Sorry @jfix, but I started studying Glow recently so my questions are pretty basic. What I’ve done so far to support a new device is the following: I created a new backend based on the CPU backend, but removing code, basically from CPULLVMIRGen, and registered it. Then I rewrote transformPostLowering based on the OpenCL backend. I can compile and validate Low-level IR representation for new device requirements in Int8. Example:
…/…/glow/build/bin/image-classifier images/*.png 
-image-layout=NCHW -image-mode=0to1 
-dump-profile=profile.yaml 
-model=resnet50 -model-input-name=“gpu_0/data”
…/…/glow/build/bin/model-compiler -load-profile=profile.yaml 
-model=resnet50 -model-input=“gpu_0/data”,float,[1,3,224,224] 
-backend=NMP -emit-bundle=bundle 
-quantization-schema=symmetric_with_power2_scale 
-quantization-precision=Int8 -quantization-precision-bias=Int8 
-dump-ir > resnet50.lir
As you can see in the gist resnet50.lir 1 both the NCHW layout and the quantization are ok. But when I try to use Int16 for quantization, the file resnet50-16.lir 1 do not show the expected result. Any help or guidance is welcome. Thanks again, Jordan.