data2/text/range/25001-30000/760240.txt

Ticket Name: TDA2: TIDI TensorFlow MobileNet

Query Text:
Part Number: TDA2 I tried to port MobileNet as described here -- e2e.ti.com/.../2717341 When running inference with -- eve_test_dl_algo.out config_list.txt I get a bunch of layers failing ~ as in here any pointers would be greatly appreciated thank you! .luca -- numFrames = 1 preProcType = 2 inData = preproc_2_224x224.y outData = "./stats_tool_out.bin" netBinFile = "tidl_net_mobilenet_1_224.bin" paramsBinFile = "tidl_param_mobilenet_1_224.bin" inWidth = 224 inHeight = 224 inNumChannels = 3 (tf1.1_env) luca@doppio tf-example eve_test_dl_algo.out config_list.txt Processing config file tidl_config_mobileNet1.txt ! 0, TIDL_DataLayer , 0, -1 , 1 , x , x , x , x , x , x , x , x , 0 , 0 , 0 , 0 , 0 , 1 , 3 , 224 , 224 , 1, TIDL_ConvolutionLayer , 1, 1 , 1 , 0 , x , x , x , x , x , x , x , 1 , 1 , 3 , 224 , 224 , 1 , 32 , 112 , 112 , 2, TIDL_ConvolutionLayer , 1, 1 , 1 , 1 , x , x , x , x , x , x , x , 2 , 1 , 32 , 112 , 112 , 1 , 32 , 112 , 112 , 3, TIDL_ConvolutionLayer , 1, 1 , 1 , 2 , x , x , x , x , x , x , x , 3 , 1 , 32 , 112 , 112 , 1 , 64 , 112 , 112 , 4, TIDL_ConvolutionLayer , 1, 1 , 1 , 3 , x , x , x , x , x , x , x , 4 , 1 , 64 , 112 , 112 , 1 , 64 , 56 , 56 , 5, TIDL_ConvolutionLayer , 1, 1 , 1 , 4 , x , x , x , x , x , x , x , 5 , 1 , 64 , 56 , 56 , 1 , 128 , 56 , 56 , 6, TIDL_ConvolutionLayer , 1, 1 , 1 , 5 , x , x , x , x , x , x , x , 6 , 1 , 128 , 56 , 56 , 1 , 128 , 56 , 56 , 7, TIDL_ConvolutionLayer , 1, 1 , 1 , 6 , x , x , x , x , x , x , x , 7 , 1 , 128 , 56 , 56 , 1 , 128 , 56 , 56 , 8, TIDL_ConvolutionLayer , 1, 1 , 1 , 7 , x , x , x , x , x , x , x , 8 , 1 , 128 , 56 , 56 , 1 , 128 , 28 , 28 , 9, TIDL_ConvolutionLayer , 1, 1 , 1 , 8 , x , x , x , x , x , x , x , 9 , 1 , 128 , 28 , 28 , 1 , 256 , 28 , 28 , 10, TIDL_ConvolutionLayer , 1, 1 , 1 , 9 , x , x , x , x , x , x , x , 10 , 1 , 256 , 28 , 28 , 1 , 256 , 28 , 28 , 11, TIDL_ConvolutionLayer , 1, 1 , 1 , 10 , x , x , x , x , x , x , x , 11 , 1 , 256 , 28 , 28 , 1 , 256 , 28 , 28 , 12, TIDL_ConvolutionLayer , 1, 1 , 1 , 11 , x , x , x , x , x , x , x , 12 , 1 , 256 , 28 , 28 , 1 , 256 , 14 , 14 , 13, TIDL_ConvolutionLayer , 1, 1 , 1 , 12 , x , x , x , x , x , x , x , 13 , 1 , 256 , 14 , 14 , 1 , 512 , 14 , 14 , 14, TIDL_ConvolutionLayer , 1, 1 , 1 , 13 , x , x , x , x , x , x , x , 14 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 15, TIDL_ConvolutionLayer , 1, 1 , 1 , 14 , x , x , x , x , x , x , x , 15 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 16, TIDL_ConvolutionLayer , 1, 1 , 1 , 15 , x , x , x , x , x , x , x , 16 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 17, TIDL_ConvolutionLayer , 1, 1 , 1 , 16 , x , x , x , x , x , x , x , 17 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 18, TIDL_ConvolutionLayer , 1, 1 , 1 , 17 , x , x , x , x , x , x , x , 18 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 19, TIDL_ConvolutionLayer , 1, 1 , 1 , 18 , x , x , x , x , x , x , x , 19 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 20, TIDL_ConvolutionLayer , 1, 1 , 1 , 19 , x , x , x , x , x , x , x , 20 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 21, TIDL_ConvolutionLayer , 1, 1 , 1 , 20 , x , x , x , x , x , x , x , 21 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 22, TIDL_ConvolutionLayer , 1, 1 , 1 , 21 , x , x , x , x , x , x , x , 22 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 23, TIDL_ConvolutionLayer , 1, 1 , 1 , 22 , x , x , x , x , x , x , x , 23 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 24, TIDL_ConvolutionLayer , 1, 1 , 1 , 23 , x , x , x , x , x , x , x , 24 , 1 , 512 , 14 , 14 , 1 , 512 , 7 , 7 , 25, TIDL_ConvolutionLayer , 1, 1 , 1 , 24 , x , x , x , x , x , x , x , 25 , 1 , 512 , 7 , 7 , 1 , 1024 , 7 , 7 , 26, TIDL_ConvolutionLayer , 1, 1 , 1 , 25 , x , x , x , x , x , x , x , 26 , 1 , 1024 , 7 , 7 , 1 , 1024 , 7 , 7 , 27, TIDL_ConvolutionLayer , 1, 1 , 1 , 26 , x , x , x , x , x , x , x , 27 , 1 , 1024 , 7 , 7 , 1 , 1024 , 7 , 7 , 28, TIDL_PoolingLayer , 1, 1 , 1 , 27 , x , x , x , x , x , x , x , 28 , 1 , 1024 , 7 , 7 , 1 , 1 , 1 , 1024 , 29, TIDL_InnerProductLayer , 1, 1 , 1 , 28 , x , x , x , x , x , x , x , 29 , 1 , 1 , 1 , 1024 , 1 , 1 , 1 , 1001 , 30, TIDL_SoftMaxLayer , 1, 1 , 1 , 29 , x , x , x , x , x , x , x , 30 , 1 , 1 , 1 , 1001 , 1 , 1 , 1 , 1001 , 31, TIDL_DataLayer , 0, 1 , -1 , 30 , x , x , x , x , x , x , x , 0 , 1 , 1 , 1 , 1001 , 0 , 0 , 0 , 0 , Layer ID ,inBlkWidth ,inBlkHeight ,inBlkPitch ,outBlkWidth ,outBlkHeight,outBlkPitch ,numInChs ,numOutChs ,numProcInChs,numLclInChs ,numLclOutChs,numProcItrs ,numAccItrs ,numHorBlock ,numVerBlock ,inBlkChPitch,outBlkChPitc,alignOrNot 1 72 60 72 32 28 32 3 32 3 1 8 1 3 4 4 4320 896 1 2 40 30 40 32 28 32 1 1 1 1 1 1 1 4 4 1200 896 1 3 32 28 32 32 28 32 32 64 32 8 8 1 4 4 4 896 896 1 4 72 60 72 32 28 32 1 1 1 1 1 1 1 2 2 4320 896 1 5 32 28 32 32 28 32 64 128 64 8 8 1 8 2 2 896 896 1 6 40 30 40 32 28 32 1 1 1 1 1 1 1 2 2 1200 896 1 7 32 28 32 32 28 32 128 128 128 8 8 1 16 2 2 896 896 1 8 72 60 72 32 28 32 1 1 1 1 1 1 1 1 1 4320 896 1 9 32 28 32 32 28 32 128 256 128 8 8 1 16 1 1 896 896 1 10 40 30 40 32 28 32 1 1 1 1 1 1 1 1 1 1200 896 1 11 32 28 32 32 28 32 256 256 256 8 8 1 32 1 1 896 896 1 12 40 32 40 16 14 16 1 1 1 1 1 1 1 1 1 1280 224 1 13 16 14 16 16 14 16 256 512 256 8 8 1 32 1 1 224 224 1 14 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1 15 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1 16 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1 17 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1 18 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1 19 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1 20 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1 21 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1 22 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1 23 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1 24 40 18 40 16 7 16 1 1 1 1 1 1 1 1 1 720 112 1 25 16 7 16 16 7 16 512 1024 512 8 8 1 64 1 1 112 112 1 26 24 9 24 16 7 16 1 1 1 1 1 1 1 1 1 216 112 1 27 16 7 16 16 7 16 1024 1024 1024 8 8 1 128 1 1 112 112 1 Processing Frame Number : 0 Layer 1 : Out Q : 95997 , TIDL_ConvolutionLayer, PASSED #MMACs = 10.84, 9.63, Sparsity : 11.11 Layer 2 : Out Q : 7608233 , Failing at 0, 1, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 3.61, 3.61, Sparsity : 0.00 Layer 3 : Out Q : 1 , Failing at 0, 1, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 25.69, 20.47, Sparsity : 20.31 Layer 4 : Out Q : 157 , TIDL_ConvolutionLayer, PASSED #MMACs = 1.81, 1.81, Sparsity : 0.00 Layer 5 : Out Q : 126194 , Failing at 0, 0, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 25.69, 24.56, Sparsity : 4.39 Layer 6 : Out Q : 9566000 , Failing at 0, 0, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 3.61, 3.61, Sparsity : 0.00 Layer 7 : Out Q : 1 , Failing at 0, 0, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 51.38, 50.97, Sparsity : 0.81 Layer 8 : Out Q : 205 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 9 : Out Q : 246241 , Failing at 0, 0, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 25.69, 25.68, Sparsity : 0.02 Layer 10 : Out Q : 78632959 , Failing at 0, 2, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 1.81, 1.81, Sparsity : 0.00 Layer 11 : Out Q : 1 , Failing at 0, 1, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 51.38, 51.38, Sparsity : 0.00 Layer 12 : Out Q : 1469 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.45, 0.45, Sparsity : 0.00 Layer 13 : Out Q : 2961619 , Failing at 0, 0, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 25.69, 25.68, Sparsity : 0.02 Layer 14 : Out Q : 729951977 , Failing at 0, 0, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 15 : Out Q : 502695931 , Failing at 0, 0, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 51.38, 51.38, Sparsity : 0.00 Layer 16 : Out Q : 1 , Failing at 0, 0, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 17 : Out Q : 3499 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.28, Sparsity : 0.20 Layer 18 : Out Q : 333160 , Failing at 0, 0, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 19 : Out Q : 808651178 , Failing at 0, 0, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 51.38, 51.28, Sparsity : 0.20 Layer 20 : Out Q : 63449855 , Failing at 0, 0, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 21 : Out Q : 1 , Failing at 0, 0, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 51.38, 51.38, Sparsity : 0.01 Layer 22 : Out Q : 1103 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 23 : Out Q : 2998754 , Failing at 0, 0, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 51.38, 51.38, Sparsity : 0.00 Layer 24 : Out Q : 427423464 , Failing at 0, 2, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 0.23, 0.23, Sparsity : 0.00 Layer 25 : Out Q : 1 , Failing at 0, 1, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 25.69, 25.59, Sparsity : 0.39 Layer 26 : Out Q : 67 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.45, 0.45, Sparsity : 0.00 Layer 27 : Out Q : 39868 , Failing at 0, 1, 0, 0 ref,out = 255,0 TIDL_ConvolutionLayer, FAILED!!!!!! #MMACs = 51.38, 51.38, Sparsity : 0.00 Layer 28 : Out Q : 409849294 , TIDL_PoolingLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 29 : Out Q : 1 , [0][0] - outData - 0 outputRef - 127 TIDL_InnerProductLayer, FAILED!!!!!! #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 30 :-------Max Index 1000 : 0 ------- #MMACs = 0.00, 0.00, Sparsity : 0.00 End of config list found !

Responses:
Hi, Did you get the expeted result during the import step?

Hi Kumar, yes it appears import was successful, see next -- any suggestions? -- luca@doppio tf-example tidl_model_import.out tidl_import_mobileNet1.txt TF Model File : mobilenet_1_224.pb Num of Layer Detected : 276 0, TIDL_DataLayer 0, -1 , 1 , x , x , x , x , x , x , x , x , 0 , 0 , 0 , 0 , 0 , 1 , 3 , 224 , 224 , 0 , 1, TIDL_ConvolutionLayer 1, 1 , 1 , 0 , x , x , x , x , x , x , x , 1 , 1 , 3 , 224 , 224 , 1 , 32 , 112 , 112 , 10838016 , 2, TIDL_ConvolutionLayer 1, 1 , 1 , 1 , x , x , x , x , x , x , x , 2 , 1 , 32 , 112 , 112 , 1 , 32 , 112 , 112 , 3612672 , 3, TIDL_ConvolutionLayer 1, 1 , 1 , 2 , x , x , x , x , x , x , x , 3 , 1 , 32 , 112 , 112 , 1 , 64 , 112 , 112 , 25690112 , 4, TIDL_ConvolutionLayer 1, 1 , 1 , 3 , x , x , x , x , x , x , x , 4 , 1 , 64 , 112 , 112 , 1 , 64 , 56 , 56 , 1806336 , 5, TIDL_ConvolutionLayer 1, 1 , 1 , 4 , x , x , x , x , x , x , x , 5 , 1 , 64 , 56 , 56 , 1 , 128 , 56 , 56 , 25690112 , 6, TIDL_ConvolutionLayer 1, 1 , 1 , 5 , x , x , x , x , x , x , x , 6 , 1 , 128 , 56 , 56 , 1 , 128 , 56 , 56 , 3612672 , 7, TIDL_ConvolutionLayer 1, 1 , 1 , 6 , x , x , x , x , x , x , x , 7 , 1 , 128 , 56 , 56 , 1 , 128 , 56 , 56 , 51380224 , 8, TIDL_ConvolutionLayer 1, 1 , 1 , 7 , x , x , x , x , x , x , x , 8 , 1 , 128 , 56 , 56 , 1 , 128 , 28 , 28 , 903168 , 9, TIDL_ConvolutionLayer 1, 1 , 1 , 8 , x , x , x , x , x , x , x , 9 , 1 , 128 , 28 , 28 , 1 , 256 , 28 , 28 , 25690112 , 10, TIDL_ConvolutionLayer 1, 1 , 1 , 9 , x , x , x , x , x , x , x , 10 , 1 , 256 , 28 , 28 , 1 , 256 , 28 , 28 , 1806336 , 11, TIDL_ConvolutionLayer 1, 1 , 1 , 10 , x , x , x , x , x , x , x , 11 , 1 , 256 , 28 , 28 , 1 , 256 , 28 , 28 , 51380224 , 12, TIDL_ConvolutionLayer 1, 1 , 1 , 11 , x , x , x , x , x , x , x , 12 , 1 , 256 , 28 , 28 , 1 , 256 , 14 , 14 , 451584 , 13, TIDL_ConvolutionLayer 1, 1 , 1 , 12 , x , x , x , x , x , x , x , 13 , 1 , 256 , 14 , 14 , 1 , 512 , 14 , 14 , 25690112 , 14, TIDL_ConvolutionLayer 1, 1 , 1 , 13 , x , x , x , x , x , x , x , 14 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 903168 , 15, TIDL_ConvolutionLayer 1, 1 , 1 , 14 , x , x , x , x , x , x , x , 15 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 51380224 , 16, TIDL_ConvolutionLayer 1, 1 , 1 , 15 , x , x , x , x , x , x , x , 16 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 903168 , 17, TIDL_ConvolutionLayer 1, 1 , 1 , 16 , x , x , x , x , x , x , x , 17 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 51380224 , 18, TIDL_ConvolutionLayer 1, 1 , 1 , 17 , x , x , x , x , x , x , x , 18 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 903168 , 19, TIDL_ConvolutionLayer 1, 1 , 1 , 18 , x , x , x , x , x , x , x , 19 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 51380224 , 20, TIDL_ConvolutionLayer 1, 1 , 1 , 19 , x , x , x , x , x , x , x , 20 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 903168 , 21, TIDL_ConvolutionLayer 1, 1 , 1 , 20 , x , x , x , x , x , x , x , 21 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 51380224 , 22, TIDL_ConvolutionLayer 1, 1 , 1 , 21 , x , x , x , x , x , x , x , 22 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 903168 , 23, TIDL_ConvolutionLayer 1, 1 , 1 , 22 , x , x , x , x , x , x , x , 23 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 51380224 , 24, TIDL_ConvolutionLayer 1, 1 , 1 , 23 , x , x , x , x , x , x , x , 24 , 1 , 512 , 14 , 14 , 1 , 512 , 7 , 7 , 225792 , 25, TIDL_ConvolutionLayer 1, 1 , 1 , 24 , x , x , x , x , x , x , x , 25 , 1 , 512 , 7 , 7 , 1 , 1024 , 7 , 7 , 25690112 , 26, TIDL_ConvolutionLayer 1, 1 , 1 , 25 , x , x , x , x , x , x , x , 26 , 1 , 1024 , 7 , 7 , 1 , 1024 , 7 , 7 , 451584 , 27, TIDL_ConvolutionLayer 1, 1 , 1 , 26 , x , x , x , x , x , x , x , 27 , 1 , 1024 , 7 , 7 , 1 , 1024 , 7 , 7 , 51380224 , 28, TIDL_PoolingLayer 1, 1 , 1 , 27 , x , x , x , x , x , x , x , 28 , 1 , 1024 , 7 , 7 , 1 , 1 , 1 , 1024 , 50176 , 29, TIDL_InnerProductLayer 1, 1 , 1 , 28 , x , x , x , x , x , x , x , 29 , 1 , 1 , 1 , 1024 , 1 , 1 , 1 , 1001 , 1025024 , 30, TIDL_SoftMaxLayer 1, 1 , 1 , 29 , x , x , x , x , x , x , x , 30 , 1 , 1 , 1 , 1001 , 1 , 1 , 1 , 1001 , 1001 , Total Giga Macs : 0.5688 Processing config file ./tempDir/qunat_stats_config.txt ! 0, TIDL_DataLayer , 0, -1 , 1 , x , x , x , x , x , x , x , x , 0 , 0 , 0 , 0 , 0 , 1 , 3 , 224 , 224 , 1, TIDL_ConvolutionLayer , 1, 1 , 1 , 0 , x , x , x , x , x , x , x , 1 , 1 , 3 , 224 , 224 , 1 , 32 , 112 , 112 , 2, TIDL_ConvolutionLayer , 1, 1 , 1 , 1 , x , x , x , x , x , x , x , 2 , 1 , 32 , 112 , 112 , 1 , 32 , 112 , 112 , 3, TIDL_ConvolutionLayer , 1, 1 , 1 , 2 , x , x , x , x , x , x , x , 3 , 1 , 32 , 112 , 112 , 1 , 64 , 112 , 112 , 4, TIDL_ConvolutionLayer , 1, 1 , 1 , 3 , x , x , x , x , x , x , x , 4 , 1 , 64 , 112 , 112 , 1 , 64 , 56 , 56 , 5, TIDL_ConvolutionLayer , 1, 1 , 1 , 4 , x , x , x , x , x , x , x , 5 , 1 , 64 , 56 , 56 , 1 , 128 , 56 , 56 , 6, TIDL_ConvolutionLayer , 1, 1 , 1 , 5 , x , x , x , x , x , x , x , 6 , 1 , 128 , 56 , 56 , 1 , 128 , 56 , 56 , 7, TIDL_ConvolutionLayer , 1, 1 , 1 , 6 , x , x , x , x , x , x , x , 7 , 1 , 128 , 56 , 56 , 1 , 128 , 56 , 56 , 8, TIDL_ConvolutionLayer , 1, 1 , 1 , 7 , x , x , x , x , x , x , x , 8 , 1 , 128 , 56 , 56 , 1 , 128 , 28 , 28 , 9, TIDL_ConvolutionLayer , 1, 1 , 1 , 8 , x , x , x , x , x , x , x , 9 , 1 , 128 , 28 , 28 , 1 , 256 , 28 , 28 , 10, TIDL_ConvolutionLayer , 1, 1 , 1 , 9 , x , x , x , x , x , x , x , 10 , 1 , 256 , 28 , 28 , 1 , 256 , 28 , 28 , 11, TIDL_ConvolutionLayer , 1, 1 , 1 , 10 , x , x , x , x , x , x , x , 11 , 1 , 256 , 28 , 28 , 1 , 256 , 28 , 28 , 12, TIDL_ConvolutionLayer , 1, 1 , 1 , 11 , x , x , x , x , x , x , x , 12 , 1 , 256 , 28 , 28 , 1 , 256 , 14 , 14 , 13, TIDL_ConvolutionLayer , 1, 1 , 1 , 12 , x , x , x , x , x , x , x , 13 , 1 , 256 , 14 , 14 , 1 , 512 , 14 , 14 , 14, TIDL_ConvolutionLayer , 1, 1 , 1 , 13 , x , x , x , x , x , x , x , 14 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 15, TIDL_ConvolutionLayer , 1, 1 , 1 , 14 , x , x , x , x , x , x , x , 15 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 16, TIDL_ConvolutionLayer , 1, 1 , 1 , 15 , x , x , x , x , x , x , x , 16 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 17, TIDL_ConvolutionLayer , 1, 1 , 1 , 16 , x , x , x , x , x , x , x , 17 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 18, TIDL_ConvolutionLayer , 1, 1 , 1 , 17 , x , x , x , x , x , x , x , 18 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 19, TIDL_ConvolutionLayer , 1, 1 , 1 , 18 , x , x , x , x , x , x , x , 19 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 20, TIDL_ConvolutionLayer , 1, 1 , 1 , 19 , x , x , x , x , x , x , x , 20 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 21, TIDL_ConvolutionLayer , 1, 1 , 1 , 20 , x , x , x , x , x , x , x , 21 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 22, TIDL_ConvolutionLayer , 1, 1 , 1 , 21 , x , x , x , x , x , x , x , 22 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 23, TIDL_ConvolutionLayer , 1, 1 , 1 , 22 , x , x , x , x , x , x , x , 23 , 1 , 512 , 14 , 14 , 1 , 512 , 14 , 14 , 24, TIDL_ConvolutionLayer , 1, 1 , 1 , 23 , x , x , x , x , x , x , x , 24 , 1 , 512 , 14 , 14 , 1 , 512 , 7 , 7 , 25, TIDL_ConvolutionLayer , 1, 1 , 1 , 24 , x , x , x , x , x , x , x , 25 , 1 , 512 , 7 , 7 , 1 , 1024 , 7 , 7 , 26, TIDL_ConvolutionLayer , 1, 1 , 1 , 25 , x , x , x , x , x , x , x , 26 , 1 , 1024 , 7 , 7 , 1 , 1024 , 7 , 7 , 27, TIDL_ConvolutionLayer , 1, 1 , 1 , 26 , x , x , x , x , x , x , x , 27 , 1 , 1024 , 7 , 7 , 1 , 1024 , 7 , 7 , 28, TIDL_PoolingLayer , 1, 1 , 1 , 27 , x , x , x , x , x , x , x , 28 , 1 , 1024 , 7 , 7 , 1 , 1 , 1 , 1024 , 29, TIDL_InnerProductLayer , 1, 1 , 1 , 28 , x , x , x , x , x , x , x , 29 , 1 , 1 , 1 , 1024 , 1 , 1 , 1 , 1001 , 30, TIDL_SoftMaxLayer , 1, 1 , 1 , 29 , x , x , x , x , x , x , x , 30 , 1 , 1 , 1 , 1001 , 1 , 1 , 1 , 1001 , 31, TIDL_DataLayer , 0, 1 , -1 , 30 , x , x , x , x , x , x , x , 0 , 1 , 1 , 1 , 1001 , 0 , 0 , 0 , 0 , Layer ID ,inBlkWidth ,inBlkHeight ,inBlkPitch ,outBlkWidth ,outBlkHeight,outBlkPitch ,numInChs ,numOutChs ,numProcInChs,numLclInChs ,numLclOutChs,numProcItrs ,numAccItrs ,numHorBlock ,numVerBlock ,inBlkChPitch,outBlkChPitc,alignOrNot 1 72 60 72 32 28 32 3 32 3 1 8 1 3 4 4 4320 896 1 2 40 30 40 32 28 32 1 1 1 1 1 1 1 4 4 1200 896 1 3 32 28 32 32 28 32 32 64 32 8 8 1 4 4 4 896 896 1 4 72 60 72 32 28 32 1 1 1 1 1 1 1 2 2 4320 896 1 5 32 28 32 32 28 32 64 128 64 8 8 1 8 2 2 896 896 1 6 40 30 40 32 28 32 1 1 1 1 1 1 1 2 2 1200 896 1 7 32 28 32 32 28 32 128 128 128 8 8 1 16 2 2 896 896 1 8 72 60 72 32 28 32 1 1 1 1 1 1 1 1 1 4320 896 1 9 32 28 32 32 28 32 128 256 128 8 8 1 16 1 1 896 896 1 10 40 30 40 32 28 32 1 1 1 1 1 1 1 1 1 1200 896 1 11 32 28 32 32 28 32 256 256 256 8 8 1 32 1 1 896 896 1 12 40 32 40 16 14 16 1 1 1 1 1 1 1 1 1 1280 224 1 13 16 14 16 16 14 16 256 512 256 8 8 1 32 1 1 224 224 1 14 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1 15 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1 16 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1 17 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1 18 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1 19 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1 20 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1 21 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1 22 24 16 24 16 14 16 1 1 1 1 1 1 1 1 1 384 224 1 23 16 14 16 16 14 16 512 512 512 8 8 1 64 1 1 224 224 1 24 40 18 40 16 7 16 1 1 1 1 1 1 1 1 1 720 112 1 25 16 7 16 16 7 16 512 1024 512 8 8 1 64 1 1 112 112 1 26 24 9 24 16 7 16 1 1 1 1 1 1 1 1 1 216 112 1 27 16 7 16 16 7 16 1024 1024 1024 8 8 1 128 1 1 112 112 1 Processing Frame Number : 0 Image reading is Not Supported. OpenCV not Enabled Layer 1 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 10.84, 9.63, Sparsity : 11.11 Layer 2 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 3.61, 3.61, Sparsity : 0.00 Layer 3 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 20.47, Sparsity : 20.31 Layer 4 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 1.81, 1.81, Sparsity : 0.00 Layer 5 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 24.56, Sparsity : 4.39 Layer 6 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 3.61, 3.61, Sparsity : 0.00 Layer 7 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 50.97, Sparsity : 0.81 Layer 8 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 9 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 25.68, Sparsity : 0.02 Layer 10 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 1.81, 1.81, Sparsity : 0.00 Layer 11 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.00 Layer 12 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.45, 0.45, Sparsity : 0.00 Layer 13 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 25.68, Sparsity : 0.02 Layer 14 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 15 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.00 Layer 16 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 17 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.28, Sparsity : 0.20 Layer 18 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 19 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.28, Sparsity : 0.20 Layer 20 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 21 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.01 Layer 22 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 23 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.00 Layer 24 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.23, 0.23, Sparsity : 0.00 Layer 25 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 25.59, Sparsity : 0.39 Layer 26 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.45, 0.45, Sparsity : 0.00 Layer 27 : Out Q : 1 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.00 Layer 28 : Out Q : 1 , TIDL_PoolingLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 29 : Out Q : 1 , TIDL_InnerProductLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 30 :-------Max Index 1000 : 0 ------- #MMACs = 0.00, 0.00, Sparsity : 0.00 End of config list found !

also something interesting happened ~ if I use the "ref" script it seems to be working is there any difference between these two scripts? which one is the correct one to use? thank you! .luca -- eve_test_dl_algo_ref.out config_list.txt ... 26 24 9 24 16 7 16 1 1 1 1 1 1 1 1 1 216 112 1 27 16 7 16 16 7 16 1024 1024 1024 8 8 1 128 1 1 112 112 1 Processing Frame Number : 0 Layer 1 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 10.84, 9.63, Sparsity : 11.11 Layer 2 : Out Q : 10877 , TIDL_ConvolutionLayer, PASSED #MMACs = 3.61, 3.61, Sparsity : 0.00 Layer 3 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 20.47, Sparsity : 20.31 Layer 4 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 1.81, 1.81, Sparsity : 0.00 Layer 5 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 24.56, Sparsity : 4.39 Layer 6 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 3.61, 3.61, Sparsity : 0.00 Layer 7 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 50.97, Sparsity : 0.81 Layer 8 : Out Q : 10879 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 9 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 25.68, Sparsity : 0.02 Layer 10 : Out Q : 10879 , TIDL_ConvolutionLayer, PASSED #MMACs = 1.81, 1.81, Sparsity : 0.00 Layer 11 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.00 Layer 12 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.45, 0.45, Sparsity : 0.00 Layer 13 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 25.68, Sparsity : 0.02 Layer 14 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 15 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.00 Layer 16 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 17 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.28, Sparsity : 0.20 Layer 18 : Out Q : 10878 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 19 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.28, Sparsity : 0.20 Layer 20 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 21 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.01 Layer 22 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.90, 0.90, Sparsity : 0.00 Layer 23 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.00 Layer 24 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.23, 0.23, Sparsity : 0.00 Layer 25 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 25.69, 25.59, Sparsity : 0.39 Layer 26 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 0.45, 0.45, Sparsity : 0.00 Layer 27 : Out Q : 10880 , TIDL_ConvolutionLayer, PASSED #MMACs = 51.38, 51.38, Sparsity : 0.00 Layer 28 : Out Q : 14700 , TIDL_PoolingLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 29 : Out Q : 1418 , TIDL_InnerProductLayer, PASSED #MMACs = 0.00, 0.00, Sparsity : 0.00 Layer 30 :-------Max Index 896 : 63 ------- #MMACs = 0.00, 0.00, Sparsity : 0.00 End of config list found !

Can you let me know the source of this "eve_test_dl_algo_ref.out". I dont see it part of the relese package? are you referering quant stats tool.

Since we haven't heard back, we hope you could find solution. Closing the thread.