# How to get the correct shape of the tensor in custom dataset

**URL:** <https://discuss.pytorch.org/t/how-to-get-the-correct-shape-of-the-tensor-in-custom-dataset/80378>\
**Category:** Uncategorized\
**Created:** [May 8, 2020, 9:51pm UTC](https://discuss.pytorch.org/t/how-to-get-the-correct-shape-of-the-tensor-in-custom-dataset/80378 "2020-05-08T21:51:32Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![olisp](https://discuss.pytorch.org/letter_avatar_proxy/v4/letter/o/e79b87/32.png) [@olisp](https://discuss.pytorch.org/u/olisp)\
**Post date:** [May 8, 2020, 9:51pm UTC](https://discuss.pytorch.org/t/how-to-get-the-correct-shape-of-the-tensor-in-custom-dataset/80378/1 "2020-05-08T21:51:32Z")

</div>

Hello,

I am using custom `Dataset` class, but the problem is that when I get the data from the `Dataloader` I am left with `array` that has different tensor shape than I want.

shape that I get: `torch.Size([1, 56, 128, 128])`  
shape that I want: `torch.Size([1, 56, 1, 128, 128])`

my approach was to:

1. to apply `numpy.expand_dims` on the `array` and get `torch.Size([1, 1, 56, 128, 128])`

2. then to `np.transpose` on the `array` to get the shape I want `torch.Size([1, 56, 1, 128, 128])`

after first step I am getting the error:

```auto
raise ValueError('pic should be 2/3 dimensional. Got {} dimensions.'.format(pic.ndim))
ValueError: pic should be 2/3 dimensional. Got 4 dimensions.

```

if I do the transpose first, none of the combination of `np.transpose(array, axes=(1,2,0))` yields the shape `torch.Size([56, 1, 128, 128])`

if I convert `array` to `Tensor` first and then do `torch.unsqueeze` I get the error:

```auto

raise TypeError('pic should be PIL Image or ndarray. Got {}'.format(type(pic)))
TypeError: pic should be PIL Image or ndarray. Got <class 'torch.Tensor'>

```

here is my code:

```auto
class patientdataset(Dataset):
    def __init__ (self, csv_file, root_dir, transform=None):
        self.annotations = pd.read_csv(csv_file)
        self.root_dir = root_dir
        self.transform = transform

    def __len__ (self):
        return len(self.annotations)

    def __getitem__ (self, index):
        img_path = os.path.join(self.root_dir, self.annotations.iloc[index,0])
        # np_load_old = np.load
        # np.load = lambda *a, **k: np_load_old(*a, allow_pickle=True,**k)

        image= np.asarray(np.load(img_path))

        image= np.transpose(image, axes=(1,2,0))
        image = torch.Tensor (image)

        image = torch.unsqueeze(image, dim=1)

        y_label = torch.tensor(np.asarray(self.annotations.iloc[index,1]))

        if self.transform:
            image = self.transform(image)

        return (image, y_label)

```

---

<div class="post-metadata">

**Author:** ![klory](https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/klory/32/5814_2.png) [@klory](https://discuss.pytorch.org/u/klory)\
**Post date:** [May 8, 2020, 10:50pm UTC](https://discuss.pytorch.org/t/how-to-get-the-correct-shape-of-the-tensor-in-custom-dataset/80378/2 "2020-05-08T22:50:05Z")

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your code should be fine, can you provide the call stack for the error?