模拟量化推理,CPU推理及MLU在线推理 CPU output data [ 0.50792 0.60933 0.85192 1.2785e-09 0.051217 0.96458 0.14716 0.52833 0.36931 0.48842 5.4355e-06 0.026613 0.0036401 0.028052 0.42166 0.59655 0.44176 1.0914e-07 0.1522 0.33789] MLU output data [ 0.50791 0.60922 0.85188 0.00043056 0.051245 0.96453 0.1467 0.52768 0.36914 0.48842 0.00043056 0.026682 0.0036404 0.028094 0.42174 0.59657 0.44175 0.00043056 0.15213 0.33806] quantification without mlu output data [ 0.59453 0.48446 0.46927 0.0023514 0.56388 0.93369 0.013752 0.49091 0.51543 0.44937 0.00078506 0.53746 0.023156 0.97789 0.48771 0.54794 0.54198 2.2038e-06 0.17354 0.67635] DUMP 逐层对比 MSE: layer_00000_model.0.conv_in errRate = 0.0 layer_00000_model.0.conv_out errRate = 1.2593555450439453 layer_00001_model.0.bn_in errRate = 1.2593555450439453 layer_00001_model.0.bn_out errRate = 1.1468819379806519 layer_00002_model.0.act_in errRate = 1.1486361026763916 layer_00002_model.0.act_out errRate = 1.1486361026763916 layer_00003_model.1.conv_in errRate = 1.1486361026763916 layer_00003_model.1.conv_out errRate = 1.41724693775177 layer_00004_model.1.bn_in errRate = 1.41724693775177 layer_00004_model.1.bn_out errRate = 1.422462821006775 layer_00005_model.1.act_in errRate = 1.4091591835021973 layer_00005_model.1.act_out errRate = 1.4091591835021973 layer_00006_model.2.conv_in errRate = 1.4091591835021973 layer_00006_model.2.conv_out errRate = 1.3829034566879272 layer_00007_model.2.bn_in errRate = 1.3829034566879272 layer_00007_model.2.bn_out errRate = 1.3737596273422241 layer_00008_model.2.act_in errRate = 1.3720648288726807 layer_00008_model.2.act_out errRate = 1.3720648288726807 layer_00009_model.3.conv_in errRate = 1.4091591835021973 layer_00009_model.3.conv_out errRate = 1.308558702468872 layer_00010_model.3.bn_in errRate = 1.308558702468872 layer_00010_model.3.bn_out errRate = 1.2832577228546143 layer_00011_model.3.act_in errRate = 1.2605966329574585 layer_00011_model.3.act_out errRate = 1.2605966329574585 layer_00012_model.4.conv_in errRate = 1.2605966329574585 layer_00012_model.4.conv_out errRate = 1.4379688501358032 layer_00013_model.4.bn_in errRate = 1.4379688501358032 layer_00013_model.4.bn_out errRate = 1.4761534929275513 layer_00014_model.4.act_in errRate = 1.4842971563339233 layer_00014_model.4.act_out errRate = 1.4842971563339233 layer_00015_model.5.conv_in errRate = 1.4842971563339233 layer_00015_model.5.conv_out errRate = 1.3860375881195068 layer_00016_model.5.bn_in errRate = 1.3860375881195068 layer_00016_model.5.bn_out errRate = 1.3833346366882324 layer_00017_model.5.act_in errRate = 1.376929521560669 layer_00017_model.5.act_out errRate = 1.376929521560669 layer_00018_model.6_in errRate = 1.376929521560669 layer_00018_model.6_in errRate = 1.4842971563339233 layer_00018_model.6_in errRate = 1.2605966329574585 layer_00018_model.6_in errRate = 1.3720648288726807 layer_00018_model.6_out errRate = 1.3737735748291016 layer_00019_model.7.conv_in errRate = 1.3737735748291016 layer_00019_model.7.conv_out errRate = 1.5061357021331787 layer_00020_model.7.bn_in errRate = 1.5061357021331787 layer_00020_model.7.bn_out errRate = 1.4032390117645264 layer_00021_model.7.act_in errRate = 1.401467204093933 layer_00021_model.7.act_out errRate = 1.401467204093933 layer_00022_model.8.m_in errRate = 1.401467204093933 layer_00022_model.8.m_out errRate = 0.9191212058067322 layer_00023_model.9.conv_in errRate = 0.9191212058067322 layer_00023_model.9.conv_out errRate = 1.3806709051132202 layer_00024_model.9.bn_in errRate = 1.3806709051132202 layer_00024_model.9.bn_out errRate = 1.3740613460540771 layer_00025_model.9.act_in errRate = 1.370930552482605 layer_00025_model.9.act_out errRate = 1.370930552482605 layer_00026_model.10.conv_in errRate = 0.9191212058067322 layer_00026_model.10.conv_out errRate = 1.396194338798523 layer_00027_model.10.bn_in errRate = 1.396194338798523 layer_00027_model.10.bn_out errRate = 1.437617540359497 layer_00028_model.10.act_in errRate = 1.441697120666504 layer_00028_model.10.act_out errRate = 1.441697120666504 layer_00029_model.11.conv_in errRate = 1.441697120666504 layer_00029_model.11.conv_out errRate = 1.4215097427368164 layer_00030_model.11.bn_in errRate = 1.4215097427368164 layer_00030_model.11.bn_out errRate = 1.4434810876846313 layer_00031_model.11.act_in errRate = 1.4419026374816895 layer_00031_model.11.act_out errRate = 1.4419026374816895 layer_00032_model.12.conv_in errRate = 1.4419026374816895 layer_00032_model.12.conv_out errRate = 1.4274742603302002 layer_00033_model.12.bn_in errRate = 1.4274742603302002 layer_00033_model.12.bn_out errRate = 1.4193565845489502 layer_00034_model.12.act_in errRate = 1.4145022630691528 layer_00034_model.12.act_out errRate = 1.4145022630691528 layer_00035_model.13_in errRate = 1.4145022630691528 layer_00035_model.13_in errRate = 1.4419026374816895 layer_00035_model.13_in errRate = 1.441697120666504 layer_00035_model.13_in errRate = 1.370930552482605 layer_00035_model.13_out errRate = 1.4172489643096924 layer_00036_model.14.conv_in errRate = 1.4172489643096924 layer_00036_model.14.conv_out errRate = 1.4074362516403198 layer_00037_model.14.bn_in errRate = 1.4074362516403198 layer_00037_model.14.bn_out errRate = 1.4332075119018555 layer_00038_model.14.act_in errRate = 1.4336706399917603 layer_00038_model.14.act_out errRate = 1.4336706399917603 layer_00039_model.15.m_in errRate = 1.4336706399917603 layer_00039_model.15.m_out errRate = 0.9368709921836853 layer_00040_model.16.conv_in errRate = 0.9368709921836853 layer_00040_model.16.conv_out errRate = 1.488540530204773 layer_00041_model.16.bn_in errRate = 1.488540530204773 layer_00041_model.16.bn_out errRate = 1.4302674531936646 layer_00042_model.16.act_in errRate = 1.4276041984558105 layer_00042_model.16.act_out errRate = 1.4276041984558105 layer_00043_model.17.conv_in errRate = 0.9368709921836853 layer_00043_model.17.conv_out errRate = 1.4992543458938599 layer_00044_model.17.bn_in errRate = 1.4992543458938599 layer_00044_model.17.bn_out errRate = 1.3895772695541382 layer_00045_model.17.act_in errRate = 1.3937089443206787 layer_00045_model.17.act_out errRate = 1.3937089443206787 layer_00046_model.18.conv_in errRate = 1.3937089443206787 layer_00046_model.18.conv_out errRate = 1.440935492515564 layer_00047_model.18.bn_in errRate = 1.440935492515564 layer_00047_model.18.bn_out errRate = 1.4363638162612915 layer_00048_model.18.act_in errRate = 1.4308037757873535 layer_00048_model.18.act_out errRate = 1.4308037757873535 layer_00049_model.19.conv_in errRate = 1.4308037757873535 layer_00049_model.19.conv_out errRate = 1.476366400718689 layer_00050_model.19.bn_in errRate = 1.476366400718689 layer_00050_model.19.bn_out errRate = 1.4180277585983276 layer_00051_model.19.act_in errRate = 1.4191924333572388 layer_00051_model.19.act_out errRate = 1.4191924333572388 layer_00052_model.20_in errRate = 1.4191924333572388 layer_00052_model.20_in errRate = 1.4308037757873535 layer_00052_model.20_in errRate = 1.3937089443206787 layer_00052_model.20_in errRate = 1.4276041984558105 layer_00052_model.20_out errRate = 1.4177950620651245 layer_00053_model.21.conv_in errRate = 1.4177950620651245 layer_00053_model.21.conv_out errRate = 1.4376143217086792 layer_00054_model.21.bn_in errRate = 1.4376143217086792 layer_00054_model.21.bn_out errRate = 1.4165914058685303 layer_00055_model.21.act_in errRate = 1.4182467460632324 layer_00055_model.21.act_out errRate = 1.4182467460632324 layer_00056_model.22.m_in errRate = 1.4182467460632324 layer_00056_model.22.m_out errRate = 0.8779253959655762 layer_00057_model.23.conv_in errRate = 0.8779253959655762 layer_00057_model.23.conv_out errRate = 1.486749529838562 layer_00058_model.23.bn_in errRate = 1.486749529838562 layer_00058_model.23.bn_out errRate = 1.4235731363296509 layer_00059_model.23.act_in errRate = 1.4278851747512817 layer_00059_model.23.act_out errRate = 1.4278851747512817 layer_00060_model.24.conv_in errRate = 0.8779253959655762 layer_00060_model.24.conv_out errRate = 1.3671362400054932 layer_00061_model.24.bn_in errRate = 1.3671362400054932 layer_00061_model.24.bn_out errRate = 1.3942465782165527 layer_00062_model.24.act_in errRate = 1.390271544456482 layer_00062_model.24.act_out errRate = 1.390271544456482 layer_00063_model.25.conv_in errRate = 1.390271544456482 layer_00063_model.25.conv_out errRate = 1.4361456632614136 layer_00064_model.25.bn_in errRate = 1.4361456632614136 layer_00064_model.25.bn_out errRate = 1.4276288747787476 layer_00065_model.25.act_in errRate = 1.4260528087615967 layer_00065_model.25.act_out errRate = 1.4260528087615967 layer_00066_model.26.conv_in errRate = 1.4260528087615967 layer_00066_model.26.conv_out errRate = 1.427897334098816 layer_00067_model.26.bn_in errRate = 1.427897334098816 layer_00067_model.26.bn_out errRate = 1.417172908782959 layer_00068_model.26.act_in errRate = 1.4174795150756836 layer_00068_model.26.act_out errRate = 1.4174795150756836 layer_00069_model.27_in errRate = 1.4174795150756836 layer_00069_model.27_in errRate = 1.4260528087615967 layer_00069_model.27_in errRate = 1.390271544456482 layer_00069_model.27_in errRate = 1.4278851747512817 layer_00069_model.27_out errRate = 1.4154218435287476 layer_00070_model.28.conv_in errRate = 1.4154218435287476 layer_00070_model.28.conv_out errRate = 1.4383620023727417 layer_00071_model.28.bn_in errRate = 1.4383620023727417 layer_00071_model.28.bn_out errRate = 1.4152649641036987 layer_00072_model.28.act_in errRate = 1.4166669845581055 layer_00072_model.28.act_out errRate = 1.4166669845581055 layer_00073_model.29.conv_in errRate = 1.4166669845581055 layer_00073_model.29.conv_out errRate = 1.3986530303955078 layer_00074_model.29.bn_in errRate = 1.3986530303955078 layer_00074_model.29.bn_out errRate = 1.404391884803772 layer_00075_model.29.act_in errRate = 1.406037449836731 layer_00075_model.29.act_out errRate = 1.406037449836731 layer_00076_model.30.conv_in errRate = 1.4166669845581055 layer_00076_model.30.conv_out errRate = 1.42221200466156 layer_00077_model.30.bn_in errRate = 1.42221200466156 layer_00077_model.30.bn_out errRate = 1.417000412940979 layer_00078_model.30.act_in errRate = 1.4176453351974487 layer_00078_model.30.act_out errRate = 1.4176453351974487 layer_00079_model.31.m_in errRate = 1.4176453351974487 layer_00079_model.31.m_out errRate = 0.3854774534702301 layer_00080_model.32.m_in errRate = 1.4176453351974487 layer_00080_model.32.m_out errRate = 0.2785249352455139 layer_00081_model.33.m_in errRate = 1.4176453351974487 layer_00081_model.33.m_out errRate = 0.24810267984867096 layer_00082_model.34_in errRate = 0.24810267984867096 layer_00082_model.34_in errRate = 0.2785249352455139 layer_00082_model.34_in errRate = 0.3854774534702301 layer_00082_model.34_in errRate = 1.4176453351974487 layer_00082_model.34_out errRate = 0.36104121804237366 layer_00083_model.35.conv_in errRate = 0.36104121804237366 layer_00083_model.35.conv_out errRate = 1.334460735321045 layer_00084_model.35.bn_in errRate = 1.334460735321045 layer_00084_model.35.bn_out errRate = 1.4105173349380493 layer_00085_model.35.act_in errRate = 1.405107021331787 layer_00085_model.35.act_out errRate = 1.405107021331787 layer_00086_model.36_in errRate = 1.405107021331787 layer_00086_model.36_in errRate = 1.406037449836731 layer_00086_model.36_out errRate = 1.4055628776550293 layer_00087_model.37.conv_in errRate = 1.4055628776550293 layer_00087_model.37.conv_out errRate = 1.4115439653396606 layer_00088_model.37.bn_in errRate = 1.4115439653396606 layer_00088_model.37.bn_out errRate = 1.409516453742981 layer_00089_model.37.act_in errRate = 1.406844139099121 layer_00089_model.37.act_out errRate = 1.406844139099121 layer_00090_model.38.conv_in errRate = 1.406844139099121 layer_00090_model.38.conv_out errRate = 1.421854019165039 layer_00091_model.38.bn_in errRate = 1.421854019165039 layer_00091_model.38.bn_out errRate = 1.4182676076889038 layer_00092_model.38.act_in errRate = 1.413456678390503 layer_00092_model.38.act_out errRate = 1.413456678390503 layer_00093_model.39_in errRate = 1.413456678390503 layer_00093_model.39_out errRate = 1.4134567975997925 layer_00094_model.40.conv_in errRate = 1.4182467460632324 layer_00094_model.40.conv_out errRate = 1.4402636289596558 layer_00095_model.40.bn_in errRate = 1.4402636289596558 layer_00095_model.40.bn_out errRate = 1.4143284559249878 layer_00096_model.40.act_in errRate = 1.416688084602356 layer_00096_model.40.act_out errRate = 1.416688084602356 layer_00097_model.41_in errRate = 1.416688084602356 layer_00097_model.41_in errRate = 1.4134567975997925 layer_00097_model.41_out errRate = 1.415039300918579 layer_00098_model.42.conv_in errRate = 1.415039300918579 layer_00098_model.42.conv_out errRate = 1.3989964723587036 layer_00099_model.42.bn_in errRate = 1.3989964723587036 layer_00099_model.42.bn_out errRate = 1.419390082359314 layer_00100_model.42.act_in errRate = 1.4209095239639282 layer_00100_model.42.act_out errRate = 1.4209095239639282 layer_00101_model.43.conv_in errRate = 1.415039300918579 layer_00101_model.43.conv_out errRate = 1.4351199865341187 layer_00102_model.43.bn_in errRate = 1.4351199865341187 layer_00102_model.43.bn_out errRate = 1.421818733215332 layer_00103_model.43.act_in errRate = 1.4230815172195435 layer_00103_model.43.act_out errRate = 1.4230815172195435 layer_00104_model.44.conv_in errRate = 1.4230815172195435 layer_00104_model.44.conv_out errRate = 1.3806616067886353 layer_00105_model.44.bn_in errRate = 1.3806616067886353 layer_00105_model.44.bn_out errRate = 1.4226521253585815 layer_00106_model.44.act_in errRate = 1.4265820980072021 layer_00106_model.44.act_out errRate = 1.4265820980072021 layer_00107_model.45.conv_in errRate = 1.4265820980072021 layer_00107_model.45.conv_out errRate = 1.3887683153152466 layer_00108_model.45.bn_in errRate = 1.3887683153152466 layer_00108_model.45.bn_out errRate = 1.4183990955352783 layer_00109_model.45.act_in errRate = 1.4209716320037842 layer_00109_model.45.act_out errRate = 1.4209716320037842 layer_00110_model.46_in errRate = 1.4209716320037842 layer_00110_model.46_in errRate = 1.4265820980072021 layer_00110_model.46_in errRate = 1.4230815172195435 layer_00110_model.46_in errRate = 1.4209095239639282 layer_00110_model.46_out errRate = 1.4228863716125488 layer_00111_model.47.conv_in errRate = 1.4228863716125488 layer_00111_model.47.conv_out errRate = 1.4053385257720947 layer_00112_model.47.bn_in errRate = 1.4053385257720947 layer_00112_model.47.bn_out errRate = 1.4155312776565552 layer_00113_model.47.act_in errRate = 1.4137115478515625 layer_00113_model.47.act_out errRate = 1.4137115478515625 layer_00114_model.48.conv_in errRate = 1.4137115478515625 layer_00114_model.48.conv_out errRate = 1.4156464338302612 layer_00115_model.48.bn_in errRate = 1.4156464338302612 layer_00115_model.48.bn_out errRate = 1.427831768989563 layer_00116_model.48.act_in errRate = 1.425695776939392 layer_00116_model.48.act_out errRate = 1.425695776939392 layer_00117_model.49_in errRate = 1.425695776939392 layer_00117_model.49_out errRate = 1.4256960153579712 layer_00118_model.50.conv_in errRate = 1.4336706399917603 layer_00118_model.50.conv_out errRate = 1.4124093055725098 layer_00119_model.50.bn_in errRate = 1.4124093055725098 layer_00119_model.50.bn_out errRate = 1.4075483083724976 layer_00120_model.50.act_in errRate = 1.4019112586975098 layer_00120_model.50.act_out errRate = 1.4019112586975098 layer_00121_model.51_in errRate = 1.4019112586975098 layer_00121_model.51_in errRate = 1.4256960153579712 layer_00121_model.51_out errRate = 1.4139927625656128 layer_00122_model.52.conv_in errRate = 1.4139927625656128 layer_00122_model.52.conv_out errRate = 1.4312307834625244 layer_00123_model.52.bn_in errRate = 1.4312307834625244 layer_00123_model.52.bn_out errRate = 1.4140489101409912 layer_00124_model.52.act_in errRate = 1.416249394416809 layer_00124_model.52.act_out errRate = 1.416249394416809 layer_00125_model.53.conv_in errRate = 1.4139927625656128 layer_00125_model.53.conv_out errRate = 1.4691576957702637 layer_00126_model.53.bn_in errRate = 1.4691576957702637 layer_00126_model.53.bn_out errRate = 1.4155759811401367 layer_00127_model.53.act_in errRate = 1.4143435955047607 layer_00127_model.53.act_out errRate = 1.4143435955047607 layer_00128_model.54.conv_in errRate = 1.4143435955047607 layer_00128_model.54.conv_out errRate = 1.396109938621521 layer_00129_model.54.bn_in errRate = 1.396109938621521 layer_00129_model.54.bn_out errRate = 1.4202864170074463 layer_00130_model.54.act_in errRate = 1.4160246849060059 layer_00130_model.54.act_out errRate = 1.4160246849060059 layer_00131_model.55.conv_in errRate = 1.4160246849060059 layer_00131_model.55.conv_out errRate = 1.3684804439544678 layer_00132_model.55.bn_in errRate = 1.3684804439544678 layer_00132_model.55.bn_out errRate = 1.3964725732803345 layer_00133_model.55.act_in errRate = 1.3992116451263428 layer_00133_model.55.act_out errRate = 1.3992116451263428 layer_00134_model.56_in errRate = 1.3992116451263428 layer_00134_model.56_in errRate = 1.4160246849060059 layer_00134_model.56_in errRate = 1.4143435955047607 layer_00134_model.56_in errRate = 1.416249394416809 layer_00134_model.56_out errRate = 1.4114240407943726 layer_00135_model.57.conv_in errRate = 1.4114240407943726 layer_00135_model.57.conv_out errRate = 1.4168369770050049 layer_00136_model.57.bn_in errRate = 1.4168369770050049 layer_00136_model.57.bn_out errRate = 1.4319652318954468 layer_00137_model.57.act_in errRate = 1.4300745725631714 layer_00137_model.57.act_out errRate = 1.4300745725631714 layer_00138_model.58.conv_in errRate = 1.4300745725631714 layer_00138_model.58.conv_out errRate = 1.4393160343170166 layer_00139_model.58.bn_in errRate = 1.4393160343170166 layer_00139_model.58.bn_out errRate = 1.4008748531341553 layer_00140_model.58.act_in errRate = 1.4022090435028076 layer_00140_model.58.act_out errRate = 1.4022090435028076 layer_00141_model.59_in errRate = 1.4022090435028076 layer_00141_model.59_in errRate = 1.4137115478515625 layer_00141_model.59_out errRate = 1.4079575538635254 layer_00142_model.60.conv_in errRate = 1.4079575538635254 layer_00142_model.60.conv_out errRate = 1.401392936706543 layer_00143_model.60.bn_in errRate = 1.401392936706543 layer_00143_model.60.bn_out errRate = 1.413087010383606 layer_00144_model.60.act_in errRate = 1.4109326601028442 layer_00144_model.60.act_out errRate = 1.4109326601028442 layer_00145_model.61.conv_in errRate = 1.4079575538635254 layer_00145_model.61.conv_out errRate = 1.451689600944519 layer_00146_model.61.bn_in errRate = 1.451689600944519 layer_00146_model.61.bn_out errRate = 1.4194958209991455 layer_00147_model.61.act_in errRate = 1.4211763143539429 layer_00147_model.61.act_out errRate = 1.4211763143539429 layer_00148_model.62.conv_in errRate = 1.4211763143539429 layer_00148_model.62.conv_out errRate = 1.4187257289886475 layer_00149_model.62.bn_in errRate = 1.4187257289886475 layer_00149_model.62.bn_out errRate = 1.4075663089752197 layer_00150_model.62.act_in errRate = 1.4060556888580322 layer_00150_model.62.act_out errRate = 1.4060556888580322 layer_00151_model.63.conv_in errRate = 1.4060556888580322 layer_00151_model.63.conv_out errRate = 1.4011880159378052 layer_00152_model.63.bn_in errRate = 1.4011880159378052 layer_00152_model.63.bn_out errRate = 1.4166160821914673 layer_00153_model.63.act_in errRate = 1.4177194833755493 layer_00153_model.63.act_out errRate = 1.4177194833755493 layer_00154_model.64_in errRate = 1.4177194833755493 layer_00154_model.64_in errRate = 1.4060556888580322 layer_00154_model.64_in errRate = 1.4211763143539429 layer_00154_model.64_in errRate = 1.4109326601028442 layer_00154_model.64_out errRate = 1.4139716625213623 layer_00155_model.65.conv_in errRate = 1.4139716625213623 layer_00155_model.65.conv_out errRate = 1.4522044658660889 layer_00156_model.65.bn_in errRate = 1.4522044658660889 layer_00156_model.65.bn_out errRate = 1.415295958518982 layer_00157_model.65.act_in errRate = 1.4143067598342896 layer_00157_model.65.act_out errRate = 1.4143067598342896 layer_00158_model.66.conv_in errRate = 1.4143067598342896 layer_00158_model.66.conv_out errRate = 1.4230519533157349 layer_00159_model.66.bn_in errRate = 1.4230519533157349 layer_00159_model.66.bn_out errRate = 1.4092557430267334 layer_00160_model.66.act_in errRate = 1.4116967916488647 layer_00160_model.66.act_out errRate = 1.4116967916488647 layer_00161_model.67_in errRate = 1.4116967916488647 layer_00161_model.67_in errRate = 1.406844139099121 layer_00161_model.67_out errRate = 1.4092456102371216 layer_00162_model.68.conv_in errRate = 1.4092456102371216 layer_00162_model.68.conv_out errRate = 1.4020265340805054 layer_00163_model.68.bn_in errRate = 1.4020265340805054 layer_00163_model.68.bn_out errRate = 1.4079257249832153 layer_00164_model.68.act_in errRate = 1.4092594385147095 layer_00164_model.68.act_out errRate = 1.4092594385147095 layer_00165_model.69.conv_in errRate = 1.4092456102371216 layer_00165_model.69.conv_out errRate = 1.4160467386245728 layer_00166_model.69.bn_in errRate = 1.4160467386245728 layer_00166_model.69.bn_out errRate = 1.410789966583252 layer_00167_model.69.act_in errRate = 1.4120181798934937 layer_00167_model.69.act_out errRate = 1.4120181798934937 layer_00168_model.70.conv_in errRate = 1.4120181798934937 layer_00168_model.70.conv_out errRate = 1.4217222929000854 layer_00169_model.70.bn_in errRate = 1.4217222929000854 layer_00169_model.70.bn_out errRate = 1.412215232849121 layer_00170_model.70.act_in errRate = 1.4141204357147217 layer_00170_model.70.act_out errRate = 1.4141204357147217 layer_00171_model.71.conv_in errRate = 1.4141204357147217 layer_00171_model.71.conv_out errRate = 1.3682897090911865 layer_00172_model.71.bn_in errRate = 1.3682897090911865 layer_00172_model.71.bn_out errRate = 1.405030369758606 layer_00173_model.71.act_in errRate = 1.4005401134490967 layer_00173_model.71.act_out errRate = 1.4005401134490967 layer_00174_model.72_in errRate = 1.4005401134490967 layer_00174_model.72_in errRate = 1.4141204357147217 layer_00174_model.72_in errRate = 1.4120181798934937 layer_00174_model.72_in errRate = 1.4092594385147095 layer_00174_model.72_out errRate = 1.4089826345443726 layer_00175_model.73.conv_in errRate = 1.4089826345443726 layer_00175_model.73.conv_out errRate = 1.39961838722229 layer_00176_model.73.bn_in errRate = 1.39961838722229 layer_00176_model.73.bn_out errRate = 1.4107825756072998 layer_00177_model.73.act_in errRate = 1.4108781814575195 layer_00177_model.73.act_out errRate = 1.4108781814575195 layer_00178_model.74.conv_in errRate = 1.4300745725631714 layer_00178_model.74.conv_out errRate = 1.4364198446273804 layer_00179_model.74.bn_in errRate = 1.4364198446273804 layer_00179_model.74.bn_out errRate = 1.408728837966919 layer_00180_model.74.act_in errRate = 1.4113008975982666 layer_00180_model.74.act_out errRate = 1.4113008975982666 layer_00181_model.75.conv_in errRate = 1.4143067598342896 layer_00181_model.75.conv_out errRate = 1.3984497785568237 layer_00182_model.75.bn_in errRate = 1.3984497785568237 layer_00182_model.75.bn_out errRate = 1.415618658065796 layer_00183_model.75.act_in errRate = 1.4155097007751465 layer_00183_model.75.act_out errRate = 1.4155097007751465 layer_00184_model.76.conv_in errRate = 1.4108781814575195 layer_00184_model.76.conv_out errRate = 1.4083398580551147 layer_00185_model.76.bn_in errRate = 1.4083398580551147 layer_00185_model.76.bn_out errRate = 1.407083511352539 layer_00186_model.76.act_in errRate = 1.4069828987121582 layer_00186_model.76.act_out errRate = 1.4069828987121582 layer_00187_model.77.ia.0_in errRate = 1.4113008975982666 layer_00187_model.77.ia.0_out errRate = 1.4112012386322021 layer_00188_model.77.m.0_in errRate = 1.4112012386322021 layer_00188_model.77.m.0_out errRate = 0.2819249927997589 layer_00189_model.77.im.0_in errRate = 0.2819249927997589 layer_00189_model.77.im.0_out errRate = 1.611032247543335 layer_00190_model.77.ia.1_in errRate = 1.4155097007751465 layer_00190_model.77.ia.1_out errRate = 1.415618896484375 layer_00191_model.77.m.1_in errRate = 1.415618896484375 layer_00191_model.77.m.1_out errRate = 0.3017179071903229 layer_00192_model.77.im.1_in errRate = 0.3017179071903229 layer_00192_model.77.im.1_out errRate = 1.0699771642684937 layer_00193_model.77.ia.2_in errRate = 1.4069828987121582 layer_00193_model.77.ia.2_out errRate = 1.4068092107772827 layer_00194_model.77.m.2_in errRate = 1.4068092107772827 layer_00194_model.77.m.2_out errRate = 0.34356391429901123 layer_00195_model.77.im.2_in errRate = 0.34356391429901123 layer_00195_model.77.im.2_out errRate = 1.385164499282837 COS: layer_00000_model.0.conv_in Similarity = 0.9999998807907104 layer_00000_model.0.conv_out Similarity = 0.2605033218860626 layer_00001_model.0.bn_in Similarity = 0.2605033218860626 layer_00001_model.0.bn_out Similarity = 0.21186228096485138 layer_00002_model.0.act_in Similarity = 0.4047788679599762 layer_00002_model.0.act_out Similarity = 0.4047788679599762 layer_00003_model.1.conv_in Similarity = 0.4047788679599762 layer_00003_model.1.conv_out Similarity = 0.02334202267229557 layer_00004_model.1.bn_in Similarity = 0.02334202267229557 layer_00004_model.1.bn_out Similarity = -0.021144675090909004 layer_00005_model.1.act_in Similarity = 0.2573935091495514 layer_00005_model.1.act_out Similarity = 0.2573935091495514 layer_00006_model.2.conv_in Similarity = 0.2573935091495514 layer_00006_model.2.conv_out Similarity = 0.03220166265964508 layer_00007_model.2.bn_in Similarity = 0.03220166265964508 layer_00007_model.2.bn_out Similarity = 0.05501933768391609 layer_00008_model.2.act_in Similarity = 0.29960617423057556 layer_00008_model.2.act_out Similarity = 0.29960617423057556 layer_00009_model.3.conv_in Similarity = 0.2573935091495514 layer_00009_model.3.conv_out Similarity = 0.0888131782412529 layer_00010_model.3.bn_in Similarity = 0.0888131782412529 layer_00010_model.3.bn_out Similarity = 0.11718618124723434 layer_00011_model.3.act_in Similarity = 0.3456920087337494 layer_00011_model.3.act_out Similarity = 0.3456920087337494 layer_00012_model.4.conv_in Similarity = 0.3456920087337494 layer_00012_model.4.conv_out Similarity = 0.00116734451148659 layer_00013_model.4.bn_in Similarity = 0.00116734451148659 layer_00013_model.4.bn_out Similarity = -0.054800502955913544 layer_00014_model.4.act_in Similarity = 0.22066248953342438 layer_00014_model.4.act_out Similarity = 0.22066248953342438 layer_00015_model.5.conv_in Similarity = 0.22066248953342438 layer_00015_model.5.conv_out Similarity = 0.007922030054032803 layer_00016_model.5.bn_in Similarity = 0.007922030054032803 layer_00016_model.5.bn_out Similarity = 0.042094990611076355 layer_00017_model.5.act_in Similarity = 0.2802388072013855 layer_00017_model.5.act_out Similarity = 0.2802388072013855 layer_00018_model.6_in Similarity = 0.2802388072013855 layer_00018_model.6_in Similarity = 0.22066248953342438 layer_00018_model.6_in Similarity = 0.3456920087337494 layer_00018_model.6_in Similarity = 0.29960617423057556 layer_00018_model.6_out Similarity = 0.2866845726966858 layer_00019_model.7.conv_in Similarity = 0.2866845726966858 layer_00019_model.7.conv_out Similarity = 0.022339338436722755 layer_00020_model.7.bn_in Similarity = 0.022339338436722755 layer_00020_model.7.bn_out Similarity = 0.01945759728550911 layer_00021_model.7.act_in Similarity = 0.2698645293712616 layer_00021_model.7.act_out Similarity = 0.2698645293712616 layer_00022_model.8.m_in Similarity = 0.2698645293712616 layer_00022_model.8.m_out Similarity = 0.6046857833862305 layer_00023_model.9.conv_in Similarity = 0.6046857833862305 layer_00023_model.9.conv_out Similarity = 0.049869682639837265 layer_00024_model.9.bn_in Similarity = 0.049869682639837265 layer_00024_model.9.bn_out Similarity = 0.0482272133231163 layer_00025_model.9.act_in Similarity = 0.2991865873336792 layer_00025_model.9.act_out Similarity = 0.2991865873336792 layer_00026_model.10.conv_in Similarity = 0.6046857833862305 layer_00026_model.10.conv_out Similarity = 0.003820116864517331 layer_00027_model.10.bn_in Similarity = 0.003820116864517331 layer_00027_model.10.bn_out Similarity = -0.022506479173898697 layer_00028_model.10.act_in Similarity = 0.255826473236084 layer_00028_model.10.act_out Similarity = 0.255826473236084 layer_00029_model.11.conv_in Similarity = 0.255826473236084 layer_00029_model.11.conv_out Similarity = -0.014733172953128815 layer_00030_model.11.bn_in Similarity = -0.014733172953128815 layer_00030_model.11.bn_out Similarity = -0.03146708756685257 layer_00031_model.11.act_in Similarity = 0.2374107837677002 layer_00031_model.11.act_out Similarity = 0.2374107837677002 layer_00032_model.12.conv_in Similarity = 0.2374107837677002 layer_00032_model.12.conv_out Similarity = -0.00040947619709186256 layer_00033_model.12.bn_in Similarity = -0.00040947619709186256 layer_00033_model.12.bn_out Similarity = 0.01045964565128088 layer_00034_model.12.act_in Similarity = 0.2582939565181732 layer_00034_model.12.act_out Similarity = 0.2582939565181732 layer_00035_model.13_in Similarity = 0.2582939565181732 layer_00035_model.13_in Similarity = 0.2374107837677002 layer_00035_model.13_in Similarity = 0.255826473236084 layer_00035_model.13_in Similarity = 0.2991865873336792 layer_00035_model.13_out Similarity = 0.26272866129875183 layer_00036_model.14.conv_in Similarity = 0.26272866129875183 layer_00036_model.14.conv_out Similarity = -0.03386233374476433 layer_00037_model.14.bn_in Similarity = -0.03386233374476433 layer_00037_model.14.bn_out Similarity = -0.0032486303243786097 layer_00038_model.14.act_in Similarity = 0.2512577176094055 layer_00038_model.14.act_out Similarity = 0.2512577176094055 layer_00039_model.15.m_in Similarity = 0.2512577176094055 layer_00039_model.15.m_out Similarity = 0.5997035503387451 layer_00040_model.16.conv_in Similarity = 0.5997035503387451 layer_00040_model.16.conv_out Similarity = -0.06495241820812225 layer_00041_model.16.bn_in Similarity = -0.06495241820812225 layer_00041_model.16.bn_out Similarity = -0.01690603606402874 layer_00042_model.16.act_in Similarity = 0.25901591777801514 layer_00042_model.16.act_out Similarity = 0.25901591777801514 layer_00043_model.17.conv_in Similarity = 0.5997035503387451 layer_00043_model.17.conv_out Similarity = -0.013585775159299374 layer_00044_model.17.bn_in Similarity = -0.013585775159299374 layer_00044_model.17.bn_out Similarity = 0.030082743614912033 layer_00045_model.17.act_in Similarity = 0.28661033511161804 layer_00045_model.17.act_out Similarity = 0.28661033511161804 layer_00046_model.18.conv_in Similarity = 0.28661033511161804 layer_00046_model.18.conv_out Similarity = -0.03171597421169281 layer_00047_model.18.bn_in Similarity = -0.03171597421169281 layer_00047_model.18.bn_out Similarity = -0.013840069994330406 layer_00048_model.18.act_in Similarity = 0.25067847967147827 layer_00048_model.18.act_out Similarity = 0.25067847967147827 layer_00049_model.19.conv_in Similarity = 0.25067847967147827 layer_00049_model.19.conv_out Similarity = -0.03029482066631317 layer_00050_model.19.bn_in Similarity = -0.03029482066631317 layer_00050_model.19.bn_out Similarity = 0.008003306575119495 layer_00051_model.19.act_in Similarity = 0.2573188245296478 layer_00051_model.19.act_out Similarity = 0.2573188245296478 layer_00052_model.20_in Similarity = 0.2573188245296478 layer_00052_model.20_in Similarity = 0.25067847967147827 layer_00052_model.20_in Similarity = 0.28661033511161804 layer_00052_model.20_in Similarity = 0.25901591777801514 layer_00052_model.20_out Similarity = 0.2635844945907593 layer_00053_model.21.conv_in Similarity = 0.2635844945907593 layer_00053_model.21.conv_out Similarity = -0.0011704355711117387 layer_00054_model.21.bn_in Similarity = -0.0011704355711117387 layer_00054_model.21.bn_out Similarity = 0.0030668950639665127 layer_00055_model.21.act_in Similarity = 0.25417056679725647 layer_00055_model.21.act_out Similarity = 0.25417056679725647 layer_00056_model.22.m_in Similarity = 0.25417056679725647 layer_00056_model.22.m_out Similarity = 0.6241138577461243 layer_00057_model.23.conv_in Similarity = 0.6241138577461243 layer_00057_model.23.conv_out Similarity = -0.06457629799842834 layer_00058_model.23.bn_in Similarity = -0.06457629799842834 layer_00058_model.23.bn_out Similarity = -0.017536630854010582 layer_00059_model.23.act_in Similarity = 0.24891184270381927 layer_00059_model.23.act_out Similarity = 0.24891184270381927 layer_00060_model.24.conv_in Similarity = 0.6241138577461243 layer_00060_model.24.conv_out Similarity = 0.05847809836268425 layer_00061_model.24.bn_in Similarity = 0.05847809836268425 layer_00061_model.24.bn_out Similarity = 0.015672072768211365 layer_00062_model.24.act_in Similarity = 0.2760127782821655 layer_00062_model.24.act_out Similarity = 0.2760127782821655 layer_00063_model.25.conv_in Similarity = 0.2760127782821655 layer_00063_model.25.conv_out Similarity = -0.008677752688527107 layer_00064_model.25.bn_in Similarity = -0.008677752688527107 layer_00064_model.25.bn_out Similarity = -0.012275908142328262 layer_00065_model.25.act_in Similarity = 0.2517410218715668 layer_00065_model.25.act_out Similarity = 0.2517410218715668 layer_00066_model.26.conv_in Similarity = 0.2517410218715668 layer_00066_model.26.conv_out Similarity = 0.0010906928218901157 layer_00067_model.26.bn_in Similarity = 0.0010906928218901157 layer_00067_model.26.bn_out Similarity = 0.00012926378985866904 layer_00068_model.26.act_in Similarity = 0.2559278905391693 layer_00068_model.26.act_out Similarity = 0.2559278905391693 layer_00069_model.27_in Similarity = 0.2559278905391693 layer_00069_model.27_in Similarity = 0.2517410218715668 layer_00069_model.27_in Similarity = 0.2760127782821655 layer_00069_model.27_in Similarity = 0.24891184270381927 layer_00069_model.27_out Similarity = 0.258150577545166 layer_00070_model.28.conv_in Similarity = 0.258150577545166 layer_00070_model.28.conv_out Similarity = -0.010213404893875122 layer_00071_model.28.bn_in Similarity = -0.010213404893875122 layer_00071_model.28.bn_out Similarity = -0.0028073107823729515 layer_00072_model.28.act_in Similarity = 0.2542288899421692 layer_00072_model.28.act_out Similarity = 0.2542288899421692 layer_00073_model.29.conv_in Similarity = 0.2542288899421692 layer_00073_model.29.conv_out Similarity = 0.011775562539696693 layer_00074_model.29.bn_in Similarity = 0.011775562539696693 layer_00074_model.29.bn_out Similarity = 0.00958949699997902 layer_00075_model.29.act_in Similarity = 0.25722602009773254 layer_00075_model.29.act_out Similarity = 0.25722602009773254 layer_00076_model.30.conv_in Similarity = 0.2542288899421692 layer_00076_model.30.conv_out Similarity = 8.947444439399987e-05 layer_00077_model.30.bn_in Similarity = 8.947444439399987e-05 layer_00077_model.30.bn_out Similarity = 0.0019076953176409006 layer_00078_model.30.act_in Similarity = 0.25228261947631836 layer_00078_model.30.act_out Similarity = 0.25228261947631836 layer_00079_model.31.m_in Similarity = 0.25228261947631836 layer_00079_model.31.m_out Similarity = 0.8929471969604492 layer_00080_model.32.m_in Similarity = 0.25228261947631836 layer_00080_model.32.m_out Similarity = 0.9386432766914368 layer_00081_model.33.m_in Similarity = 0.25228261947631836 layer_00081_model.33.m_out Similarity = 0.9505641460418701 layer_00082_model.34_in Similarity = 0.9505641460418701 layer_00082_model.34_in Similarity = 0.9386432766914368 layer_00082_model.34_in Similarity = 0.8929471969604492 layer_00082_model.34_in Similarity = 0.25228261947631836 layer_00082_model.34_out Similarity = 0.9141823649406433 layer_00083_model.35.conv_in Similarity = 0.9141823649406433 layer_00083_model.35.conv_out Similarity = 0.010603783652186394 layer_00084_model.35.bn_in Similarity = 0.010603783652186394 layer_00084_model.35.bn_out Similarity = -0.021690528839826584 layer_00085_model.35.act_in Similarity = 0.2552984952926636 layer_00085_model.35.act_out Similarity = 0.2552984952926636 layer_00086_model.36_in Similarity = 0.2552984952926636 layer_00086_model.36_in Similarity = 0.25722602009773254 layer_00086_model.36_out Similarity = 0.2562589943408966 layer_00087_model.37.conv_in Similarity = 0.2562589943408966 layer_00087_model.37.conv_out Similarity = 0.017505500465631485 layer_00088_model.37.bn_in Similarity = 0.017505500465631485 layer_00088_model.37.bn_out Similarity = 0.0006932570831850171 layer_00089_model.37.act_in Similarity = 0.2613305151462555 layer_00089_model.37.act_out Similarity = 0.2613305151462555 layer_00090_model.38.conv_in Similarity = 0.2613305151462555 layer_00090_model.38.conv_out Similarity = 0.005980407353490591 layer_00091_model.38.bn_in Similarity = 0.005980407353490591 layer_00091_model.38.bn_out Similarity = -0.00959364976733923 layer_00092_model.38.act_in Similarity = 0.2540968656539917 layer_00092_model.38.act_out Similarity = 0.2540968656539917 layer_00093_model.39_in Similarity = 0.2540968656539917 layer_00093_model.39_out Similarity = 0.2540968954563141 layer_00094_model.40.conv_in Similarity = 0.25417056679725647 layer_00094_model.40.conv_out Similarity = -0.009543882682919502 layer_00095_model.40.bn_in Similarity = -0.009543882682919502 layer_00095_model.40.bn_out Similarity = 0.008532592095434666 layer_00096_model.40.act_in Similarity = 0.2569575011730194 layer_00096_model.40.act_out Similarity = 0.2569575011730194 layer_00097_model.41_in Similarity = 0.2569575011730194 layer_00097_model.41_in Similarity = 0.2540968954563141 layer_00097_model.41_out Similarity = 0.25552356243133545 layer_00098_model.42.conv_in Similarity = 0.25552356243133545 layer_00098_model.42.conv_out Similarity = 0.019564073532819748 layer_00099_model.42.bn_in Similarity = 0.019564073532819748 layer_00099_model.42.bn_out Similarity = 0.004426488187164068 layer_00100_model.42.act_in Similarity = 0.25775212049484253 layer_00100_model.42.act_out Similarity = 0.25775212049484253 layer_00101_model.43.conv_in Similarity = 0.25552356243133545 layer_00101_model.43.conv_out Similarity = -0.03360985964536667 layer_00102_model.43.bn_in Similarity = -0.03360985964536667 layer_00102_model.43.bn_out Similarity = -0.008071293123066425 layer_00103_model.43.act_in Similarity = 0.24969090521335602 layer_00103_model.43.act_out Similarity = 0.24969090521335602 layer_00104_model.44.conv_in Similarity = 0.24969090521335602 layer_00104_model.44.conv_out Similarity = 0.015503841452300549 layer_00105_model.44.bn_in Similarity = 0.015503841452300549 layer_00105_model.44.bn_out Similarity = -0.005335462279617786 layer_00106_model.44.act_in Similarity = 0.2472379058599472 layer_00106_model.44.act_out Similarity = 0.2472379058599472 layer_00107_model.45.conv_in Similarity = 0.2472379058599472 layer_00107_model.45.conv_out Similarity = 0.0147425951436162 layer_00108_model.45.bn_in Similarity = 0.0147425951436162 layer_00108_model.45.bn_out Similarity = 0.003876713803038001 layer_00109_model.45.act_in Similarity = 0.2537548542022705 layer_00109_model.45.act_out Similarity = 0.2537548542022705 layer_00110_model.46_in Similarity = 0.2537548542022705 layer_00110_model.46_in Similarity = 0.2472379058599472 layer_00110_model.46_in Similarity = 0.24969090521335602 layer_00110_model.46_in Similarity = 0.25775212049484253 layer_00110_model.46_out Similarity = 0.2521106004714966 layer_00111_model.47.conv_in Similarity = 0.2521106004714966 layer_00111_model.47.conv_out Similarity = 0.04265005141496658 layer_00112_model.47.bn_in Similarity = 0.04265005141496658 layer_00112_model.47.bn_out Similarity = 0.009689072147011757 layer_00113_model.47.act_in Similarity = 0.25926879048347473 layer_00113_model.47.act_out Similarity = 0.25926879048347473 layer_00114_model.48.conv_in Similarity = 0.25926879048347473 layer_00114_model.48.conv_out Similarity = -0.03695233166217804 layer_00115_model.48.bn_in Similarity = -0.03695233166217804 layer_00115_model.48.bn_out Similarity = -0.011527457274496555 layer_00116_model.48.act_in Similarity = 0.24735775589942932 layer_00116_model.48.act_out Similarity = 0.24735775589942932 layer_00117_model.49_in Similarity = 0.24735775589942932 layer_00117_model.49_out Similarity = 0.2473578304052353 layer_00118_model.50.conv_in Similarity = 0.2512577176094055 layer_00118_model.50.conv_out Similarity = 0.02007986605167389 layer_00119_model.50.bn_in Similarity = 0.02007986605167389 layer_00119_model.50.bn_out Similarity = 0.022236064076423645 layer_00120_model.50.act_in Similarity = 0.26905229687690735 layer_00120_model.50.act_out Similarity = 0.26905229687690735 layer_00121_model.51_in Similarity = 0.26905229687690735 layer_00121_model.51_in Similarity = 0.2473578304052353 layer_00121_model.51_out Similarity = 0.2581822872161865 layer_00122_model.52.conv_in Similarity = 0.2581822872161865 layer_00122_model.52.conv_out Similarity = 0.07057759910821915 layer_00123_model.52.bn_in Similarity = 0.07057759910821915 layer_00123_model.52.bn_out Similarity = 0.010803554207086563 layer_00124_model.52.act_in Similarity = 0.25957879424095154 layer_00124_model.52.act_out Similarity = 0.25957879424095154 layer_00125_model.53.conv_in Similarity = 0.2581822872161865 layer_00125_model.53.conv_out Similarity = -0.05250699445605278 layer_00126_model.53.bn_in Similarity = -0.05250699445605278 layer_00126_model.53.bn_out Similarity = 0.0037225177511572838 layer_00127_model.53.act_in Similarity = 0.2541294991970062 layer_00127_model.53.act_out Similarity = 0.2541294991970062 layer_00128_model.54.conv_in Similarity = 0.2541294991970062 layer_00128_model.54.conv_out Similarity = 0.00019630549650173634 layer_00129_model.54.bn_in Similarity = 0.00019630549650173634 layer_00129_model.54.bn_out Similarity = -0.013494321145117283 layer_00130_model.54.act_in Similarity = 0.24567347764968872 layer_00130_model.54.act_out Similarity = 0.24567347764968872 layer_00131_model.55.conv_in Similarity = 0.24567347764968872 layer_00131_model.55.conv_out Similarity = 0.026082783937454224 layer_00132_model.55.bn_in Similarity = 0.026082783937454224 layer_00132_model.55.bn_out Similarity = 0.019403256475925446 layer_00133_model.55.act_in Similarity = 0.259259432554245 layer_00133_model.55.act_out Similarity = 0.259259432554245 layer_00134_model.56_in Similarity = 0.259259432554245 layer_00134_model.56_in Similarity = 0.24567347764968872 layer_00134_model.56_in Similarity = 0.2541294991970062 layer_00134_model.56_in Similarity = 0.25957879424095154 layer_00134_model.56_out Similarity = 0.2546803057193756 layer_00135_model.57.conv_in Similarity = 0.2546803057193756 layer_00135_model.57.conv_out Similarity = -0.05976806953549385 layer_00136_model.57.bn_in Similarity = -0.05976806953549385 layer_00136_model.57.bn_out Similarity = -0.02093471772968769 layer_00137_model.57.act_in Similarity = 0.2409810572862625 layer_00137_model.57.act_out Similarity = 0.2409810572862625 layer_00138_model.58.conv_in Similarity = 0.2409810572862625 layer_00138_model.58.conv_out Similarity = -0.014420874416828156 layer_00139_model.58.bn_in Similarity = -0.014420874416828156 layer_00139_model.58.bn_out Similarity = 0.010077406652271748 layer_00140_model.58.act_in Similarity = 0.2591383159160614 layer_00140_model.58.act_out Similarity = 0.2591383159160614 layer_00141_model.59_in Similarity = 0.2591383159160614 layer_00141_model.59_in Similarity = 0.25926879048347473 layer_00141_model.59_out Similarity = 0.2592029869556427 layer_00142_model.60.conv_in Similarity = 0.2592029869556427 layer_00142_model.60.conv_out Similarity = 0.009951605461537838 layer_00143_model.60.bn_in Similarity = 0.009951605461537838 layer_00143_model.60.bn_out Similarity = 0.002501503797248006 layer_00144_model.60.act_in Similarity = 0.2519686222076416 layer_00144_model.60.act_out Similarity = 0.2519686222076416 layer_00145_model.61.conv_in Similarity = 0.2592029869556427 layer_00145_model.61.conv_out Similarity = -0.032714277505874634 layer_00146_model.61.bn_in Similarity = -0.032714277505874634 layer_00146_model.61.bn_out Similarity = -0.0045561050064861774 layer_00147_model.61.act_in Similarity = 0.254146546125412 layer_00147_model.61.act_out Similarity = 0.254146546125412 layer_00148_model.62.conv_in Similarity = 0.254146546125412 layer_00148_model.62.conv_out Similarity = 0.028777385130524635 layer_00149_model.62.bn_in Similarity = 0.028777385130524635 layer_00149_model.62.bn_out Similarity = 0.008214669302105904 layer_00150_model.62.act_in Similarity = 0.2620335817337036 layer_00150_model.62.act_out Similarity = 0.2620335817337036 layer_00151_model.63.conv_in Similarity = 0.2620335817337036 layer_00151_model.63.conv_out Similarity = 0.016959963366389275 layer_00152_model.63.bn_in Similarity = 0.016959963366389275 layer_00152_model.63.bn_out Similarity = -0.007765155751258135 layer_00153_model.63.act_in Similarity = 0.25075778365135193 layer_00153_model.63.act_out Similarity = 0.25075778365135193 layer_00154_model.64_in Similarity = 0.25075778365135193 layer_00154_model.64_in Similarity = 0.2620335817337036 layer_00154_model.64_in Similarity = 0.254146546125412 layer_00154_model.64_in Similarity = 0.2519686222076416 layer_00154_model.64_out Similarity = 0.2547321319580078 layer_00155_model.65.conv_in Similarity = 0.2547321319580078 layer_00155_model.65.conv_out Similarity = -0.015279472805559635 layer_00156_model.65.bn_in Similarity = -0.015279472805559635 layer_00156_model.65.bn_out Similarity = -0.0001407241215929389 layer_00157_model.65.act_in Similarity = 0.2558472752571106 layer_00157_model.65.act_out Similarity = 0.2558472752571106 layer_00158_model.66.conv_in Similarity = 0.2558472752571106 layer_00158_model.66.conv_out Similarity = -0.002424970269203186 layer_00159_model.66.bn_in Similarity = -0.002424970269203186 layer_00159_model.66.bn_out Similarity = 0.006989762652665377 layer_00160_model.66.act_in Similarity = 0.2561931908130646 layer_00160_model.66.act_out Similarity = 0.2561931908130646 layer_00161_model.67_in Similarity = 0.2561931908130646 layer_00161_model.67_in Similarity = 0.2613305151462555 layer_00161_model.67_out Similarity = 0.2587675154209137 layer_00162_model.68.conv_in Similarity = 0.2587675154209137 layer_00162_model.68.conv_out Similarity = -0.0196846891194582 layer_00163_model.68.bn_in Similarity = -0.0196846891194582 layer_00163_model.68.bn_out Similarity = 0.005883821751922369 layer_00164_model.68.act_in Similarity = 0.2579226791858673 layer_00164_model.68.act_out Similarity = 0.2579226791858673 layer_00165_model.69.conv_in Similarity = 0.2587675154209137 layer_00165_model.69.conv_out Similarity = -0.021257326006889343 layer_00166_model.69.bn_in Similarity = -0.021257326006889343 layer_00166_model.69.bn_out Similarity = 0.0010725905885919929 layer_00167_model.69.act_in Similarity = 0.25537392497062683 layer_00167_model.69.act_out Similarity = 0.25537392497062683 layer_00168_model.70.conv_in Similarity = 0.25537392497062683 layer_00168_model.70.conv_out Similarity = -0.03700775280594826 layer_00169_model.70.bn_in Similarity = -0.03700775280594826 layer_00169_model.70.bn_out Similarity = 0.0005099025438539684 layer_00170_model.70.act_in Similarity = 0.25358274579048157 layer_00170_model.70.act_out Similarity = 0.25358274579048157 layer_00171_model.71.conv_in Similarity = 0.25358274579048157 layer_00171_model.71.conv_out Similarity = 0.03099515102803707 layer_00172_model.71.bn_in Similarity = 0.03099515102803707 layer_00172_model.71.bn_out Similarity = 0.013050160370767117 layer_00173_model.71.act_in Similarity = 0.2667635679244995 layer_00173_model.71.act_out Similarity = 0.2667635679244995 layer_00174_model.72_in Similarity = 0.2667635679244995 layer_00174_model.72_in Similarity = 0.25358274579048157 layer_00174_model.72_in Similarity = 0.25537392497062683 layer_00174_model.72_in Similarity = 0.2579226791858673 layer_00174_model.72_out Similarity = 0.25839096307754517 layer_00175_model.73.conv_in Similarity = 0.25839096307754517 layer_00175_model.73.conv_out Similarity = -0.009811034426093102 layer_00176_model.73.bn_in Similarity = -0.009811034426093102 layer_00176_model.73.bn_out Similarity = 0.003534147748723626 layer_00177_model.73.act_in Similarity = 0.25942257046699524 layer_00177_model.73.act_out Similarity = 0.25942257046699524 layer_00178_model.74.conv_in Similarity = 0.2409810572862625 layer_00178_model.74.conv_out Similarity = -2.4913548259064555e-05 layer_00179_model.74.bn_in Similarity = -2.4913548259064555e-05 layer_00179_model.74.bn_out Similarity = 0.003444998525083065 layer_00180_model.74.act_in Similarity = 0.2553435266017914 layer_00180_model.74.act_out Similarity = 0.2553435266017914 layer_00181_model.75.conv_in Similarity = 0.2558472752571106 layer_00181_model.75.conv_out Similarity = -0.006735384464263916 layer_00182_model.75.bn_in Similarity = -0.006735384464263916 layer_00182_model.75.bn_out Similarity = -0.00506032258272171 layer_00183_model.75.act_in Similarity = 0.2504546642303467 layer_00183_model.75.act_out Similarity = 0.2504546642303467 layer_00184_model.76.conv_in Similarity = 0.25942257046699524 layer_00184_model.76.conv_out Similarity = 0.011769432574510574 layer_00185_model.76.bn_in Similarity = 0.011769432574510574 layer_00185_model.76.bn_out Similarity = 0.006071590818464756 layer_00186_model.76.act_in Similarity = 0.260139137506485 layer_00186_model.76.act_out Similarity = 0.260139137506485 layer_00187_model.77.ia.0_in Similarity = 0.2553435266017914 layer_00187_model.77.ia.0_out Similarity = 0.2547018527984619 layer_00188_model.77.m.0_in Similarity = 0.2547018527984619 layer_00188_model.77.m.0_out Similarity = 0.9730231165885925 layer_00189_model.77.im.0_in Similarity = 0.9730231165885925 layer_00189_model.77.im.0_out Similarity = 0.02467404492199421 layer_00190_model.77.ia.1_in Similarity = 0.2504546642303467 layer_00190_model.77.ia.1_out Similarity = 0.24894513189792633 layer_00191_model.77.m.1_in Similarity = 0.24894513189792633 layer_00191_model.77.m.1_out Similarity = 0.9633361101150513 layer_00192_model.77.im.1_in Similarity = 0.9633361101150513 layer_00192_model.77.im.1_out Similarity = 0.572359561920166 layer_00193_model.77.ia.2_in Similarity = 0.260139137506485 layer_00193_model.77.ia.2_out Similarity = 0.26007696986198425 layer_00194_model.77.m.2_in Similarity = 0.26007696986198425 layer_00194_model.77.m.2_out Similarity = 0.9482917785644531 layer_00195_model.77.im.2_in Similarity = 0.9482917785644531 layer_00195_model.77.im.2_out Similarity = 0.4365496039390564