Basic Usage

Loading Kernels

Here is how you would use the activation kernels from the Hugging Face Hub:

import torch
from kernels import get_kernel

# Download optimized kernels from the Hugging Face hub
activation = get_kernel("kernels-community/activation", version=1)

# Create a random tensor
x = torch.randn((10, 10), dtype=torch.float16, device="cuda")

# Run the kernel
y = torch.empty_like(x)
activation.gelu_fast(y, x)

print(y)

This fetches version 1 of the kernel kernels-community/activation. Kernels are versioned using a major version number. Using version=1 will get the latest kernel build from the v1 branch.

Kernels within a version branch must never break the API or remove builds for older PyTorch versions. This ensures that your code will continue to work.

Checking Kernel Availability

You can check if a particular version of a kernel supports the environment that the program is running on:

from kernels import has_kernel

# Check if kernel is available for current environment
is_available = has_kernel("kernels-community/activation", version=1)
print(f"Kernel available: {is_available}")