How to count the number of parameters of a NN and measure FLOPs required for the NN from fvcore.nn import FlopCountAnalysisdef count_parameters(model): return sum(p.numel() for p in model.parameters() if p.requires_grad) ResNet = ConvNet(use_pretrained=True, feature_extract=False, resent_model=saved_args.resnet_model)N_param = count_parameters(ResNet) / 1e6input_tensor = torch.randn(1, 3, 320, 640)flops = FlopCountAnalysis(ResNet, input_tensor.. 더보기 Install a conda environment compatible with 'Resnoise' 0. install miniconda1. create conda env$ conda create -y -n resnoise python=3.82. activate created env$ source activate cvt3. install pytorch lightening through pip$ pip install pytorch-lightening==1.9.0 4. Reinstall pytorch, torchvision, cuda toolkit$ pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 --extra-index-url https://download.pytorch.org/whl/cu113 https://download.pytorch.org/w.. 더보기 Denoising Diffusion Probabilistic model (1) https://towardsdatascience.com/diffusion-model-from-scratch-in-pytorch-ddpm-9d9760528946 Diffusion Model from Scratch in PytorchImplementation of Denoising Diffusion Probabilistic Models (DDPM)towardsdatascience.com (2) https://jang-inspiration.com/ddpm-1https://jang-inspiration.com/ddpm-2 [논문리뷰] DDPM: Denoising Diffusion Probabilistic ModelDDPM의 Loss Function과 각 term들의 의미, 그리고 Sampling 및 T.. 더보기 이전 1 2 3 4 ··· 66 다음