# 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 #12 #10
# 0 : 8bit Unsigned, 1 : 8bit Signed Default - 1
inElementType      = 0 

inputNetFile       = "..\..\test\testvecs\config\caffe_jacinto_models\trained\image_detection\Eiclassifier_caffe_jacinto_sparse_I3\deploy.prototxt"  
inputParamsFile       = "..\..\test\testvecs\config\caffe_jacinto_models\trained\image_detection\Eiclassifier_caffe_jacinto_sparse_I3\cat_dog_ssd120000.caffemodel"
outputNetFile      = "..\..\test\testvecs\config\tidl_models\jdetnet\Eiclassifier_caffe_jacinto_sparse_I3\NET_OD.BIN"
outputParamsFile   = "..\..\test\testvecs\config\tidl_models\jdetnet\Eiclassifier_caffe_jacinto_sparse_I3\PRM_OD.BIN"

rawSampleInData = 1
preProcType   = 4
sampleInData = "..\..\test\testvecs\input\dog_512x512.y"
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 2 0
conv2dKernelType = 0	0 	0	0	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

