Got it.

Sir, one more question.

As my data are tensor type, I have defined 54 signals in total. Now I want to insert them into a CNN network, which requires `(target, label)`

. In my case the target is in definition my data, however, its data has no labels as identifiers, this is my major problem. In fact, I want to assign to each data a label, to compile the designed network. I first enumerate each data as a label of each data, unfortunately, an error is raised `ValueError: only one element tensors can be converted to Python scalars`

. I proceeded like the codes below, but in vain.

```
def create_data_loader(train_data, batch_size):
train_dataloader = DataLoader(train_data, batch_size=batch_size)
print(train_dataloader)
return train_dataloader
```

```
for jj, y in enumerate(storage_data, index):
# print(jj, ". ", y)
train_data = (jj, y)
index += 1
print("My signals are : ", '\n', train_data, '\n')
```

So, how to label my data and make the training of my network? Here is an example listed below (the `54`

denotes the listing of the last data). Thanks in advance.

```
(54, tensor([[[ 6.7071e-49+9.6242e-67j, -5.7732e-53-1.1452e-50j,
1.0942e-50+1.2945e-51j, ...,
7.2834e-52-4.2107e-51j, 5.7082e-51-3.9200e-51j,
-4.9956e-51+6.2307e-51j],
[-5.7732e-53+1.1452e-50j, 6.6808e-49+8.0598e-67j,
-5.2926e-53-1.1456e-50j, ...,
3.8010e-51+2.0603e-51j, 7.3626e-52-4.2001e-51j,
5.6491e-51-3.8731e-51j],
[ 1.0942e-50-1.2945e-51j, -5.2926e-53+1.1456e-50j,
6.6689e-49+6.7971e-68j, ...,
5.4084e-51-6.5998e-51j, 3.7788e-51+1.9931e-51j,
7.7121e-52-4.1535e-51j],
...,
[ 7.2834e-52+4.2107e-51j, 3.8010e-51-2.0603e-51j,
5.4084e-51+6.5998e-51j, ...,
5.7495e-49+1.8567e-67j, -1.5623e-51-2.1687e-52j,
6.8474e-51-3.8617e-52j],
[ 5.7082e-51+3.9200e-51j, 7.3626e-52+4.2001e-51j,
3.7788e-51-1.9931e-51j, ...,
-1.5623e-51+2.1687e-52j, 5.7503e-49+2.4958e-67j,
-1.6490e-51-6.3735e-53j],
[-4.9956e-51-6.2307e-51j, 5.6491e-51+3.8731e-51j,
7.7121e-52+4.1535e-51j, ...,
6.8474e-51+3.8617e-52j, -1.6490e-51+6.3735e-53j,
5.7527e-49-5.1433e-67j]],
[[ 5.7611e-49-3.0056e-67j, -1.6267e-51+1.7540e-52j,
6.8346e-51-5.1263e-52j, ...,
-2.2249e-52-4.9047e-51j, 5.2019e-51-2.8803e-51j,
-6.4842e-51+6.2802e-51j],
[-1.6267e-51-1.7540e-52j, 5.7591e-49-1.2227e-67j,
-1.7296e-51+3.3187e-52j, ...,
4.2446e-51+3.1161e-51j, -2.9077e-52-4.8340e-51j,
5.2237e-51-2.8507e-51j],
[ 6.8346e-51+5.1263e-52j, -1.7296e-51-3.3187e-52j,
5.7666e-49-4.0239e-67j, ...,
4.7945e-51-7.9020e-51j, 4.3089e-51+3.1792e-51j,
-2.3726e-52-4.8676e-51j],
...,
[-2.2249e-52+4.9047e-51j, 4.2446e-51-3.1161e-51j,
4.7945e-51+7.9020e-51j, ...,
7.2150e-49+5.8171e-67j, -3.9169e-51+1.2124e-50j,
5.8248e-51-3.1926e-51j],
[ 5.2019e-51+2.8803e-51j, -2.9077e-52+4.8340e-51j,
4.3089e-51-3.1792e-51j, ...,
-3.9169e-51-1.2124e-50j, 7.2353e-49-4.0999e-67j,
-3.9812e-51+1.2184e-50j],
[-6.4842e-51-6.2802e-51j, 5.2237e-51+2.8507e-51j,
-2.3726e-52+4.8676e-51j, ...,
5.8248e-51+3.1926e-51j, -3.9812e-51-1.2184e-50j,
7.2597e-49+2.2527e-67j]]], dtype=torch.complex128))
```