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* Load the image from disk and convert it to a tensor.
* Tweak the function name.
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* Start adding the module trait.
* Use the module trait.
* Implement module for qmatmul.
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* 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.
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* Use the image crate to write the generated images.
* Make the dependency optional.
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* Skeleton for the avg-pool2d and upsample-nearest2d ops.
* Preliminary conv2d support.
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* Simple pad support.
* Fix the tensor indexing when padding.
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* Implement group-norm.
* Add some testing for group-norm.
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* Add the recip unary op.
* Fix the cuda kernel.
* Use the recip op in sigmoid.
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* 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.
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