```
to_tensor = transforms.ToTensor()
img = to_tensor(train_dataset[0]['image'])
img
```

Converts my images values between 0 and 1 which is expected. It also converts img which is an ndarray to a torch.Tensor

Previously, without using to_tensor (which I need it now), the following code snippet worked (not sure if this is best way to find means and stds of train set, however now doesn’t work. How can I make it work?

```
image_arr = []
for i in range(len(train_dataset)):
image_arr.append(to_tensor(train_dataset[i]['image']))
print(np.mean(image_arr, axis=(0, 1, 2)))
print(np.std(image_arr, axis=(0, 1, 2)))
```

The error is:

```
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-147-0e007c030629> in <module>
4 image_arr.append(to_tensor(train_dataset[i]['image']))
5
----> 6 print(np.mean(image_arr, axis=(0, 1, 2)))
7 print(np.std(image_arr, axis=(0, 1, 2)))
<__array_function__ internals> in mean(*args, **kwargs)
~/anaconda3/lib/python3.7/site-packages/numpy/core/fromnumeric.py in mean(a, axis, dtype, out, keepdims)
3333
3334 return _methods._mean(a, axis=axis, dtype=dtype,
-> 3335 out=out, **kwargs)
3336
3337
~/anaconda3/lib/python3.7/site-packages/numpy/core/_methods.py in _mean(a, axis, dtype, out, keepdims)
133
134 def _mean(a, axis=None, dtype=None, out=None, keepdims=False):
--> 135 arr = asanyarray(a)
136
137 is_float16_result = False
~/anaconda3/lib/python3.7/site-packages/numpy/core/_asarray.py in asanyarray(a, dtype, order)
136
137 """
--> 138 return array(a, dtype, copy=False, order=order, subok=True)
139
140
ValueError: only one element tensors can be converted to Python scalars
```