Validate a Model
After you train a model, you can validate it in the Validation tab. This topic describes how to configure validation parameters, validate models, and view the validation results.
Configure Validation Parameters
Click 
to open Validation Parameter Settings.
You can configure the following parameters:
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Hardware type
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CPU: Use CPU for deep learning model inference, which will increase inference time and reduce recognition accuracy compared with GPU.
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GPU (default): Do model inference without optimizing according to the hardware, and the model inference will not be accelerated.
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GPU (optimization): Do model inference after optimizing according to the hardware. The optimization only needs to be done once and is expected to take 1–20 minutes.
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GPU ID
The graphics card information of the device deployed by the user. If multiple GPUs are available on the model deployment device, the model can be deployed on a specified GPU.
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Float precision
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FP32: high model accuracy, low inference speed.
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FP16: low model accuracy, high inference speed.
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Max num of inference objects (only visible in the Instance Segmentation module and Object Detection module)
The maximum number of inference objects during a round of inference.
