# 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
# 0 : 8bit Unsigned, 1 : 8bit Signed Default - 1
inElementType      = 0 

inputNetFile       = "_trained_model\deploy.prototxt"
inputParamsFile    = "_trained_model\test_mobiledetnet-1.0_iter_3000.caffemodel"
outputNetFile      = "_output_model\tidl_net_jdetNet_ssd.bin"
outputParamsFile   = "_output_model\tidl_param_jdetNet_ssd.bin"

rawSampleInData = 0
preProcType   = 4
sampleInData = "_test_image\test.jpg"
tidlStatsTool = "..\quantStatsTool\eve_test_dl_algo.out.exe"
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 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 2 0
#layersGroupId =    0 2 2 2 2 2 2 2 2 2	2 2 2 2 2 2 2 2 2 2	2 2 2 2 2 2 2 2 2 2	2 2 2 2 2 2 2 2 2 2	2 2 2 2 2 2 2 2 2 2	0
conv2dKernelType =  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	1 1 	1 1 1 1 1 1 1 1	1 1 1 1 1 1 1 1