Currently, no_grad() is the primary context — it disables gradient tracking during ML inference when using host tensor capabilities. This avoids unnecessary memory and computation for operations that do not need backpropagation:
Making it easierThere are issues with my solution thus far, many of which boil down to the physical spaces assigned to hold queries and results and transformations and data. If I bring in new data with new genres, new result lists could physically lengthen and overlap one another. Planning a physical map for the worksheet is a priority.
，更多细节参见新收录的资料
import usb.core
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