Here’s the log of what I see for one epochs and also commenting the transform.Normalize
size of train loader is:  90
loss_train_step before backward:  tensor(157314.2188, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(157314.2188, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  157314.21875
step:  1
running loss:  157314.21875
Train Steps: 1/90  Loss: 157314.2188 loss_train_step before backward:  tensor(172433.0312, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(172433.0312, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  329747.25
step:  2
running loss:  164873.625
Train Steps: 2/90  Loss: 164873.6250 loss_train_step before backward:  tensor(161687.8438, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(161687.8438, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  491435.09375
step:  3
running loss:  163811.69791666666
Train Steps: 3/90  Loss: 163811.6979 loss_train_step before backward:  tensor(172857.6250, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(172857.6250, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  664292.71875
step:  4
running loss:  166073.1796875
Train Steps: 4/90  Loss: 166073.1797 loss_train_step before backward:  tensor(167570.2188, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(167570.2188, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  831862.9375
step:  5
running loss:  166372.5875
Train Steps: 5/90  Loss: 166372.5875 loss_train_step before backward:  tensor(164119.4062, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(164119.4062, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  995982.34375
step:  6
running loss:  165997.05729166666
Train Steps: 6/90  Loss: 165997.0573 loss_train_step before backward:  tensor(174509.2500, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(174509.2500, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  1170491.59375
step:  7
running loss:  167213.08482142858
Train Steps: 7/90  Loss: 167213.0848 loss_train_step before backward:  tensor(167285.3906, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(167285.3906, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  1337776.984375
step:  8
running loss:  167222.123046875
Train Steps: 8/90  Loss: 167222.1230 loss_train_step before backward:  tensor(176070.6094, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(176070.6094, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  1513847.59375
step:  9
running loss:  168205.28819444444
Train Steps: 9/90  Loss: 168205.2882 loss_train_step before backward:  tensor(167046.6875, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(167046.6875, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  1680894.28125
step:  10
running loss:  168089.428125
Train Steps: 10/90  Loss: 168089.4281 loss_train_step before backward:  tensor(159272.8438, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(159272.8438, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  1840167.125
step:  11
running loss:  167287.92045454544
Train Steps: 11/90  Loss: 167287.9205 loss_train_step before backward:  tensor(169830.3125, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(169830.3125, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  2009997.4375
step:  12
running loss:  167499.78645833334
Train Steps: 12/90  Loss: 167499.7865 loss_train_step before backward:  tensor(159050.5156, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(159050.5156, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  2169047.953125
step:  13
running loss:  166849.84254807694
Train Steps: 13/90  Loss: 166849.8425 loss_train_step before backward:  tensor(166620.4375, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(166620.4375, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  2335668.390625
step:  14
running loss:  166833.4564732143
Train Steps: 14/90  Loss: 166833.4565 loss_train_step before backward:  tensor(157660.1094, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(157660.1094, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  2493328.5
step:  15
running loss:  166221.9
Train Steps: 15/90  Loss: 166221.9000 loss_train_step before backward:  tensor(157721.7969, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(157721.7969, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  2651050.296875
step:  16
running loss:  165690.6435546875
Train Steps: 16/90  Loss: 165690.6436 loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  17
running loss:  nan
Train Steps: 17/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  18
running loss:  nan
Train Steps: 18/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  19
running loss:  nan
Train Steps: 19/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  20
running loss:  nan
Train Steps: 20/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  21
running loss:  nan
Train Steps: 21/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  22
running loss:  nan
Train Steps: 22/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  23
running loss:  nan
Train Steps: 23/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  24
running loss:  nan
Train Steps: 24/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  25
running loss:  nan
Train Steps: 25/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  26
running loss:  nan
Train Steps: 26/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  27
running loss:  nan
Train Steps: 27/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  28
running loss:  nan
Train Steps: 28/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  29
running loss:  nan
Train Steps: 29/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)

loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  30
running loss:  nan
Train Steps: 30/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  31
running loss:  nan
Train Steps: 31/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  32
running loss:  nan
Train Steps: 32/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  33
running loss:  nan
Train Steps: 33/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  34
running loss:  nan
Train Steps: 34/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  35
running loss:  nan
Train Steps: 35/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  36
running loss:  nan
Train Steps: 36/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  37
running loss:  nan
Train Steps: 37/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  38
running loss:  nan
Train Steps: 38/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  39
running loss:  nan
Train Steps: 39/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  40
running loss:  nan
Train Steps: 40/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  41
running loss:  nan
Train Steps: 41/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  42
running loss:  nan
Train Steps: 42/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  43
running loss:  nan
Train Steps: 43/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  44
running loss:  nan
Train Steps: 44/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  45
running loss:  nan
Train Steps: 45/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  46
running loss:  nan
Train Steps: 46/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  47
running loss:  nan
Train Steps: 47/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  48
running loss:  nan
Train Steps: 48/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  49
running loss:  nan
Train Steps: 49/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  50
running loss:  nan
Train Steps: 50/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  51
running loss:  nan
Train Steps: 51/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  52
running loss:  nan
Train Steps: 52/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  53
running loss:  nan
Train Steps: 53/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  54
running loss:  nan
Train Steps: 54/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  55
running loss:  nan
Train Steps: 55/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  56
running loss:  nan
Train Steps: 56/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  57
running loss:  nan
Train Steps: 57/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  58
running loss:  nan
Train Steps: 58/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  59
running loss:  nan
Train Steps: 59/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  60
running loss:  nan
Train Steps: 60/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  61
running loss:  nan
Train Steps: 61/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)

loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  62
running loss:  nan
Train Steps: 62/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  63
running loss:  nan
Train Steps: 63/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  64
running loss:  nan
Train Steps: 64/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  65
running loss:  nan
Train Steps: 65/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  66
running loss:  nan
Train Steps: 66/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  67
running loss:  nan
Train Steps: 67/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  68
running loss:  nan
Train Steps: 68/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  69
running loss:  nan
Train Steps: 69/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  70
running loss:  nan
Train Steps: 70/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  71
running loss:  nan
Train Steps: 71/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  72
running loss:  nan
Train Steps: 72/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  73
running loss:  nan
Train Steps: 73/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  74
running loss:  nan
Train Steps: 74/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  75
running loss:  nan
Train Steps: 75/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  76
running loss:  nan
Train Steps: 76/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  77
running loss:  nan
Train Steps: 77/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  78
running loss:  nan
Train Steps: 78/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  79
running loss:  nan
Train Steps: 79/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  80
running loss:  nan
Train Steps: 80/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  81
running loss:  nan
Train Steps: 81/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  82
running loss:  nan
Train Steps: 82/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  83
running loss:  nan
Train Steps: 83/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  84
running loss:  nan
Train Steps: 84/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  85
running loss:  nan
Train Steps: 85/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  86
running loss:  nan
Train Steps: 86/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  87
running loss:  nan
Train Steps: 87/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  88
running loss:  nan
Train Steps: 88/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  89
running loss:  nan
Train Steps: 89/90  Loss: nan loss_train_step before backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(nan, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  nan
step:  90
running loss:  nan
Valid Steps: 10/10  Loss: nan 
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Epoch: 1  Train Loss: nan Valid Loss: nan
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Training Complete
Total Elapsed Time : 95.49646234512329 s