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Diogo 02de234ef0 Activations LeakyReLU / PReLU / Softplus / Mish (#109) 
* Leaky_relu / prelu / softplus / mish

* added tests

* updated bench

* remove torch refs, add init to PReLU

* added arvix reference to mish

* added missing docs
2023-12-11 19:40:57 -08:00
..
bench_mlx.py
Activations LeakyReLU / PReLU / Softplus / Mish (#109)
2023-12-11 19:40:57 -08:00
bench_torch.py
Activations LeakyReLU / PReLU / Softplus / Mish (#109)
2023-12-11 19:40:57 -08:00
compare.py
Activations LeakyReLU / PReLU / Softplus / Mish (#109)
2023-12-11 19:40:57 -08:00
README.md
awni's commit files
2023-11-29 10:30:41 -08:00

README.md

Microbenchmarks comparing MLX to PyTorch

Implement the same microbenchmarks in MLX and PyTorch to compare and make a list of the biggest possible performance improvements and/or regressions.

Run with python bench_mlx.py sum_axis --size 8x1024x128 --axis 2 --cpu for instance to measure the times it takes to sum across the 3rd axis of the above tensor on the cpu.

compare.py runs several benchmarks and compares the speed-up or lack thereof in comparison to PyTorch.

Each bench script can be run with --print-pid to print the PID and wait for a key in order to ease attaching a debugger.