# 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 = "./deploy.prototxt" inputParamsFile = "./cm-custom_ssdJacintoNetV2_iter_2000.caffemodel" outputNetFile = "./tidl_net_cm-custom_ssdJacintoNetV2.bin" outputParamsFile = "./tidl_param_cm-custom_ssdJacintoNetV2.bin" rawSampleInData = 1 preProcType = 4 sampleInData = "./000000_bgr_768x320.raw" tidlStatsTool = "eve_test_dl_algo_ref.out" layersGroupId = 011111111111111111111111111111111111111111111120 conv2dKernelType = 000000000000000011111111111111111111111111111111 result =============================== TIDL import - parsing =============================== Caffe Network File : ./deploy.prototxt Caffe Model File : ./cm-custom_ssdJacintoNetV2_iter_2000.caffemodel TIDL Network File : ./tidl_net_cm-custom_ssdJacintoNetV2.bin TIDL Model File : ./tidl_param_cm-custom_ssdJacintoNetV2.bin Name of the Network : ssdJacintoNetV2_deploy Num Inputs : 1 Error in DetectionOutput layer: could not find parameters for detection_out! Num of Layer Detected : 57 0, TIDL_DataLayer , data 0, -1 , 1 , x , x , x , x , x , x , x , x , 0 , 0 , 0 , 0 , 0 , 1 , 3 , 320 , 768 , 0 , 1, TIDL_BatchNormLayer , data/bias 1, 1 , 1 , 0 , x , x , x , x , x , x , x , 1 , 1 , 3 , 320 , 768 , 1 , 3 , 320 , 768 , 737280 , 2, TIDL_ConvolutionLayer , conv1a 1, 1 , 1 , 1 , x , x , x , x , x , x , x , 2 , 1 , 3 , 320 , 768 , 1 , 32 , 160 , 384 , 147456000 , 3, TIDL_ConvolutionLayer , conv1b 1, 1 , 1 , 2 , x , x , x , x , x , x , x , 3 , 1 , 32 , 160 , 384 , 1 , 32 , 80 , 192 , 141557760 , 4, TIDL_ConvolutionLayer , res2a_branch2a 1, 1 , 1 , 3 , x , x , x , x , x , x , x , 4 , 1 , 32 , 80 , 192 , 1 , 64 , 80 , 192 , 283115520 , 5, TIDL_ConvolutionLayer , res2a_branch2b 1, 1 , 1 , 4 , x , x , x , x , x , x , x , 5 , 1 , 64 , 80 , 192 , 1 , 64 , 40 , 96 , 141557760 , 6, TIDL_ConvolutionLayer , res3a_branch2a 1, 1 , 1 , 5 , x , x , x , x , x , x , x , 6 , 1 , 64 , 40 , 96 , 1 , 128 , 40 , 96 , 283115520 , 7, TIDL_ConvolutionLayer , res3a_branch2b 1, 1 , 1 , 6 , x , x , x , x , x , x , x , 7 , 1 , 128 , 40 , 96 , 1 , 128 , 40 , 96 , 141557760 , 8, TIDL_PoolingLayer , pool3 1, 1 , 1 , 7 , x , x , x , x , x , x , x , 8 , 1 , 128 , 40 , 96 , 1 , 128 , 20 , 48 , 491520 , 9, TIDL_ConvolutionLayer , res4a_branch2a 1, 1 , 1 , 8 , x , x , x , x , x , x , x , 9 , 1 , 128 , 20 , 48 , 1 , 256 , 20 , 48 , 283115520 , 10, TIDL_ConvolutionLayer , res4a_branch2b 1, 1 , 1 , 9 , x , x , x , x , x , x , x , 10 , 1 , 256 , 20 , 48 , 1 , 256 , 10 , 24 , 141557760 , 11, TIDL_ConvolutionLayer , res5a_branch2a 1, 1 , 1 , 10 , x , x , x , x , x , x , x , 11 , 1 , 256 , 10 , 24 , 1 , 512 , 10 , 24 , 283115520 , 12, TIDL_ConvolutionLayer , res5a_branch2b 1, 1 , 1 , 11 , x , x , x , x , x , x , x , 12 , 1 , 512 , 10 , 24 , 1 , 512 , 10 , 24 , 141557760 , 13, TIDL_PoolingLayer , pool6 1, 1 , 1 , 12 , x , x , x , x , x , x , x , 13 , 1 , 512 , 10 , 24 , 1 , 512 , 5 , 12 , 122880 , 14, TIDL_PoolingLayer , pool7 1, 1 , 1 , 13 , x , x , x , x , x , x , x , 14 , 1 , 512 , 5 , 12 , 1 , 512 , 3 , 6 , 36864 , 15, TIDL_PoolingLayer , pool8 1, 1 , 1 , 14 , x , x , x , x , x , x , x , 15 , 1 , 512 , 3 , 6 , 1 , 512 , 2 , 3 , 12288 , 16, TIDL_PoolingLayer , pool9 1, 1 , 1 , 15 , x , x , x , x , x , x , x , 16 , 1 , 512 , 2 , 3 , 1 , 512 , 1 , 2 , 4096 , 17, TIDL_ConvolutionLayer , ctx_output1 1, 1 , 1 , 7 , x , x , x , x , x , x , x , 17 , 1 , 128 , 40 , 96 , 1 , 256 , 40 , 96 , 125829120 , 18, TIDL_ConvolutionLayer , ctx_output2 1, 1 , 1 , 12 , x , x , x , x , x , x , x , 18 , 1 , 512 , 10 , 24 , 1 , 256 , 10 , 24 , 31457280 , 19, TIDL_ConvolutionLayer , ctx_output3 1, 1 , 1 , 13 , x , x , x , x , x , x , x , 19 , 1 , 512 , 5 , 12 , 1 , 256 , 5 , 12 , 7864320 , 20, TIDL_ConvolutionLayer , ctx_output4 1, 1 , 1 , 14 , x , x , x , x , x , x , x , 20 , 1 , 512 , 3 , 6 , 1 , 256 , 3 , 6 , 2359296 , 21, TIDL_ConvolutionLayer , ctx_output5 1, 1 , 1 , 15 , x , x , x , x , x , x , x , 21 , 1 , 512 , 2 , 3 , 1 , 256 , 2 , 3 , 786432 , 22, TIDL_ConvolutionLayer , ctx_output6 1, 1 , 1 , 16 , x , x , x , x , x , x , x , 22 , 1 , 512 , 1 , 2 , 1 , 256 , 1 , 2 , 262144 , 23, TIDL_ConvolutionLayer , ctx_output1/relu_mbox_loc 1, 1 , 1 , 17 , x , x , x , x , x , x , x , 23 , 1 , 256 , 40 , 96 , 1 , 16 , 40 , 96 , 15728640 , 24, TIDL_FlattenLayer , ctx_output1/relu_mbox_loc_perm 1, 1 , 1 , 23 , x , x , x , x , x , x , x , 24 , 1 , 16 , 40 , 96 , 1 , 1 , 1 , 61440 , 1 , 25, TIDL_ConvolutionLayer , ctx_output1/relu_mbox_conf 1, 1 , 1 , 17 , x , x , x , x , x , x , x , 25 , 1 , 256 , 40 , 96 , 1 , 8 , 40 , 96 , 7864320 , 26, TIDL_FlattenLayer , ctx_output1/relu_mbox_conf_perm 1, 1 , 1 , 25 , x , x , x , x , x , x , x , 26 , 1 , 8 , 40 , 96 , 1 , 1 , 1 , 30720 , 1 , 28, TIDL_ConvolutionLayer , ctx_output2/relu_mbox_loc 1, 1 , 1 , 18 , x , x , x , x , x , x , x , 28 , 1 , 256 , 10 , 24 , 1 , 24 , 10 , 24 , 1474560 , 29, TIDL_FlattenLayer , ctx_output2/relu_mbox_loc_perm 1, 1 , 1 , 28 , x , x , x , x , x , x , x , 29 , 1 , 24 , 10 , 24 , 1 , 1 , 1 , 5760 , 1 , 30, TIDL_ConvolutionLayer , ctx_output2/relu_mbox_conf 1, 1 , 1 , 18 , x , x , x , x , x , x , x , 30 , 1 , 256 , 10 , 24 , 1 , 12 , 10 , 24 , 737280 , 31, TIDL_FlattenLayer , ctx_output2/relu_mbox_conf_perm 1, 1 , 1 , 30 , x , x , x , x , x , x , x , 31 , 1 , 12 , 10 , 24 , 1 , 1 , 1 , 2880 , 1 , 33, TIDL_ConvolutionLayer , ctx_output3/relu_mbox_loc 1, 1 , 1 , 19 , x , x , x , x , x , x , x , 33 , 1 , 256 , 5 , 12 , 1 , 24 , 5 , 12 , 368640 , 34, TIDL_FlattenLayer , ctx_output3/relu_mbox_loc_perm 1, 1 , 1 , 33 , x , x , x , x , x , x , x , 34 , 1 , 24 , 5 , 12 , 1 , 1 , 1 , 1440 , 1 , 35, TIDL_ConvolutionLayer , ctx_output3/relu_mbox_conf 1, 1 , 1 , 19 , x , x , x , x , x , x , x , 35 , 1 , 256 , 5 , 12 , 1 , 12 , 5 , 12 , 184320 , 36, TIDL_FlattenLayer , ctx_output3/relu_mbox_conf_perm 1, 1 , 1 , 35 , x , x , x , x , x , x , x , 36 , 1 , 12 , 5 , 12 , 1 , 1 , 1 , 720 , 1 , 38, TIDL_ConvolutionLayer , ctx_output4/relu_mbox_loc 1, 1 , 1 , 20 , x , x , x , x , x , x , x , 38 , 1 , 256 , 3 , 6 , 1 , 24 , 3 , 6 , 110592 , 39, TIDL_FlattenLayer , ctx_output4/relu_mbox_loc_perm 1, 1 , 1 , 38 , x , x , x , x , x , x , x , 39 , 1 , 24 , 3 , 6 , 1 , 1 , 1 , 432 , 1 , 40, TIDL_ConvolutionLayer , ctx_output4/relu_mbox_conf 1, 1 , 1 , 20 , x , x , x , x , x , x , x , 40 , 1 , 256 , 3 , 6 , 1 , 12 , 3 , 6 , 55296 , 41, TIDL_FlattenLayer , ctx_output4/relu_mbox_conf_perm 1, 1 , 1 , 40 , x , x , x , x , x , x , x , 41 , 1 , 12 , 3 , 6 , 1 , 1 , 1 , 216 , 1 , 43, TIDL_ConvolutionLayer , ctx_output5/relu_mbox_loc 1, 1 , 1 , 21 , x , x , x , x , x , x , x , 43 , 1 , 256 , 2 , 3 , 1 , 16 , 2 , 3 , 24576 , 44, TIDL_FlattenLayer , ctx_output5/relu_mbox_loc_perm 1, 1 , 1 , 43 , x , x , x , x , x , x , x , 44 , 1 , 16 , 2 , 3 , 1 , 1 , 1 , 96 , 1 , 45, TIDL_ConvolutionLayer , ctx_output5/relu_mbox_conf 1, 1 , 1 , 21 , x , x , x , x , x , x , x , 45 , 1 , 256 , 2 , 3 , 1 , 8 , 2 , 3 , 12288 , 46, TIDL_FlattenLayer , ctx_output5/relu_mbox_conf_perm 1, 1 , 1 , 45 , x , x , x , x , x , x , x , 46 , 1 , 8 , 2 , 3 , 1 , 1 , 1 , 48 , 1 , 48, TIDL_ConvolutionLayer , ctx_output6/relu_mbox_loc 1, 1 , 1 , 22 , x , x , x , x , x , x , x , 48 , 1 , 256 , 1 , 2 , 1 , 16 , 1 , 2 , 8192 , 49, TIDL_FlattenLayer , ctx_output6/relu_mbox_loc_perm 1, 1 , 1 , 48 , x , x , x , x , x , x , x , 49 , 1 , 16 , 1 , 2 , 1 , 1 , 1 , 32 , 1 , 50, TIDL_ConvolutionLayer , ctx_output6/relu_mbox_conf 1, 1 , 1 , 22 , x , x , x , x , x , x , x , 50 , 1 , 256 , 1 , 2 , 1 , 8 , 1 , 2 , 4096 , 51, TIDL_FlattenLayer , ctx_output6/relu_mbox_conf_perm 1, 1 , 1 , 50 , x , x , x , x , x , x , x , 51 , 1 , 8 , 1 , 2 , 1 , 1 , 1 , 16 , 1 , 53, TIDL_ConcatLayer , mbox_loc 1, 6 , 1 , 24 , 29 , 34 , 39 , 44 , 49 , x , x , 53 , 1 , 1 , 1 , 61440 , 1 , 1 , 1 , 69200 , 1 , 54, TIDL_ConcatLayer , mbox_conf 1, 6 , 1 , 26 , 31 , 36 , 41 , 46 , 51 , x , x , 54 , 1 , 1 , 1 , 30720 , 1 , 1 , 1 , 34600 , 1 , 56, TIDL_DetectionOutputLayer , detection_out 1, 2 , 1 , 53 , 54 , x , x , x , x , x , x , 56 , 1 , 1 , 1 , 69200 , 1 , 1 , 1 , 5600 , 1 , Total Giga Macs : 2.1842 =============================== TIDL import - calibration =============================== Processing config file ./tempDir/qunat_stats_config.txt ! Running TIDL simulation for calibration. 0, TIDL_DataLayer , 0, -1 , 1 , x , x , x , x , x , x , x , x , 0 , 0 , 0 , 0 , 0 , 1 , 3 , 320 , 768 , 1, TIDL_BatchNormLayer , 1, 1 , 1 , 0 , x , x , x , x , x , x , x , 1 , 1 , 3 , 320 , 768 , 1 , 3 , 320 , 768 , 2, TIDL_ConvolutionLayer , 1, 1 , 1 , 1 , x , x , x , x , x , x , x , 2 , 1 , 3 , 320 , 768 , 1 , 32 , 160 , 384 , 3, TIDL_ConvolutionLayer , 1, 1 , 1 , 2 , x , x , x , x , x , x , x , 3 , 1 , 32 , 160 , 384 , 1 , 32 , 80 , 192 , 4, TIDL_ConvolutionLayer , 1, 1 , 1 , 3 , x , x , x , x , x , x , x , 4 , 1 , 32 , 80 , 192 , 1 , 64 , 80 , 192 , 5, TIDL_ConvolutionLayer , 1, 1 , 1 , 4 , x , x , x , x , x , x , x , 5 , 1 , 64 , 80 , 192 , 1 , 64 , 40 , 96 , 6, TIDL_ConvolutionLayer , 1, 1 , 1 , 5 , x , x , x , x , x , x , x , 6 , 1 , 64 , 40 , 96 , 1 , 128 , 40 , 96 , 7, TIDL_ConvolutionLayer , 1, 1 , 1 , 6 , x , x , x , x , x , x , x , 7 , 1 , 128 , 40 , 96 , 1 , 128 , 40 , 96 , 8, TIDL_PoolingLayer , 1, 1 , 1 , 7 , x , x , x , x , x , x , x , 8 , 1 , 128 , 40 , 96 , 1 , 128 , 20 , 48 , 9, TIDL_ConvolutionLayer , 1, 1 , 1 , 8 , x , x , x , x , x , x , x , 9 , 1 , 128 , 20 , 48 , 1 , 256 , 20 , 48 , 10, TIDL_ConvolutionLayer , 1, 1 , 1 , 9 , x , x , x , x , x , x , x , 10 , 1 , 256 , 20 , 48 , 1 , 256 , 10 , 24 , 11, TIDL_ConvolutionLayer , 1, 1 , 1 , 10 , x , x , x , x , x , x , x , 11 , 1 , 256 , 10 , 24 , 1 , 512 , 10 , 24 , 12, TIDL_ConvolutionLayer , 1, 1 , 1 , 11 , x , x , x , x , x , x , x , 12 , 1 , 512 , 10 , 24 , 1 , 512 , 10 , 24 , 13, TIDL_PoolingLayer , 1, 1 , 1 , 12 , x , x , x , x , x , x , x , 13 , 1 , 512 , 10 , 24 , 1 , 512 , 5 , 12 , 14, TIDL_PoolingLayer , 1, 1 , 1 , 13 , x , x , x , x , x , x , x , 14 , 1 , 512 , 5 , 12 , 1 , 512 , 3 , 6 , 15, TIDL_PoolingLayer , 1, 1 , 1 , 14 , x , x , x , x , x , x , x , 15 , 1 , 512 , 3 , 6 , 1 , 512 , 2 , 3 , 16, TIDL_PoolingLayer , 1, 1 , 1 , 15 , x , x , x , x , x , x , x , 16 , 1 , 512 , 2 , 3 , 1 , 512 , 1 , 2 , 17, TIDL_ConvolutionLayer , 1, 1 , 1 , 7 , x , x , x , x , x , x , x , 17 , 1 , 128 , 40 , 96 , 1 , 256 , 40 , 96 , 18, TIDL_ConvolutionLayer , 1, 1 , 1 , 12 , x , x , x , x , x , x , x , 18 , 1 , 512 , 10 , 24 , 1 , 256 , 10 , 24 , 19, TIDL_ConvolutionLayer , 1, 1 , 1 , 13 , x , x , x , x , x , x , x , 19 , 1 , 512 , 5 , 12 , 1 , 256 , 5 , 12 , 20, TIDL_ConvolutionLayer , 1, 1 , 1 , 14 , x , x , x , x , x , x , x , 20 , 1 , 512 , 3 , 6 , 1 , 256 , 3 , 6 , 21, TIDL_ConvolutionLayer , 1, 1 , 1 , 15 , x , x , x , x , x , x , x , 21 , 1 , 512 , 2 , 3 , 1 , 256 , 2 , 3 , 22, TIDL_ConvolutionLayer , 1, 1 , 1 , 16 , x , x , x , x , x , x , x , 22 , 1 , 512 , 1 , 2 , 1 , 256 , 1 , 2 , 23, TIDL_ConvolutionLayer , 1, 1 , 1 , 17 , x , x , x , x , x , x , x , 23 , 1 , 256 , 40 , 96 , 1 , 16 , 40 , 96 , 24, TIDL_FlattenLayer , 1, 1 , 1 , 23 , x , x , x , x , x , x , x , 24 , 1 , 16 , 40 , 96 , 1 , 1 , 1 ,61440 , 25, TIDL_ConvolutionLayer , 1, 1 , 1 , 17 , x , x , x , x , x , x , x , 25 , 1 , 256 , 40 , 96 , 1 , 8 , 40 , 96 , 26, TIDL_FlattenLayer , 1, 1 , 1 , 25 , x , x , x , x , x , x , x , 26 , 1 , 8 , 40 , 96 , 1 , 1 , 1 ,30720 , 27, TIDL_ConvolutionLayer , 1, 1 , 1 , 18 , x , x , x , x , x , x , x , 28 , 1 , 256 , 10 , 24 , 1 , 24 , 10 , 24 , 28, TIDL_FlattenLayer , 1, 1 , 1 , 28 , x , x , x , x , x , x , x , 29 , 1 , 24 , 10 , 24 , 1 , 1 , 1 , 5760 , 29, TIDL_ConvolutionLayer , 1, 1 , 1 , 18 , x , x , x , x , x , x , x , 30 , 1 , 256 , 10 , 24 , 1 , 12 , 10 , 24 , 30, TIDL_FlattenLayer , 1, 1 , 1 , 30 , x , x , x , x , x , x , x , 31 , 1 , 12 , 10 , 24 , 1 , 1 , 1 , 2880 , 31, TIDL_ConvolutionLayer , 1, 1 , 1 , 19 , x , x , x , x , x , x , x , 33 , 1 , 256 , 5 , 12 , 1 , 24 , 5 , 12 , 32, TIDL_FlattenLayer , 1, 1 , 1 , 33 , x , x , x , x , x , x , x , 34 , 1 , 24 , 5 , 12 , 1 , 1 , 1 , 1440 , 33, TIDL_ConvolutionLayer , 1, 1 , 1 , 19 , x , x , x , x , x , x , x , 35 , 1 , 256 , 5 , 12 , 1 , 12 , 5 , 12 , 34, TIDL_FlattenLayer , 1, 1 , 1 , 35 , x , x , x , x , x , x , x , 36 , 1 , 12 , 5 , 12 , 1 , 1 , 1 , 720 , 35, TIDL_ConvolutionLayer , 1, 1 , 1 , 20 , x , x , x , x , x , x , x , 38 , 1 , 256 , 3 , 6 , 1 , 24 , 3 , 6 , 36, TIDL_FlattenLayer , 1, 1 , 1 , 38 , x , x , x , x , x , x , x , 39 , 1 , 24 , 3 , 6 , 1 , 1 , 1 , 432 , 37, TIDL_ConvolutionLayer , 1, 1 , 1 , 20 , x , x , x , x , x , x , x , 40 , 1 , 256 , 3 , 6 , 1 , 12 , 3 , 6 , 38, TIDL_FlattenLayer , 1, 1 , 1 , 40 , x , x , x , x , x , x , x , 41 , 1 , 12 , 3 , 6 , 1 , 1 , 1 , 216 , 39, TIDL_ConvolutionLayer , 1, 1 , 1 , 21 , x , x , x , x , x , x , x , 43 , 1 , 256 , 2 , 3 , 1 , 16 , 2 , 3 , 40, TIDL_FlattenLayer , 1, 1 , 1 , 43 , x , x , x , x , x , x , x , 44 , 1 , 16 , 2 , 3 , 1 , 1 , 1 , 96 , 41, TIDL_ConvolutionLayer , 1, 1 , 1 , 21 , x , x , x , x , x , x , x , 45 , 1 , 256 , 2 , 3 , 1 , 8 , 2 , 3 , 42, TIDL_FlattenLayer , 1, 1 , 1 , 45 , x , x , x , x , x , x , x , 46 , 1 , 8 , 2 , 3 , 1 , 1 , 1 , 48 , 43, TIDL_ConvolutionLayer , 1, 1 , 1 , 22 , x , x , x , x , x , x , x , 48 , 1 , 256 , 1 , 2 , 1 , 16 , 1 , 2 , 44, TIDL_FlattenLayer , 1, 1 , 1 , 48 , x , x , x , x , x , x , x , 49 , 1 , 16 , 1 , 2 , 1 , 1 , 1 , 32 , 45, TIDL_ConvolutionLayer , 1, 1 , 1 , 22 , x , x , x , x , x , x , x , 50 , 1 , 256 , 1 , 2 , 1 , 8 , 1 , 2 , 46, TIDL_FlattenLayer , 1, 1 , 1 , 50 , x , x , x , x , x , x , x , 51 , 1 , 8 , 1 , 2 , 1 , 1 , 1 , 16 , 47, TIDL_ConcatLayer , 1, 6 , 1 , 24 , 29 , 34 , 39 , 44 , 49 , x , x , 53 , 1 , 1 , 1 ,61440 , 1 , 1 , 1 ,69200 , 48, TIDL_ConcatLayer , 1, 6 , 1 , 26 , 31 , 36 , 41 , 46 , 51 , x , x , 54 , 1 , 1 , 1 ,30720 , 1 , 1 , 1 ,34600 , 49, TIDL_DetectionOutputLayer , 1, 2 , 1 , 53 , 54 , x , x , x , x , x , x , 56 , 1 , 1 , 1 ,69200 , 1 , 1 , 1 , 5600 , 50, TIDL_DataLayer , 0, 1 , -1 , 56 , x , x , x , x , x , x , x , 0 , 1 , 1 , 1 , 5600 , 0 , 0 , 0 , 0 , Layer ID ,inBlkWidth ,inBlkHeight ,inBlkPitch ,outBlkWidth ,outBlkHeight,outBlkPitch ,numInChs ,numOutChs ,numProcInChs,numLclInChs ,numLclOutChs,numProcItrs ,numAccItrs ,numHorBlock ,numVerBlock ,inBlkChPitch,outBlkChPitc,alignOrNot 2 72 72 72 32 32 32 3 32 3 1 8 1 3 12 5 5184 1024 1 3 40 34 40 32 32 32 8 8 8 4 8 1 2 12 5 1360 1024 1 4 40 22 40 32 20 32 32 64 32 8 8 1 4 6 4 880 640 1 5 40 22 40 32 20 32 16 16 16 8 8 1 2 6 4 880 640 1 6 40 22 40 32 20 32 64 128 64 8 8 1 8 3 2 880 640 1 7 40 22 40 32 20 32 32 32 32 8 8 1 4 3 2 880 640 1 9 56 22 56 48 20 48 128 256 128 7 8 1 19 1 1 1232 960 1 10 56 22 56 48 20 48 64 64 64 7 8 1 10 1 1 1232 960 1 11 40 12 40 32 10 32 256 512 256 8 8 1 32 1 1 480 320 1 12 40 12 40 32 10 32 128 128 128 8 8 1 16 1 1 480 320 1 17 32 20 32 32 20 32 128 256 128 8 8 1 16 3 2 640 640 1 18 32 10 32 32 10 32 512 256 512 8 8 1 64 1 1 320 320 1 19 16 5 16 16 5 16 512 256 512 8 8 1 64 1 1 80 80 1 20 16 3 16 16 3 16 512 256 512 8 8 1 64 1 1 48 48 1 21 16 2 16 16 2 16 512 256 512 8 8 1 64 1 1 32 32 1 22 16 1 16 16 1 16 512 256 512 8 8 1 64 1 1 16 16 1 23 32 20 32 32 20 32 256 16 256 8 8 1 32 3 2 640 640 1 25 32 20 32 32 20 32 256 8 256 8 8 1 32 3 2 640 640 1 27 32 10 32 32 10 32 256 24 256 8 8 1 32 1 1 320 320 1 29 32 10 32 32 10 32 256 16 256 8 8 1 32 1 1 320 320 1 31 16 5 16 16 5 16 256 24 256 8 8 1 32 1 1 80 80 1 33 16 5 16 16 5 16 256 16 256 8 8 1 32 1 1 80 80 1 35 16 3 16 16 3 16 256 24 256 8 8 1 32 1 1 48 48 1 37 16 3 16 16 3 16 256 16 256 8 8 1 32 1 1 48 48 1 39 16 2 16 16 2 16 256 16 256 8 8 1 32 1 1 32 32 1 41 16 2 16 16 2 16 256 8 256 8 8 1 32 1 1 32 32 1 43 16 1 16 16 1 16 256 16 256 8 8 1 32 1 1 16 16 1 45 16 1 16 16 1 16 256 8 256 8 8 1 32 1 1 16 16 1 Processing Frame Number : 0 Layer 1 : Out Q : 254 , TIDL_BatchNormLayer , PASSED #MMACs = 0.74, 0.74, Sparsity : 0.00 Layer 2 : Out Q : 6267 , TIDL_ConvolutionLayer, PASSED #MMACs = 147.46, 111.82, Sparsity : 24.17 Layer 3 : Out Q : 6824 , TIDL_ConvolutionLayer, PASSED #MMACs = 141.56, 78.40, Sparsity : 44.62 Layer 4 : Out Q : 11198 , TIDL_ConvolutionLayer, PASSED #MMACs = 283.12, 147.46, Sparsity : 47.92 Layer 5 : Out Q : 13528 , TIDL_ConvolutionLayer, PASSED #MMACs = 141.56, 74.53, Sparsity : 47.35 Layer 6 : Out Q : 18712 , TIDL_ConvolutionLayer, PASSED #MMACs = 283.12, 147.36, Sparsity : 47.95 Layer 7 : Out Q : 15612 , TIDL_ConvolutionLayer, PASSED #MMACs = 141.56, 73.88, Sparsity : 47.81 Layer 8 :TIDL_PoolingLayer, PASSED #MMACs = 0.12, 0.12, Sparsity : 0.00 Layer 9 : Out Q : 16635 , TIDL_ConvolutionLayer, PASSED #MMACs = 283.12, 148.61, Sparsity : 47.51 Layer 10 : Out Q : 16681 , TIDL_ConvolutionLayer, PASSED #MMACs = 141.56, 74.50, Sparsity : 47.37 Layer 11 : Out Q : 31142 , TIDL_ConvolutionLayer, PASSED #MMACs = 283.12, 147.26, Sparsity : 47.99 Layer 12 : Out Q : 1563 , TIDL_ConvolutionLayer, PASSED #MMACs = 141.56, 57.05, Sparsity : 59.70 Layer 13 :TIDL_PoolingLayer, PASSED #MMACs = 0.03, 0.03, Sparsity : 0.00 Layer 14 :TIDL_PoolingLayer, PASSED #MMACs = 0.01, 0.01, Sparsity : 0.00 Layer 15 :TIDL_PoolingLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 16 :TIDL_PoolingLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 17 : Out Q : 10483 , TIDL_ConvolutionLayer, PASSED #MMACs = 125.83, 125.83, Sparsity : 0.00 Layer 18 : Out Q : 6560 , TIDL_ConvolutionLayer, PASSED #MMACs = 31.46, 31.40, Sparsity : 0.19 Layer 19 : Out Q : 10169 , TIDL_ConvolutionLayer, PASSED #MMACs = 7.86, 7.81, Sparsity : 0.72 Layer 20 : Out Q : 12413 , TIDL_ConvolutionLayer, PASSED #MMACs = 2.36, 2.25, Sparsity : 4.51 Layer 21 : Out Q : 13955 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.79, 0.74, Sparsity : 6.22 Layer 22 : Out Q : 18080 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.26, 0.25, Sparsity : 6.06 Layer 23 : Out Q : 3515 , TIDL_ConvolutionLayer, PASSED #MMACs = 15.73, 15.70, Sparsity : 0.20 Layer 24 :TIDL_FlattenLayer, PASSED #MMACs = 0.06, 0.06, Sparsity : 0.00 Layer 25 : Out Q : 2235 , TIDL_ConvolutionLayer, PASSED #MMACs = 7.86, 7.86, Sparsity : 0.00 Layer 26 :TIDL_FlattenLayer, PASSED #MMACs = 0.03, 0.03, Sparsity : 0.00 Layer 27 : Out Q : 8044 , TIDL_ConvolutionLayer, PASSED #MMACs = 1.47, 1.47, Sparsity : 0.13 Layer 28 :TIDL_FlattenLayer, PASSED #MMACs = 0.01, 0.01, Sparsity : 0.00 Layer 29 : Out Q : 2251 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.98, 0.98, Sparsity : 0.10 Layer 30 :TIDL_FlattenLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 31 : Out Q : 7807 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.37, 0.37, Sparsity : 0.33 Layer 32 :TIDL_FlattenLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 33 : Out Q : 3413 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.25, 0.25, Sparsity : 0.20 Layer 34 :TIDL_FlattenLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 35 : Out Q : 9928 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.11, 0.11, Sparsity : 1.95 Layer 36 :TIDL_FlattenLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 37 : Out Q : 4070 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.07, 0.07, Sparsity : 0.59 Layer 38 :TIDL_FlattenLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 39 : Out Q : 9309 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.02, 0.02, Sparsity : 1.37 Layer 40 :TIDL_FlattenLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 41 : Out Q : 4367 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.01, 0.01, Sparsity : 0.59 Layer 42 :TIDL_FlattenLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 43 : Out Q : 15272 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.01, 0.01, Sparsity : 1.46 Layer 44 :TIDL_FlattenLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 45 : Out Q : 6094 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.59 Layer 46 :TIDL_FlattenLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 47 : Out Q : 3529 , TIDL_ConcatLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : nan Layer 48 : Out Q : 2244 , TIDL_ConcatLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : nan Layer 49 : Target: number label value xmin ymin xmax ymax Target: 0.00 1.00 0.90 0.03 0.54 0.06 0.64 Target: 1.00 1.00 0.66 0.71 0.17 0.53 0.81 Target: 2.00 1.00 0.66 1.04 0.49 0.93 0.52 Target: 3.00 1.00 0.56 0.50 0.93 0.53 1.04 Target: 4.00 1.00 0.47 0.50 0.57 0.53 0.65 Target: 5.00 1.00 0.36 0.54 0.02 0.56 0.06 Target: 6.00 1.00 0.36 0.53 0.04 0.50 0.50 Target: 7.00 1.00 0.29 0.53 0.30 0.55 0.37 Target: 8.00 1.00 0.24 -0.01 0.75 0.03 0.60 Target: 9.00 1.00 0.10 0.44 0.36 0.49 0.49 Target: 10.00 1.00 0.06 0.25 0.91 0.28 1.02 Target: 11.00 1.00 0.04 1.02 0.24 0.91 0.27 Target: 12.00 1.00 0.02 0.20 0.46 0.91 -0.05 Target: 13.00 1.00 0.02 0.49 0.17 0.53 0.21 Target: 14.00 1.00 0.02 0.28 0.90 0.35 1.02 Target: 15.00 1.00 0.02 0.50 1.04 0.48 0.93 Target: 16.00 1.00 0.01 0.12 0.50 0.37 1.11 Target: 17.00 1.00 0.01 0.46 0.11 0.55 0.21 Target: 18.00 1.00 0.01 0.00 0.32 0.35 1.26 Target: 19.00 1.00 0.01 0.48 0.56 0.51 0.64 Target: 20.00 1.00 0.01 0.51 0.17 0.54 0.21 Target: 21.00 1.00 0.01 0.41 0.97 0.45 1.01 Target: 22.00 1.00 0.01 0.33 0.23 0.37 0.29 Target: 23.00 1.00 0.01 0.69 0.93 0.76 1.03 Target: 24.00 1.00 0.01 0.57 -0.22 0.67 0.39 Target: 25.00 1.00 0.01 0.54 0.29 0.57 0.36 Target: 26.00 1.00 0.01 0.60 0.61 0.67 0.73 Target: 27.00 1.00 0.01 0.38 0.85 0.47 0.50 #MMACs = 0.01, 0.01, Sparsity : 0.00 End of config list found !