Hello,
I have generated a stitched IP using FINN builder of the Brevitas cnv-w2a2 pre-trained model using the notebook under "finn/notebookes/advanced/4_advanced_builder_settings.ipynb", then implemented it on a FPGA target board (NOT PYNQ) which has been connected to communication blocks to read/write to the finn design.
My question is that how should I prepare/feed the input data concerning its folding shape and packaging its inner most dimension in order to obtain a ".dat" file? I got inspired from the data preparation function "custom_step_gen_tb_and_io", that I found in the "finn/tutorials/fpga_flow/build.py" script, but it is for the MNIST classification (tfc-w1a1), but I did not succeed to adapt it for this model (CNV).
Your help would be appreciated!
Hello,
I have generated a stitched IP using FINN builder of the Brevitas cnv-w2a2 pre-trained model using the notebook under "finn/notebookes/advanced/4_advanced_builder_settings.ipynb", then implemented it on a FPGA target board (NOT PYNQ) which has been connected to communication blocks to read/write to the finn design.
My question is that how should I prepare/feed the input data concerning its folding shape and packaging its inner most dimension in order to obtain a ".dat" file? I got inspired from the data preparation function "custom_step_gen_tb_and_io", that I found in the "finn/tutorials/fpga_flow/build.py" script, but it is for the MNIST classification (tfc-w1a1), but I did not succeed to adapt it for this model (CNV).
Your help would be appreciated!