Cannot convert list to array: ValueError: only one element tensors can be converted to Python scalars

Question

I'm currently working with the PyTorch framework and trying to understand foreign code. I got an indices issue and wanted to print the shape of a list.
The only way of doing so (as far as Google tells me) is to convert the list into a numpy array and then getting the shape with numpy.ndarray.shape().

But trying to convert my list into an array, I got a ValueError: only one element tensors can be converted to Python scalars.

My List is a converted PyTorch Tensor (list(pytorchTensor)) and looks somewhat like this:

[
tensor([[-0.2781, -0.2567, -0.2353,  ..., -0.9640, -0.9855, -1.0069],  
        [-0.2781, -0.2567, -0.2353,  ..., -1.0069, -1.0283, -1.0927],  
        [-0.2567, -0.2567, -0.2138,  ..., -1.0712, -1.1141, -1.1784],  
        ...,  
        [-0.6640, -0.6425, -0.6211,  ..., -1.0712, -1.1141, -1.0927],  
        [-0.6640, -0.6425, -0.5997,  ..., -0.9426, -0.9640, -0.9640],  
        [-0.6640, -0.6425, -0.5997,  ..., -0.9640, -0.9426, -0.9426]]),

tensor([[-0.0769, -0.0980, -0.0769,  ..., -0.9388, -0.9598, -0.9808],  
        [-0.0559, -0.0769, -0.0980,  ..., -0.9598, -1.0018, -1.0228],    
        [-0.0559, -0.0769, -0.0769,  ..., -1.0228, -1.0439, -1.0859],  
        ...,  
        [-0.4973, -0.4973, -0.4973,  ..., -1.0018, -1.0439, -1.0228],  
        [-0.4973, -0.4973, -0.4973,  ..., -0.8757, -0.9177, -0.9177],  
        [-0.4973, -0.4973, -0.4973,  ..., -0.9177, -0.8967, -0.8967]]),

tensor([[-0.1313, -0.1313, -0.1100,  ..., -0.8115, -0.8328, -0.8753],  
        [-0.1313, -0.1525, -0.1313,  ..., -0.8541, -0.8966, -0.9391],  
        [-0.1100, -0.1313, -0.1100,  ..., -0.9391, -0.9816, -1.0666],  
        ...,  
        [-0.4502, -0.4714, -0.4502,  ..., -0.8966, -0.8966, -0.8966],  
        [-0.4502, -0.4714, -0.4502,  ..., -0.8115, -0.8115, -0.7903],  
        [-0.4502, -0.4714, -0.4502,  ..., -0.8115, -0.7690, -0.7690]]),
]

Is there a way of getting the shape of that list without converting it into a numpy array?

Not sure if you had the same issue but I was trying to convert a nested list of torch tensors to a bigger tensor that respected the nesting by having more indices/dimensions for the final tensor. I found that incrementally growing the list of torch tensors and then to torch.stack it helped. I wrote a non recursive example but I think it should be easy to extend it. Hope it helps: stackoverflow.com/questions/54307225/… — Charlie Parker
– Charlie Parker, Commented Feb 4, 2021 at 17:33
@CharlieParker I was trying to do the same thing. it should work. but it doesn't!! — user3180
– user3180, Commented Apr 30, 2021 at 4:11

Mateen Ulhaq · Accepted Answer · 2022-03-29 06:14:28Z

39

It seems like you have a list of tensors. For each tensor you can see its size() (no need to convert to list/numpy). If you insist, you can convert a tensor to numpy array using numpy():

Return a list of tensor shapes:

>> [t.size() for t in my_list_of_tensors]

Returns a list of numpy arrays:

>> [t.numpy() for t in my_list_of_tensors]

In terms of performance, it is always best to avoid casting of tensors into numpy arrays, as it may incur sync of device/host memory. If you only need to check the shape of a tensor, use size() function.

edited Mar 29, 2022 at 6:14

Mateen Ulhaq

27.9k21 gold badges121 silver badges155 bronze badges

answered Aug 29, 2018 at 10:10

Shai

115k39 gold badges259 silver badges398 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

Koke Cacao · Accepted Answer · 2018-10-31 22:53:59Z

7

The simplest way to convert pytorch tensor to numpy array is:

nparray = tensor.numpy()

Also, for size and shape:

tensor_size = tensor.size()
tensor_shape = tensor.shape()
tensor_size
>>> (1080)
tensor_shape
>>> (32, 3, 128, 128)

answered Oct 31, 2018 at 22:53

Koke Cacao

4836 silver badges9 bronze badges

Comments

loretoparisi · Accepted Answer · 2021-06-11 17:50:55Z

5

A real-world example, would require to handle torch no grad issue:

with torch.no_grad():
    probs = [t.numpy() for t in my_tensors]

or

probs = [t.detach().numpy() for t in my_tensors]

answered Jun 11, 2021 at 17:50

loretoparisi

16.3k12 gold badges113 silver badges159 bronze badges

Collectives™ on Stack Overflow

Cannot convert list to array: ValueError: only one element tensors can be converted to Python scalars

3 Answers 3

Comments

Comments

Comments

Your Answer

Linked

Hot Network Questions

Collectives™ on Stack Overflow

3 Answers 3

Comments

Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Linked

Related