# Default - 0
randParams         = 0 

# 0: Caffe, 1: TensorFlow, Default - 0
modelType          = 0 

# 0: Fixed quantization By tarininng Framework, 1: Dyanamic quantization by TIDL, Default - 1
quantizationStyle  = 1 

# quantRoundAdd/100 will be added while rounding to integer, Default - 50
quantRoundAdd      = 50

numParamBits       = 8

#inNumChannels      = 3
inElementType = 0

inputNetFile       = "deploy.prototxt"
inputParamsFile    = "SSD_512x512_nonsparse_STEP_iter_60000.caffemodel"
outputNetFile      = "NET_OD.BIN"
outputParamsFile   = "PRM_OD.BIN"

rawSampleInData = 1
preProcType   = 0
sampleInData = "..\..\test\testvecs\input\trace_dump_0_512x512.y"
#sampleInData = "..\..\test\testvecs\input\trace_dump_0_768x320.y"
tidlStatsTool = "..\quantStatsTool\eve_test_dl_algo.out.exe"

#6 heads
layersGroupId = 0	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	2	1	2	1	2	1	2	1	2	1	2	1	2	1	2	1	2	1	2	1	2	1	2	2	2	2	0
conv2dKernelType = 0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1

#All sparse
#conv2dKernelType = 0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

#All dense
#conv2dKernelType = 1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1


#5 heads
#layersGroupId = 0	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	2	1	2	1	2	1	2	1	2	1	2	1	2	1	2	1	2	1	2	2	2	2	2	2	2	0
#conv2dKernelType = 0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1
