epoch: 1, train_loss_TEST_TASK:
[8.62151 1.7348814 1.4287004]
<NDArray 3 @cpu(0)>
epoch: 1, train_loss_CONTROL_TASK:
[3.3143055 2.6961389 6.5755267 2.7496517]
<NDArray 4 @cpu(0)>
epoch: 2, train_loss_TEST_TASK:
[1.7090356 8.558825 1.4016223]
<NDArray 3 @cpu(0)>
epoch: 2, train_loss_CONTROL_TASK:
[2.722022 6.5049357 3.2557647 2.6794322]
<NDArray 4 @cpu(0)>
epoch: 3, train_loss_TEST_TASK:
[8.495208 1.3743348 1.6830173]
<NDArray 3 @cpu(0)>
epoch: 3, train_loss_CONTROL_TASK:
[3.1966267 2.6941004 2.662689 6.4332805]
<NDArray 4 @cpu(0)>
epoch: 4, train_loss_TEST_TASK:
[1.656776 8.430145 1.3467298]
<NDArray 3 @cpu(0)>
epoch: 4, train_loss_CONTROL_TASK:
[3.137936 2.6658368 6.360365 2.6458442]
<NDArray 4 @cpu(0)>
epoch: 5, train_loss_TEST_TASK:
[1.6302229 8.361879 1.3187424]
<NDArray 3 @cpu(0)>
epoch: 5, train_loss_CONTROL_TASK:
[6.284238 2.628588 2.6366503 3.0766547]
<NDArray 4 @cpu(0)>
epoch: 6, train_loss_TEST_TASK:
[1.2898209 8.286601 1.6028273]
<NDArray 3 @cpu(0)>
epoch: 6, train_loss_CONTROL_TASK:
[2.607107 6.2064266 2.6116507 3.0138392]
<NDArray 4 @cpu(0)>
epoch: 7, train_loss_TEST_TASK:
[8.208974 1.2603858 1.5751398]
<NDArray 3 @cpu(0)>
epoch: 7, train_loss_CONTROL_TASK:
[2.5771189 2.5944636 2.949321 6.127756 ]
<NDArray 4 @cpu(0)>
epoch: 8, train_loss_TEST_TASK:
[8.13189 1.2303796 1.5468522]
<NDArray 3 @cpu(0)>
epoch: 8, train_loss_CONTROL_TASK:
[6.0472555 2.5465946 2.8837414 2.5770898]
<NDArray 4 @cpu(0)>
epoch: 9, train_loss_TEST_TASK:
[1.1999923 1.5180264 8.052104 ]
<NDArray 3 @cpu(0)>
epoch: 9, train_loss_CONTROL_TASK:
[5.963794 2.816373 2.5593448 2.5149956]
<NDArray 4 @cpu(0)>
epoch: 10, train_loss_TEST_TASK:
[1.1688788 1.488097 7.969059 ]
<NDArray 3 @cpu(0)>
epoch: 10, train_loss_CONTROL_TASK:
[2.7467475 2.4823556 5.8764305 2.5415492]
<NDArray 4 @cpu(0)>
epoch: 11, train_loss_TEST_TASK:
[7.8825173 1.1370294 1.4573431]
<NDArray 3 @cpu(0)>
epoch: 11, train_loss_CONTROL_TASK:
[2.6747384 2.4490395 2.5234365 5.785742 ]
<NDArray 4 @cpu(0)>
epoch: 12, train_loss_TEST_TASK:
[1.42618 7.792291 1.1044526]
<NDArray 3 @cpu(0)>
epoch: 12, train_loss_CONTROL_TASK:
[2.6003847 2.504911 2.414864 5.6929955]
<NDArray 4 @cpu(0)>
epoch: 13, train_loss_TEST_TASK:
[1.0712123 7.69821 1.3942409]
<NDArray 3 @cpu(0)>
epoch: 13, train_loss_CONTROL_TASK:
[2.5235982 5.59688 2.4859056 2.379958 ]
<NDArray 4 @cpu(0)>
epoch: 14, train_loss_TEST_TASK:
[1.3616843 7.600129 1.0373111]
<NDArray 3 @cpu(0)>
epoch: 14, train_loss_CONTROL_TASK:
[2.4664032 2.3438663 2.444786 5.4978127]
<NDArray 4 @cpu(0)>
epoch: 15, train_loss_TEST_TASK:
[1.0030949 7.497924 1.3281574]
<NDArray 3 @cpu(0)>
epoch: 15, train_loss_CONTROL_TASK:
[5.394723 2.4463882 2.3065438 2.3640413]
<NDArray 4 @cpu(0)>
epoch: 16, train_loss_TEST_TASK:
[0.9683027 1.2936819 7.391499 ]
<NDArray 3 @cpu(0)>
epoch: 16, train_loss_CONTROL_TASK:
[2.4258494 5.287532 2.2808514 2.2679763]
<NDArray 4 @cpu(0)>
epoch: 17, train_loss_TEST_TASK:
[7.2807903 0.93303794 1.2582934 ]
<NDArray 3 @cpu(0)>
epoch: 17, train_loss_CONTROL_TASK:
[2.4047806 5.176232 2.2281609 2.195344 ]
<NDArray 4 @cpu(0)>
epoch: 18, train_loss_TEST_TASK:
[1.2220438 0.8974302 7.1657715]
<NDArray 3 @cpu(0)>
epoch: 18, train_loss_CONTROL_TASK:
[2.107689 2.1871045 5.060853 2.3831804]
<NDArray 4 @cpu(0)>
epoch: 19, train_loss_TEST_TASK:
[7.0464544 0.86163175 1.1850003 ]
<NDArray 3 @cpu(0)>
epoch: 19, train_loss_CONTROL_TASK:
[2.3610518 4.9414644 2.0180984 2.1448271]
<NDArray 4 @cpu(0)>
epoch: 20, train_loss_TEST_TASK:
[1.1472461 0.8258177 6.9228916]
<NDArray 3 @cpu(0)>
epoch: 20, train_loss_CONTROL_TASK:
[2.1013613 4.81818 2.3384032 1.9268289]
<NDArray 4 @cpu(0)>
epoch: 21, train_loss_TEST_TASK:
[1.1088824 6.795183 0.7901859]
<NDArray 3 @cpu(0)>
epoch: 21, train_loss_CONTROL_TASK:
[2.3152504 2.0567534 1.8341818 4.691158 ]
<NDArray 4 @cpu(0)>
epoch: 22, train_loss_TEST_TASK:
[6.6634746 0.75495607 1.0700263 ]
<NDArray 3 @cpu(0)>
epoch: 22, train_loss_CONTROL_TASK:
[4.5606027 2.011064 1.740502 2.2916136]
<NDArray 4 @cpu(0)>
epoch: 23, train_loss_TEST_TASK:
[0.7203683 6.5279636 1.0308125]
<NDArray 3 @cpu(0)>
epoch: 23, train_loss_CONTROL_TASK:
[2.2675204 4.426769 1.964368 1.6461773]
<NDArray 4 @cpu(0)>
epoch: 24, train_loss_TEST_TASK:
[0.68668145 6.388895 0.9913916 ]
<NDArray 3 @cpu(0)>
epoch: 24, train_loss_CONTROL_TASK:
[2.2430053 4.289958 1.5516343 1.9167548]
<NDArray 4 @cpu(0)>
epoch: 25, train_loss_TEST_TASK:
[6.2465706 0.9519297 0.6541693]
<NDArray 3 @cpu(0)>
epoch: 25, train_loss_CONTROL_TASK:
[4.1505184 2.2181091 1.8683283 1.4573362]
<NDArray 4 @cpu(0)>
epoch: 26, train_loss_TEST_TASK:
[0.623118 6.101339 0.91260624]
<NDArray 3 @cpu(0)>
epoch: 26, train_loss_CONTROL_TASK:
[2.1928785 4.008845 1.3637757 1.8192067]
<NDArray 4 @cpu(0)>
epoch: 27, train_loss_TEST_TASK:
[5.953603 0.87361264 0.59382135]
<NDArray 3 @cpu(0)>
epoch: 27, train_loss_CONTROL_TASK:
[1.7695205 1.2714694 2.1673682 3.8653736]
<NDArray 4 @cpu(0)>
epoch: 28, train_loss_TEST_TASK:
[0.5665754 0.83514893 5.8038077 ]
<NDArray 3 @cpu(0)>
epoch: 28, train_loss_CONTROL_TASK:
[1.7194128 3.7205803 1.1809494 2.1416378]
<NDArray 4 @cpu(0)>
epoch: 29, train_loss_TEST_TASK:
[0.5416727 0.79742193 5.652446 ]
<NDArray 3 @cpu(0)>
epoch: 29, train_loss_CONTROL_TASK:
[2.1157537 3.5749736 1.0927551 1.6690369]
<NDArray 4 @cpu(0)>
epoch: 30, train_loss_TEST_TASK:
[5.500046 0.7606407 0.5193966]
<NDArray 3 @cpu(0)>
epoch: 30, train_loss_CONTROL_TASK:
[1.6185547 1.0074217 2.089786 3.429088 ]
<NDArray 4 @cpu(0)>