Creating a tensor from array versus a numpy array

[tgkolda]

It seems that ttb.tensor only supports creating a tensor from a numpy array. Is there any reason it cannot create a tensor directly from a Python array?

Right now, the user has to type the following:

X = ttb.tensor(np.array([8, 9, 2, 9, 6, 1, 3, 5]), (2, 2, 2));

I'm suggesting instead that the following should be possible:

X = ttb.tensor([8, 9, 2, 9, 6, 1, 3, 5], (2, 2, 2));

Also, I'm not sure where the creation is clearly documented. I sort of inferred that it had to be a numpy array, but it's not clearly stated nor is there any example where you specify a simple tensor like this one.

[ntjohnson1]

I see the potential additional user friendliness to the later. Will share some thoughts but I'd be interested to hear Danny's thoughts on it.

A python list is effectively a list of pointers so it can be a collection of arbitrary types, and isn't contiguous in memory. Internally we'd have to convert to a numpy array, and make a decision about when to complain that the conversion isn't appropriately accurate. If we do make this move we can probably generate a utility to help for it, and we'd want to push that interface change out across the project, since right now I think for all numeric containers we've be requiring numpy arrays as the defacto python standard.

As for the documentation can you clarify what you were looking at?
help(ttb.tensor) vs https://pyttb.readthedocs.io/en/latest/tensor.html we do have types in the signature, and a very basic example where we provide a numpy array to construct a tensor. But I'm not sure where a new user looks first.

[tgkolda]

I was looking at the tutorials. I think most folks will start there, though they are in a sort of random order rather than structured like in the MATLAB help pages. I was looking here: https://pyttb.readthedocs.io/en/latest/tutorial/class_tensor.html.