I have create the case code for above file but output is incorrect i couldn’t find what went wrong .i am trying to print layer wise information.
Need to know what parameter need to change for different framework (tf ,pytorch ,onnx) to convert pre-trained models
TF pretrained model casecodes are working fine but when i tried with onnx the accuracy is not right
Import
$convert_onnx
–onnx-model ./onnx_models/${NAME}.onnx
–net-output ${NAME}.json
–data-output ${NAME}.data
Quantize$tensorzone
–action quantization
–dtype float32
–source text
–source-file data/validation_tf.txt
–model-input ${NAME}.json
–model-data ${NAME}.data
–quantized-dtype asymmetric_affine-u8
–quantized-rebuild \
Export
$export_ovxlib
–model-input ${NAME}.json
–data-input ${NAME}.data
–model-quantize ${NAME}.quantize
–export-dtype quantized \
#–optimize VIPNANOQI_PID0X88
#–viv-sdk ${ACUITY_PATH}vcmdtools
#–pack-nbg-unify \