Now it is working to some extent. But loss calculated for only  one iteration, dont know what is wrong here.
python classfn3daj3.py
15
[[6.01671520e+05 4.49484606e+06 3.98000000e+00 … 0.00000000e+00
0.00000000e+00 0.00000000e+00]
[6.05909290e+05 4.49509237e+06 1.21200000e+01 … 0.00000000e+00
0.00000000e+00 0.00000000e+00]
[5.97163600e+05 4.49254968e+06 5.94000000e+00 … 0.00000000e+00
0.00000000e+00 0.00000000e+00]
…
[6.01516880e+05 4.49428028e+06 8.25000000e+00 … 0.00000000e+00
0.00000000e+00 0.00000000e+00]
[5.92138930e+05 4.49045314e+06 5.42000000e+00 … 0.00000000e+00
0.00000000e+00 0.00000000e+00]
[6.04355840e+05 4.49610921e+06 1.15700000e+01 … 0.00000000e+00
0.00000000e+00 0.00000000e+00]]
tensor([[6.0167e+05, 4.4948e+06, 3.9800e+00,  …, 0.0000e+00, 0.0000e+00,
0.0000e+00],
[6.0591e+05, 4.4951e+06, 1.2120e+01,  …, 0.0000e+00, 0.0000e+00,
0.0000e+00],
[5.9716e+05, 4.4925e+06, 5.9400e+00,  …, 0.0000e+00, 0.0000e+00,
0.0000e+00],
…,
[6.0152e+05, 4.4943e+06, 8.2500e+00,  …, 0.0000e+00, 0.0000e+00,
0.0000e+00],
[5.9214e+05, 4.4905e+06, 5.4200e+00,  …, 0.0000e+00, 0.0000e+00,
0.0000e+00],
[6.0436e+05, 4.4961e+06, 1.1570e+01,  …, 0.0000e+00, 0.0000e+00,
0.0000e+00]])
size of tensor points torch.Size([15, 3480])
-tensor label points**********************************-
tensor([0, 1, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 1, 0, 1])
size of tensor label torch.Size([15])
the points after returing to class… tensor([[6.0167e+05, 4.4948e+06, 3.9800e+00,  …, 0.0000e+00, 0.0000e+00,
0.0000e+00],
[6.0591e+05, 4.4951e+06, 1.2120e+01,  …, 0.0000e+00, 0.0000e+00,
0.0000e+00],
[5.9716e+05, 4.4925e+06, 5.9400e+00,  …, 0.0000e+00, 0.0000e+00,
0.0000e+00],
…,
[6.0152e+05, 4.4943e+06, 8.2500e+00,  …, 0.0000e+00, 0.0000e+00,
0.0000e+00],
[5.9214e+05, 4.4905e+06, 5.4200e+00,  …, 0.0000e+00, 0.0000e+00,
0.0000e+00],
[6.0436e+05, 4.4961e+06, 1.1570e+01,  …, 0.0000e+00, 0.0000e+00,
0.0000e+00]])
Custom-b_from_csv… <main.BDatasetFromCSV object at 0x7f7d8f54fa90>
**--------------------------------------
<torch.utils.data.dataloader.DataLoader object at 0x7f7d7f7a9160>
size of dataloader… 15
/home/raman/anaconda2/envs/pyto3/lib/python3.6/site-packages/torch/cuda/init.py:116: UserWarning:
Found GPU1 NVS 315 which is of cuda capability 2.1.
PyTorch no longer supports this GPU because it is too old.
warnings.warn(old_gpu_warn % (d, name, major, capability[1]))
the model is … NeuralNet(
(fc1): Linear(in_features=3480, out_features=10, bias=True)
(relu): ReLU()
(fc2): Linear(in_features=10, out_features=3, bias=True)
)
the points after getting to class… tensor([6.0167e+05, 4.4948e+06, 3.9800e+00,  …, 0.0000e+00, 0.0000e+00,
0.0000e+00])
i is … 0
The points tensor from dataloader… tensor([[6.0167e+05, 4.4948e+06, 3.9800e+00,  …, 0.0000e+00, 0.0000e+00,
0.0000e+00]])
The labels tensor from dataloader … tensor([0])
Type of data before giving to model  torch.cuda.FloatTensor
Type of data inside model  torch.cuda.FloatTensor
Loss is … tensor(394650.5000, device=‘cuda:0’, grad_fn=)