Commit Graph

10 Commits

Author SHA1 Message Date
4f1541526c dinov2 - read images from disk and compute the class probabilities (#503)
* Load the image from disk and convert it to a tensor.

* Tweak the function name.
2023-08-18 15:50:33 +01:00
c78ce76501 Add a simple Module trait and implement it for the various nn layers (#500)
* Start adding the module trait.

* Use the module trait.

* Implement module for qmatmul.
2023-08-18 09:38:22 +01:00
9af438ac1b Track the conv2d operations in stable-diffusion. (#431)
* Track the conv2d operations in stable-diffusion.

* Add more tracing to stable-diffusion.

* Also trace the resnet bits.

* Trace the attention blocks.

* Also trace the attention inner part.

* Small tweak.
2023-08-13 15:58:26 +01:00
3a62aee91f Write the generated images using the image crate. (#363)
* Use the image crate to write the generated images.

* Make the dependency optional.
2023-08-09 15:26:44 +01:00
2345b8ce3f Skeleton for the avg-pool2d and upsample-nearest2d ops. (#337)
* Skeleton for the avg-pool2d and upsample-nearest2d ops.

* Preliminary conv2d support.
2023-08-07 16:15:38 +01:00
f53a333ea9 Simple pad support. (#336)
* Simple pad support.

* Fix the tensor indexing when padding.
2023-08-07 15:24:56 +01:00
5bb2fce998 Implement group-norm. (#334)
* Implement group-norm.

* Add some testing for group-norm.
2023-08-07 06:53:05 +01:00
166bfd5847 Add the recip op + use it in stable-diffusion. (#331)
* Add the recip unary op.

* Fix the cuda kernel.

* Use the recip op in sigmoid.
2023-08-06 21:14:52 +01:00
1c062bf06b Add the ddim scheduler. (#330) 2023-08-06 20:44:00 +01:00
d34039e352 Add a stable diffusion example (#328)
* Start adding a stable-diffusion example.

* Proper computation of the causal mask.

* Add the chunk operation.

* Work in progress: port the attention module.

* Add some dummy modules for conv2d and group-norm, get the attention module to compile.

* Re-enable the 2d convolution.

* Add the embeddings module.

* Add the resnet module.

* Add the unet blocks.

* Add the unet.

* And add the variational auto-encoder.

* Use the pad function from utils.
2023-08-06 17:49:43 +01:00