[2024-05-27 22:01:08,234][__main__][INFO] - Using GPU for training. Main device : cuda:0
[2024-05-27 22:01:08,235][__main__][INFO] - Using multiple GPUs : [0, 1, 2, 3]
[2024-05-27 22:01:16,404][__main__][INFO] - PSF shape : torch.Size([1, 380, 507, 3])
[2024-05-27 22:01:16,426][__main__][INFO] - PSF min : 3.7760526956527246e-17
[2024-05-27 22:01:16,432][__main__][INFO] - PSF max : 0.02279210090637207
[2024-05-27 22:01:16,433][__main__][INFO] - PSF dtype : torch.float32
[2024-05-27 22:01:16,448][__main__][INFO] - PSF norm : 1.0000208616256714
[2024-05-27 22:01:16,449][__main__][INFO] - Reconstruction a few images with ADMM...
[2024-05-27 22:01:17,074][__main__][INFO] - Cropped shape :  (200, 266, 3)
[2024-05-27 22:01:17,131][matplotlib.image][WARNING] - Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
[2024-05-27 22:01:17,581][matplotlib.image][WARNING] - Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
[2024-05-27 22:01:18,022][matplotlib.image][WARNING] - Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
[2024-05-27 22:01:18,471][matplotlib.image][WARNING] - Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
[2024-05-27 22:01:18,902][matplotlib.image][WARNING] - Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
[2024-05-27 22:01:19,141][__main__][INFO] - Train test size : 21250
[2024-05-27 22:01:19,141][__main__][INFO] - Test test size : 3750
[2024-05-27 22:01:19,229][__main__][INFO] - Training model with 8161289 parameters
[2024-05-27 22:01:19,229][__main__][INFO] - Setup time : 0.08754658699035645 s
[2024-05-27 22:01:19,229][__main__][INFO] - PSF shape : torch.Size([1, 380, 507, 3])
[2024-05-27 22:01:19,229][__main__][INFO] - Results saved in /root/LenslessPiCam/outputs/2024-05-27/22-01-02
[2024-05-27 22:07:03,105][__main__][INFO] - Epoch 0 with learning rate [0.0001]
[2024-05-27 23:14:59,352][__main__][INFO] - loss : 0.6394710385281087
[2024-05-27 23:20:32,256][__main__][INFO] - Epoch 1 with learning rate [0.0001]
[2024-05-28 00:28:21,619][__main__][INFO] - loss : 0.5649175963932651
[2024-05-28 00:33:53,659][__main__][INFO] - Epoch 2 with learning rate [0.0001]
[2024-05-28 01:41:48,238][__main__][INFO] - loss : 0.5405690594287602
[2024-05-28 01:47:19,377][__main__][INFO] - Epoch 3 with learning rate [0.0001]
[2024-05-28 02:55:13,866][__main__][INFO] - loss : 0.526726677416408
[2024-05-28 03:00:48,546][__main__][INFO] - Epoch 4 with learning rate [0.0001]
[2024-05-28 04:08:46,578][__main__][INFO] - loss : 0.5178703271622436
[2024-05-28 04:14:21,834][__main__][INFO] - Epoch 5 with learning rate [0.0001]
[2024-05-28 05:22:22,341][__main__][INFO] - loss : 0.5108633535170375
[2024-05-28 05:27:55,480][__main__][INFO] - Epoch 6 with learning rate [0.0001]
[2024-05-28 06:35:51,478][__main__][INFO] - loss : 0.5053675666426213
[2024-05-28 06:41:24,795][__main__][INFO] - Epoch 7 with learning rate [0.0001]
[2024-05-28 07:49:20,203][__main__][INFO] - loss : 0.5004707537318004
[2024-05-28 07:54:50,396][__main__][INFO] - Epoch 8 with learning rate [0.0001]
[2024-05-28 09:02:41,424][__main__][INFO] - loss : 0.4962051761940158
[2024-05-28 09:08:16,206][__main__][INFO] - Epoch 9 with learning rate [0.0001]
[2024-05-28 10:16:12,008][__main__][INFO] - loss : 0.4924592228398462
[2024-05-28 10:21:42,036][__main__][INFO] - Epoch 10 with learning rate [0.0001]
[2024-05-28 11:29:35,745][__main__][INFO] - loss : 0.4897828212166683
[2024-05-28 11:35:10,312][__main__][INFO] - Epoch 11 with learning rate [0.0001]
[2024-05-28 12:43:07,575][__main__][INFO] - loss : 0.48674833137347656
[2024-05-28 12:48:40,953][__main__][INFO] - Epoch 12 with learning rate [0.0001]
[2024-05-28 13:56:40,415][__main__][INFO] - loss : 0.48417162012295584
[2024-05-28 14:02:12,662][__main__][INFO] - Epoch 13 with learning rate [0.0001]
[2024-05-28 15:10:39,564][__main__][INFO] - loss : 0.4816779625992438
[2024-05-28 15:16:20,759][__main__][INFO] - Epoch 14 with learning rate [0.0001]
[2024-05-28 16:24:57,006][__main__][INFO] - loss : 0.47936023426509106
[2024-05-28 16:30:27,425][__main__][INFO] - Epoch 15 with learning rate [0.0001]
[2024-05-28 17:38:08,061][__main__][INFO] - loss : 0.47724702483109255
[2024-05-28 17:43:38,707][__main__][INFO] - Epoch 16 with learning rate [0.0001]
[2024-05-28 18:51:23,619][__main__][INFO] - loss : 0.475030184869104
[2024-05-28 18:56:54,717][__main__][INFO] - Epoch 17 with learning rate [0.0001]
[2024-05-28 20:04:39,528][__main__][INFO] - loss : 0.4727901375138905
[2024-05-28 20:10:12,089][__main__][INFO] - Epoch 18 with learning rate [0.0001]
[2024-05-28 21:18:12,274][__main__][INFO] - loss : 0.4710608096013251
[2024-05-28 21:23:46,286][__main__][INFO] - Epoch 19 with learning rate [0.0001]
[2024-05-28 22:31:45,315][__main__][INFO] - loss : 0.469172975375516
[2024-05-28 22:37:19,223][__main__][INFO] - Epoch 20 with learning rate [0.0001]
[2024-05-28 23:45:13,795][__main__][INFO] - loss : 0.46683422611097647
[2024-05-28 23:50:43,923][__main__][INFO] - Epoch 21 with learning rate [0.0001]
[2024-05-29 00:58:33,991][__main__][INFO] - loss : 0.46494334411109506
[2024-05-29 01:04:06,393][__main__][INFO] - Epoch 22 with learning rate [0.0001]
[2024-05-29 02:12:08,000][__main__][INFO] - loss : 0.4631072437888859
[2024-05-29 02:17:39,906][__main__][INFO] - Epoch 23 with learning rate [0.0001]
[2024-05-29 03:25:40,184][__main__][INFO] - loss : 0.4611755203229208
[2024-05-29 03:31:10,953][__main__][INFO] - Epoch 24 with learning rate [0.0001]
[2024-05-29 04:39:07,755][__main__][INFO] - loss : 0.4594755102108142
[2024-05-29 04:44:39,729][__main__][INFO] - Train time [hour] : 30.72196141448286 h
[2024-05-29 04:44:39,730][__main__][INFO] - Results saved in /root/LenslessPiCam/outputs/2024-05-27/22-01-02