CUDA-only PyTorch operations for Apple Silicon - metapackage
Project description
MPS Ops
CUDA-only PyTorch operations for Apple Silicon.
This metapackage installs all mpsops packages - Metal implementations of operations that are typically CUDA-only.
Installation
Install everything:
pip install mpsops
Or install individual packages:
pip install mps-flash-attn # Flash attention
pip install mps-bitsandbytes # Quantized ops
pip install mps-deform-conv # Deformable convolution
pip install mps-correlation # Optical flow correlation
pip install mps-carafe # Content-aware upsampling
pip install mps-conv3d # 3D convolution for video
Packages
| Package | Description | Use Case |
|---|---|---|
| mps-flash-attn | Flash Attention | Transformers, LLMs |
| mps-bitsandbytes | 8-bit/4-bit quantization | LLM inference, QLoRA |
| mps-deform-conv | Deformable convolution | Object detection (DETR, DCN) |
| mps-correlation | Correlation layer | Optical flow (RAFT, PWC-Net) |
| mps-carafe | CARAFE upsampling | Segmentation (Mask R-CNN) |
| mps-conv3d | 3D Convolution | Video models (I3D, SlowFast, MMAudio) |
Quick Start
import mpsops
# Check what's installed
mpsops.print_status()
# Use the ops directly
from mpsops import flash_attn_func, deform_conv2d, correlation, carafe, conv3d, patch_conv3d
Compatibility
- PyTorch: 2.0+
- macOS: 12.0+ (Monterey)
- Hardware: Apple Silicon (M1/M2/M3/M4)
Why?
Many state-of-the-art models use CUDA-only operations:
- LLMs need flash attention and quantization
- Object detection needs deformable convolution
- Optical flow needs correlation layers
- Segmentation needs specialized upsampling
On Mac, you get errors like:
NotImplementedError: flash_attn not implemented for MPS
MPS Ops provides native Metal implementations so these models run on Apple Silicon.
License
MIT
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