Volutionn

Thank you for your reply! As requested, here's a minimum code snippet that contains **deform_conv2d**: ```python import torch from torchvision.ops import deform_conv2d import coremltools as ct class DeformConv2DModel(torch.nn.Module): def __init__(self):...

Hello, I was wondering if there's any update regarding the support of the deform_conv2d operation? Thank you!

Thank you @TobyRoseman for looking into this. Based on my understanding of the topic, the PyTorch implementation references the following two papers: [Deformable ConvNets](https://arxiv.org/pdf/1703.06211.pdf) [Deformable ConvNets v2](https://arxiv.org/pdf/1811.11168.pdf) I've summarized the...

That's what I understand about the `deform_conv2d` operation in PyTorch: it supports both Deformable Convolution versions 1 and 2, including the modulated formulas. When the `mask` parameter is `None`, it...

@bitanath I imagine it's just a complex operator to add. I tried to implement it using composite operators, but without any success. Hopefully, this hasn't been abandoned on @TobyRoseman's side;...

Wow, you made my day! That's amazing, thanks a lot for sharing it @dneprDroid 🙏🏻

Was looking for a solution to this exact issue—having it random would make it much more useful.

### Quick Fix If you're looking for a quick solution, here's what worked for me: 1. Open the following file: [invokeai_directory]/.venv/lib/python3.x/site-packages/invokeai/app/api/routers/utilities.py 2. Locate the function `parse_dynamicprompts`. 3. Update the following...

> Great, thanks. The only caveat left is that at always generates the same combinations on consecutive batches. If it would just reshuffle them after a users submission it would...

Thank you for your help! I assumed it was an issue with my custom build for iOS, but I just tried the macOS build (M1) and encountered issues there as...