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sample_output_cfd_adv_diff.txt
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sample_output_cfd_adv_diff.txt
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/usr/bin/python3 /home/arthur/Documents/Projects/PDE-Net-In-TensorFlow/module/main.py
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
* https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
* https://github.com/tensorflow/addons
If you depend on functionality not listed there, please file an issue.
2019-04-05 13:24:00.320777: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3399670000 Hz
2019-04-05 13:24:00.321823: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x5588df0 executing computations on platform Host. Devices:
2019-04-05 13:24:00.321839: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): <undefined>, <undefined>
2019-04-05 13:24:00.419550: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-04-05 13:24:00.420118: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x4e26ae0 executing computations on platform CUDA. Devices:
2019-04-05 13:24:00.420133: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): GeForce RTX 2060, Compute Capability 7.5
2019-04-05 13:24:00.420409: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 0 with properties:
name: GeForce RTX 2060 major: 7 minor: 5 memoryClockRate(GHz): 1.755
pciBusID: 0000:01:00.0
totalMemory: 5.76GiB freeMemory: 5.35GiB
2019-04-05 13:24:00.420419: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0
2019-04-05 13:24:00.992834: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-04-05 13:24:00.992862: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 0
2019-04-05 13:24:00.992868: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0: N
2019-04-05 13:24:00.993138: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4131 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2060, pci bus id: 0000:01:00.0, compute capability: 7.5)
Loss: 5.025586e+03
Loss: 6.718286e+02
Loss: 3.100502e+02
Loss: 2.479233e+02
Loss: 1.257969e+02
Loss: 6.217235e+01
Loss: 4.302345e+00
Loss: 3.742739e+00
Loss: 1.304996e+00
Loss: 8.577622e-01
Loss: 2.571510e-01
Loss: 2.236768e-01
Loss: 2.148204e-01
Loss: 1.966915e-01
Loss: 1.579984e-01
Loss: 9.149755e-02
Loss: 2.463449e-02
Loss: 3.166592e-03
Loss: 4.256686e-04
Loss: 3.226926e-04
Loss: 3.211442e-04
Loss: 3.211121e-04
Loss: 3.211110e-04
Loss: 3.211091e-04
Loss: 3.211091e-04
Loss: 3.211091e-04
Loss: 3.211100e-04
Loss: 3.211091e-04
Loss: 3.211091e-04
Loss: 3.211091e-04
Loss: 3.211091e-04
Loss: 3.211091e-04
Loss: 3.211091e-04
Loss: 3.211091e-04
===========================
Loss: 1.444998e+03
Loss: 5.944987e+02
Loss: 2.093873e+02
Loss: 1.845082e+02
Loss: 1.444902e+02
Loss: 6.536826e+01
Loss: 1.015620e+01
Loss: 3.925701e+00
Loss: 1.630718e+00
Loss: 1.476480e+00
Loss: 1.434361e+00
Loss: 1.360176e+00
Loss: 1.272425e+00
Loss: 1.096097e+00
Loss: 7.816406e-01
Loss: 3.699096e-01
Loss: 7.536807e-02
Loss: 7.961652e-03
Loss: 3.482641e-04
Loss: 3.217662e-04
Loss: 3.211113e-04
Loss: 3.211095e-04
Loss: 3.211081e-04
Loss: 3.211086e-04
Loss: 3.211081e-04
Loss: 3.211081e-04
Loss: 3.211081e-04
Loss: 3.211081e-04
Loss: 3.211081e-04
Loss: 3.211081e-04
Loss: 3.211081e-04
Loss: 3.211081e-04
Loss: 3.211081e-04
Loss: 3.211081e-04
===========================
Loss: 1.362005e+04
Loss: 5.347644e+03
Loss: 2.126391e+03
Loss: 1.938038e+03
Loss: 5.400456e+02
Loss: 1.397336e+02
Loss: 3.560000e+01
Loss: 2.467817e+01
Loss: 1.140697e+01
Loss: 2.744261e+00
Loss: 2.294787e+00
Loss: 2.274929e+00
Loss: 2.253209e+00
Loss: 2.183216e+00
Loss: 2.016237e+00
Loss: 1.640869e+00
Loss: 9.966916e-01
Loss: 3.142670e-01
Loss: 6.268331e-02
Loss: 5.858601e-03
Loss: 3.350321e-04
Loss: 3.213675e-04
Loss: 3.211084e-04
Loss: 3.211089e-04
Loss: 3.211081e-04
Loss: 3.211081e-04
Loss: 3.211070e-04
Loss: 3.211109e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
Loss: 3.211070e-04
===========================
Loss: 1.005486e+03
Loss: 7.999449e+02
Loss: 3.782520e+02
Loss: 3.239841e+02
Loss: 2.599867e+02
Loss: 1.311923e+02
Loss: 2.395726e+01
Loss: 5.083235e+00
Loss: 2.976623e+00
Loss: 1.740903e+00
Loss: 6.863706e-01
Loss: 4.950765e-01
Loss: 4.828555e-01
Loss: 4.772279e-01
Loss: 4.678280e-01
Loss: 4.315174e-01
Loss: 3.592731e-01
Loss: 2.234494e-01
Loss: 7.570814e-02
Loss: 1.017757e-02
Loss: 7.903129e-04
Loss: 3.263800e-04
Loss: 3.211767e-04
Loss: 3.214596e-04
Loss: 3.211158e-04
Loss: 3.211080e-04
Loss: 3.211085e-04
Loss: 3.211080e-04
Loss: 3.211080e-04
Loss: 3.211080e-04
Loss: 3.211080e-04
Loss: 3.211080e-04
Loss: 3.211080e-04
Loss: 3.211080e-04
Loss: 3.211080e-04
Loss: 3.211080e-04
Loss: 3.211080e-04
Loss: 3.211080e-04
Loss: 3.211080e-04
Loss: 3.211080e-04
Loss: 3.211080e-04
Loss: 3.211080e-04
===========================
Loss: 1.328107e+04
Loss: 4.272791e+03
Loss: 3.246496e+02
Loss: 2.476223e+02
Loss: 9.594195e+01
Loss: 6.163586e+01
Loss: 6.226107e+00
Loss: 4.376597e+00
Loss: 3.211712e+00
Loss: 3.106237e+00
Loss: 3.008575e+00
Loss: 2.886175e+00
Loss: 2.403130e+00
Loss: 1.629516e+00
Loss: 5.933287e-01
Loss: 2.314843e-01
Loss: 1.915863e-02
Loss: 9.970971e-04
Loss: 3.268659e-04
Loss: 3.211232e-04
Loss: 3.211098e-04
Loss: 3.211088e-04
Loss: 3.211084e-04
Loss: 3.211095e-04
Loss: 3.211084e-04
Loss: 3.211084e-04
Loss: 3.211078e-04
Loss: 3.211078e-04
Loss: 3.211078e-04
Loss: 3.211074e-04
Loss: 3.211074e-04
Loss: 3.211074e-04
Loss: 3.211073e-04
Loss: 3.211073e-04
Loss: 3.211073e-04
Loss: 3.211094e-04
Loss: 3.211073e-04
Loss: 3.211085e-04
Loss: 3.211073e-04
Loss: 3.211073e-04
Loss: 3.211073e-04
Loss: 3.211073e-04
Loss: 3.211073e-04
Loss: 3.211073e-04
Loss: 3.211073e-04
Loss: 3.211073e-04
Loss: 3.211073e-04
Loss: 3.211073e-04
===========================
End of warmup
The coefficients are:
-0.00273260
1.98965955
1.98871613
0.52059609
0.00002195
0.52039540
The moment matrices are:
[[1. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]]
[[0. 0. 0. 0. 0. 0. 0.]
[1. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]]
[[0. 1. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]]
[[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[1. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]]
[[0. 0. 0. 0. 0. 0. 0.]
[0. 1. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]]
[[0. 0. 1. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]]
[[1. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]
[0. 0. 0. 0. 0. 0. 0.]]
----------------------------------------------
2019-04-05 13:24:04.204297: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0
2019-04-05 13:24:04.204332: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-04-05 13:24:04.204337: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 0
2019-04-05 13:24:04.204342: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0: N
2019-04-05 13:24:04.204487: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4131 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2060, pci bus id: 0000:01:00.0, compute capability: 7.5)
2019-04-05 13:24:04.785764: I tensorflow/stream_executor/dso_loader.cc:152] successfully opened CUDA library libcublas.so.10.0 locally
Loss: 3.208547e-04
Loss: 1.223098e+03
Loss: 2.706502e-04
Loss: 1.941455e-04
Loss: 9.135025e-05
Loss: 7.958633e-05
Loss: 6.843010e-05
Loss: 6.719031e-05
Loss: 6.310290e-05
Loss: 4.818012e-05
Loss: 3.456410e-05
Loss: 5.506576e-05
Loss: 3.127523e-05
Loss: 2.412808e-05
Loss: 1.898115e-05
Loss: 1.610519e-05
Loss: 1.482716e-05
Loss: 1.461510e-05
Loss: 1.435398e-05
Loss: 1.425054e-05
Loss: 1.359562e-05
Loss: 1.254703e-05
Loss: 1.156443e-05
Loss: 1.150142e-05
Loss: 1.129649e-05
Loss: 1.142433e-05
Loss: 1.129297e-05
Loss: 1.142302e-05
Loss: 1.129150e-05
Loss: 1.128869e-05
Loss: 1.145233e-05
Loss: 1.128869e-05
Loss: 1.121066e-05
Loss: 1.099670e-05
Loss: 1.075796e-05
Loss: 9.567412e-06
Loss: 8.276716e-06
Loss: 5.766359e-06
Loss: 4.117143e-06
Loss: 3.015935e-06
Loss: 2.538396e-06
Loss: 2.380312e-06
Loss: 2.099562e-06
Loss: 1.834872e-06
Loss: 1.664113e-06
Loss: 1.495033e-06
Loss: 1.290357e-06
Loss: 1.218982e-06
Loss: 1.181760e-06
Loss: 1.187452e-06
Loss: 1.124510e-06
Loss: 1.160990e-06
Loss: 1.124510e-06
Loss: 9.902845e-05
Loss: 1.168396e-06
Loss: 1.192056e-06
Loss: 1.137151e-06
Loss: 1.124510e-06
Loss: 1.124510e-06
Loss: 1.124510e-06
Loss: 1.124510e-06
Loss: 1.124510e-06
Loss: 1.124510e-06
Loss: 1.124510e-06
Loss: 1.124510e-06
Loss: 1.124510e-06
Loss: 1.124510e-06
Loss: 1.124510e-06
Loss: 1.124510e-06
Loss: 1.124510e-06
Loss: 1.124510e-06
Loss: 1.124510e-06
End of layer 1
The coefficients are:
-0.00060882
1.98968983
1.98876131
0.52076405
-0.00001018
0.52059674
The moment matrices are:
[[ 1.00000000e+00 -4.40495906e-09 -2.59581903e-08 -4.13139745e-08 -1.44906531e-08 -1.64656200e-08
2.09721875e-08]
[-1.40462246e-08 1.24522714e-09 2.47070453e-09 -2.71273937e-09 -9.72336239e-11 2.71808243e-09
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[-1.65592997e-08 -2.05986650e-09 2.00891161e-08 3.37491501e-09 9.47611767e-09 2.22877095e-09
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[-3.54730183e-08 6.79600110e-09 3.47725471e-09 -1.72882819e-09 -6.06938555e-10 1.51360327e-10
1.69424225e-10]
[-3.08504937e-08 -6.99394542e-09 7.12234494e-09 1.57187607e-09 -5.30436806e-09 -1.03569486e-09
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[ 1.35812925e-08 2.48984611e-09 -3.11848680e-09 -6.47451204e-10 1.63026603e-09 3.03817915e-10
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[[ 0.00000000e+00 0.00000000e+00 5.03372758e-05 2.36633583e-04 1.20371878e-04 1.11840403e-04
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[[ 0.00000000e+00 1.00000000e+00 5.03207229e-05 2.36532447e-04 1.20292338e-04 1.11769012e-04
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[-2.68368021e-05 5.81575341e-06 1.64600146e-06 -2.47774256e-06 -4.96892216e-09 4.41431155e-07
7.11655712e-09]
[-8.60294676e-05 -1.56431997e-05 2.14301981e-05 3.95946381e-06 -9.77256332e-06 -1.62358867e-06
2.11497445e-06]]
[[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 4.92707477e-04 2.50650191e-04 2.32839549e-04
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[ 0.00000000e+00 0.00000000e+00 -1.20317882e-05 1.05584568e-05 -3.14978502e-06 -2.43572795e-05
5.46596902e-06]
[ 1.00000000e+00 1.75169298e-05 -1.64031298e-04 -4.08342275e-05 -1.57419330e-04 -3.05503454e-05
9.52331684e-05]
[ 4.20230150e-04 -8.85582776e-05 -4.08484484e-05 2.82517158e-05 6.27168401e-06 -4.54491510e-06
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[ 4.19398857e-04 9.21960891e-05 -1.14089366e-04 -2.09814134e-05 7.66792000e-05 1.37635488e-05
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[-5.58569118e-05 1.21204266e-05 3.33327193e-06 -5.18278966e-06 2.57211468e-07 9.68917561e-07
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[-1.79232651e-04 -3.26468507e-05 4.51313317e-05 8.48339641e-06 -2.23412098e-05 -3.97989379e-06
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[[ 0.0000000e+00 0.0000000e+00 0.0000000e+00 1.7996438e-08 -4.4800663e-10 -2.5690052e-09
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[ 0.0000000e+00 1.0000000e+00 1.3689674e-09 3.8000150e-09 -1.1654689e-09 -1.1402981e-09
5.7458599e-10]
[ 0.0000000e+00 -6.6908884e-10 5.4961444e-09 -1.1406044e-09 -4.3713233e-09 -3.4978301e-12
1.9487243e-09]
[ 2.0437154e-08 5.8374840e-11 -3.3150800e-09 3.6670206e-10 1.0203662e-09 -1.1811974e-10
-3.4330819e-10]
[ 1.0088318e-08 1.3836966e-09 -3.2374867e-09 -1.4781520e-10 1.5693388e-09 9.5389870e-11
-6.2015648e-10]
[-5.4728546e-09 1.2267984e-10 8.4326268e-10 -1.2301510e-10 -2.5227759e-10 4.0089931e-11
8.2377154e-11]
[-3.2865717e-09 -4.4433104e-10 9.6814134e-10 7.6433790e-11 -4.2942050e-10 -2.8458270e-11
1.8398416e-10]]
[[ 0.0000000e+00 0.0000000e+00 1.0000000e+00 4.9257593e-04 2.5053605e-04 2.3283978e-04
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[ 0.0000000e+00 0.0000000e+00 -1.2030302e-05 1.0585009e-05 -3.1333250e-06 -2.4374534e-05
5.4836896e-06]
[ 0.0000000e+00 1.7537997e-05 -1.6397113e-04 -4.0856507e-05 -1.5750490e-04 -3.0442856e-05
9.5600750e-05]
[ 4.2010233e-04 -8.8563138e-05 -4.0828567e-05 2.8270650e-05 6.2646641e-06 -4.5513339e-06
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[ 4.1937904e-04 9.2169044e-05 -1.1416147e-04 -2.0857175e-05 7.7044169e-05 1.3341317e-05
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[-5.5833319e-05 1.2137254e-05 3.3315316e-06 -5.2324121e-06 2.4643978e-07 1.0005646e-06
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[-1.7934035e-04 -3.2614793e-05 4.5290868e-05 8.2084662e-06 -2.3165039e-05 -3.0318288e-06
1.3050479e-05]]
[[ 1.0000000e+00 3.7858760e-04 2.1195605e-04 9.9636870e-04 5.0675368e-04 4.7087736e-04
-5.8083975e-04]
[ 2.5400979e-04 -3.3828666e-05 -2.4314833e-05 2.1389396e-05 -6.5116633e-06 -4.9302365e-05
1.1408287e-05]
[ 1.7680040e-04 3.5444624e-05 -3.3167834e-04 -8.2565275e-05 -3.1847676e-04 -6.1762687e-05
1.9311772e-04]
[ 8.4983540e-04 -1.7907092e-04 -8.2741288e-05 5.7106899e-05 1.3271717e-05 -9.1090033e-06
-4.0196619e-06]
[ 8.4820134e-04 1.8641706e-04 -2.3104448e-04 -4.2478350e-05 1.5585561e-04 2.7741553e-05
-6.9815585e-05]
[-1.1300110e-04 2.4477842e-05 6.9994267e-06 -1.0442409e-05 -5.7025181e-07 1.8275076e-06
1.2191911e-06]
[-3.6273160e-04 -6.5984808e-05 9.2047405e-05 1.7276419e-05 -4.7200621e-05 -7.8287621e-06
2.5434065e-05]]
2019-04-05 13:24:09.037567: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0
2019-04-05 13:24:09.037603: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-04-05 13:24:09.037608: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 0
2019-04-05 13:24:09.037612: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0: N
2019-04-05 13:24:09.037751: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4131 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2060, pci bus id: 0000:01:00.0, compute capability: 7.5)
Loss: 3.440997e-06
Loss: 3.734418e+05
Loss: 3.434086e-06
Loss: 3.559259e-06
Loss: 3.558602e-06
Loss: 3.437176e-06
Loss: 3.434086e-06
Loss: 3.434086e-06
Loss: 3.434086e-06
Loss: 3.434086e-06
Loss: 3.434086e-06
Loss: 3.434086e-06
Loss: 3.434086e-06
Loss: 3.434086e-06
Loss: 3.434086e-06
Loss: 3.434086e-06
Loss: 3.434086e-06
Loss: 3.434086e-06
Loss: 3.434086e-06
Loss: 3.434086e-06
Loss: 3.434086e-06
End of layer 2
The coefficients are:
-0.00060881
1.98968983
1.98876131
0.52076405
-0.00001017
0.52059680
The moment matrices are:
[[ 1.0000000e+00 -4.4051451e-09 -2.5958649e-08 -4.1314028e-08 -1.4490509e-08 -1.6465645e-08
2.0972131e-08]
[-1.4046343e-08 1.2451215e-09 2.4706601e-09 -2.7126876e-09 -9.7223646e-11 2.7180675e-09
-3.5392114e-10]
[-1.6559495e-08 -2.0599262e-09 2.0089148e-08 3.3749368e-09 9.4761123e-09 2.2287689e-09
-6.4773666e-09]
[-3.5473050e-08 6.7958590e-09 3.4772583e-09 -1.7287960e-09 -6.0693806e-10 1.5135104e-10
1.6942375e-10]
[-3.0850341e-08 -6.9939303e-09 7.1223289e-09 1.5718720e-09 -5.3043649e-09 -1.0356945e-09
2.3923672e-09]
[ 5.4165059e-09 -8.9038704e-10 -3.9646642e-10 2.9107025e-10 4.2667762e-11 -2.8085177e-11
-2.1989128e-11]
[ 1.3581248e-08 2.4898426e-09 -3.1184824e-09 -6.4745043e-10 1.6302655e-09 3.0381786e-10
-7.7044854e-10]]
[[ 0.00000000e+00 0.00000000e+00 5.03491901e-05 2.36634995e-04 1.20368146e-04 1.11841044e-04
-1.37987357e-04]
[ 1.00000000e+00 -8.02908653e-06 -5.77535457e-06 5.07841241e-06 -1.53269366e-06 -1.17050668e-05
2.71516342e-06]
[ 4.19977878e-05 8.40961184e-06 -7.87805402e-05 -1.95807625e-05 -7.56693189e-05 -1.47240526e-05
4.58710711e-05]
[ 2.01836694e-04 -4.25325125e-05 -1.96385608e-05 1.35645932e-05 3.08907261e-06 -2.17579986e-06
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[ 2.01445000e-04 4.43131867e-05 -5.48517637e-05 -1.02035838e-05 3.71041424e-05 6.80587482e-06
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[-2.68381664e-05 5.82461598e-06 1.63594461e-06 -2.48688116e-06 -1.55008042e-08 4.59797803e-07
1.91547016e-07]
[-8.61657609e-05 -1.57558225e-05 2.18108416e-05 4.35952870e-06 -1.13595297e-05 -2.34245499e-06
5.84576810e-06]]
[[ 0.00000000e+00 1.00000000e+00 5.03326337e-05 2.36533844e-04 1.20288605e-04 1.11769652e-04
-1.37847950e-04]
[ 0.00000000e+00 -8.02670638e-06 -5.77024775e-06 5.07714367e-06 -1.53198425e-06 -1.17038571e-05
2.67504811e-06]
[ 4.19831413e-05 8.41875863e-06 -7.87754107e-05 -1.96232686e-05 -7.54833163e-05 -1.46250532e-05
4.54845213e-05]
[ 2.01748320e-04 -4.25085564e-05 -1.96336950e-05 1.35531145e-05 3.07874575e-06 -2.16322087e-06
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[ 2.01314368e-04 4.42445489e-05 -5.46743177e-05 -1.00138259e-05 3.64176158e-05 6.47086472e-06
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[-2.68366548e-05 5.81463246e-06 1.64595679e-06 -2.47748471e-06 -4.95032415e-09 4.41357514e-07
7.10962356e-09]
[-8.60283180e-05 -1.56431106e-05 2.14300817e-05 3.95944562e-06 -9.77254876e-06 -1.62358879e-06
2.11499105e-06]]
[[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 4.92710387e-04 2.50642421e-04 2.32840874e-04
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[ 0.00000000e+00 0.00000000e+00 -1.20293835e-05 1.05556546e-05 -3.15032548e-06 -2.43564700e-05
5.46607725e-06]
[ 1.00000000e+00 1.75201694e-05 -1.64033045e-04 -4.08354026e-05 -1.57419039e-04 -3.05502399e-05
9.52330302e-05]
[ 4.20231867e-04 -8.85505797e-05 -4.08486376e-05 2.82499695e-05 6.27165764e-06 -4.54441215e-06
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[ 4.19390650e-04 9.21952669e-05 -1.14088507e-04 -2.09811915e-05 7.66790326e-05 1.37635270e-05
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[-5.58566062e-05 1.21180910e-05 3.33317848e-06 -5.18225215e-06 2.57251230e-07 9.68763857e-07
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[-1.79230265e-04 -3.26466616e-05 4.51310880e-05 8.48335458e-06 -2.23411735e-05 -3.97988970e-06
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[[ 0.0000000e+00 0.0000000e+00 0.0000000e+00 1.7996381e-08 -4.4785459e-10 -2.5690312e-09
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[ 0.0000000e+00 1.0000000e+00 1.3689204e-09 3.8000696e-09 -1.1654584e-09 -1.1403140e-09
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[ 0.0000000e+00 -6.6915218e-10 5.4961786e-09 -1.1405814e-09 -4.3713291e-09 -3.4999286e-12
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[ 2.0437120e-08 5.8224342e-11 -3.3150762e-09 3.6673617e-10 1.0203668e-09 -1.1812955e-10
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[ 1.0088478e-08 1.3837127e-09 -3.2375036e-09 -1.4781955e-10 1.5693420e-09 9.5390307e-11
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[-5.4728604e-09 1.2272548e-10 8.4326451e-10 -1.2302559e-10 -2.5227836e-10 4.0092915e-11
8.2377515e-11]
[-3.2866183e-09 -4.4433471e-10 9.6814601e-10 7.6434616e-11 -4.2942111e-10 -2.8458371e-11
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[[ 0.0000000e+00 0.0000000e+00 1.0000000e+00 4.9257884e-04 2.5052828e-04 2.3284111e-04
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[ 0.0000000e+00 0.0000000e+00 -1.2027898e-05 1.0582207e-05 -3.1338654e-06 -2.4373725e-05
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[ 0.0000000e+00 1.7541237e-05 -1.6397287e-04 -4.0857682e-05 -1.5750460e-04 -3.0442749e-05
9.5600612e-05]
[ 4.2010404e-04 -8.8555440e-05 -4.0828756e-05 2.8268905e-05 6.2646386e-06 -4.5508314e-06
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[ 4.1937083e-04 9.2168222e-05 -1.1416061e-04 -2.0856953e-05 7.7044002e-05 1.3341296e-05
-3.4807374e-05]
[-5.5833014e-05 1.2134919e-05 3.3314388e-06 -5.2318751e-06 2.4647750e-07 1.0004112e-06
-4.0750027e-07]
[-1.7933796e-04 -3.2614607e-05 4.5290624e-05 8.2084252e-06 -2.3165003e-05 -3.0318258e-06
1.3050507e-05]]
[[ 1.00000000e+00 3.78607830e-04 2.12006111e-04 9.96374176e-04 5.06737735e-04 4.70879808e-04
-5.80833177e-04]
[ 2.54022656e-04 -3.38170757e-05 -2.43099621e-05 2.13837211e-05 -6.51275241e-06 -4.93007065e-05
1.14085005e-05]
[ 1.76821792e-04 3.54511540e-05 -3.31681746e-04 -8.25676179e-05 -3.18476028e-04 -6.17624391e-05
1.93117361e-04]
[ 8.49838427e-04 -1.79055263e-04 -8.27416297e-05 5.71033452e-05 1.32716577e-05 -9.10798190e-06
-4.01960824e-06]
[ 8.48184340e-04 1.86415316e-04 -2.31042621e-04 -4.24778809e-05 1.55855203e-04 2.77414983e-05
-6.98154836e-05]
[-1.13000431e-04 2.44731091e-05 6.99923476e-06 -1.04413184e-05 -5.70172574e-07 1.82719600e-06
1.21916048e-06]
[-3.62726598e-04 -6.59844009e-05 9.20468738e-05 1.72763303e-05 -4.72005413e-05 -7.82875486e-06
2.54341303e-05]]
2019-04-05 13:24:13.344192: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0
2019-04-05 13:24:13.344223: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-04-05 13:24:13.344228: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 0
2019-04-05 13:24:13.344232: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0: N
2019-04-05 13:24:13.344387: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4131 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2060, pci bus id: 0000:01:00.0, compute capability: 7.5)
Loss: 6.442259e-06
Loss: 2.160075e+06
Loss: 5.946313e+03
Loss: 6.349640e-06
Loss: 6.288478e-06
Loss: 6.348075e-06
Loss: 6.241276e-06
Loss: 6.312929e-06
Loss: 6.253195e-06
Loss: 6.241276e-06
Loss: 6.343709e-06
Loss: 6.147580e-06
Loss: 6.260594e-06
Loss: 6.155892e-06
Loss: 6.190060e-06
Loss: 6.147580e-06
Loss: 6.147580e-06
Loss: 6.147580e-06
Loss: 6.147580e-06
Loss: 6.147580e-06
Loss: 6.147580e-06
Loss: 6.147580e-06
Loss: 6.147580e-06
Loss: 6.147580e-06
Loss: 6.147580e-06
Loss: 6.147580e-06
Loss: 6.147580e-06
Loss: 6.147580e-06
Loss: 6.147580e-06
Loss: 6.147580e-06
Loss: 6.147580e-06
End of layer 3
The coefficients are:
-0.00060880
1.98968983
1.98876131
0.52076411
-0.00001011
0.52059704
The moment matrices are:
[[ 1.0000000e+00 -4.4057646e-09 -2.5960622e-08 -4.1314429e-08 -1.4489999e-08 -1.6465616e-08
2.0971953e-08]
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[[ 0.00000000e+00 1.00000000e+00 5.03839256e-05 2.36544292e-04 1.20275348e-04 1.11768924e-04
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[-8.60249274e-05 -1.56428960e-05 2.14298652e-05 3.95938014e-06 -9.77277978e-06 -1.62357412e-06
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[[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 4.92732157e-04 2.50614801e-04 2.32839346e-04
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[ 0.00000000e+00 0.00000000e+00 -1.20230379e-05 1.05448498e-05 -3.15176044e-06 -2.43532595e-05
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[ 1.00000000e+00 1.75278456e-05 -1.64038051e-04 -4.08394371e-05 -1.57418690e-04 -3.05495851e-05
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[ 4.20239696e-04 -8.85342233e-05 -4.08496962e-05 2.82466517e-05 6.27173677e-06 -4.54351675e-06
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[ 4.19365620e-04 9.21933024e-05 -1.14086448e-04 -2.09804766e-05 7.66789744e-05 1.37634070e-05
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[-5.58565844e-05 1.21128805e-05 3.33307298e-06 -5.18115712e-06 2.57307562e-07 9.68467248e-07
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[[ 0.0000000e+00 0.0000000e+00 0.0000000e+00 1.7995957e-08 -4.4731657e-10 -2.5690015e-09
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[ 0.0000000e+00 1.0000000e+00 1.3687967e-09 3.8002801e-09 -1.1654304e-09 -1.1403766e-09
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[ 0.0000000e+00 -6.6930178e-10 5.4962759e-09 -1.1405028e-09 -4.3713357e-09 -3.5126420e-12
1.9487278e-09]
[ 2.0436968e-08 5.7905531e-11 -3.3150556e-09 3.6680081e-10 1.0203652e-09 -1.1814701e-10
-3.4330913e-10]
[ 1.0088965e-08 1.3837509e-09 -3.2375438e-09 -1.4783344e-10 1.5693432e-09 9.5392548e-11
-6.2014766e-10]
[-5.4728608e-09 1.2282705e-10 8.4326657e-10 -1.2304693e-10 -2.5227953e-10 4.0098702e-11
8.2377792e-11]
[-3.2867560e-09 -4.4434342e-10 9.6815478e-10 7.6437162e-11 -4.2941181e-10 -2.8458784e-11
1.8395827e-10]]
[[ 0.0000000e+00 0.0000000e+00 1.0000000e+00 4.9260055e-04 2.5050063e-04 2.3283956e-04
-2.8724404e-04]
[ 0.0000000e+00 0.0000000e+00 -1.2021553e-05 1.0571404e-05 -3.1352993e-06 -2.4370513e-05
5.4840662e-06]
[ 0.0000000e+00 1.7548909e-05 -1.6397786e-04 -4.0861709e-05 -1.5750424e-04 -3.0442092e-05
9.5600546e-05]
[ 4.2011181e-04 -8.8539084e-05 -4.0829811e-05 2.8265586e-05 6.2647164e-06 -4.5499364e-06
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[ 4.1934574e-04 9.2166243e-05 -1.1415854e-04 -2.0856236e-05 7.7043936e-05 1.3341174e-05
-3.4807865e-05]
[-5.5832985e-05 1.2129709e-05 3.3313327e-06 -5.2307810e-06 2.4653522e-07 1.0001162e-06
-4.0751024e-07]
[-1.7933089e-04 -3.2614156e-05 4.5290173e-05 8.2082861e-06 -2.3165485e-05 -3.0317915e-06
1.3051813e-05]]
[[ 1.0000000e+00 3.7867529e-04 2.1222197e-04 9.9641725e-04 5.0668145e-04 4.7087629e-04
-5.8081310e-04]
[ 2.5408572e-04 -3.3760170e-05 -2.4297111e-05 2.1361859e-05 -6.5156460e-06 -4.9294169e-05
1.1409029e-05]
[ 1.7690213e-04 3.5466641e-05 -3.3169152e-04 -8.2575694e-05 -3.1847504e-04 -6.1761064e-05
1.9311708e-04]
[ 8.4985344e-04 -1.7902203e-04 -8.2743689e-05 5.7096586e-05 1.3271803e-05 -9.1061629e-06
-4.0195650e-06]
[ 8.4813288e-04 1.8641118e-04 -2.3103824e-04 -4.2476397e-05 1.5585496e-04 2.7741238e-05
-6.9816473e-05]
[-1.1300028e-04 2.4462552e-05 6.9990137e-06 -1.0439095e-05 -5.7005423e-07 1.8265948e-06
1.2191346e-06]
[-3.6271196e-04 -6.5983433e-05 9.2045892e-05 1.7276045e-05 -4.7201531e-05 -7.8287012e-06
2.5436866e-05]]
2019-04-05 13:24:19.283428: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0
2019-04-05 13:24:19.283462: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-04-05 13:24:19.283467: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 0
2019-04-05 13:24:19.283472: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0: N
2019-04-05 13:24:19.283607: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4131 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2060, pci bus id: 0000:01:00.0, compute capability: 7.5)
Loss: 1.132257e-05
Loss: 9.087599e+06
Loss: 3.740758e+04
Loss: 1.069093e-05
Loss: 1.057289e-05
Loss: 1.082905e-05
Loss: 1.091102e-05
Loss: 1.062253e-05
Loss: 1.057289e-05
Loss: 1.057289e-05
Loss: 1.057289e-05
Loss: 1.057289e-05
Loss: 1.057289e-05
Loss: 1.057289e-05
Loss: 1.057289e-05
Loss: 1.057289e-05
Loss: 1.057289e-05
Loss: 1.057289e-05
Loss: 1.057289e-05
Loss: 1.057289e-05
Loss: 1.057289e-05
End of layer 4
The coefficients are:
-0.00060879
1.98968983
1.98876131
0.52076411
-0.00001007
0.52059710
The moment matrices are:
[[ 1.0000000e+00 -4.4063300e-09 -2.5961306e-08 -4.1314625e-08 -1.4489850e-08 -1.6465592e-08
2.0971905e-08]
[-1.4047412e-08 1.2442213e-09 2.4704883e-09 -2.7123692e-09 -9.7182873e-11 2.7179734e-09
-3.5392941e-10]
[-1.6560254e-08 -2.0601041e-09 2.0089253e-08 3.3750436e-09 9.4761177e-09 2.2287510e-09
-6.4773831e-09]
[-3.5473274e-08 6.7954593e-09 3.4772913e-09 -1.7287175e-09 -6.0694177e-10 1.5133035e-10
1.6942428e-10]
[-3.0849723e-08 -6.9938828e-09 7.1222868e-09 1.5718530e-09 -5.3043920e-09 -1.0356909e-09
2.3924425e-09]
[ 5.4165095e-09 -8.9025659e-10 -3.9646506e-10 2.9104361e-10 4.2667068e-11 -2.8078095e-11
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[ 1.3581071e-08 2.4898315e-09 -3.1184866e-09 -6.4744637e-10 1.6303394e-09 3.0381600e-10
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[[ 0.00000000e+00 0.00000000e+00 5.04182754e-05 2.36650551e-04 1.20351004e-04 1.11839661e-04
-1.37981493e-04]
[ 1.00000000e+00 -8.00567614e-06 -5.77088713e-06 5.07012828e-06 -1.53375368e-06 -1.17026175e-05
2.71537783e-06]
[ 4.20175238e-05 8.41423935e-06 -7.87832614e-05 -1.95835455e-05 -7.56694644e-05 -1.47235805e-05
4.58715003e-05]
[ 2.01842457e-04 -4.25221115e-05 -1.96394212e-05 1.35625542e-05 3.08916947e-06 -2.17526144e-06
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[ 2.01428877e-04 4.43119570e-05 -5.48506650e-05 -1.02030908e-05 3.71048372e-05 6.80577887e-06
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[-2.68382628e-05 5.82122357e-06 1.63590857e-06 -2.48618767e-06 -1.54819322e-08 4.59613545e-07
1.91569015e-07]
[-8.61611697e-05 -1.57555332e-05 2.18109508e-05 4.35942093e-06 -1.13614451e-05 -2.34240451e-06
5.85030921e-06]]
[[ 0.0000000e+00 1.0000000e+00 5.0401686e-05 2.3654940e-04 1.2027147e-04 1.1176827e-04
-1.3784209e-04]
[ 0.0000000e+00 -8.0033069e-06 -5.7657817e-06 5.0688632e-06 -1.5330448e-06 -1.1701410e-05
2.6752641e-06]
[ 4.2002866e-05 8.4233852e-06 -7.8778132e-05 -1.9626050e-05 -7.5483462e-05 -1.4624581e-05
4.5484954e-05]
[ 2.0175407e-04 -4.2498159e-05 -1.9634555e-05 1.3551076e-05 3.0788440e-06 -2.1626827e-06
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[ 2.0129824e-04 4.4243319e-05 -5.4673223e-05 -1.0013334e-05 3.6418307e-05 6.4707692e-06
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[-2.6836751e-05 5.8112414e-06 1.6459212e-06 -2.4767917e-06 -4.9336468e-09 4.4117363e-07
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[-8.6023727e-05 -1.5642821e-05 2.1430187e-05 3.9593378e-06 -9.7744560e-06 -1.6235394e-06
2.1195208e-06]]
[[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 4.92742809e-04 2.50606710e-04 2.32837992e-04
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[ 0.00000000e+00 0.00000000e+00 -1.20200775e-05 1.05384006e-05 -3.15253465e-06 -2.43513696e-05
5.46652518e-06]
[ 1.00000000e+00 1.75298082e-05 -1.64038720e-04 -4.08411979e-05 -1.57419330e-04 -3.05492576e-05
9.52339251e-05]
[ 4.20243858e-04 -8.85289192e-05 -4.08504311e-05 2.82457222e-05 6.27186182e-06 -4.54329074e-06
-1.31270883e-06]
[ 4.19357064e-04 9.21927058e-05 -1.14086222e-04 -2.09801674e-05 7.66804733e-05 1.37633288e-05
-3.33240496e-05]
[-5.58568063e-05 1.21110252e-05 3.33310481e-06 -5.18080788e-06 2.57285137e-07 9.68380164e-07
-6.33119384e-07]
[-1.79220689e-04 -3.26460613e-05 4.51313099e-05 8.48313448e-06 -2.23451534e-05 -3.97979011e-06
9.65171694e-06]]
[[ 0.0000000e+00 0.0000000e+00 0.0000000e+00 1.7995751e-08 -4.4716020e-10 -2.5689750e-09
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[ 0.0000000e+00 1.0000000e+00 1.3687393e-09 3.8004053e-09 -1.1654154e-09 -1.1404132e-09
5.7457517e-10]
[ 0.0000000e+00 -6.6933986e-10 5.4962888e-09 -1.1404686e-09 -4.3713233e-09 -3.5190100e-12
1.9487094e-09]
[ 2.0436888e-08 5.7802652e-11 -3.3150414e-09 3.6681885e-10 1.0203628e-09 -1.1815139e-10
-3.4330819e-10]
[ 1.0089130e-08 1.3837625e-09 -3.2375480e-09 -1.4783946e-10 1.5693140e-09 9.5394075e-11
-6.2007871e-10]
[-5.4728564e-09 1.2286305e-10 8.4326596e-10 -1.2305371e-10 -2.5227911e-10 4.0100392e-11
8.2376592e-11]
[-3.2868044e-09 -4.4434642e-10 9.6814168e-10 7.6438841e-11 -4.2934384e-10 -2.8460101e-11
1.8380038e-10]]
[[ 0.0000000e+00 0.0000000e+00 1.0000000e+00 4.9261120e-04 2.5049257e-04 2.3283821e-04
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[ 0.0000000e+00 0.0000000e+00 -1.2018593e-05 1.0564958e-05 -3.1360735e-06 -2.4368623e-05
5.4842480e-06]
[ 0.0000000e+00 1.7550872e-05 -1.6397852e-04 -4.0863470e-05 -1.5750488e-04 -3.0441763e-05
9.5601492e-05]
[ 4.2011598e-04 -8.8533779e-05 -4.0830546e-05 2.8264656e-05 6.2648419e-06 -4.5497100e-06
-1.4336721e-06]
[ 4.1933719e-04 9.2165646e-05 -1.1415831e-04 -2.0855925e-05 7.7045435e-05 1.3341094e-05
-3.4811408e-05]
[-5.5833207e-05 1.2127854e-05 3.3313645e-06 -5.2304317e-06 2.4651246e-07 1.0000283e-06
-4.0744487e-07]
[-1.7932839e-04 -3.2614003e-05 4.5290846e-05 8.2081988e-06 -2.3168979e-05 -3.0317215e-06
1.3059930e-05]]
[[ 1.00000000e+00 3.78736877e-04 2.12296611e-04 9.96437971e-04 5.06664743e-04 4.70873114e-04
-5.80807449e-04]
[ 2.54139275e-04 -3.37184429e-05 -2.42911065e-05 2.13488038e-05 -6.51720438e-06 -4.92903091e-05
1.14093828e-05]
[ 1.76904563e-04 3.54705808e-05 -3.31692572e-04 -8.25791867e-05 -3.18476086e-04 -6.17603509e-05
1.93118845e-04]
[ 8.49861128e-04 -1.79011156e-04 -8.27451076e-05 5.70946577e-05 1.32720406e-05 -9.10569815e-06
-4.01965372e-06]
[ 8.48114898e-04 1.86409816e-04 -2.31037600e-04 -4.24757345e-05 1.55857881e-04 2.77410563e-05
-6.98236181e-05]
[-1.13000635e-04 2.44587809e-05 6.99907059e-06 -1.04383789e-05 -5.70091231e-07 1.82641554e-06
1.21924802e-06]
[-3.62706603e-04 -6.59830621e-05 9.20471794e-05 1.72758591e-05 -4.72085885e-05 -7.82855841e-06
2.54533334e-05]]
2019-04-05 13:24:26.741728: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0
2019-04-05 13:24:26.741761: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-04-05 13:24:26.741767: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 0
2019-04-05 13:24:26.741771: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0: N
2019-04-05 13:24:26.741910: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4131 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2060, pci bus id: 0000:01:00.0, compute capability: 7.5)
Loss: 3.664416e-05
Loss: 1.101769e+20
Loss: 4.582643e+14
Loss: 1.596559e+09
Loss: 3.345198e+03
Loss: 3.418686e+01
Loss: 3.608503e-05
Loss: 3.660870e-05
Loss: 3.667290e-05
Loss: 3.669186e-05
Loss: 3.696863e-05
Loss: 3.608503e-05
Loss: 3.608503e-05
Loss: 3.696863e-05
Loss: 3.608503e-05
Loss: 3.608503e-05
Loss: 3.608503e-05
Loss: 3.608503e-05
Loss: 3.608503e-05
Loss: 3.608503e-05
Loss: 3.608503e-05
Loss: 3.608503e-05
Loss: 3.608503e-05
Loss: 3.608503e-05
Loss: 3.608503e-05
Loss: 3.608503e-05
Loss: 3.608503e-05
End of layer 5
The coefficients are:
-0.00060877
1.98968983
1.98876131
0.52076411
-0.00001004
0.52059710
The moment matrices are:
[[ 1.0000000e+00 -4.4067865e-09 -2.5961510e-08 -4.1314745e-08 -1.4489811e-08 -1.6465576e-08
2.0971912e-08]
[-1.4047799e-08 1.2439252e-09 2.4704556e-09 -2.7122897e-09 -9.7171833e-11 2.7179508e-09
-3.5393377e-10]
[-1.6560030e-08 -2.0601154e-09 2.0089230e-08 3.3750636e-09 9.4761834e-09 2.2287463e-09
-6.4775234e-09]
[-3.5473338e-08 6.7954176e-09 3.4773020e-09 -1.7287108e-09 -6.0694588e-10 1.5132889e-10
1.6942986e-10]
[-3.0849669e-08 -6.9938770e-09 7.1223423e-09 1.5718477e-09 -5.3046372e-09 -1.0356864e-09
2.3930116e-09]
[ 5.4165170e-09 -8.9024027e-10 -3.9646683e-10 2.9104069e-10 4.2671193e-11 -2.8077355e-11
-2.1999447e-11]
[ 1.3581072e-08 2.4898286e-09 -3.1186207e-09 -6.4744093e-10 1.6309036e-09 3.0380701e-10
-7.7193513e-10]]
[[ 0.0000000e+00 0.0000000e+00 5.0423580e-05 2.3665369e-04 1.2034998e-04 1.1183925e-04
-1.3798167e-04]
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