# 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      = 25

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

inputNetFile      = "/home/ubuntu/caffe-jacinto-models/scripts/training/ti-custom-cfg1/JDetNet/20200128_00-56_ds_PSP_dsFac_32_hdDS8_1/sparse/ti-custom-cfg1_ssdJacintoNetV2_iter_120000.caffemodel"

inputParamsFile    = "/home/ubuntu/caffe-jacinto-models/scripts/training/ti-custom-cfg1/JDetNet/20200128_00-56_ds_PSP_dsFac_32_hdDS8_1/sparse/deploy.prototxt"

outputNetFile      = "/home/ubuntu/tidl_net_jdetNet_ssd_512x512.bin"
outputParamsFile   = "/home/ubuntu/tidl_param_jdetNet_ssd_512x512.bin"

rawSampleInData = 1
preProcType   = 4
#sampleInData = "./test/testvecs/input/trace_dump_0_768x320.y"
tidlStatsTool = "eve_test_dl_algo_ref.out"
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	2	0


