[PY] refactoring - move devices-related functions from tvm.runtime.ndarray

[pfk-beta]

Hello,

I'm not sure whether it needs RFC, but it was little messy in python runtime code (related to my answer, not main thread in this post https://discuss.tvm.apache.org/t/pre-rfc-more-meaningful-names-in-rpc-module-in-python/12618). I have moved device, cpu, cuda, gpu, opencl, cl, vulkan, metal, mtl, vpi, rocm, ext_dev functions from tvm.runtime.ndarray to tvm.runtime.devices and reimported them in tvm.runtime, so we can use following statement:

import tvm.runtime
runtime.cpu(0)

In previous version there was mix of following:

import tvm
tvm.cpu()

from tvm.runtime import ndarray as _nd
_nd.cuda(0)

[tqchen]

Thanks @pfk-beta , the original rationale was that device is closely coupled with ndarray itself(as ndarray is the only places that device get allocated).

Re-exposing the devices under tvm.runtime namespace would indeed be a readability improvement. From UX's pov we intentionally expose tvm.cpu/tvm.cuda not for internal development but for users, so we would like to keep those exposures to avoid API breaking.

For the same reason(although weaker as there are less usages here), we might want to to keep nd.device usages when possible for one version. Personally i think putting devices definition as separate file or in ndarray do not have a big difference, although in this case it does bring a minor readability gain.

One simple approach is to re-expose nd.cpu etc in the runtime namespace, and use runtime.device in most of the places you mention. This would be the least surgical change while retains the readability part.

[pfk-beta]

Re-exposing the devices under tvm.runtime namespace

You mean devices - functions, not module which I created, right? They were already exposed, I just standrized imports and usage of them. Even python api documentation list these functions in tvm.runtime (https://tvm.apache.org/docs/reference/api/python/runtime.html)

From UX's pov we intentionally expose tvm.cpu/tvm.cuda not for internal development but for users, so we would like to keep those exposures to avoid API breaking.

That is why, I didn't remove devices functions from top tvm module. I think we should put this informations in guideline for python developers, which want to contribute to TVM. Because I refactored mix of usage, and I don't want do this again :) Is there such guideline, or should we create one?

My proposition is:

• we have devices.py with devices functions
• they will be imported in ndarray, for backward compatibility (explain when we should use nd.<device>)
• we still have devices availabe through import tvm and import tvm.runtime - runtime.<device> is used for most of the internal developers, tvm.<device> is used for tvm users.
• we put these informations to python contribution guideline - is this place https://tvm.apache.org/docs/contribute/code_guide.html#python-code-styles suitable?

[tqchen]

Thanks @pfk-beta . I agree this is a positive change towards readability. Please check the linter error(all new files needs ASF header). The overall convention of using tvm.runtime.device sounds good. Although I do not think we should prevent developers from using tvm.device itself as this is also what intended for the users

[pfk-beta]

Although I do not think we should prevent developers from using tvm.device itself as this is also what intended for the users

To clarify, you mean using tvm.device.cuda or tvm.cuda?

[tqchen]

sorry, i meant tvm.cuda