I love what you guys are doing, and I love improving the ML ecosystem, but you’ve godda understand, people see this and think “oh, ok, it’s a small difference, no big deal.” In fact it’s a huge difference.
Picture a person with one arm and without legs. Would you say they aren’t “1:1 in terms of features”? They certainly won’t be winning any races.
And unlike real people, you can’t graft on a prosthetic limb to help this situation. The issue I’m describing here is a fundamental one that everyone keeps trying to sweep under the rug and pretend isn’t an issue. And then everyone wonders what’s going on.
I 100% agree. We don't want to misrepresent TPU support. In fact, we explicitly warn users in our docs. Open to suggestions about how we can communicate this much better to our users.
We just need to be a part of the effort to help bridge the big gap and barriers keeping users from TPU adoption.
Comments
I love what you guys are doing, and I love improving the ML ecosystem, but you’ve godda understand, people see this and think “oh, ok, it’s a small difference, no big deal.” In fact it’s a huge difference.
Picture a person with one arm and without legs. Would you say they aren’t “1:1 in terms of features”? They certainly won’t be winning any races.
And unlike real people, you can’t graft on a prosthetic limb to help this situation. The issue I’m describing here is a fundamental one that everyone keeps trying to sweep under the rug and pretend isn’t an issue. And then everyone wonders what’s going on.
I 100% agree. We don't want to misrepresent TPU support. In fact, we explicitly warn users in our docs. Open to suggestions about how we can communicate this much better to our users.
We just need to be a part of the effort to help bridge the big gap and barriers keeping users from TPU adoption.
https://pytorch-lightning.readthedocs.io/en/latest/tpu.html#...
This was mentioned above, but nowhere on that page does it talk about any limitations whatsoever.