# VisionPro Deep Learning Startup Options

When launching the Deep Learning GUI, there are several options that you can use to control the GPU Mode, which GPU device to use and the allocation of GPU memory, in addition to project settings.

At the Starting Cognex Deep Learning screen, press the Options button.

Command | Settings
--- | ---
GPU Mode | Specifies the GPU mode to be used by the application.
SingleDevicePerTool | A single GPU is used for the analysis of the tool. When using multiple GPUs, the processing time of a single image remains the same, but multiple images can be processed concurrently on different devices.
MultipleDevicesPerTool | It is no longer supported.
NoSupport | Specifies that a GPU will not be used. Note: This option conflicts with --gpu-devices and/or --optimized-gpu-memory.
Optimized GPU Memory | Specifies the size of the pre-allocated optimized memory buffer. This setting is activated by default, with the default size of 2GB. Tip: Compute Devices You can set Optimized GPU Memory in the Help > Compute Devices option. This dialog contains the information about computing resources. Available Devices This shows the GPUs that are used for VisionPro Deep Learning. You can check list of multiple devices and GRAM information here. Optimized GPU Memory You can enable/disable GPU memory optimization for use with High Detail mode and other tools. If you turn on this option (move toggle to the right side), system pre-allocates GPU memory for tool optimization. You can also select the amount of pre-allocated GPU memory size with input box. It is recommended to turn on this option when training the tools except for the High Detail mode. If you turn off this option (move toggle to the left side), system stops to pre-allocate GPU memory. It is helpful to train Green Classify tool in High Detail mode more efficiently and faster. When you process Green Classify tool in High Detail mode with the other VisionPro Deep Learning tools together, enabling Optimized GPU Memory makes processing time faster. When it comes to processing, enabling Optimized GPU Memory gives less impact to High Detail mode while it makes Focused mode and other Deep Learning tool process much faster.
Auto Save Interval | Specifies how often a workspace will be auto-saved. The default is every 5 minutes.
Training Image Cache Path | Specifies a cache location for training images. This is useful if the images in a stream are in non-raster format (e.g. JPG, PNG, or GIF), since they must be converted to a raster (BMP) format for training. By default, this conversion happens multiple times for each image. By enabling the Training Image Cache Path, the conversion is only performed once and the converted images are stored in a local cache directory. The cache directory should be local, and preferably on a Solid-State Drive (SSD). This option can also speed up training in cases where the workspace is stored on a slower drive or a remote storage device.
Locale | Specifies the language to use throughout the VisionPro Deep Learning Suite GUI.
Debug Logging | Specifies whether or not debug logs should be activated for the project.