Initial Checks
!conda list | grep "pytorch"
pytorch 2.0.1 py3.11_cuda11.8_cudnn8.7.0_0 pytorch
pytorch-cuda 11.8 h7e8668a_5 pytorch
pytorch-ignite 0.4.12 pypi_0 pypi
pytorch-lightning 2.0.7 pypi_0 pypi
pytorch-mutex 1.0 cuda pytorch
torchaudio 2.0.2 py311_cu118 pytorch
torchtriton 2.0.0 py311 pytorch
torchvision 0.15.2 py311_cu118 pytorch
!pip list | grep "fastai"
!pip list | grep "fastbook"
!pip list | grep "ipywidgets"
fastai 2.7.12
fastbook 0.0.28
ipywidgets 8.1.0
torch.cuda.is_available()
“UNET”
- input - somewhat noisy image
- output - the noise
image = image + noise
Model trained to calculate noise in a image
Autoencoder = “VAE”
Model trained to compress and decompress images
Latents
latents = Autoencoders middle output (compressed version of the image)
CLIP
CL - Contrast loss
model trained to create image latents from text input
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