This thread has been locked.
If you have a related question, please click the "Ask a related question" button in the top right corner. The newly created question will be automatically linked to this question.
Hi Team,
I am trying to understand, how memory will be managed during the Neural Network model Inference on DSP.
Question1: Will the two .bin files(net.bin and io.bin, which are required for model inference) be loaded entirely into a ram from the SD card.
Question2: For example The size of two bin files is 5Mb then, Will the 5Mb be loaded entirely at application initialization and released at deinitialization (OR) It will be loaded and released only at inference time.
Could you please help me to understand the answers to these two questions?
Thanks and Regards,
Aneesh
Hi Aneesh,
Question1: Will the two .bin files(net.bin and io.bin, which are required for model inference) be loaded entirely into a ram from the SD card.
Yes.
Question2: For example The size of two bin files is 5Mb then, Will the 5Mb be loaded entirely at application initialization and released at deinitialization (OR) It will be loaded and released only at inference time.
Yes its expected to be this way.
Regards,
Anshu
Hi Anshu,
Thank you for the information.
I understood the answer to the first question. But I did not understand the second question. Can you please elaborate on the second question answer?
Thanks and Regards,
Aneesh
Hi Aneesh,
What i meant is model are expected to be loaded once during application initialization and are not expected to be loaded again for each frames inference.
Regards,
Anshu