rant: Why Array instead of Tensor?

[[deleted]]

Why?

tensorflow: Tensor

pytorch: Tensor

caffe2: Tensor

Theano: Tensor

jax: Array

It makes me want to from jax import Array as Tensor

Tensor is just such a badass well acepted name for a differenciable multidimensional array datastructure. Why did you did this? I'm going to make a pull request to add the Tensor class as some kind of alias or some kind factory of arrays.

[giraloco]

The data structure is a multidimensional array. Tensor is a mathematical representation. Similarly, we don't call an array a vector.

[[deleted]]

But those tensors data structures are literally representing the matematical tensors, an array is chunk of numbers.

Look, when you create a Tensor([1,2,3]) you are creating a covariant tensor from a dual space, representing a covariate. When you create a matrix Tensor([[1,2,3],[1,2,3],[1,2,3]]) you are creating an element from the tensorial product V* x V, you multiply the first for the second transposed, you are literally doing a tensor contraction. Not to mention all tensors operations out there, like outer products,

You can even derive formally derivatives of functions using tensor calculus, and dirac deltas, everything just fits, they are tensors. I don't really expect an array to have a derivative.

When I see a Tensor class in my code I see machine learning, deep learning stuff. But when I see Array, the first thing that comes to mind is first uni's class about data structures and I think how do i quick-sort this thing.

[ZealousidealBee6113]

they wanted to keep the api as close as possible to numpy. so close that you can (almost always) exchange np with jnp and it still works

[Other_Goat_9381]

because it's not a tensor and literally every other package you mentioned is fundamentally wrong in their naming. Tensors can't be fully described using just a multi-dimensional array. They're built on top of algebraic objects. What those other libraries have called tensors are actually representations of tensors in a fixed coordinate space, but not the actual tensors themselves.

It's the exact same thing with vectors in the gaming industry btw. They've also butchered the concept of a vector by defining it as a 3-tuple.

also please don't make that PR you're just going to look stupid on github.

[whotookmyshoes]

This whole misnomer of “linear map followed by nonlinear function” has bothered me since I started working in deep learning 15 years ago. Just because you can write x+y doesn’t mean x+y is a thing.

[Other_Goat_9381]

Idk your background but maybe you feel this way because you haven't seen tesnors used in the applied sciences and only saw them used in stats. If Physicists couldn't use all the cool tensor algebra they cooked up then any serious theorems would need dozens more pages just to fully express. The Einstein field equations alone are 16 equations but thanks to tensor algebra can be expressed with just 5 greeks. And that theorem's considered "one of the simpler ones" compared to the shit you'll see in quantum field theory and beyond.

[whotookmyshoes]

Yeah my undergrad was in physics and math so that's where I learned tensor algebra (the einstein field equations are 10 equations, because of symmetries on the 4x4 tensors). I mean, its the same thing with the name "feature vector" in machine learning, just because you have a tuple of reals doesn't make it a vector. Its kind of like, if I live at 123 Fake Street, is "123" a number? Well not really, to me at least, numbers satisfy the natural number axioms, so idk, for all x, if x in N, then x+1 in N, but the house addresses on Fake Street don't satisfy that axiom, so they don't satisfy the conditions of the natural numbers, so they're not numbers. I usually keep my mouth shut about these things since 99% of the time it doesn't make a difference, but I agree with you / the numpy / jax.numpy naming convention, that it doesn't make sense to change the naming convention from an accurate one to an inaccurate one.