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C:\PROCESSOR_SDK_VISION_03_07_00_00\ti_components\algorithms\REL.TIDL.01.01.03.00\modules\ti_dl\test\testvecs\config\import>tidl_model_import.out.exe tidl_import_jseg21.txt Caffe Network File : C:\PROCESSOR_SDK_VISION_03_07_00_00\ti_components\algorithms\REL.TIDL.01.01.03.00\modules\ti_dl\test\testvecs\config\caffe_jacinto_models_caffe\trained\image_segmentation\cityscapes5_jsegnet21v2\sparse\deploy.prototxt Caffe Model File : C:\PROCESSOR_SDK_VISION_03_07_00_00\ti_components\algorithms\REL.TIDL.01.01.03.00\modules\ti_dl\test\testvecs\config\caffe_jacinto_models_caffe\trained\image_segmentation\cityscapes5_jsegnet21v2\sparse\cityscapes5_jsegnet21v2_iter_32000.caffemodel TIDL Network File : C:\PROCESSOR_SDK_VISION_03_07_00_00\ti_components\algorithms\REL.TIDL.01.01.03.00\modules\ti_dl\test\testvecs\config\tidl_models\tidl_net_jsegnet21v2.bin TIDL Model File : C:\PROCESSOR_SDK_VISION_03_07_00_00\ti_components\algorithms\REL.TIDL.01.01.03.00\modules\ti_dl\test\testvecs\config\tidl_models\tidl_param_jsegnet21v2.bin Name of the Network : jsegnet21v2_deploy Num Inputs : 1 Num of Layer Detected : 27 0, TIDL_DataLayer , data 0, -1 , 1 , x , x , x , x , x , x , x , x , 0 , 0 , 0 , 0 , 0 , 1 , 3 , 512 , 1024 , 0 , 1, TIDL_BatchNormLayer , data/bias 1, 1 , 1 , 0 , x , x , x , x , x , x , x , 1 , 1 , 3 , 512 , 1024 , 1 , 3 , 512 , 1024 , 1572864 , 2, TIDL_ConvolutionLayer , conv1a 1, 1 , 1 , 1 , x , x , x , x , x , x , x , 2 , 1 , 3 , 512 , 1024 , 1 , 32 , 256 , 512 , 314572800 , 3, TIDL_ConvolutionLayer , conv1b 1, 1 , 1 , 2 , x , x , x , x , x , x , x , 3 , 1 , 32 , 256 , 512 , 1 , 32 , 128 , 256 , 301989888 , 4, TIDL_ConvolutionLayer , res2a_branch2a 1, 1 , 1 , 3 , x , x , x , x , x , x , x , 4 , 1 , 32 , 128 , 256 , 1 , 64 , 128 , 256 , 603979776 , 5, TIDL_ConvolutionLayer , res2a_branch2b 1, 1 , 1 , 4 , x , x , x , x , x , x , x , 5 , 1 , 64 , 128 , 256 , 1 , 64 , 64 , 128 , 301989888 , 6, TIDL_ConvolutionLayer , res3a_branch2a 1, 1 , 1 , 5 , x , x , x , x , x , x , x , 6 , 1 , 64 , 64 , 128 , 1 , 128 , 64 , 128 , 603979776 , 7, TIDL_ConvolutionLayer , res3a_branch2b 1, 1 , 1 , 6 , x , x , x , x , x , x , x , 7 , 1 , 128 , 64 , 128 , 1 , 128 , 64 , 128 , 301989888 , 8, TIDL_PoolingLayer , pool3 1, 1 , 1 , 7 , x , x , x , x , x , x , x , 8 , 1 , 128 , 64 , 128 , 1 , 128 , 32 , 64 , 1048576 , 9, TIDL_ConvolutionLayer , res4a_branch2a 1, 1 , 1 , 8 , x , x , x , x , x , x , x , 9 , 1 , 128 , 32 , 64 , 1 , 256 , 32 , 64 , 603979776 , 10, TIDL_ConvolutionLayer , res4a_branch2b 1, 1 , 1 , 9 , x , x , x , x , x , x , x , 10 , 1 , 256 , 32 , 64 , 1 , 256 , 32 , 64 , 301989888 , 11, TIDL_PoolingLayer , pool4 1, 1 , 1 , 10 , x , x , x , x , x , x , x , 11 , 1 , 256 , 32 , 64 , 1 , 256 , 32 , 64 , 524288 , 12, TIDL_ConvolutionLayer , res5a_branch2a 1, 1 , 1 , 11 , x , x , x , x , x , x , x , 12 , 1 , 256 , 32 , 64 , 1 , 512 , 32 , 64 ,2415919104 , 13, TIDL_ConvolutionLayer , res5a_branch2b 1, 1 , 1 , 12 , x , x , x , x , x , x , x , 13 , 1 , 512 , 32 , 64 , 1 , 512 , 32 , 64 ,1207959552 , 14, TIDL_ConvolutionLayer , out5a 1, 1 , 1 , 13 , x , x , x , x , x , x , x , 14 , 1 , 512 , 32 , 64 , 1 , 64 , 32 , 64 , 301989888 , 15, TIDL_Deconv2DLayer , out5a_up2 1, 1 , 1 , 14 , x , x , x , x , x , x , x , 15 , 1 , 64 , 32 , 64 , 1 , 64 , 64 , 128 , 2097152 , 16, TIDL_ConvolutionLayer , out3a 1, 1 , 1 , 7 , x , x , x , x , x , x , x , 16 , 1 , 128 , 64 , 128 , 1 , 64 , 64 , 128 , 301989888 , 17, TIDL_EltWiseLayer , out3_out5_combined 1, 2 , 1 , 15 , 16 , x , x , x , x , x , x , 17 , 1 , 64 , 64 , 128 , 1 , 64 , 64 , 128 , 524288 , 18, TIDL_ConvolutionLayer , ctx_conv1 1, 1 , 1 , 17 , x , x , x , x , x , x , x , 18 , 1 , 64 , 64 , 128 , 1 , 64 , 64 , 128 , 301989888 , 19, TIDL_ConvolutionLayer , ctx_conv2 1, 1 , 1 , 18 , x , x , x , x , x , x , x , 19 , 1 , 64 , 64 , 128 , 1 , 64 , 64 , 128 , 301989888 , 20, TIDL_ConvolutionLayer , ctx_conv3 1, 1 , 1 , 19 , x , x , x , x , x , x , x , 20 , 1 , 64 , 64 , 128 , 1 , 64 , 64 , 128 , 301989888 , 21, TIDL_ConvolutionLayer , ctx_conv4 1, 1 , 1 , 20 , x , x , x , x , x , x , x , 21 , 1 , 64 , 64 , 128 , 1 , 64 , 64 , 128 , 301989888 , 22, TIDL_ConvolutionLayer , ctx_final 1, 1 , 1 , 21 , x , x , x , x , x , x , x , 22 , 1 , 64 , 64 , 128 , 1 , 8 , 64 , 128 , 37748736 , 23, TIDL_Deconv2DLayer , out_deconv_final_up2 1, 1 , 1 , 22 , x , x , x , x , x , x , x , 23 , 1 , 8 , 64 , 128 , 1 , 8 , 128 , 256 , 1048576 , 24, TIDL_Deconv2DLayer , out_deconv_final_up4 1, 1 , 1 , 23 , x , x , x , x , x , x , x , 24 , 1 , 8 , 128 , 256 , 1 , 8 , 256 , 512 , 4194304 , 25, TIDL_Deconv2DLayer , out_deconv_final_up8 1, 1 , 1 , 24 , x , x , x , x , x , x , x , 25 , 1 , 8 , 256 , 512 , 1 , 8 , 512 , 1024 , 16777216 , 26, TIDL_ArgMaxLayer , argMaxOut 1, 1 , 1 , 25 , x , x , x , x , x , x , x , 26 , 1 , 8 , 512 , 1024 , 1 , 1 , 512 , 1024 , 8388608 , Total Giga Macs : 8.8442 1 file(s) copied. 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 , 512 , 1024 , 1, TIDL_BatchNormLayer , 1, 1 , 1 , 0 , x , x , x , x , x , x , x , 1 , 1 , 3 , 512 , 1024 , 1 , 3 , 512 , 1024 , 2, TIDL_ConvolutionLayer , 1, 1 , 1 , 1 , x , x , x , x , x , x , x , 2 , 1 , 3 , 512 , 1024 , 1 , 32 , 256 , 512 , 3, TIDL_ConvolutionLayer , 1, 1 , 1 , 2 , x , x , x , x , x , x , x , 3 , 1 , 32 , 256 , 512 , 1 , 32 , 128 , 256 , 4, TIDL_ConvolutionLayer , 1, 1 , 1 , 3 , x , x , x , x , x , x , x , 4 , 1 , 32 , 128 , 256 , 1 , 64 , 128 , 256 , 5, TIDL_ConvolutionLayer , 1, 1 , 1 , 4 , x , x , x , x , x , x , x , 5 , 1 , 64 , 128 , 256 , 1 , 64 , 64 , 128 , 6, TIDL_ConvolutionLayer , 1, 1 , 1 , 5 , x , x , x , x , x , x , x , 6 , 1 , 64 , 64 , 128 , 1 , 128 , 64 , 128 , 7, TIDL_ConvolutionLayer , 1, 1 , 1 , 6 , x , x , x , x , x , x , x , 7 , 1 , 128 , 64 , 128 , 1 , 128 , 64 , 128 , 8, TIDL_PoolingLayer , 1, 1 , 1 , 7 , x , x , x , x , x , x , x , 8 , 1 , 128 , 64 , 128 , 1 , 128 , 32 , 64 , 9, TIDL_ConvolutionLayer , 1, 1 , 1 , 8 , x , x , x , x , x , x , x , 9 , 1 , 128 , 32 , 64 , 1 , 256 , 32 , 64 , 10, TIDL_ConvolutionLayer , 1, 1 , 1 , 9 , x , x , x , x , x , x , x , 10 , 1 , 256 , 32 , 64 , 1 , 256 , 32 , 64 , 11, TIDL_PoolingLayer , 1, 1 , 1 , 10 , x , x , x , x , x , x , x , 11 , 1 , 256 , 32 , 64 , 1 , 256 , 32 , 64 , 12, TIDL_ConvolutionLayer , 1, 1 , 1 , 11 , x , x , x , x , x , x , x , 12 , 1 , 256 , 32 , 64 , 1 , 512 , 32 , 64 , 13, TIDL_ConvolutionLayer , 1, 1 , 1 , 12 , x , x , x , x , x , x , x , 13 , 1 , 512 , 32 , 64 , 1 , 512 , 32 , 64 , 14, TIDL_ConvolutionLayer , 1, 1 , 1 , 13 , x , x , x , x , x , x , x , 14 , 1 , 512 , 32 , 64 , 1 , 64 , 32 , 64 , 15, TIDL_Deconv2DLayer , 1, 1 , 1 , 14 , x , x , x , x , x , x , x , 15 , 1 , 64 , 32 , 64 , 1 , 64 , 64 , 128 , 16, TIDL_ConvolutionLayer , 1, 1 , 1 , 7 , x , x , x , x , x , x , x , 16 , 1 , 128 , 64 , 128 , 1 , 64 , 64 , 128 , 17, TIDL_EltWiseLayer , 1, 2 , 1 , 15 , 16 , x , x , x , x , x , x , 17 , 1 , 64 , 64 , 128 , 1 , 64 , 64 , 128 , 18, TIDL_ConvolutionLayer , 1, 1 , 1 , 17 , x , x , x , x , x , x , x , 18 , 1 , 64 , 64 , 128 , 1 , 64 , 64 , 128 , 19, TIDL_ConvolutionLayer , 1, 1 , 1 , 18 , x , x , x , x , x , x , x , 19 , 1 , 64 , 64 , 128 , 1 , 64 , 64 , 128 , 20, TIDL_ConvolutionLayer , 1, 1 , 1 , 19 , x , x , x , x , x , x , x , 20 , 1 , 64 , 64 , 128 , 1 , 64 , 64 , 128 , 21, TIDL_ConvolutionLayer , 1, 1 , 1 , 20 , x , x , x , x , x , x , x , 21 , 1 , 64 , 64 , 128 , 1 , 64 , 64 , 128 , 22, TIDL_ConvolutionLayer , 1, 1 , 1 , 21 , x , x , x , x , x , x , x , 22 , 1 , 64 , 64 , 128 , 1 , 8 , 64 , 128 , 23, TIDL_Deconv2DLayer , 1, 1 , 1 , 22 , x , x , x , x , x , x , x , 23 , 1 , 8 , 64 , 128 , 1 , 8 , 128 , 256 , 24, TIDL_Deconv2DLayer , 1, 1 , 1 , 23 , x , x , x , x , x , x , x , 24 , 1 , 8 , 128 , 256 , 1 , 8 , 256 , 512 , 25, TIDL_Deconv2DLayer , 1, 1 , 1 , 24 , x , x , x , x , x , x , x , 25 , 1 , 8 , 256 , 512 , 1 , 8 , 512 , 1024 , 26, TIDL_ArgMaxLayer , 1, 1 , 1 , 25 , x , x , x , x , x , x , x , 26 , 1 , 8 , 512 , 1024 , 1 , 1 , 512 , 1024 , 27, TIDL_DataLayer , 0, 1 , -1 , 26 , x , x , x , x , x , x , x , 0 , 1 , 1 , 512 , 1024 , 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 16 8 5184 1024 1 3 40 34 40 32 32 32 8 8 8 4 8 1 2 16 8 1360 1024 1 4 40 34 40 32 32 32 32 64 32 6 8 1 6 8 4 1360 1024 1 5 40 34 40 32 32 32 16 16 16 6 8 1 3 8 4 1360 1024 1 6 40 34 40 32 32 32 64 128 64 6 8 1 11 4 2 1360 1024 1 7 40 34 40 32 32 32 32 32 32 6 8 1 6 4 2 1360 1024 1 9 40 34 40 32 32 32 128 256 128 6 8 1 22 2 1 1360 1024 1 10 40 34 40 32 32 32 64 64 64 6 8 1 11 2 1 1360 1024 1 12 40 20 40 32 16 32 256 512 256 8 8 1 32 2 2 800 512 1 13 40 36 40 32 32 32 128 128 128 5 8 1 26 2 1 1440 1024 1 14 40 24 40 32 16 32 256 32 256 8 8 1 32 2 2 960 512 1 16 40 34 40 32 32 32 64 32 64 6 8 1 11 4 2 1360 1024 1 18 40 34 40 32 32 32 64 64 64 6 8 1 11 4 2 1360 1024 1 19 40 40 40 32 32 32 64 64 64 5 8 1 13 4 2 1600 1024 1 20 40 40 40 32 32 32 64 64 64 5 8 1 13 4 2 1600 1024 1 21 40 40 40 32 32 32 64 64 64 5 8 1 13 4 2 1600 1024 1 22 40 34 40 32 32 32 64 8 64 6 8 1 11 4 2 1360 1024 1 Processing Frame Number : 0 Layer 1 : Out Q : 254 , TIDL_BatchNormLayer , PASSED #MMACs = 1.57, 1.57, Sparsity : 0.00 Layer 2 : Out Q : 6097 , TIDL_ConvolutionLayer, PASSED #MMACs = 314.57, 209.19, Sparsity : 33.50 Layer 3 : Out Q : 5378 , TIDL_ConvolutionLayer, PASSED #MMACs = 301.99, 122.16, Sparsity : 59.55 Layer 4 : Out Q : 13609 , TIDL_ConvolutionLayer, PASSED #MMACs = 603.98, 162.66, Sparsity : 73.07 Layer 5 : Out Q : 8489 , TIDL_ConvolutionLayer, PASSED #MMACs = 301.99, 123.86, Sparsity : 58.98 Layer 6 : Out Q : 9235 , TIDL_ConvolutionLayer, PASSED #MMACs = 603.98, 153.91, Sparsity : 74.52 Layer 7 : Out Q : 11745 , TIDL_ConvolutionLayer, PASSED #MMACs = 301.99, 103.55, Sparsity : 65.71 Layer 8 :TIDL_PoolingLayer, PASSED #MMACs = 0.26, 0.26, Sparsity : 0.00 Layer 9 : Out Q : 16199 , TIDL_ConvolutionLayer, PASSED #MMACs = 603.98, 142.94, Sparsity : 76.33 Layer 10 : Out Q : 14923 , TIDL_ConvolutionLayer, PASSED #MMACs = 301.99, 76.61, Sparsity : 74.63 Layer 11 :TIDL_PoolingLayer, PASSED #MMACs = 0.52, 0.52, Sparsity : 0.00 Layer 12 : Out Q : 25787 , TIDL_ConvolutionLayer, PASSED #MMACs = 2415.92, 500.01, Sparsity : 79.30 Layer 13 : Out Q : 6224 , TIDL_ConvolutionLayer, PASSED #MMACs = 1207.96, 221.44, Sparsity : 81.67 Layer 14 : Out Q : 10770 , TIDL_ConvolutionLayer, PASSED #MMACs = 301.99, 79.45, Sparsity : 73.69 Layer 15 : Out Q : 6165 , TIDL_Deconv2DLayer, PASSED #MMACs = 0.52, 0.52, Sparsity : 0.00 Layer 16 : Out Q : 10642 , TIDL_ConvolutionLayer, PASSED #MMACs = 301.99, 96.17, Sparsity : 68.15 Layer 17 : Out Q : 4658 , TIDL_EltWiseLayer, PASSED #MMACs = 1.05, 1.05, Sparsity : 0.00 Layer 18 : Out Q : 13159 , TIDL_ConvolutionLayer, PASSED #MMACs = 301.99, 131.50, Sparsity : 56.46 Layer 19 : Out Q : 15034 , TIDL_ConvolutionLayer, PASSED #MMACs = 301.99, 125.67, Sparsity : 58.39 Layer 20 : Out Q : 16267 , TIDL_ConvolutionLayer, PASSED #MMACs = 301.99, 128.61, Sparsity : 57.41 Layer 21 : Out Q : 11247 , TIDL_ConvolutionLayer, PASSED #MMACs = 301.99, 122.65, Sparsity : 59.39 Layer 22 : Out Q : 3107 , TIDL_ConvolutionLayer, PASSED #MMACs = 37.75, 14.84, Sparsity : 60.68 Layer 23 : Out Q : 1583 , TIDL_Deconv2DLayer, PASSED #MMACs = 0.26, 0.26, Sparsity : 0.00 Layer 24 : Out Q : 1600 , TIDL_Deconv2DLayer, PASSED #MMACs = 1.05, 1.05, Sparsity : 0.00 Layer 25 : Out Q : 1604 , TIDL_Deconv2DLayer, PASSED #MMACs = 4.19, 4.19, Sparsity : 0.00 Layer 26 :TIDL_ArgMaxLayer, PASSED #MMACs = 4.19, 4.19, Sparsity : 0.00 End of config list found ! C:\PROCESSOR_SDK_VISION_03_07_00_00\ti_components\algorithms\REL.TIDL.01.01.03.00\modules\ti_dl\test\testvecs\config\import> same thnk i asked please tell me sir Optimization I have told u many times U have to understand where on tda2 the DL network is running what operation are happening in each network layer and then check for possibility of optimization of those low level operation |