Crash when calling MacenkoNormalizer.fit with tensorflow backend

Hi,
I am sorry if my question is trivial but I have trouble using this package with the tensorflow backend.
Using torchstain 1.2.0, I have no problem performing a Macenko normalization with numpy. But as I try with tensorflow, it crashes using normalizer.fit

```
target_path = '/XXX.jpg'
target = cv2.cvtColor(cv2.imread(target_path), cv2.COLOR_BGR2RGB)
tf_normalizer = torchstain.normalizers.MacenkoNormalizer(backend='tensorflow')
```

The only thing that I am doing differently from the provided example is the tensor conversion of the numpy array.
That is, I am not doing this

```
T = transforms.Compose([
transforms.ToTensor(),
transforms.Lambda(lambda x: x*255)
])
```

But rather tried this to match the transformation:

```
target = tf.constant(target, dtype=tf.float32) #convert to tensor
target = tf.transpose(target, perm=[2, 0, 1]) #channel first

tf_normalizer.fit(target)
```

Is this why it crashes ? Is there a way to run this without using torchvision.transforms/on a pure TF basis?

I am using Tensorflow_2.10.0 and have installed torchstain using pip install torchstain[tf].
I currently do not use nor have installed torchvision in my TF environment.

Thank you for your advice