacts of training jobs
  • Predict deployment time and cost to cloud hardware

DeepView

Backend Installation

This plugin requires DeepView.Profile to be installed for which can be found here You need to launch DeepView.Profile before running this extension.

Usage example

  1. Run DeepView.Profile
  2. Open one of the examples DNN project examples, i.e. Resnet from DeepView.Profile in VSCode
  3. (Optional) You can add other external cloud instances using the providers option in the extension
  4. Press Ctrl+Shift+P, then select DeepView from the dropdown list.
  5. Click on Begin Analysis.

Disabling telemetry

If you do not want to send usage data to CentML, you can set isTelemetryEnabled setting to "No".

You can set the value by going to File > Preferences > Settings (On macOS: Code > Preferences > Settings), and search for telemetry. Then set the value in DeepView > Is Telemetry Enabled. This will disable all telemetry events.

As well, DeepView respects VSCode's telemetry levels. IF telemetry.telemetryLevel is set to off, then no telemetry events will be sent to CentML, even if deepview.telemetry.enabled is set to true. If telemetry.telemetryLevel is set to error or crash, only events containing an error or errors property will be sent to CentML.

Adding cloud instances to the Deployment Tab: You can include information about the instances that you use through the extension settings. There you will find an option named providers that accepts a list of urls separated by commas. Each url must be a JSON file that follows the schema specified here: schema.
Additionally, you need to add the necessary access so the extension can read the file.
You can use an AWS S3 bucket to store your files. Note that you need to update the CORS settings in Permissions tab to enable the extension to read your file.

CORS requirements:

[
    {
        "AllowedHeaders": [],
        "AllowedMethods": [
            "GET"
        ],
        "AllowedOrigins": [
            "http://*",
            "https://*",
            "vscode-webview://*"
        ],
        "ExposeHeaders": []
    }
]

This is our file that you can use as an example.

Additional Documentation

Documentation can be found at https://docs.centml.ai/index.html

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