I have made train and validation splits of data using sklearn splits. The results of sklearn splits are of nd array type , i am converting them to tensor before building data loader , but I am getting an assertion error

```
from torch.utils.data import TensorDataset
from torch.utils.data import DataLoader
x_tr = torch.tensor(x_tr, dtype=torch.long)
y_tr = torch.tensor(y_tr, dtype=torch.float32)
Train = TensorDataset(x_tr, y_tr)
Trainloader = DataLoader(Train, batch_size=128)
x_valid2 = torch.tensor(x_valid2, dtype=torch.long)
y_valid2 = torch.tensor(y_valid2, dtype=torch.float32)
valid2 = TensorDataset(x_valid2, y_valid2)
validloader2 = DataLoader(valid2, batch_size=128)
```

Error is as follows:

AssertionError Traceback (most recent call last)

in ()

32 x_tr = torch.tensor(x_tr, dtype=torch.long)

33 y_tr = torch.tensor(y_tr, dtype=torch.float32)

—> 34 Train = TensorDataset(x_tr, y_tr)

35 Trainloader = DataLoader(Train, batch_size=128)

36

```
/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataset.py in __init__(self, *tensors)
156
157 def __init__(self, *tensors):
--> 158 assert all(tensors[0].size(0) == tensor.size(0) for tensor in tensors)
159 self.tensors = tensors
160
AssertionError:
```

I also tried to convert the the nd arrays to tensors using torch.numpy(), to mitigate the issue, but still this error at Tensordataset before data loader persists.

Any help is appreciated.