elbencho VS Pytorch

You can also use elbencho (https://github.com/breuner/elbencho) which is functionally equivalent to IOR but a little more flexible.

I won't speak for him but Tallis is definitely aware (see his recent article on updated testing) and so are others. I regularly work with Sean Webster of Tom's Hardware (/u/TurboSSD) and we spend an insane amount of time working around SLC cache response and discussing it on my discord. These guys often use different tools (e.g. Iometer vs. FIO) although the one I've been playing with moving forward is elbencho. Either way, it's something that takes up a lot of time in SSD reviewer circles since it's a relatively tightknit group. It's a challenging topic especially as SLC caching algorithms are getting more complex, with behavioral and performance-based profiles and reviewers already doing preconditioning.

> does PyTorch have a similar concept

of course https://github.com/pytorch/pytorch/blob/main/torch/utils/_py...

fyi should work on most 40xx[1]

[1] https://github.com/pytorch/pytorch/issues/119638#issuecommen...

Sure, right here: https://github.com/pytorch/pytorch/blob/main/torch/autograd/...

Here's the documentation: https://pytorch.org/tutorials/intermediate/forward_ad_usage....

> When an input, which we call “primal”, is associated with a “direction” tensor, which we call “tangent”, the resultant new tensor object is called a “dual tensor” for its connection to dual numbers[0].

*My post explains Dot, Matrix and Element-wise multiplication in PyTorch.

In PyTorch with @, dot() or matmul():

import torch # we use PyTorch: https://pytorch.org data = torch.tensor(encode(text), dtype=torch.long) print(data.shape, data.dtype) print(data[:1000]) # the 1000 characters we looked at earlier will to the GPT look like this

AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.

Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework.

In PyTorch with * or mul(). ` or mul()` can multiply 0D or more D tensors by element-wise multiplication:

When I was at Facebook, I wrote a Python script to extract shell scripts from GitHub Actions workflows, so we could run them all through ShellCheck: https://github.com/pytorch/pytorch/blob/69e0bda9996865e319db...